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sha256:48550d87653eafb1894c252dd091406bd8ec1ef0bd363853516d23f70230d5e7 +size 21688 diff --git a/debug/episode_0005/images/sceneannotator_0_img_8.jpg b/debug/episode_0005/images/sceneannotator_0_img_8.jpg new file mode 100644 index 0000000000000000000000000000000000000000..1187534272fb0f527a9f5f36b035c7ef45a65e67 --- /dev/null +++ b/debug/episode_0005/images/sceneannotator_0_img_8.jpg @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3548539c4477ab1e82a0c4d50229e1508eb9f01d90bea82916673b4950df4bbe +size 16863 diff --git a/debug/episode_0005/trace_report.md b/debug/episode_0005/trace_report.md new file mode 100644 index 0000000000000000000000000000000000000000..07f89546c414d1ee0f179d5fe99cc6fda2b490be --- /dev/null +++ b/debug/episode_0005/trace_report.md @@ -0,0 +1,6283 @@ +# 🤖 Episode_0005 标注追踪报告 + + +# 🌍 全局场景语义理解 +==================== + +## 🎬 SceneAnnotator_0 + +### 👁️ 视觉输入 +![sceneannotator_0_img_0.jpg](./images/sceneannotator_0_img_0.jpg) +![sceneannotator_0_img_1.jpg](./images/sceneannotator_0_img_1.jpg) +![sceneannotator_0_img_2.jpg](./images/sceneannotator_0_img_2.jpg) +![sceneannotator_0_img_3.jpg](./images/sceneannotator_0_img_3.jpg) +![sceneannotator_0_img_4.jpg](./images/sceneannotator_0_img_4.jpg) +![sceneannotator_0_img_5.jpg](./images/sceneannotator_0_img_5.jpg) +![sceneannotator_0_img_6.jpg](./images/sceneannotator_0_img_6.jpg) +![sceneannotator_0_img_7.jpg](./images/sceneannotator_0_img_7.jpg) +![sceneannotator_0_img_8.jpg](./images/sceneannotator_0_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are an Embodied AI Scene Architect. + Your task is to perform a "Global Inventory & Topological Mapping" of the workspace. + + [CONTEXT]: + - Environment: unknown + - Scene: unknown -> unknown + - Target Objects: table, bag + - Task Description: Unknown Task + + [STRICT INSTRUCTIONS]: + 1. **SEMANTIC ANCHOR REGISTRATION (Critical)**: + - 🌟 **Task-Driven Affordance (CRITICAL)**: Analyze the `Task Description` first. ONLY register semantic anchors that are functionally relevant to completing this specific task. Ask yourself: "Which precise parts of the objects will the robot need to grasp, place, align, or avoid?" + - **Functional Decomposition**: Do NOT mindlessly exhaust or grid the object. Identify interaction hotspots. For example: + - If task is "Pour water": register "bottle:cap", "bottle:body", "cup:rim". + - If task is "Fold jacket": register "jacket:left_sleeve", "jacket:collar", "jacket:bottom_hem". + - If task is simply "Move the box": registering "box:main_body" is sufficient; do not invent micro-corners. + - **Naming Convention**: Use `object_name:part_name` (e.g., "jacket:left_sleeve", "table:center_bin"). + - **Scope**: Include essential parts of the target objects AND key functional zones of the workspace (e.g., "workspace:placement_zone"). + - **Initial Status**: Describe the visual topology at the start. ⚠️ DO NOT label main functional parts as "hidden", "unreachable", or "buried" unless absolutely invisible, as this prevents downstream agents from interacting with them. Use neutral terms like "partially_obscured_but_accessible" instead. + + 2. **SPATIAL LAYOUT**: + Provide a one-sentence summary of where the main objects are relative to the robot. + + 3. **SCENE FACTORS**: + Identify environment conditions (lighting, material, clutter) that might affect robot perception or grasp stability. + + 4. **DISTRACTORS**: + List objects that are NOT part of the task but might cause visual noise. Do NOT register them as Semantic Anchors. + + [OUTPUT RULE]: + Return ONLY a JSON object matching the schema. Do not include any explanations. + + [SCHEMA]: + { + "$defs": { + "SceneFactors": { + "additionalProperties": false, + "properties": { + "environment": { + "enum": [ + "kitchen", + "lab", + "outdoor", + "unknown" + ], + "title": "Environment", + "type": "string" + }, + "lighting_type": { + "enum": [ + "bright_indoor", + "dim", + "natural", + "mixed" + ], + "title": "Lighting Type", + "type": "string" + }, + "surface_material": { + "enum": [ + "wood", + "metal", + "plastic", + "tile", + "unknown" + ], + "title": "Surface Material", + "type": "string" + }, + "clutter_level": { + "enum": [ + "low", + "medium", + "high" + ], + "title": "Clutter Level", + "type": "string" + } + }, + "required": [ + "environment", + "lighting_type", + "surface_material", + "clutter_level" + ], + "title": "SceneFactors", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + } + }, + "additionalProperties": false, + "properties": { + "scene_factors": { + "$ref": "#/$defs/SceneFactors" + }, + "spatial_layout": { + "description": "Objective spatial arrangement.", + "title": "Spatial Layout", + "type": "string" + }, + "initial_semantic_anchors": { + "description": "Initial registration of key topological zones for the target objects.", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Initial Semantic Anchors", + "type": "array" + }, + "background_distractors": { + "items": { + "type": "string" + }, + "title": "Background Distractors", + "type": "array" + } + }, + "required": [ + "scene_factors", + "spatial_layout", + "initial_semantic_anchors", + "background_distractors" + ], + "title": "SceneAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "scene_factors": { + "environment": "lab", + "lighting_type": "bright_indoor", + "surface_material": "plastic", + "clutter_level": "low" + }, + "spatial_layout": "A white table occupies the immediate workspace with a beige insulated bag positioned in the center-right area, while the robot's grippers are positioned at the bottom edge of the view.", + "initial_semantic_anchors": [ + { + "anchor_id": "table:surface_center", + "current_status": "exposed" + }, + { + "anchor_id": "bag:main_body", + "current_status": "upright" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "exposed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "visible" + }, + { + "anchor_id": "bag:side_handle", + "current_status": "accessible" + } + ], + "background_distractors": [ + "grey_floor_mat", + "robot_grippers" + ] +} +```` +--- + +# 🤖 动作切片(Chunk) 语义闭环标注 +==================== + +## 🎬 ChunkAnnotator_0 + +### 👁️ 视觉输入 +![chunkannotator_0_img_0.jpg](./images/chunkannotator_0_img_0.jpg) +![chunkannotator_0_img_1.jpg](./images/chunkannotator_0_img_1.jpg) +![chunkannotator_0_img_2.jpg](./images/chunkannotator_0_img_2.jpg) +![chunkannotator_0_img_3.jpg](./images/chunkannotator_0_img_3.jpg) +![chunkannotator_0_img_4.jpg](./images/chunkannotator_0_img_4.jpg) +![chunkannotator_0_img_5.jpg](./images/chunkannotator_0_img_5.jpg) +![chunkannotator_0_img_6.jpg](./images/chunkannotator_0_img_6.jpg) +![chunkannotator_0_img_7.jpg](./images/chunkannotator_0_img_7.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 4 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T0 (Curr Start)] + - Image 3: [T1 (Curr End)] + - Image 4: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "visible"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "none", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.02, "angle": 8.64, "vel_score": 0.27, "angle_score": 142.04, "vel_fft": [0.016, 0.015, 0.013, 0.011, 0.009, 0.005, 0.003, 0.002, 0.002, 0.003, 0.003, 0.003, 0.002, 0.002, 0.002, 0.003, 0.002, 0.002, 0.002, 0.001], "angle_fft": [8.641, 6.47, 2.521, 5.265, 6.98, 4.859, 0.872, 2.732, 3.099, 2.599, 4.583, 4.94, 2.046, 3.654, 7.514, 7.64, 4.098, 4.111, 7.639, 7.498]}, "right": {"vel": 0.24, "angle": 0.6, "vel_score": 3.37, "angle_score": 7.66, "vel_fft": [0.236, 0.193, 0.098, 0.016, 0.023, 0.021, 0.005, 0.012, 0.005, 0.007, 0.009, 0.003, 0.003, 0.003, 0.005, 0.004, 0.005, 0.005, 0.0, 0.007], "angle_fft": [0.6, 0.399, 0.071, 0.16, 0.063, 0.067, 0.051, 0.064, 0.034, 0.074, 0.084, 0.033, 0.0, 0.016, 0.019, 0.044, 0.061, 0.034, 0.025, 0.031]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 3.1, "left_arm_ry": 1.15, "left_arm_rz": 3.03, "left_gripper": 0.25, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.08, "right_arm_ry": 1.13, "right_arm_rz": -3.0, "right_gripper": 0.39}, "1": {"left_arm_vel": 0.067, "left_gripper_vel": -0.462, "left_arm_rx": 3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.04, "left_gripper": 0.25, "right_arm_vel": 0.067, "right_gripper_vel": -0.462, "right_arm_rx": 2.87, "right_arm_ry": 1.13, "right_arm_rz": -3.14, "right_gripper": 0.36}, "2": {"left_arm_vel": 0.334, "left_gripper_vel": -0.105, "left_arm_rx": 3.12, "left_arm_ry": 1.15, "left_arm_rz": 3.05, "left_gripper": 0.25, "right_arm_vel": 0.334, "right_gripper_vel": -0.105, "right_arm_rx": 2.87, "right_arm_ry": 1.14, "right_arm_rz": -3.07, "right_gripper": 0.33}, "3": {"left_arm_vel": 0.76, "left_gripper_vel": 0.0, "left_arm_rx": -3.14, "left_arm_ry": 1.15, "left_arm_rz": 3.06, "left_gripper": 0.25, "right_arm_vel": 0.76, "right_gripper_vel": 0.0, "right_arm_rx": 2.77, "right_arm_ry": 1.07, "right_arm_rz": -2.99, "right_gripper": 0.33}, "4": {"left_arm_vel": 0.691, "left_gripper_vel": 0.168, "left_arm_rx": -3.14, "left_arm_ry": 1.12, "left_arm_rz": 3.06, "left_gripper": 0.25, "right_arm_vel": 0.691, "right_gripper_vel": 0.168, "right_arm_rx": 2.76, "right_arm_ry": 0.99, "right_arm_rz": -2.72, "right_gripper": 0.33}, "5": {"left_arm_vel": 0.724, "left_gripper_vel": 0.294, "left_arm_rx": -3.14, "left_arm_ry": 1.09, "left_arm_rz": 3.06, "left_gripper": 0.25, "right_arm_vel": 0.724, "right_gripper_vel": 0.294, "right_arm_rx": 2.76, "right_arm_ry": 0.95, "right_arm_rz": -2.61, "right_gripper": 0.35}, "6": {"left_arm_vel": 0.569, "left_gripper_vel": 0.21, "left_arm_rx": 3.13, "left_arm_ry": 1.02, "left_arm_rz": 3.05, "left_gripper": 0.25, "right_arm_vel": 0.569, "right_gripper_vel": 0.21, "right_arm_rx": 2.72, "right_arm_ry": 0.92, "right_arm_rz": -2.48, "right_gripper": 0.38}, "7": {"left_arm_vel": 0.456, "left_gripper_vel": 0.042, "left_arm_rx": -3.11, "left_arm_ry": 0.98, "left_arm_rz": 3.08, "left_gripper": 0.25, "right_arm_vel": 0.456, "right_gripper_vel": 0.042, "right_arm_rx": 2.67, "right_arm_ry": 0.88, "right_arm_rz": -2.4, "right_gripper": 0.38}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.030899999663233757, -0.005200000014156103, 0.007000000216066837], "delta_rot": [-6.215799808502197, -0.17149999737739563, 0.04450000077486038], "gripper_changed": false, "flow_direction": "+X(Forward)", "magnitude": 0.0321}, "right": {"delta_pos": [0.4514999985694885, 0.17110000550746918, 0.026100000366568565], "delta_rot": [-0.4065000116825104, -0.243599995970726, 0.6044999957084656], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and +Z(Up)", "magnitude": 0.4835}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.26080000400543213, -0.06419999897480011, -0.04010000079870224], "delta_rot": [-5.855299949645996, -0.31130000948905945, -0.015200000256299973], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.2715}, "right": {"delta_pos": [0.4542999863624573, 0.25029999017715454, -0.08209999650716782], "delta_rot": [-0.48190000653266907, -0.49779999256134033, 0.6935999989509583], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and -Z(Down)", "magnitude": 0.5252}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Right arm approaches and makes contact with the bag's top surface to initiate manipulation, while left arm remains idle.", + "actions": [ + { + "reasoning_cot": "The right arm exhibits significant forward (+X) and leftward (+Y) displacement (delta_pos magnitude ~0.48), moving from a neutral position directly over the bag. The gripper is open but positioned immediately above the object, indicating an approach or initial touch phase before grasping. Visual evidence confirms the end-effector hovering over/touching the top reflective panel.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "Moving from free space to bag:top_surface", + "topology_change": false + }, + { + "reasoning_cot": "The left arm shows negligible kinematic activity (vel ~0.02, minimal delta_pos). Visually, it remains stationary in the foreground/left zone, not interacting with the bag or table surface actively.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "static_at_initial_position", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Initiating interaction with the bag by positioning the right end-effector over the top surface." + } +} +```` +--- +## 🎬 ChunkAnnotator_1 + +### 👁️ 视觉输入 +![chunkannotator_1_img_0.jpg](./images/chunkannotator_1_img_0.jpg) +![chunkannotator_1_img_1.jpg](./images/chunkannotator_1_img_1.jpg) +![chunkannotator_1_img_2.jpg](./images/chunkannotator_1_img_2.jpg) +![chunkannotator_1_img_3.jpg](./images/chunkannotator_1_img_3.jpg) +![chunkannotator_1_img_4.jpg](./images/chunkannotator_1_img_4.jpg) +![chunkannotator_1_img_5.jpg](./images/chunkannotator_1_img_5.jpg) +![chunkannotator_1_img_6.jpg](./images/chunkannotator_1_img_6.jpg) +![chunkannotator_1_img_7.jpg](./images/chunkannotator_1_img_7.jpg) +![chunkannotator_1_img_8.jpg](./images/chunkannotator_1_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "visible"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm approaches and makes contact with the bag's top surface to initiate manipulation, while left arm remains idle.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.17, "angle": 9.36, "vel_score": 1.54, "angle_score": 116.85, "vel_fft": [0.171, 0.07, 0.02, 0.011, 0.008, 0.014, 0.013, 0.007, 0.003, 0.007, 0.009, 0.01, 0.008, 0.005, 0.009, 0.009, 0.006, 0.006, 0.005, 0.004], "angle_fft": [9.362, 8.56, 7.362, 5.599, 3.366, 0.897, 1.637, 4.03, 6.063, 7.591, 8.461, 8.642, 8.078, 6.811, 5.032, 2.844, 0.356, 2.131, 4.437, 6.338]}, "right": {"vel": 0.11, "angle": 0.28, "vel_score": 1.08, "angle_score": 2.61, "vel_fft": [0.106, 0.065, 0.044, 0.031, 0.003, 0.012, 0.008, 0.01, 0.01, 0.008, 0.004, 0.006, 0.005, 0.005, 0.003, 0.002, 0.004, 0.006, 0.004, 0.001], "angle_fft": [0.279, 0.118, 0.064, 0.09, 0.035, 0.009, 0.011, 0.009, 0.01, 0.017, 0.01, 0.011, 0.008, 0.014, 0.012, 0.007, 0.01, 0.017, 0.007, 0.01]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.08, "left_arm_ry": 0.97, "left_arm_rz": 3.1, "left_gripper": 0.25, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.88, "right_arm_rz": -2.4, "right_gripper": 0.39}, "1": {"left_arm_vel": 0.308, "left_gripper_vel": 0.021, "left_arm_rx": -2.9, "left_arm_ry": 0.91, "left_arm_rz": -3.08, "left_gripper": 0.25, "right_arm_vel": 0.308, "right_gripper_vel": 0.021, "right_arm_rx": 2.64, "right_arm_ry": 0.85, "right_arm_rz": -2.4, "right_gripper": 0.39}, "2": {"left_arm_vel": 0.342, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.89, "left_arm_rz": -3.04, "left_gripper": 0.25, "right_arm_vel": 0.342, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.78, "right_arm_rz": -2.35, "right_gripper": 0.39}, "3": {"left_arm_vel": 0.088, "left_gripper_vel": 0.0, "left_arm_rx": -2.78, "left_arm_ry": 0.88, "left_arm_rz": -3.01, "left_gripper": 0.25, "right_arm_vel": 0.088, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.74, "right_arm_rz": -2.28, "right_gripper": 0.39}, "4": {"left_arm_vel": 0.136, "left_gripper_vel": 0.0, "left_arm_rx": -2.7, "left_arm_ry": 0.88, "left_arm_rz": -2.96, "left_gripper": 0.25, "right_arm_vel": 0.136, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.66, "right_arm_rz": -2.3, "right_gripper": 0.39}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": -0.861, "left_arm_rx": -2.67, "left_arm_ry": 0.83, "left_arm_rz": -2.98, "left_gripper": 0.25, "right_arm_vel": 0.0, "right_gripper_vel": -0.861, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.32, "right_gripper": 0.36}, "6": {"left_arm_vel": 0.016, "left_gripper_vel": -2.1, "left_arm_rx": -2.65, "left_arm_ry": 0.84, "left_arm_rz": -2.97, "left_gripper": 0.26, "right_arm_vel": 0.016, "right_gripper_vel": -2.1, "right_arm_rx": 2.6, "right_arm_ry": 0.64, "right_arm_rz": -2.31, "right_gripper": 0.23}, "7": {"left_arm_vel": 0.016, "left_gripper_vel": -2.73, "left_arm_rx": -2.63, "left_arm_ry": 0.84, "left_arm_rz": -2.96, "left_gripper": 0.26, "right_arm_vel": 0.016, "right_gripper_vel": -2.73, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.14}, "8": {"left_arm_vel": 0.019, "left_gripper_vel": -1.68, "left_arm_rx": -2.62, "left_arm_ry": 0.83, "left_arm_rz": -2.95, "left_gripper": 0.27, "right_arm_vel": 0.019, "right_gripper_vel": -1.68, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.08}, "9": {"left_arm_vel": 0.0, "left_gripper_vel": -0.084, "left_arm_rx": -2.6, "left_arm_ry": 0.8, "left_arm_rz": -2.95, "left_gripper": 0.3, "right_arm_vel": 0.0, "right_gripper_vel": -0.084, "right_arm_rx": 2.61, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "10": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -2.59, "left_arm_ry": 0.79, "left_arm_rz": -2.95, "left_gripper": 0.32, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "11": {"left_arm_vel": 0.006, "left_gripper_vel": 0.0, "left_arm_rx": -2.58, "left_arm_ry": 0.8, "left_arm_rz": -2.99, "left_gripper": 0.35, "right_arm_vel": 0.006, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "12": {"left_arm_vel": 0.013, "left_gripper_vel": 0.0, "left_arm_rx": -2.57, "left_arm_ry": 0.79, "left_arm_rz": -3.01, "left_gripper": 0.36, "right_arm_vel": 0.013, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "13": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": -2.75, "left_arm_ry": 0.84, "left_arm_rz": 3.02, "left_gripper": 0.36, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.2249000072479248, -0.05689999833703041, -0.050700001418590546], "delta_rot": [0.32420000433921814, -0.13449999690055847, -0.08209999650716782], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.2375}, "right": {"delta_pos": [-0.006599999964237213, 0.07329999655485153, -0.10300000011920929], "delta_rot": [-0.06939999759197235, -0.2493000030517578, 0.08799999952316284], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.1266}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.30820000171661377, -0.12860000133514404, -0.1251000016927719], "delta_rot": [5.965199947357178, -0.20280000567436218, -1.0633000135421753], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.3566}, "right": {"delta_pos": [-0.006599999964237213, 0.07339999824762344, -0.10300000011920929], "delta_rot": [-0.07159999758005142, -0.2506999969482422, 0.08449999988079071], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.1266}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Right arm approaches and makes contact with the bag's top surface to initiate manipulation, while left arm remains idle.", + "actions": [ + { + "reasoning_cot": "The right arm executes a significant forward (+X) and downward (-Z) trajectory (delta_mag 0.1266), transitioning from free space to direct contact with the bag's upper reflective panel. The gripper signal is 'stable' but visual evidence confirms 'touching', indicating an approach-to-contact phase rather than a grasp.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "moving from free_space to bag:top_surface", + "topology_change": false + }, + { + "reasoning_cot": "The left arm exhibits negligible kinematic change (vel ~0.0) and remains visually distant from the bag in the peripheral view. It maintains its previous state without engaging in the current interaction.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "static_in_free_space", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Initiating contact with the bag's top surface using the right arm." + } +} +```` +--- +## 🎬 ChunkAnnotator_2 + +### 👁️ 视觉输入 +![chunkannotator_2_img_0.jpg](./images/chunkannotator_2_img_0.jpg) +![chunkannotator_2_img_1.jpg](./images/chunkannotator_2_img_1.jpg) +![chunkannotator_2_img_2.jpg](./images/chunkannotator_2_img_2.jpg) +![chunkannotator_2_img_3.jpg](./images/chunkannotator_2_img_3.jpg) +![chunkannotator_2_img_4.jpg](./images/chunkannotator_2_img_4.jpg) +![chunkannotator_2_img_5.jpg](./images/chunkannotator_2_img_5.jpg) +![chunkannotator_2_img_6.jpg](./images/chunkannotator_2_img_6.jpg) +![chunkannotator_2_img_7.jpg](./images/chunkannotator_2_img_7.jpg) +![chunkannotator_2_img_8.jpg](./images/chunkannotator_2_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "visible"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm approaches and makes contact with the bag's top surface to initiate manipulation, while left arm remains idle.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.11, "angle": 5.63, "vel_score": 0.97, "angle_score": 9.31, "vel_fft": [0.115, 0.044, 0.035, 0.013, 0.012, 0.01, 0.009, 0.007, 0.009, 0.005, 0.005, 0.008, 0.006, 0.007, 0.006, 0.007, 0.007, 0.007, 0.003, 0.003], "angle_fft": [5.631, 5.32, 5.086, 4.875, 4.743, 4.687, 4.669, 4.691, 4.687, 4.713, 4.765, 4.746, 4.755, 4.744, 4.739, 4.708, 4.696, 4.719, 4.762, 4.782]}, "right": {"vel": 0.0, "angle": 0.01, "vel_score": 0.0, "angle_score": 0.04, "vel_fft": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "angle_fft": [0.005, 0.003, 0.001, 0.001, 0.002, 0.001, 0.003, 0.002, 0.002, 0.003, 0.003, 0.001, 0.001, 0.001, 0.002, 0.001, 0.003, 0.002, 0.003, 0.002]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.86, "left_arm_rz": 2.93, "left_gripper": 0.36, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 3.11, "left_arm_ry": 0.83, "left_arm_rz": 2.45, "left_gripper": 0.36, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": -0.084, "left_arm_rx": 2.89, "left_arm_ry": 0.76, "left_arm_rz": 2.09, "left_gripper": 0.36, "right_arm_vel": 0.0, "right_gripper_vel": -0.084, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.89, "left_arm_ry": 0.75, "left_arm_rz": 2.07, "left_gripper": 0.36, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": -0.063, "left_arm_rx": 2.86, "left_arm_ry": 0.77, "left_arm_rz": 2.04, "left_gripper": 0.37, "right_arm_vel": 0.0, "right_gripper_vel": -0.063, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.88, "left_arm_ry": 0.77, "left_arm_rz": 2.03, "left_gripper": 0.37, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.88, "left_arm_ry": 0.77, "left_arm_rz": 2.03, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.89, "left_arm_ry": 0.77, "left_arm_rz": 2.04, "left_gripper": 0.34, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.07180000096559525, -0.07129999995231628, -0.0714000016450882], "delta_rot": [5.720600128173828, -0.08640000224113464, -0.89410001039505], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.1238}, "right": {"delta_pos": [-0.0, 0.0, 0.0], "delta_rot": [-0.002300000051036477, -0.00139999995008111, -0.0034000000450760126], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.04280000180006027, -0.06129999831318855, -0.044199999421834946], "delta_rot": [-0.07069999724626541, -0.03240000084042549, -0.4887999892234802], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "magnitude": 0.0869}, "right": {"delta_pos": [-0.006399999838322401, 0.010099999606609344, -0.0], "delta_rot": [-0.1103999987244606, -0.05220000073313713, -0.11630000174045563], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0119}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm approaches and stabilizes the bag's top surface near the zipper, while right arm remains idle.", + "actions": [ + { + "reasoning_cot": "The left arm executes a significant approach trajectory (delta_pos magnitude ~0.12m) moving forward and down towards the bag. Visual evidence in frames T0-T4 confirms the gripper making contact with the 'bag:top_surface' to stabilize or prepare for manipulation. The gripper signal is stable/closing slightly upon contact.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "moving from free space to bag:top_surface", + "topology_change": false + }, + { + "reasoning_cot": "The right arm shows zero kinematic displacement (delta_pos [0,0,0]) and remains in a static hovering position throughout the chunk. Visuals confirm no interaction with the environment.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": null, + "spatial_logic": "static_hover", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Left arm has established contact with the bag's top surface, likely to stabilize it for subsequent zipper or handle manipulation." + } +} +```` +--- +## 🎬 ChunkAnnotator_3 + +### 👁️ 视觉输入 +![chunkannotator_3_img_0.jpg](./images/chunkannotator_3_img_0.jpg) +![chunkannotator_3_img_1.jpg](./images/chunkannotator_3_img_1.jpg) +![chunkannotator_3_img_2.jpg](./images/chunkannotator_3_img_2.jpg) +![chunkannotator_3_img_3.jpg](./images/chunkannotator_3_img_3.jpg) +![chunkannotator_3_img_4.jpg](./images/chunkannotator_3_img_4.jpg) +![chunkannotator_3_img_5.jpg](./images/chunkannotator_3_img_5.jpg) +![chunkannotator_3_img_6.jpg](./images/chunkannotator_3_img_6.jpg) +![chunkannotator_3_img_7.jpg](./images/chunkannotator_3_img_7.jpg) +![chunkannotator_3_img_8.jpg](./images/chunkannotator_3_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "visible"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and stabilizes the bag's top surface near the zipper, while right arm remains idle.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.11, "angle": 5.33, "vel_score": 1.05, "angle_score": 5.28, "vel_fft": [0.111, 0.068, 0.03, 0.013, 0.004, 0.007, 0.003, 0.004, 0.004, 0.003, 0.004, 0.006, 0.002, 0.002, 0.002, 0.002, 0.003, 0.002, 0.0, 0.004], "angle_fft": [5.326, 5.036, 4.868, 4.879, 4.709, 4.684, 4.786, 4.779, 4.778, 4.795, 4.775, 4.768, 4.752, 4.774, 4.788, 4.778, 4.777, 4.778, 4.785, 4.764]}, "right": {"vel": 0.01, "angle": 0.13, "vel_score": 0.11, "angle_score": 1.15, "vel_fft": [0.011, 0.009, 0.005, 0.002, 0.001, 0.001, 0.002, 0.003, 0.002, 0.002, 0.001, 0.0, 0.0, 0.001, 0.002, 0.001, 0.001, 0.001, 0.001, 0.001], "angle_fft": [0.133, 0.06, 0.033, 0.003, 0.018, 0.006, 0.016, 0.017, 0.006, 0.004, 0.003, 0.013, 0.009, 0.009, 0.007, 0.006, 0.006, 0.003, 0.003, 0.006]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.89, "left_arm_ry": 0.77, "left_arm_rz": 2.03, "left_gripper": 0.33, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.9, "left_arm_ry": 0.78, "left_arm_rz": 2.03, "left_gripper": 0.22, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.91, "left_arm_ry": 0.78, "left_arm_rz": 2.03, "left_gripper": 0.14, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.91, "left_arm_ry": 0.78, "left_arm_rz": 2.03, "left_gripper": 0.02, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.59, "right_arm_ry": 0.63, "right_arm_rz": -2.31, "right_gripper": 0.05}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 3.0, "left_arm_ry": 0.81, "left_arm_rz": 2.17, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.58, "right_arm_ry": 0.6, "right_arm_rz": -2.35, "right_gripper": 0.05}, "5": {"left_arm_vel": 0.042, "left_gripper_vel": -0.063, "left_arm_rx": 3.1, "left_arm_ry": 0.87, "left_arm_rz": 2.28, "left_gripper": -0.01, "right_arm_vel": 0.042, "right_gripper_vel": -0.063, "right_arm_rx": 2.55, "right_arm_ry": 0.6, "right_arm_rz": -2.38, "right_gripper": 0.05}, "6": {"left_arm_vel": 0.01, "left_gripper_vel": 0.0, "left_arm_rx": -3.07, "left_arm_ry": 0.87, "left_arm_rz": 2.33, "left_gripper": -0.01, "right_arm_vel": 0.01, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.59, "right_arm_rz": -2.39, "right_gripper": 0.04}, "7": {"left_arm_vel": 0.014, "left_gripper_vel": 0.0, "left_arm_rx": -2.9, "left_arm_ry": 0.82, "left_arm_rz": 2.44, "left_gripper": -0.01, "right_arm_vel": 0.014, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.58, "right_arm_rz": -2.43, "right_gripper": 0.04}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.11469999700784683, 0.010099999606609344, 0.027000000700354576], "delta_rot": [-5.790999889373779, 0.053199999034404755, 0.40689998865127563], "gripper_changed": false, "flow_direction": "-X(Backward) and +Z(Up)", "magnitude": 0.1183}, "right": {"delta_pos": [-0.006399999838322401, 0.009999999776482582, -0.0], "delta_rot": [-0.10819999873638153, -0.05090000107884407, -0.11289999634027481], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0119}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.1476999968290329, -0.0803999975323677, 0.009200000204145908], "delta_rot": [-5.784599781036377, -0.004600000102072954, 0.249099999666214], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.1684}, "right": {"delta_pos": [-0.004000000189989805, 0.005900000222027302, -0.0005000000237487257], "delta_rot": [-0.13989999890327454, -0.09080000221729279, -0.1800999939441681], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0071}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm approaches and stabilizes the bag's top surface near the zipper, while right arm remains idle.", + "actions": [ + { + "reasoning_cot": "The left arm moves from a hovering position to make contact with the bag's top surface. The gripper closes (delta_gripper negative) as it touches the material near the zipper pull, indicating an intent to grasp or stabilize this specific zone for manipulation.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "touching" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "Approaching and contacting bag:top_surface/zipper_pull", + "topology_change": false + }, + { + "reasoning_cot": "The right arm exhibits negligible kinematic displacement (vel ~0.01) and maintains its open gripper state throughout the sequence. It remains in a passive hovering state above the table/bag area without interacting.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": null, + "spatial_logic": "Static hover", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "contacted" + } + ], + "task_progress": "Left arm has established initial contact with the bag's zipper area to prepare for opening or stabilization." + } +} +```` +--- +## 🎬 ChunkAnnotator_4 + +### 👁️ 视觉输入 +![chunkannotator_4_img_0.jpg](./images/chunkannotator_4_img_0.jpg) +![chunkannotator_4_img_1.jpg](./images/chunkannotator_4_img_1.jpg) +![chunkannotator_4_img_2.jpg](./images/chunkannotator_4_img_2.jpg) +![chunkannotator_4_img_3.jpg](./images/chunkannotator_4_img_3.jpg) +![chunkannotator_4_img_4.jpg](./images/chunkannotator_4_img_4.jpg) +![chunkannotator_4_img_5.jpg](./images/chunkannotator_4_img_5.jpg) +![chunkannotator_4_img_6.jpg](./images/chunkannotator_4_img_6.jpg) +![chunkannotator_4_img_7.jpg](./images/chunkannotator_4_img_7.jpg) +![chunkannotator_4_img_8.jpg](./images/chunkannotator_4_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and stabilizes the bag's top surface near the zipper, while right arm remains idle.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.17, "angle": 0.45, "vel_score": 0.86, "angle_score": 2.25, "vel_fft": [0.172, 0.045, 0.021, 0.018, 0.02, 0.015, 0.012, 0.011, 0.009, 0.002], "angle_fft": [0.455, 0.135, 0.114, 0.051, 0.111, 0.03, 0.052, 0.057, 0.01, 0.004]}, "right": {"vel": 0.01, "angle": 0.13, "vel_score": 0.03, "angle_score": 0.66, "vel_fft": [0.008, 0.003, 0.002, 0.003, 0.002, 0.003, 0.001, 0.003, 0.002, 0.001], "angle_fft": [0.127, 0.074, 0.027, 0.023, 0.031, 0.024, 0.013, 0.014, 0.003, 0.002]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.9, "left_arm_ry": 0.82, "left_arm_rz": 2.43, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.48, "right_arm_ry": 0.57, "right_arm_rz": -2.43, "right_gripper": 0.04}, "1": {"left_arm_vel": 0.035, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.8, "left_arm_rz": 2.36, "left_gripper": -0.01, "right_arm_vel": 0.035, "right_gripper_vel": 0.0, "right_arm_rx": 2.47, "right_arm_ry": 0.56, "right_arm_rz": -2.45, "right_gripper": 0.04}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.8, "left_arm_rz": 2.34, "left_gripper": -0.0, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.47, "right_arm_ry": 0.55, "right_arm_rz": -2.46, "right_gripper": 0.04}, "3": {"left_arm_vel": 0.012, "left_gripper_vel": 0.0, "left_arm_rx": -2.89, "left_arm_ry": 0.79, "left_arm_rz": 2.32, "left_gripper": -0.0, "right_arm_vel": 0.012, "right_gripper_vel": 0.0, "right_arm_rx": 2.47, "right_arm_ry": 0.55, "right_arm_rz": -2.47, "right_gripper": 0.04}, "4": {"left_arm_vel": 0.001, "left_gripper_vel": 0.0, "left_arm_rx": -2.89, "left_arm_ry": 0.79, "left_arm_rz": 2.3, "left_gripper": -0.0, "right_arm_vel": 0.001, "right_gripper_vel": 0.0, "right_arm_rx": 2.47, "right_arm_ry": 0.55, "right_arm_rz": -2.47, "right_gripper": 0.04}, "5": {"left_arm_vel": 0.005, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.78, "left_arm_rz": 2.29, "left_gripper": -0.0, "right_arm_vel": 0.005, "right_gripper_vel": 0.0, "right_arm_rx": 2.46, "right_arm_ry": 0.54, "right_arm_rz": -2.48, "right_gripper": 0.04}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": -0.021, "left_arm_rx": -2.86, "left_arm_ry": 0.77, "left_arm_rz": 2.28, "left_gripper": -0.0, "right_arm_vel": 0.0, "right_gripper_vel": -0.021, "right_arm_rx": 2.46, "right_arm_ry": 0.54, "right_arm_rz": -2.48, "right_gripper": 0.04}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.021, "left_arm_rx": -2.86, "left_arm_ry": 0.77, "left_arm_rz": 2.28, "left_gripper": -0.0, "right_arm_vel": 0.0, "right_gripper_vel": 0.021, "right_arm_rx": 2.46, "right_arm_ry": 0.54, "right_arm_rz": -2.48, "right_gripper": 0.04}, "8": {"left_arm_vel": 0.013, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.76, "left_arm_rz": 2.28, "left_gripper": -0.0, "right_arm_vel": 0.013, "right_gripper_vel": 0.0, "right_arm_rx": 2.46, "right_arm_ry": 0.54, "right_arm_rz": -2.48, "right_gripper": 0.04}, "9": {"left_arm_vel": 0.016, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.76, "left_arm_rz": 2.28, "left_gripper": -0.0, "right_arm_vel": 0.016, "right_gripper_vel": 0.0, "right_arm_rx": 2.46, "right_arm_ry": 0.54, "right_arm_rz": -2.49, "right_gripper": 0.04}, "10": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.89, "left_arm_ry": 0.77, "left_arm_rz": 2.27, "left_gripper": -0.0, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.46, "right_arm_ry": 0.54, "right_arm_rz": -2.49, "right_gripper": 0.04}, "11": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.9, "left_arm_ry": 0.77, "left_arm_rz": 2.26, "left_gripper": -0.0, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.46, "right_arm_ry": 0.54, "right_arm_rz": -2.49, "right_gripper": 0.04}, "12": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.91, "left_arm_ry": 0.77, "left_arm_rz": 2.26, "left_gripper": -0.0, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.46, "right_arm_ry": 0.54, "right_arm_rz": -2.49, "right_gripper": 0.04}, "13": {"left_arm_vel": 0.017, "left_gripper_vel": 0.0, "left_arm_rx": -2.9, "left_arm_ry": 0.77, "left_arm_rz": 2.28, "left_gripper": -0.0, "right_arm_vel": 0.017, "right_gripper_vel": 0.0, "right_arm_rx": 2.46, "right_arm_ry": 0.54, "right_arm_rz": -2.49, "right_gripper": 0.04}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.030500000342726707, -0.08609999716281891, -0.017899999395012856], "delta_rot": [0.0032999999821186066, -0.05469999834895134, -0.15139999985694885], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.0931}, "right": {"delta_pos": [0.0024999999441206455, -0.00419999985024333, 0.0], "delta_rot": [-0.026799999177455902, -0.03480000048875809, -0.060600001364946365], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0049}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.03310000151395798, -0.09279999881982803, -0.009700000286102295], "delta_rot": [0.19249999523162842, -0.16200000047683716, -0.04699999839067459], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.099}, "right": {"delta_pos": [0.011699999682605267, -0.01860000006854534, 0.0020000000949949026], "delta_rot": [-0.06390000134706497, -0.049300000071525574, -0.1412999927997589], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.022}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by holding the zipper pull, while right arm approaches and makes contact with the top surface near the opening to prepare for manipulation.", + "actions": [ + { + "reasoning_cot": "The left arm maintains a static position relative to the bag's zipper pull. Visual evidence shows the gripper is closed around the metal tab, providing stabilization. Kinematic data confirms minimal movement (delta ~0), indicating a 'hold' state rather than active pulling in this specific chunk.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "static_at_zipper_pull", + "topology_change": false + }, + { + "reasoning_cot": "The right arm transitions from a hovering state to making physical contact with the bag's top surface/rim. The trajectory shows a downward and forward motion ending with the gripper tips touching the silver thermal lining area. This is an approach and initial touch action, likely to stabilize or open the bag further.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": "stabilize_top_rim", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "moving_from_hover_to_top_surface_contact", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:top_surface", + "current_status": "contacted" + } + ], + "task_progress": "Bag is stabilized by left hand; right hand establishes contact with top rim for potential opening or inspection." + } +} +```` +--- +## 🎬 ChunkAnnotator_5 + +### 👁️ 视觉输入 +![chunkannotator_5_img_0.jpg](./images/chunkannotator_5_img_0.jpg) +![chunkannotator_5_img_1.jpg](./images/chunkannotator_5_img_1.jpg) +![chunkannotator_5_img_2.jpg](./images/chunkannotator_5_img_2.jpg) +![chunkannotator_5_img_3.jpg](./images/chunkannotator_5_img_3.jpg) +![chunkannotator_5_img_4.jpg](./images/chunkannotator_5_img_4.jpg) +![chunkannotator_5_img_5.jpg](./images/chunkannotator_5_img_5.jpg) +![chunkannotator_5_img_6.jpg](./images/chunkannotator_5_img_6.jpg) +![chunkannotator_5_img_7.jpg](./images/chunkannotator_5_img_7.jpg) +![chunkannotator_5_img_8.jpg](./images/chunkannotator_5_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by holding the zipper pull, while right arm approaches and makes contact with the top surface near the opening to prepare for manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.08, "angle": 0.43, "vel_score": 0.39, "angle_score": 2.21, "vel_fft": [0.076, 0.022, 0.018, 0.009, 0.005, 0.007, 0.006, 0.007, 0.006, 0.005], "angle_fft": [0.427, 0.142, 0.065, 0.042, 0.007, 0.049, 0.062, 0.048, 0.053, 0.026]}, "right": {"vel": 0.03, "angle": 0.15, "vel_score": 0.15, "angle_score": 0.8, "vel_fft": [0.027, 0.022, 0.016, 0.008, 0.007, 0.005, 0.007, 0.006, 0.007, 0.002], "angle_fft": [0.148, 0.115, 0.069, 0.032, 0.036, 0.025, 0.023, 0.03, 0.034, 0.016]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.9, "left_arm_ry": 0.77, "left_arm_rz": 2.28, "left_gripper": -0.0, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.46, "right_arm_ry": 0.54, "right_arm_rz": -2.49, "right_gripper": 0.04}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.84, "left_arm_ry": 0.74, "left_arm_rz": 2.32, "left_gripper": -0.0, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.46, "right_arm_ry": 0.54, "right_arm_rz": -2.5, "right_gripper": 0.04}, "2": {"left_arm_vel": 0.018, "left_gripper_vel": 0.063, "left_arm_rx": -2.78, "left_arm_ry": 0.72, "left_arm_rz": 2.35, "left_gripper": 0.07, "right_arm_vel": 0.018, "right_gripper_vel": 0.063, "right_arm_rx": 2.45, "right_arm_ry": 0.53, "right_arm_rz": -2.51, "right_gripper": 0.05}, "3": {"left_arm_vel": 0.078, "left_gripper_vel": 0.315, "left_arm_rx": -2.75, "left_arm_ry": 0.7, "left_arm_rz": 2.36, "left_gripper": 0.13, "right_arm_vel": 0.078, "right_gripper_vel": 0.315, "right_arm_rx": 2.45, "right_arm_ry": 0.52, "right_arm_rz": -2.52, "right_gripper": 0.06}, "4": {"left_arm_vel": 0.076, "left_gripper_vel": 0.84, "left_arm_rx": -2.73, "left_arm_ry": 0.68, "left_arm_rz": 2.36, "left_gripper": 0.21, "right_arm_vel": 0.076, "right_gripper_vel": 0.84, "right_arm_rx": 2.44, "right_arm_ry": 0.52, "right_arm_rz": -2.54, "right_gripper": 0.08}, "5": {"left_arm_vel": 0.126, "left_gripper_vel": 1.428, "left_arm_rx": -2.72, "left_arm_ry": 0.67, "left_arm_rz": 2.37, "left_gripper": 0.27, "right_arm_vel": 0.126, "right_gripper_vel": 1.428, "right_arm_rx": 2.43, "right_arm_ry": 0.52, "right_arm_rz": -2.55, "right_gripper": 0.13}, "6": {"left_arm_vel": 0.154, "left_gripper_vel": 1.869, "left_arm_rx": -2.71, "left_arm_ry": 0.66, "left_arm_rz": 2.39, "left_gripper": 0.34, "right_arm_vel": 0.154, "right_gripper_vel": 1.869, "right_arm_rx": 2.42, "right_arm_ry": 0.52, "right_arm_rz": -2.57, "right_gripper": 0.19}, "7": {"left_arm_vel": 0.154, "left_gripper_vel": 1.869, "left_arm_rx": -2.71, "left_arm_ry": 0.66, "left_arm_rz": 2.39, "left_gripper": 0.34, "right_arm_vel": 0.154, "right_gripper_vel": 1.869, "right_arm_rx": 2.42, "right_arm_ry": 0.52, "right_arm_rz": -2.57, "right_gripper": 0.19}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.00430000014603138, -0.004800000227987766, 0.007799999788403511], "delta_rot": [0.18729999661445618, -0.10949999839067459, 0.10360000282526016], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0101}, "right": {"delta_pos": [0.009200000204145908, -0.014399999752640724, 0.0019000000320374966], "delta_rot": [-0.03720000013709068, -0.014600000344216824, -0.08070000261068344], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0172}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.21699999272823334, -0.0414000004529953, 0.07739999890327454], "delta_rot": [-0.045899998396635056, -0.007000000216066837, -0.25589999556541443], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.2341}, "right": {"delta_pos": [-0.11699999868869781, -0.19480000436306, -0.009499999694526196], "delta_rot": [-0.02669999934732914, 0.15150000154972076, -0.49790000915527344], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.2274}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by holding the zipper pull, while right arm approaches and makes contact with the top surface near the opening to prepare for manipulation.", + "actions": [ + { + "reasoning_cot": "The left arm is visually confirmed to be gripping the metal zipper pull of the bag. The gripper state is stable (closed/secured) throughout the sequence, maintaining tension on the bag's opening to facilitate access for the other arm.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "static_at_zipper_pull", + "topology_change": false + }, + { + "reasoning_cot": "The right arm moves from a hovering position towards the bag's interior/top edge. In the final frames, the gripper tips are in direct contact with the white material near the silver reflective lining. The action transitions from approach to initial contact/touching without yet securing a grasp.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "touch", + "semantic_action": "approach_and_contact", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "moving_from_free_space_to_top_surface", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:top_surface", + "current_status": "contacted" + } + ], + "task_progress": "Bag stabilization achieved via left arm; right arm has established initial contact with the bag opening area." + } +} +```` +--- +## 🎬 ChunkAnnotator_6 + +### 👁️ 视觉输入 +![chunkannotator_6_img_0.jpg](./images/chunkannotator_6_img_0.jpg) +![chunkannotator_6_img_1.jpg](./images/chunkannotator_6_img_1.jpg) +![chunkannotator_6_img_2.jpg](./images/chunkannotator_6_img_2.jpg) +![chunkannotator_6_img_3.jpg](./images/chunkannotator_6_img_3.jpg) +![chunkannotator_6_img_4.jpg](./images/chunkannotator_6_img_4.jpg) +![chunkannotator_6_img_5.jpg](./images/chunkannotator_6_img_5.jpg) +![chunkannotator_6_img_6.jpg](./images/chunkannotator_6_img_6.jpg) +![chunkannotator_6_img_7.jpg](./images/chunkannotator_6_img_7.jpg) +![chunkannotator_6_img_8.jpg](./images/chunkannotator_6_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by holding the zipper pull, while right arm approaches and makes contact with the top surface near the opening to prepare for manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.37, "angle": 1.12, "vel_score": 2.57, "angle_score": 7.82, "vel_fft": [0.366, 0.056, 0.021, 0.015, 0.014, 0.01, 0.007, 0.011, 0.008, 0.011, 0.008, 0.009, 0.014, 0.007, 0.011], "angle_fft": [1.117, 0.256, 0.17, 0.265, 0.09, 0.104, 0.058, 0.018, 0.016, 0.027, 0.049, 0.015, 0.036, 0.033, 0.052]}, "right": {"vel": 0.33, "angle": 0.72, "vel_score": 2.34, "angle_score": 4.9, "vel_fft": [0.332, 0.055, 0.061, 0.014, 0.009, 0.008, 0.007, 0.01, 0.018, 0.004, 0.007, 0.002, 0.006, 0.01, 0.008], "angle_fft": [0.718, 0.033, 0.098, 0.08, 0.041, 0.032, 0.038, 0.029, 0.063, 0.044, 0.078, 0.042, 0.017, 0.039, 0.017]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.71, "left_arm_ry": 0.65, "left_arm_rz": 2.41, "left_gripper": 0.38, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.41, "right_arm_ry": 0.52, "right_arm_rz": -2.59, "right_gripper": 0.25}, "1": {"left_arm_vel": 0.248, "left_gripper_vel": 1.89, "left_arm_rx": -2.72, "left_arm_ry": 0.66, "left_arm_rz": 2.42, "left_gripper": 0.4, "right_arm_vel": 0.248, "right_gripper_vel": 1.89, "right_arm_rx": 2.4, "right_arm_ry": 0.52, "right_arm_rz": -2.62, "right_gripper": 0.31}, "2": {"left_arm_vel": 0.28, "left_gripper_vel": 1.365, "left_arm_rx": -2.71, "left_arm_ry": 0.66, "left_arm_rz": 2.43, "left_gripper": 0.42, "right_arm_vel": 0.28, "right_gripper_vel": 1.365, "right_arm_rx": 2.39, "right_arm_ry": 0.52, "right_arm_rz": -2.65, "right_gripper": 0.36}, "3": {"left_arm_vel": 0.32, "left_gripper_vel": 0.672, "left_arm_rx": -2.71, "left_arm_ry": 0.68, "left_arm_rz": 2.46, "left_gripper": 0.42, "right_arm_vel": 0.32, "right_gripper_vel": 0.672, "right_arm_rx": 2.38, "right_arm_ry": 0.53, "right_arm_rz": -2.67, "right_gripper": 0.38}, "4": {"left_arm_vel": 0.378, "left_gripper_vel": 0.147, "left_arm_rx": -2.72, "left_arm_ry": 0.74, "left_arm_rz": 2.53, "left_gripper": 0.42, "right_arm_vel": 0.378, "right_gripper_vel": 0.147, "right_arm_rx": 2.36, "right_arm_ry": 0.54, "right_arm_rz": -2.73, "right_gripper": 0.4}, "5": {"left_arm_vel": 0.36, "left_gripper_vel": 0.0, "left_arm_rx": -2.71, "left_arm_ry": 0.78, "left_arm_rz": 2.6, "left_gripper": 0.4, "right_arm_vel": 0.36, "right_gripper_vel": 0.0, "right_arm_rx": 2.35, "right_arm_ry": 0.56, "right_arm_rz": -2.79, "right_gripper": 0.4}, "6": {"left_arm_vel": 0.296, "left_gripper_vel": 0.0, "left_arm_rx": -2.71, "left_arm_ry": 0.79, "left_arm_rz": 2.67, "left_gripper": 0.39, "right_arm_vel": 0.296, "right_gripper_vel": 0.0, "right_arm_rx": 2.35, "right_arm_ry": 0.58, "right_arm_rz": -2.82, "right_gripper": 0.4}, "7": {"left_arm_vel": 0.236, "left_gripper_vel": 0.0, "left_arm_rx": -2.71, "left_arm_ry": 0.8, "left_arm_rz": 2.69, "left_gripper": 0.38, "right_arm_vel": 0.236, "right_gripper_vel": 0.0, "right_arm_rx": 2.36, "right_arm_ry": 0.58, "right_arm_rz": -2.85, "right_gripper": 0.4}, "8": {"left_arm_vel": 0.311, "left_gripper_vel": -0.063, "left_arm_rx": -2.75, "left_arm_ry": 0.84, "left_arm_rz": 2.64, "left_gripper": 0.37, "right_arm_vel": 0.311, "right_gripper_vel": -0.063, "right_arm_rx": 2.37, "right_arm_ry": 0.53, "right_arm_rz": -2.87, "right_gripper": 0.39}, "9": {"left_arm_vel": 0.476, "left_gripper_vel": 0.0, "left_arm_rx": -2.74, "left_arm_ry": 0.84, "left_arm_rz": 2.56, "left_gripper": 0.37, "right_arm_vel": 0.476, "right_gripper_vel": 0.0, "right_arm_rx": 2.39, "right_arm_ry": 0.5, "right_arm_rz": -2.94, "right_gripper": 0.39}, "10": {"left_arm_vel": 0.554, "left_gripper_vel": 0.0, "left_arm_rx": -2.74, "left_arm_ry": 0.84, "left_arm_rz": 2.5, "left_gripper": 0.37, "right_arm_vel": 0.554, "right_gripper_vel": 0.0, "right_arm_rx": 2.37, "right_arm_ry": 0.5, "right_arm_rz": -2.98, "right_gripper": 0.39}, "11": {"left_arm_vel": 0.481, "left_gripper_vel": 0.0, "left_arm_rx": -2.75, "left_arm_ry": 0.83, "left_arm_rz": 2.38, "left_gripper": 0.37, "right_arm_vel": 0.481, "right_gripper_vel": 0.0, "right_arm_rx": 2.37, "right_arm_ry": 0.57, "right_arm_rz": -3.01, "right_gripper": 0.39}, "12": {"left_arm_vel": 0.21, "left_gripper_vel": 0.0, "left_arm_rx": -2.84, "left_arm_ry": 0.81, "left_arm_rz": 2.2, "left_gripper": 0.37, "right_arm_vel": 0.21, "right_gripper_vel": 0.0, "right_arm_rx": 2.41, "right_arm_ry": 0.65, "right_arm_rz": -3.0, "right_gripper": 0.39}, "13": {"left_arm_vel": 0.087, "left_gripper_vel": 0.0, "left_arm_rx": -2.94, "left_arm_ry": 0.76, "left_arm_rz": 2.03, "left_gripper": 0.37, "right_arm_vel": 0.087, "right_gripper_vel": 0.0, "right_arm_rx": 2.43, "right_arm_ry": 0.69, "right_arm_rz": -2.99, "right_gripper": 0.39}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.22100000083446503, -0.04230000078678131, 0.06629999727010727], "delta_rot": [-0.23430000245571136, 0.10899999737739563, -0.37779998779296875], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.2346}, "right": {"delta_pos": [-0.1289999932050705, -0.17569999396800995, -0.013000000268220901], "delta_rot": [0.02019999921321869, 0.16380000114440918, -0.39750000834465027], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.2184}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.2094999998807907, -0.07859999686479568, 0.039799999445676804], "delta_rot": [-0.24899999797344208, 0.030899999663233757, -0.5065000057220459], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.2272}, "right": {"delta_pos": [-0.12950000166893005, -0.17640000581741333, -0.015599999576807022], "delta_rot": [0.05380000174045563, 0.20440000295639038, -0.3668999969959259], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.2194}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by holding the zipper pull, while right arm approaches and makes contact with the top surface near the opening to prepare for manipulation.", + "actions": [ + { + "reasoning_cot": "The left gripper is visually clamped onto the metal zipper pull of the bag. Kinematic data shows low velocity (0.37) and stable angle, indicating a static hold to anchor the object against potential movement from the other arm.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "static_at_zipper_pull", + "topology_change": false + }, + { + "reasoning_cot": "The right arm moves from a hovering position to make direct contact with the reflective top panel of the bag. The gripper remains open (width ~0.4), indicating an approach or positioning action rather than a grasp. This prepares the arm to interact with the bag's opening or contents.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": "position_for_opening", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "moving_from_hover_to_top_surface_contact", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:top_surface", + "current_status": "contacted" + } + ], + "task_progress": "Bag stabilized by left hand; right hand positioned on top surface to initiate opening or inspection." + } +} +```` +--- +## 🎬 ChunkAnnotator_7 + +### 👁️ 视觉输入 +![chunkannotator_7_img_0.jpg](./images/chunkannotator_7_img_0.jpg) +![chunkannotator_7_img_1.jpg](./images/chunkannotator_7_img_1.jpg) +![chunkannotator_7_img_2.jpg](./images/chunkannotator_7_img_2.jpg) +![chunkannotator_7_img_3.jpg](./images/chunkannotator_7_img_3.jpg) +![chunkannotator_7_img_4.jpg](./images/chunkannotator_7_img_4.jpg) +![chunkannotator_7_img_5.jpg](./images/chunkannotator_7_img_5.jpg) +![chunkannotator_7_img_6.jpg](./images/chunkannotator_7_img_6.jpg) +![chunkannotator_7_img_7.jpg](./images/chunkannotator_7_img_7.jpg) +![chunkannotator_7_img_8.jpg](./images/chunkannotator_7_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by holding the zipper pull, while right arm approaches and makes contact with the top surface near the opening to prepare for manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.12, "angle": 0.38, "vel_score": 0.36, "angle_score": 1.1, "vel_fft": [0.116, 0.042, 0.014, 0.021, 0.016, 0.016], "angle_fft": [0.377, 0.158, 0.079, 0.095, 0.07, 0.062]}, "right": {"vel": 0.01, "angle": 0.16, "vel_score": 0.01, "angle_score": 0.53, "vel_fft": [0.006, 0.004, 0.003, 0.002, 0.002, 0.002], "angle_fft": [0.159, 0.01, 0.023, 0.03, 0.021, 0.01]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 0.75, "left_arm_rz": 1.99, "left_gripper": 0.37, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.44, "right_arm_ry": 0.69, "right_arm_rz": -2.99, "right_gripper": 0.39}, "1": {"left_arm_vel": 0.026, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 0.74, "left_arm_rz": 1.96, "left_gripper": 0.37, "right_arm_vel": 0.026, "right_gripper_vel": 0.0, "right_arm_rx": 2.44, "right_arm_ry": 0.7, "right_arm_rz": -2.98, "right_gripper": 0.39}, "2": {"left_arm_vel": 0.009, "left_gripper_vel": 0.0, "left_arm_rx": -2.98, "left_arm_ry": 0.72, "left_arm_rz": 1.93, "left_gripper": 0.37, "right_arm_vel": 0.009, "right_gripper_vel": 0.0, "right_arm_rx": 2.45, "right_arm_ry": 0.71, "right_arm_rz": -2.99, "right_gripper": 0.39}, "3": {"left_arm_vel": 0.004, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 0.71, "left_arm_rz": 1.92, "left_gripper": 0.37, "right_arm_vel": 0.004, "right_gripper_vel": 0.0, "right_arm_rx": 2.45, "right_arm_ry": 0.71, "right_arm_rz": -2.98, "right_gripper": 0.39}, "4": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 0.69, "left_arm_rz": 1.91, "left_gripper": 0.37, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.45, "right_arm_ry": 0.72, "right_arm_rz": -2.98, "right_gripper": 0.39}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 0.69, "left_arm_rz": 1.9, "left_gripper": 0.37, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.46, "right_arm_ry": 0.73, "right_arm_rz": -2.97, "right_gripper": 0.39}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 0.68, "left_arm_rz": 1.9, "left_gripper": 0.37, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.46, "right_arm_ry": 0.73, "right_arm_rz": -2.96, "right_gripper": 0.39}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 0.68, "left_arm_rz": 1.9, "left_gripper": 0.37, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.46, "right_arm_ry": 0.73, "right_arm_rz": -2.96, "right_gripper": 0.39}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.010499999858438969, -0.02800000086426735, -0.023000000044703484], "delta_rot": [0.0026000000070780516, -0.06679999828338623, -0.09149999916553497], "gripper_changed": false, "flow_direction": "-Y(Right) and -Z(Down)", "magnitude": 0.0377}, "right": {"delta_pos": [0.0006000000284984708, -0.0003000000142492354, -0.0003000000142492354], "delta_rot": [0.02280000038444996, 0.03400000184774399, 0.02500000037252903], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0007}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.008100000210106373, -0.027499999850988388, -0.027400000020861626], "delta_rot": [-0.010700000450015068, -0.10279999673366547, -0.09929999709129333], "gripper_changed": false, "flow_direction": "-Y(Right) and -Z(Down)", "magnitude": 0.0396}, "right": {"delta_pos": [0.0142000000923872, 0.0478999987244606, -0.040800001472234726], "delta_rot": [0.3402999937534332, 0.013000000268220901, 0.296099990606308], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.0645}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by holding the top flap, while right arm approaches and makes contact with the zipper pull to prepare for opening.", + "actions": [ + { + "reasoning_cot": "The left arm is positioned over the bag's top surface/flap. Kinematic data shows a small downward/rightward adjustment (-Y, -Z) consistent with settling into a stable hold or pressing down to secure the object against table friction. Visuals confirm the gripper is in contact with the top material.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "stabilizing_at_top_flap", + "topology_change": false + }, + { + "reasoning_cot": "The right arm executes a precise approach trajectory towards the side of the bag where the zipper mechanism is located. The hindsight flow indicates a final downward movement (+Y relative to bag orientation, -Z absolute) to make contact. The gripper remains open but transitions from free space to touching the zipper pull area.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving_from_hover_to_zipper_contact", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "contacted" + } + ], + "task_progress": "Right arm has successfully located and contacted the zipper pull; left arm maintains bag stability." + } +} +```` +--- +## 🎬 ChunkAnnotator_8 + +### 👁️ 视觉输入 +![chunkannotator_8_img_0.jpg](./images/chunkannotator_8_img_0.jpg) +![chunkannotator_8_img_1.jpg](./images/chunkannotator_8_img_1.jpg) +![chunkannotator_8_img_2.jpg](./images/chunkannotator_8_img_2.jpg) +![chunkannotator_8_img_3.jpg](./images/chunkannotator_8_img_3.jpg) +![chunkannotator_8_img_4.jpg](./images/chunkannotator_8_img_4.jpg) +![chunkannotator_8_img_5.jpg](./images/chunkannotator_8_img_5.jpg) +![chunkannotator_8_img_6.jpg](./images/chunkannotator_8_img_6.jpg) +![chunkannotator_8_img_7.jpg](./images/chunkannotator_8_img_7.jpg) +![chunkannotator_8_img_8.jpg](./images/chunkannotator_8_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by holding the top flap, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.01, "angle": 0.06, "vel_score": 0.08, "angle_score": 0.62, "vel_fft": [0.008, 0.005, 0.002, 0.0, 0.001, 0.001, 0.002, 0.001, 0.001, 0.001, 0.001, 0.0, 0.0, 0.001, 0.001, 0.0, 0.001, 0.001, 0.001, 0.001], "angle_fft": [0.063, 0.035, 0.016, 0.013, 0.007, 0.007, 0.014, 0.007, 0.006, 0.007, 0.003, 0.004, 0.004, 0.004, 0.006, 0.004, 0.007, 0.002, 0.002, 0.005]}, "right": {"vel": 0.05, "angle": 0.32, "vel_score": 0.53, "angle_score": 3.2, "vel_fft": [0.054, 0.001, 0.025, 0.007, 0.011, 0.006, 0.006, 0.003, 0.001, 0.002, 0.0, 0.001, 0.001, 0.001, 0.001, 0.002, 0.001, 0.001, 0.001, 0.002], "angle_fft": [0.323, 0.15, 0.087, 0.027, 0.031, 0.014, 0.023, 0.016, 0.023, 0.012, 0.008, 0.015, 0.012, 0.007, 0.02, 0.009, 0.011, 0.007, 0.005, 0.008]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 0.68, "left_arm_rz": 1.9, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.47, "right_arm_ry": 0.73, "right_arm_rz": -2.95, "right_gripper": 0.39}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 0.67, "left_arm_rz": 1.89, "left_gripper": 0.3, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.48, "right_arm_ry": 0.74, "right_arm_rz": -2.94, "right_gripper": 0.39}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.94, "left_arm_ry": 0.65, "left_arm_rz": 1.89, "left_gripper": 0.27, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.48, "right_arm_ry": 0.74, "right_arm_rz": -2.93, "right_gripper": 0.39}, "3": {"left_arm_vel": 0.016, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.65, "left_arm_rz": 1.89, "left_gripper": 0.2, "right_arm_vel": 0.016, "right_gripper_vel": 0.0, "right_arm_rx": 2.48, "right_arm_ry": 0.74, "right_arm_rz": -2.93, "right_gripper": 0.39}, "4": {"left_arm_vel": 0.042, "left_gripper_vel": -0.063, "left_arm_rx": -2.95, "left_arm_ry": 0.65, "left_arm_rz": 1.89, "left_gripper": 0.14, "right_arm_vel": 0.042, "right_gripper_vel": -0.063, "right_arm_rx": 2.48, "right_arm_ry": 0.73, "right_arm_rz": -2.93, "right_gripper": 0.39}, "5": {"left_arm_vel": 0.074, "left_gripper_vel": -0.126, "left_arm_rx": -2.96, "left_arm_ry": 0.65, "left_arm_rz": 1.89, "left_gripper": 0.09, "right_arm_vel": 0.074, "right_gripper_vel": -0.126, "right_arm_rx": 2.48, "right_arm_ry": 0.73, "right_arm_rz": -2.91, "right_gripper": 0.38}, "6": {"left_arm_vel": 0.118, "left_gripper_vel": -0.084, "left_arm_rx": -2.96, "left_arm_ry": 0.64, "left_arm_rz": 1.89, "left_gripper": 0.05, "right_arm_vel": 0.118, "right_gripper_vel": -0.084, "right_arm_rx": 2.49, "right_arm_ry": 0.73, "right_arm_rz": -2.9, "right_gripper": 0.38}, "7": {"left_arm_vel": 0.119, "left_gripper_vel": -0.021, "left_arm_rx": -2.96, "left_arm_ry": 0.64, "left_arm_rz": 1.89, "left_gripper": 0.04, "right_arm_vel": 0.119, "right_gripper_vel": -0.021, "right_arm_rx": 2.48, "right_arm_ry": 0.72, "right_arm_rz": -2.89, "right_gripper": 0.38}, "8": {"left_arm_vel": 0.08, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.64, "left_arm_rz": 1.9, "left_gripper": 0.04, "right_arm_vel": 0.08, "right_gripper_vel": 0.0, "right_arm_rx": 2.5, "right_arm_ry": 0.7, "right_arm_rz": -2.83, "right_gripper": 0.38}, "9": {"left_arm_vel": 0.031, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 0.65, "left_arm_rz": 1.89, "left_gripper": 0.04, "right_arm_vel": 0.031, "right_gripper_vel": 0.0, "right_arm_rx": 2.59, "right_arm_ry": 0.71, "right_arm_rz": -2.78, "right_gripper": 0.38}, "10": {"left_arm_vel": 0.04, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 0.65, "left_arm_rz": 1.89, "left_gripper": 0.04, "right_arm_vel": 0.04, "right_gripper_vel": 0.0, "right_arm_rx": 2.71, "right_arm_ry": 0.71, "right_arm_rz": -2.73, "right_gripper": 0.38}, "11": {"left_arm_vel": 0.112, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 0.65, "left_arm_rz": 1.89, "left_gripper": 0.04, "right_arm_vel": 0.112, "right_gripper_vel": 0.0, "right_arm_rx": 2.78, "right_arm_ry": 0.71, "right_arm_rz": -2.68, "right_gripper": 0.38}, "12": {"left_arm_vel": 0.092, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 0.65, "left_arm_rz": 1.89, "left_gripper": 0.04, "right_arm_vel": 0.092, "right_gripper_vel": 0.0, "right_arm_rx": 2.78, "right_arm_ry": 0.71, "right_arm_rz": -2.68, "right_gripper": 0.38}, "13": {"left_arm_vel": 0.088, "left_gripper_vel": -0.168, "left_arm_rx": -2.97, "left_arm_ry": 0.65, "left_arm_rz": 1.89, "left_gripper": 0.04, "right_arm_vel": 0.088, "right_gripper_vel": -0.168, "right_arm_rx": 2.78, "right_arm_ry": 0.71, "right_arm_rz": -2.69, "right_gripper": 0.37}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0024999999441206455, 0.0005000000237487257, -0.0044999998062849045], "delta_rot": [-0.013799999840557575, -0.03539999946951866, -0.007400000002235174], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0051}, "right": {"delta_pos": [0.013700000010430813, 0.04830000177025795, -0.040300000458955765], "delta_rot": [0.3095000088214874, -0.024000000208616257, 0.2612999975681305], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.0644}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.0034000000450760126, -0.0007999999797903001, -0.005400000140070915], "delta_rot": [0.00860000029206276, -0.0681999996304512, 0.09849999845027924], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0064}, "right": {"delta_pos": [-0.1200999990105629, 0.16910000145435333, -0.0010000000474974513], "delta_rot": [0.18940000236034393, -0.09040000289678574, 0.3944000005722046], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left)", "magnitude": 0.2074}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by holding the top flap, while right arm approaches and makes contact with the zipper pull to prepare for opening.", + "actions": [ + { + "reasoning_cot": "The left arm is visually confirmed to be in contact with the top edge of the bag's main body (specifically the flap area) to provide stability. The gripper is closed around this soft material, indicating a 'hold' action to prevent the bag from shifting while the other arm operates the zipper.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "static_at_top_flap", + "topology_change": false + }, + { + "reasoning_cot": "The right arm executes a precise approach trajectory towards the metal ring attached to the zipper slider. Visual evidence shows the gripper tips making contact with the ring at the end of the sequence. This is a preparatory grasp action targeting the specific mechanism required to open the bag.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": "target_zipper_pull", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving_from_free_space_to_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "contacted" + } + ], + "task_progress": "Right arm has successfully located and touched the zipper pull; left arm maintains bag stability." + } +} +```` +--- +## 🎬 ChunkAnnotator_9 + +### 👁️ 视觉输入 +![chunkannotator_9_img_0.jpg](./images/chunkannotator_9_img_0.jpg) +![chunkannotator_9_img_1.jpg](./images/chunkannotator_9_img_1.jpg) +![chunkannotator_9_img_2.jpg](./images/chunkannotator_9_img_2.jpg) +![chunkannotator_9_img_3.jpg](./images/chunkannotator_9_img_3.jpg) +![chunkannotator_9_img_4.jpg](./images/chunkannotator_9_img_4.jpg) +![chunkannotator_9_img_5.jpg](./images/chunkannotator_9_img_5.jpg) +![chunkannotator_9_img_6.jpg](./images/chunkannotator_9_img_6.jpg) +![chunkannotator_9_img_7.jpg](./images/chunkannotator_9_img_7.jpg) +![chunkannotator_9_img_8.jpg](./images/chunkannotator_9_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by holding the top flap, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.0, "angle": 0.08, "vel_score": 0.05, "angle_score": 0.84, "vel_fft": [0.005, 0.001, 0.002, 0.001, 0.001, 0.001, 0.0, 0.0, 0.001, 0.001, 0.0, 0.0, 0.001, 0.001, 0.001, 0.0, 0.001, 0.001, 0.001, 0.0], "angle_fft": [0.084, 0.023, 0.029, 0.01, 0.008, 0.013, 0.016, 0.008, 0.005, 0.004, 0.006, 0.013, 0.01, 0.009, 0.008, 0.003, 0.005, 0.0, 0.007, 0.005]}, "right": {"vel": 0.17, "angle": 0.39, "vel_score": 1.81, "angle_score": 3.97, "vel_fft": [0.173, 0.055, 0.041, 0.023, 0.012, 0.003, 0.006, 0.003, 0.004, 0.007, 0.007, 0.003, 0.004, 0.004, 0.002, 0.006, 0.002, 0.004, 0.003, 0.004], "angle_fft": [0.392, 0.093, 0.073, 0.072, 0.054, 0.021, 0.03, 0.041, 0.006, 0.014, 0.027, 0.011, 0.01, 0.01, 0.004, 0.016, 0.016, 0.008, 0.007, 0.017]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 0.65, "left_arm_rz": 1.89, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.78, "right_arm_ry": 0.71, "right_arm_rz": -2.69, "right_gripper": 0.36}, "1": {"left_arm_vel": 0.057, "left_gripper_vel": -2.1, "left_arm_rx": -2.97, "left_arm_ry": 0.65, "left_arm_rz": 1.89, "left_gripper": 0.04, "right_arm_vel": 0.057, "right_gripper_vel": -2.1, "right_arm_rx": 2.79, "right_arm_ry": 0.72, "right_arm_rz": -2.69, "right_gripper": 0.16}, "2": {"left_arm_vel": 0.045, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 0.65, "left_arm_rz": 1.89, "left_gripper": 0.04, "right_arm_vel": 0.045, "right_gripper_vel": 0.0, "right_arm_rx": 2.77, "right_arm_ry": 0.69, "right_arm_rz": -2.7, "right_gripper": 0.01}, "3": {"left_arm_vel": 0.225, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 0.63, "left_arm_rz": 1.92, "left_gripper": 0.04, "right_arm_vel": 0.225, "right_gripper_vel": 0.0, "right_arm_rx": 2.78, "right_arm_ry": 0.62, "right_arm_rz": -2.71, "right_gripper": 0.01}, "4": {"left_arm_vel": 0.173, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.62, "left_arm_rz": 1.95, "left_gripper": 0.04, "right_arm_vel": 0.173, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 0.63, "right_arm_rz": -2.72, "right_gripper": 0.01}, "5": {"left_arm_vel": 0.398, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.62, "left_arm_rz": 1.97, "left_gripper": 0.04, "right_arm_vel": 0.398, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.68, "right_arm_rz": -2.54, "right_gripper": 0.01}, "6": {"left_arm_vel": 0.292, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.62, "left_arm_rz": 1.99, "left_gripper": 0.04, "right_arm_vel": 0.292, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.68, "right_arm_rz": -2.48, "right_gripper": 0.01}, "7": {"left_arm_vel": 0.157, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.157, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.64, "right_arm_rz": -2.56, "right_gripper": 0.01}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0007999999797903001, -0.0013000000035390258, -0.0008999999845400453], "delta_rot": [0.022700000554323196, -0.032499998807907104, 0.10620000213384628], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0018}, "right": {"delta_pos": [-0.13609999418258667, 0.12039999663829803, 0.04010000079870224], "delta_rot": [-0.120899997651577, -0.0674000009894371, 0.1356000006198883], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1861}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.000699999975040555, -0.0012000000569969416, -0.0007999999797903001], "delta_rot": [0.023900000378489494, -0.03359999880194664, 0.1062999963760376], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0016}, "right": {"delta_pos": [-0.16179999709129333, 0.05180000141263008, 0.02669999934732914], "delta_rot": [0.030400000512599945, -0.03680000081658363, -0.16410000622272491], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.172}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by holding the top flap, while right arm approaches and makes contact with the zipper pull to prepare for opening.", + "actions": [ + { + "reasoning_cot": "The left arm maintains a static position on the bag's top surface. Visual evidence shows the gripper is closed around the fabric edge, providing stability against the forces applied by the right arm. The kinematic data confirms zero velocity (idle) but high grip force maintenance.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "static_at_top_flap", + "topology_change": false + }, + { + "reasoning_cot": "The right arm executes a significant spatial displacement (-X, +Y, +Z) moving from an open position towards the side of the bag. The gripper closes (signal: closing) precisely as it reaches the metal ring/zipper pull area. This indicates a transition from approaching to grasping the specific manipulation point.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "touching" + }, + "action_verb": "grasp", + "semantic_action": "approach_zipper", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving_from_free_space_to_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "contacted" + } + ], + "task_progress": "Right arm has successfully located and initiated grasp on the zipper pull; left arm continues stabilization." + } +} +```` +--- +## 🎬 ChunkAnnotator_10 + +### 👁️ 视觉输入 +![chunkannotator_10_img_0.jpg](./images/chunkannotator_10_img_0.jpg) +![chunkannotator_10_img_1.jpg](./images/chunkannotator_10_img_1.jpg) +![chunkannotator_10_img_2.jpg](./images/chunkannotator_10_img_2.jpg) +![chunkannotator_10_img_3.jpg](./images/chunkannotator_10_img_3.jpg) +![chunkannotator_10_img_4.jpg](./images/chunkannotator_10_img_4.jpg) +![chunkannotator_10_img_5.jpg](./images/chunkannotator_10_img_5.jpg) +![chunkannotator_10_img_6.jpg](./images/chunkannotator_10_img_6.jpg) +![chunkannotator_10_img_7.jpg](./images/chunkannotator_10_img_7.jpg) +![chunkannotator_10_img_8.jpg](./images/chunkannotator_10_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by holding the top flap, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.0, "angle": 0.01, "vel_score": 0.0, "angle_score": 0.04, "vel_fft": [0.001, 0.0, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.001, 0.001], "angle_fft": [0.009, 0.002, 0.003, 0.004, 0.003, 0.001, 0.003, 0.003, 0.007, 0.002]}, "right": {"vel": 0.12, "angle": 0.56, "vel_score": 0.63, "angle_score": 2.98, "vel_fft": [0.118, 0.054, 0.036, 0.017, 0.01, 0.011, 0.012, 0.011, 0.006, 0.008], "angle_fft": [0.564, 0.103, 0.042, 0.077, 0.021, 0.041, 0.042, 0.031, 0.045, 0.025]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.62, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.63, "right_arm_rz": -2.58, "right_gripper": 0.01}, "1": {"left_arm_vel": 0.313, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.313, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 0.62, "right_arm_rz": -2.63, "right_gripper": 0.01}, "2": {"left_arm_vel": 0.282, "left_gripper_vel": 0.42, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.282, "right_gripper_vel": 0.42, "right_arm_rx": 2.72, "right_arm_ry": 0.62, "right_arm_rz": -2.66, "right_gripper": 0.03}, "3": {"left_arm_vel": 0.235, "left_gripper_vel": 1.071, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.235, "right_gripper_vel": 1.071, "right_arm_rx": 2.74, "right_arm_ry": 0.62, "right_arm_rz": -2.67, "right_gripper": 0.06}, "4": {"left_arm_vel": 0.149, "left_gripper_vel": 1.596, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.149, "right_gripper_vel": 1.596, "right_arm_rx": 2.76, "right_arm_ry": 0.63, "right_arm_rz": -2.68, "right_gripper": 0.12}, "5": {"left_arm_vel": 0.116, "left_gripper_vel": 1.68, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.116, "right_gripper_vel": 1.68, "right_arm_rx": 2.76, "right_arm_ry": 0.64, "right_arm_rz": -2.7, "right_gripper": 0.17}, "6": {"left_arm_vel": 0.067, "left_gripper_vel": 2.163, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.067, "right_gripper_vel": 2.163, "right_arm_rx": 2.76, "right_arm_ry": 0.65, "right_arm_rz": -2.73, "right_gripper": 0.24}, "7": {"left_arm_vel": 0.054, "left_gripper_vel": 2.016, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.054, "right_gripper_vel": 2.016, "right_arm_rx": 2.76, "right_arm_ry": 0.65, "right_arm_rz": -2.75, "right_gripper": 0.31}, "8": {"left_arm_vel": 0.042, "left_gripper_vel": 1.554, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.042, "right_gripper_vel": 1.554, "right_arm_rx": 2.76, "right_arm_ry": 0.66, "right_arm_rz": -2.78, "right_gripper": 0.36}, "9": {"left_arm_vel": 0.033, "left_gripper_vel": 0.819, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.033, "right_gripper_vel": 0.819, "right_arm_rx": 2.76, "right_arm_ry": 0.66, "right_arm_rz": -2.8, "right_gripper": 0.39}, "10": {"left_arm_vel": 0.052, "left_gripper_vel": 0.609, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.052, "right_gripper_vel": 0.609, "right_arm_rx": 2.76, "right_arm_ry": 0.65, "right_arm_rz": -2.81, "right_gripper": 0.41}, "11": {"left_arm_vel": 0.06, "left_gripper_vel": 0.378, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.06, "right_gripper_vel": 0.378, "right_arm_rx": 2.76, "right_arm_ry": 0.65, "right_arm_rz": -2.82, "right_gripper": 0.42}, "12": {"left_arm_vel": 0.073, "left_gripper_vel": 0.147, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.073, "right_gripper_vel": 0.147, "right_arm_rx": 2.78, "right_arm_ry": 0.65, "right_arm_rz": -2.84, "right_gripper": 0.43}, "13": {"left_arm_vel": 0.038, "left_gripper_vel": 0.042, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.038, "right_gripper_vel": 0.042, "right_arm_rx": 2.81, "right_arm_ry": 0.67, "right_arm_rz": -2.86, "right_gripper": 0.44}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-9.999999747378752e-05, 9.999999747378752e-05, 9.999999747378752e-05], "delta_rot": [0.00039999998989515007, -0.001500000013038516, -0.00039999998989515007], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0002}, "right": {"delta_pos": [-0.021700000390410423, -0.061799999326467514, -0.012600000016391277], "delta_rot": [0.1395999938249588, 0.03739999979734421, -0.27970001101493835], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.0667}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-9.999999747378752e-05, -0.0, 0.00039999998989515007], "delta_rot": [0.0006000000284984708, -0.00039999998989515007, -0.0003000000142492354], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0004}, "right": {"delta_pos": [-0.03350000083446503, -0.07069999724626541, -0.008200000040233135], "delta_rot": [0.21089999377727509, 0.121799997985363, -0.30070000886917114], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.0786}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", + "actions": [ + { + "reasoning_cot": "The left arm is visually confirmed in contact with the bag's top surface/flap (silver interior visible). Kinematic data shows near-zero velocity (0.0) and stable gripper width (0.03), indicating a static hold to stabilize the object against the table.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "static_at_top_flap", + "topology_change": false + }, + { + "reasoning_cot": "The right arm executes a significant approach trajectory (-Y/Right, -X/Backward) with a magnitude of ~0.07m. The gripper opens from 0.01 to 0.44, transitioning from closed to fully open. Visuals show the gripper moving towards and hovering over the zipper pull area, preparing to grasp it.", + "causal_trace": { + "gripper_signal": "opening", + "visual_contact": "none" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving_from_free_space_to_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Approaching zipper pull with right arm while stabilizing bag with left arm." + } +} +```` +--- +## 🎬 ChunkAnnotator_11 + +### 👁️ 视觉输入 +![chunkannotator_11_img_0.jpg](./images/chunkannotator_11_img_0.jpg) +![chunkannotator_11_img_1.jpg](./images/chunkannotator_11_img_1.jpg) +![chunkannotator_11_img_2.jpg](./images/chunkannotator_11_img_2.jpg) +![chunkannotator_11_img_3.jpg](./images/chunkannotator_11_img_3.jpg) +![chunkannotator_11_img_4.jpg](./images/chunkannotator_11_img_4.jpg) +![chunkannotator_11_img_5.jpg](./images/chunkannotator_11_img_5.jpg) +![chunkannotator_11_img_6.jpg](./images/chunkannotator_11_img_6.jpg) +![chunkannotator_11_img_7.jpg](./images/chunkannotator_11_img_7.jpg) +![chunkannotator_11_img_8.jpg](./images/chunkannotator_11_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.0, "angle": 0.0, "vel_score": 0.0, "angle_score": 0.04, "vel_fft": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "angle_fft": [0.003, 0.002, 0.0, 0.001, 0.0, 0.001, 0.001, 0.001, 0.002, 0.003, 0.001, 0.001, 0.001, 0.001, 0.001, 0.0, 0.002, 0.002, 0.002, 0.001]}, "right": {"vel": 0.12, "angle": 0.52, "vel_score": 1.21, "angle_score": 4.96, "vel_fft": [0.12, 0.031, 0.017, 0.032, 0.023, 0.023, 0.008, 0.011, 0.001, 0.004, 0.002, 0.002, 0.004, 0.004, 0.004, 0.003, 0.002, 0.001, 0.002, 0.002], "angle_fft": [0.522, 0.057, 0.072, 0.082, 0.009, 0.027, 0.026, 0.051, 0.034, 0.028, 0.043, 0.023, 0.03, 0.004, 0.019, 0.017, 0.018, 0.024, 0.016, 0.011]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.82, "right_arm_ry": 0.68, "right_arm_rz": -2.86, "right_gripper": 0.44}, "1": {"left_arm_vel": 0.141, "left_gripper_vel": -1.281, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.141, "right_gripper_vel": -1.281, "right_arm_rx": 2.91, "right_arm_ry": 0.73, "right_arm_rz": -2.88, "right_gripper": 0.37}, "2": {"left_arm_vel": 0.043, "left_gripper_vel": -3.045, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.043, "right_gripper_vel": -3.045, "right_arm_rx": 2.94, "right_arm_ry": 0.74, "right_arm_rz": -2.87, "right_gripper": 0.12}, "3": {"left_arm_vel": 0.054, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.054, "right_gripper_vel": 0.0, "right_arm_rx": 2.9, "right_arm_ry": 0.73, "right_arm_rz": -2.83, "right_gripper": 0.01}, "4": {"left_arm_vel": 0.141, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.141, "right_gripper_vel": 0.0, "right_arm_rx": 2.81, "right_arm_ry": 0.75, "right_arm_rz": -2.7, "right_gripper": 0.01}, "5": {"left_arm_vel": 0.376, "left_gripper_vel": 2.289, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.376, "right_gripper_vel": 2.289, "right_arm_rx": 2.78, "right_arm_ry": 0.66, "right_arm_rz": -2.81, "right_gripper": 0.18}, "6": {"left_arm_vel": 0.216, "left_gripper_vel": 2.709, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.216, "right_gripper_vel": 2.709, "right_arm_rx": 2.82, "right_arm_ry": 0.68, "right_arm_rz": -2.84, "right_gripper": 0.34}, "7": {"left_arm_vel": 0.098, "left_gripper_vel": 0.693, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.098, "right_gripper_vel": 0.693, "right_arm_rx": 2.88, "right_arm_ry": 0.76, "right_arm_rz": -2.88, "right_gripper": 0.49}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [9.999999747378752e-05, -0.0, 0.0003000000142492354], "delta_rot": [-0.0007999999797903001, 0.0005000000237487257, -0.0006000000284984708], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0003}, "right": {"delta_pos": [-0.012799999676644802, -0.008100000210106373, 0.00430000014603138], "delta_rot": [0.06390000134706497, 0.07760000228881836, -0.01510000042617321], "gripper_changed": true, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0158}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-9.999999747378752e-05, 0.00139999995008111, 0.0003000000142492354], "delta_rot": [0.01759999990463257, -0.0038999998942017555, 0.01119999960064888], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0014}, "right": {"delta_pos": [0.05130000039935112, 0.10700000077486038, 0.009700000286102295], "delta_rot": [-0.06560000032186508, 0.05380000174045563, 0.16670000553131104], "gripper_changed": true, "flow_direction": "+X(Forward) and +Y(Left)", "magnitude": 0.119}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", + "actions": [ + { + "reasoning_cot": "The left gripper is visually clamped onto the silver mesh interior of the bag's top flap. Kinematic data shows zero velocity (vel: 0.0) and stable gripper width, indicating a static hold to maintain the bag's opening for the right arm's operation.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "static_at_top_flap_interior", + "topology_change": false + }, + { + "reasoning_cot": "The right arm executes a precise approach trajectory towards the bag's side hardware. Visual sequence shows the gripper moving from free space to directly over the metal zipper pull. The gripper closes significantly (width 0.44 -> 0.01) to secure the target, confirming a grasp action on the zipper mechanism.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": "target_zipper_pull", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving_from_free_space_to_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped" + } + ], + "task_progress": "Right arm has successfully located and grasped the zipper pull while left arm maintains bag stability." + } +} +```` +--- +## 🎬 ChunkAnnotator_12 + +### 👁️ 视觉输入 +![chunkannotator_12_img_0.jpg](./images/chunkannotator_12_img_0.jpg) +![chunkannotator_12_img_1.jpg](./images/chunkannotator_12_img_1.jpg) +![chunkannotator_12_img_2.jpg](./images/chunkannotator_12_img_2.jpg) +![chunkannotator_12_img_3.jpg](./images/chunkannotator_12_img_3.jpg) +![chunkannotator_12_img_4.jpg](./images/chunkannotator_12_img_4.jpg) +![chunkannotator_12_img_5.jpg](./images/chunkannotator_12_img_5.jpg) +![chunkannotator_12_img_6.jpg](./images/chunkannotator_12_img_6.jpg) +![chunkannotator_12_img_7.jpg](./images/chunkannotator_12_img_7.jpg) +![chunkannotator_12_img_8.jpg](./images/chunkannotator_12_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.0, "angle": 0.02, "vel_score": 0.02, "angle_score": 0.18, "vel_fft": [0.002, 0.001, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.001, 0.001, 0.001], "angle_fft": [0.021, 0.009, 0.006, 0.002, 0.007, 0.006, 0.004, 0.004, 0.004, 0.003, 0.004, 0.003, 0.005, 0.005, 0.003, 0.004, 0.002, 0.004, 0.005, 0.005]}, "right": {"vel": 0.1, "angle": 0.33, "vel_score": 0.99, "angle_score": 3.13, "vel_fft": [0.096, 0.019, 0.04, 0.009, 0.009, 0.005, 0.003, 0.002, 0.004, 0.002, 0.001, 0.003, 0.001, 0.001, 0.002, 0.004, 0.001, 0.0, 0.0, 0.001], "angle_fft": [0.327, 0.038, 0.045, 0.059, 0.041, 0.023, 0.015, 0.004, 0.026, 0.011, 0.014, 0.011, 0.008, 0.006, 0.011, 0.023, 0.001, 0.008, 0.014, 0.016]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.89, "right_arm_ry": 0.77, "right_arm_rz": -2.88, "right_gripper": 0.5}, "1": {"left_arm_vel": 0.147, "left_gripper_vel": -0.042, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.147, "right_gripper_vel": -0.042, "right_arm_rx": 2.97, "right_arm_ry": 0.85, "right_arm_rz": -2.85, "right_gripper": 0.52}, "2": {"left_arm_vel": 0.065, "left_gripper_vel": -3.171, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.065, "right_gripper_vel": -3.171, "right_arm_rx": 3.0, "right_arm_ry": 0.82, "right_arm_rz": -2.87, "right_gripper": 0.31}, "3": {"left_arm_vel": 0.02, "left_gripper_vel": -1.344, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.02, "right_gripper_vel": -1.344, "right_arm_rx": 2.99, "right_arm_ry": 0.8, "right_arm_rz": -2.87, "right_gripper": 0.05}, "4": {"left_arm_vel": 0.072, "left_gripper_vel": -0.021, "left_arm_rx": -2.94, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.072, "right_gripper_vel": -0.021, "right_arm_rx": 2.94, "right_arm_ry": 0.76, "right_arm_rz": -2.81, "right_gripper": 0.01}, "5": {"left_arm_vel": 0.216, "left_gripper_vel": 0.0, "left_arm_rx": -2.94, "left_arm_ry": 0.61, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.216, "right_gripper_vel": 0.0, "right_arm_rx": 2.85, "right_arm_ry": 0.79, "right_arm_rz": -2.77, "right_gripper": 0.01}, "6": {"left_arm_vel": 0.214, "left_gripper_vel": 0.0, "left_arm_rx": -2.94, "left_arm_ry": 0.62, "left_arm_rz": 2.0, "left_gripper": 0.03, "right_arm_vel": 0.214, "right_gripper_vel": 0.0, "right_arm_rx": 2.79, "right_arm_ry": 0.76, "right_arm_rz": -2.73, "right_gripper": 0.01}, "7": {"left_arm_vel": 0.02, "left_gripper_vel": 0.231, "left_arm_rx": -2.93, "left_arm_ry": 0.61, "left_arm_rz": 2.01, "left_gripper": 0.03, "right_arm_vel": 0.02, "right_gripper_vel": 0.231, "right_arm_rx": 2.75, "right_arm_ry": 0.73, "right_arm_rz": -2.7, "right_gripper": 0.02}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-9.999999747378752e-05, 0.00139999995008111, 9.999999747378752e-05], "delta_rot": [0.018400000408291817, -0.004399999976158142, 0.011800000444054604], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0014}, "right": {"delta_pos": [0.06239999830722809, 0.11569999903440475, 0.0038999998942017555], "delta_rot": [-0.13860000669956207, -0.03799999877810478, 0.18780000507831573], "gripper_changed": true, "flow_direction": "+X(Forward) and +Y(Left)", "magnitude": 0.1315}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.04809999838471413, 0.07029999792575836, 0.07769999653100967], "delta_rot": [-0.01080000028014183, -0.044599998742341995, 0.32519999146461487], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1153}, "right": {"delta_pos": [0.02410000003874302, -0.014600000344216824, 0.0812000036239624], "delta_rot": [-0.13269999623298645, -0.20990000665187836, 0.0746999979019165], "gripper_changed": true, "flow_direction": "+X(Forward) and +Z(Up)", "magnitude": 0.0859}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", + "actions": [ + { + "reasoning_cot": "The left arm maintains a static position on the bag's top surface/flap. Visual evidence shows the gripper is closed around the material, providing stability against the forces applied by the right arm. No significant movement or topology change occurs on this side.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "static_at_top_flap", + "topology_change": false + }, + { + "reasoning_cot": "The right arm executes a precise approach trajectory towards the zipper mechanism. Kinematic data shows forward (+X) and leftward (+Y) displacement ending in a gripper closure event (closing signal). Visually, the gripper jaws align with and clamp onto the metal zipper pull tab, transitioning from free space to secured contact.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": "engage_zipper", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving_from_free_space_to_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped" + } + ], + "task_progress": "Right arm has successfully located and grasped the zipper pull; left arm continues to stabilize the bag opening." + } +} +```` +--- +## 🎬 ChunkAnnotator_13 + +### 👁️ 视觉输入 +![chunkannotator_13_img_0.jpg](./images/chunkannotator_13_img_0.jpg) +![chunkannotator_13_img_1.jpg](./images/chunkannotator_13_img_1.jpg) +![chunkannotator_13_img_2.jpg](./images/chunkannotator_13_img_2.jpg) +![chunkannotator_13_img_3.jpg](./images/chunkannotator_13_img_3.jpg) +![chunkannotator_13_img_4.jpg](./images/chunkannotator_13_img_4.jpg) +![chunkannotator_13_img_5.jpg](./images/chunkannotator_13_img_5.jpg) +![chunkannotator_13_img_6.jpg](./images/chunkannotator_13_img_6.jpg) +![chunkannotator_13_img_7.jpg](./images/chunkannotator_13_img_7.jpg) +![chunkannotator_13_img_8.jpg](./images/chunkannotator_13_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.17, "angle": 0.46, "vel_score": 1.04, "angle_score": 2.78, "vel_fft": [0.172, 0.06, 0.024, 0.025, 0.012, 0.012, 0.012, 0.016, 0.007, 0.01, 0.014, 0.004, 0.006], "angle_fft": [0.463, 0.033, 0.093, 0.087, 0.031, 0.041, 0.021, 0.017, 0.024, 0.019, 0.029, 0.026, 0.026]}, "right": {"vel": 0.22, "angle": 0.6, "vel_score": 1.38, "angle_score": 3.62, "vel_fft": [0.222, 0.063, 0.046, 0.02, 0.008, 0.01, 0.016, 0.006, 0.007, 0.004, 0.006, 0.008, 0.003], "angle_fft": [0.6, 0.128, 0.061, 0.063, 0.075, 0.04, 0.059, 0.004, 0.052, 0.041, 0.012, 0.012, 0.013]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.92, "left_arm_ry": 0.61, "left_arm_rz": 2.01, "left_gripper": 0.03, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.75, "right_arm_ry": 0.72, "right_arm_rz": -2.69, "right_gripper": 0.05}, "1": {"left_arm_vel": 0.097, "left_gripper_vel": 2.079, "left_arm_rx": -2.92, "left_arm_ry": 0.61, "left_arm_rz": 2.02, "left_gripper": 0.05, "right_arm_vel": 0.097, "right_gripper_vel": 2.079, "right_arm_rx": 2.71, "right_arm_ry": 0.68, "right_arm_rz": -2.66, "right_gripper": 0.16}, "2": {"left_arm_vel": 0.126, "left_gripper_vel": 2.037, "left_arm_rx": -2.92, "left_arm_ry": 0.61, "left_arm_rz": 2.04, "left_gripper": 0.08, "right_arm_vel": 0.126, "right_gripper_vel": 2.037, "right_arm_rx": 2.69, "right_arm_ry": 0.65, "right_arm_rz": -2.65, "right_gripper": 0.23}, "3": {"left_arm_vel": 0.167, "left_gripper_vel": 2.436, "left_arm_rx": -2.91, "left_arm_ry": 0.61, "left_arm_rz": 2.05, "left_gripper": 0.12, "right_arm_vel": 0.167, "right_gripper_vel": 2.436, "right_arm_rx": 2.67, "right_arm_ry": 0.62, "right_arm_rz": -2.66, "right_gripper": 0.31}, "4": {"left_arm_vel": 0.249, "left_gripper_vel": 1.806, "left_arm_rx": -2.9, "left_arm_ry": 0.61, "left_arm_rz": 2.07, "left_gripper": 0.17, "right_arm_vel": 0.249, "right_gripper_vel": 1.806, "right_arm_rx": 2.66, "right_arm_ry": 0.6, "right_arm_rz": -2.66, "right_gripper": 0.37}, "5": {"left_arm_vel": 0.362, "left_gripper_vel": 0.882, "left_arm_rx": -2.89, "left_arm_ry": 0.61, "left_arm_rz": 2.1, "left_gripper": 0.21, "right_arm_vel": 0.362, "right_gripper_vel": 0.882, "right_arm_rx": 2.67, "right_arm_ry": 0.58, "right_arm_rz": -2.67, "right_gripper": 0.4}, "6": {"left_arm_vel": 0.446, "left_gripper_vel": 0.567, "left_arm_rx": -2.88, "left_arm_ry": 0.6, "left_arm_rz": 2.12, "left_gripper": 0.25, "right_arm_vel": 0.446, "right_gripper_vel": 0.567, "right_arm_rx": 2.68, "right_arm_ry": 0.57, "right_arm_rz": -2.7, "right_gripper": 0.42}, "7": {"left_arm_vel": 0.461, "left_gripper_vel": 0.336, "left_arm_rx": -2.87, "left_arm_ry": 0.59, "left_arm_rz": 2.14, "left_gripper": 0.27, "right_arm_vel": 0.461, "right_gripper_vel": 0.336, "right_arm_rx": 2.69, "right_arm_ry": 0.57, "right_arm_rz": -2.72, "right_gripper": 0.43}, "8": {"left_arm_vel": 0.394, "left_gripper_vel": 0.168, "left_arm_rx": -2.87, "left_arm_ry": 0.59, "left_arm_rz": 2.15, "left_gripper": 0.28, "right_arm_vel": 0.394, "right_gripper_vel": 0.168, "right_arm_rx": 2.69, "right_arm_ry": 0.57, "right_arm_rz": -2.74, "right_gripper": 0.44}, "9": {"left_arm_vel": 0.334, "left_gripper_vel": 0.063, "left_arm_rx": -2.88, "left_arm_ry": 0.58, "left_arm_rz": 2.17, "left_gripper": 0.29, "right_arm_vel": 0.334, "right_gripper_vel": 0.063, "right_arm_rx": 2.69, "right_arm_ry": 0.58, "right_arm_rz": -2.77, "right_gripper": 0.44}, "10": {"left_arm_vel": 0.187, "left_gripper_vel": 0.0, "left_arm_rx": -2.91, "left_arm_ry": 0.59, "left_arm_rz": 2.19, "left_gripper": 0.28, "right_arm_vel": 0.187, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.62, "right_arm_rz": -2.79, "right_gripper": 0.45}, "11": {"left_arm_vel": 0.146, "left_gripper_vel": 0.021, "left_arm_rx": -2.91, "left_arm_ry": 0.59, "left_arm_rz": 2.23, "left_gripper": 0.25, "right_arm_vel": 0.146, "right_gripper_vel": 0.021, "right_arm_rx": 2.68, "right_arm_ry": 0.6, "right_arm_rz": -2.81, "right_gripper": 0.45}, "12": {"left_arm_vel": 0.193, "left_gripper_vel": 0.0, "left_arm_rx": -2.93, "left_arm_ry": 0.58, "left_arm_rz": 2.28, "left_gripper": 0.23, "right_arm_vel": 0.193, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.57, "right_arm_rz": -2.82, "right_gripper": 0.45}, "13": {"left_arm_vel": 0.246, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 0.57, "left_arm_rz": 2.32, "left_gripper": 0.23, "right_arm_vel": 0.246, "right_gripper_vel": 0.0, "right_arm_rx": 2.76, "right_arm_ry": 0.56, "right_arm_rz": -2.81, "right_gripper": 0.45}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.0478999987244606, 0.06889999657869339, 0.07769999653100967], "delta_rot": [-0.03280000016093254, -0.038600001484155655, 0.3082999885082245], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1143}, "right": {"delta_pos": [-0.03819999843835831, -0.12939999997615814, 0.07769999653100967], "delta_rot": [0.013000000268220901, -0.16110000014305115, -0.1185000017285347], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.1558}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.4027999937534332, 0.2971000075340271, 0.05979999899864197], "delta_rot": [-0.13109999895095825, 0.5245000123977661, 0.7307000160217285], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.5041}, "right": {"delta_pos": [-0.2362000048160553, -0.28209999203681946, 0.09749999642372131], "delta_rot": [0.3643999993801117, 0.39010000228881836, 0.061799999326467514], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.3806}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", + "actions": [ + { + "reasoning_cot": "The left arm maintains a static position on the bag's top surface (silver mesh area) to provide stability. The gripper is closed but not moving, indicating a 'hold' action to keep the bag steady while the other arm operates.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "static_at_top_surface", + "topology_change": false + }, + { + "reasoning_cot": "The right arm moves from a free-space hover towards the bag's side. Visual evidence in frames T0-T1 shows the gripper jaws closing around the metal zipper pull tab. This is a precise approach and grasp maneuver targeting the zipper mechanism.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "touching" + }, + "action_verb": "grasp", + "semantic_action": "approach_zipper", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving_from_free_space_to_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped" + } + ], + "task_progress": "Right arm has successfully located and grasped the zipper pull; left arm continues to stabilize the bag body." + } +} +```` +--- +## 🎬 ChunkAnnotator_14 + +### 👁️ 视觉输入 +![chunkannotator_14_img_0.jpg](./images/chunkannotator_14_img_0.jpg) +![chunkannotator_14_img_1.jpg](./images/chunkannotator_14_img_1.jpg) +![chunkannotator_14_img_2.jpg](./images/chunkannotator_14_img_2.jpg) +![chunkannotator_14_img_3.jpg](./images/chunkannotator_14_img_3.jpg) +![chunkannotator_14_img_4.jpg](./images/chunkannotator_14_img_4.jpg) +![chunkannotator_14_img_5.jpg](./images/chunkannotator_14_img_5.jpg) +![chunkannotator_14_img_6.jpg](./images/chunkannotator_14_img_6.jpg) +![chunkannotator_14_img_7.jpg](./images/chunkannotator_14_img_7.jpg) +![chunkannotator_14_img_8.jpg](./images/chunkannotator_14_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.33, "angle": 0.71, "vel_score": 3.26, "angle_score": 6.32, "vel_fft": [0.334, 0.193, 0.048, 0.019, 0.02, 0.027, 0.005, 0.008, 0.017, 0.013, 0.006, 0.012, 0.016, 0.003, 0.002, 0.008, 0.009, 0.004, 0.003, 0.011], "angle_fft": [0.709, 0.236, 0.123, 0.044, 0.036, 0.128, 0.06, 0.023, 0.041, 0.028, 0.019, 0.04, 0.017, 0.003, 0.014, 0.028, 0.038, 0.017, 0.021, 0.029]}, "right": {"vel": 0.2, "angle": 0.68, "vel_score": 1.85, "angle_score": 6.09, "vel_fft": [0.197, 0.095, 0.014, 0.01, 0.013, 0.012, 0.007, 0.006, 0.012, 0.006, 0.002, 0.007, 0.011, 0.011, 0.002, 0.005, 0.007, 0.003, 0.003, 0.004], "angle_fft": [0.676, 0.236, 0.17, 0.075, 0.052, 0.021, 0.04, 0.048, 0.032, 0.035, 0.017, 0.002, 0.045, 0.048, 0.034, 0.021, 0.013, 0.007, 0.014, 0.03]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 0.58, "left_arm_rz": 2.34, "left_gripper": 0.23, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.77, "right_arm_ry": 0.56, "right_arm_rz": -2.8, "right_gripper": 0.45}, "1": {"left_arm_vel": 0.288, "left_gripper_vel": -0.084, "left_arm_rx": -3.02, "left_arm_ry": 0.67, "left_arm_rz": 2.48, "left_gripper": 0.23, "right_arm_vel": 0.288, "right_gripper_vel": -0.084, "right_arm_rx": 2.85, "right_arm_ry": 0.55, "right_arm_rz": -2.73, "right_gripper": 0.44}, "2": {"left_arm_vel": 0.381, "left_gripper_vel": -0.042, "left_arm_rx": -3.01, "left_arm_ry": 0.76, "left_arm_rz": 2.6, "left_gripper": 0.23, "right_arm_vel": 0.381, "right_gripper_vel": -0.042, "right_arm_rx": 3.01, "right_arm_ry": 0.51, "right_arm_rz": -2.65, "right_gripper": 0.44}, "3": {"left_arm_vel": 0.521, "left_gripper_vel": 0.0, "left_arm_rx": -3.02, "left_arm_ry": 0.88, "left_arm_rz": 2.66, "left_gripper": 0.23, "right_arm_vel": 0.521, "right_gripper_vel": 0.0, "right_arm_rx": 3.06, "right_arm_ry": 0.57, "right_arm_rz": -2.62, "right_gripper": 0.44}, "4": {"left_arm_vel": 0.313, "left_gripper_vel": -0.021, "left_arm_rx": -3.09, "left_arm_ry": 1.0, "left_arm_rz": 2.72, "left_gripper": 0.23, "right_arm_vel": 0.313, "right_gripper_vel": -0.021, "right_arm_rx": 3.06, "right_arm_ry": 0.7, "right_arm_rz": -2.63, "right_gripper": 0.43}, "5": {"left_arm_vel": 0.141, "left_gripper_vel": 0.0, "left_arm_rx": -3.09, "left_arm_ry": 1.12, "left_arm_rz": 2.75, "left_gripper": 0.23, "right_arm_vel": 0.141, "right_gripper_vel": 0.0, "right_arm_rx": 3.1, "right_arm_ry": 1.03, "right_arm_rz": -2.62, "right_gripper": 0.43}, "6": {"left_arm_vel": 0.006, "left_gripper_vel": -0.168, "left_arm_rx": -3.05, "left_arm_ry": 1.14, "left_arm_rz": 2.75, "left_gripper": 0.23, "right_arm_vel": 0.006, "right_gripper_vel": -0.168, "right_arm_rx": 3.11, "right_arm_ry": 1.11, "right_arm_rz": -2.63, "right_gripper": 0.42}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": -0.105, "left_arm_rx": -3.06, "left_arm_ry": 1.13, "left_arm_rz": 2.74, "left_gripper": 0.23, "right_arm_vel": 0.0, "right_gripper_vel": -0.105, "right_arm_rx": 3.11, "right_arm_ry": 1.11, "right_arm_rz": -2.63, "right_gripper": 0.39}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.34389999508857727, 0.22010000050067902, -0.023600000888109207], "delta_rot": [-0.08150000125169754, 0.5526999831199646, 0.40389999747276306], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and -Z(Down)", "magnitude": 0.409}, "right": {"delta_pos": [-0.19349999725818634, -0.14869999885559082, 0.01549999974668026], "delta_rot": [0.3375999927520752, 0.5558000206947327, 0.1754000037908554], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.2446}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.34689998626708984, 0.2160000056028366, -0.024000000208616257], "delta_rot": [-0.06970000267028809, 0.5641999840736389, -5.3958001136779785], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and -Z(Down)", "magnitude": 0.4093}, "right": {"delta_pos": [-0.19460000097751617, -0.1459999978542328, 0.015599999576807022], "delta_rot": [0.3368000090122223, 0.5583000183105469, 5.895299911499023], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.2438}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm approaches and makes contact with the bag's top surface to stabilize it, while right arm remains idle in a hovering position.", + "actions": [ + { + "reasoning_cot": "The left arm moves from a retracted position towards the bag (Images 1-3) and establishes physical contact with the top reflective panel (Images 4-9). The gripper remains open but applies downward pressure or rests on the surface, indicating a 'touch' or 'hold' action for stabilization rather than grasping. This aligns with the spatial logic of moving from free space to the 'bag:top_surface'.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "touch", + "semantic_action": "stabilize_bag_top", + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "moving from free_space to bag:top_surface", + "topology_change": false + }, + { + "reasoning_cot": "The right arm shows minimal displacement and remains positioned over the table edge/side handle area without making significant contact or changing state. It acts as a passive observer or stabilizer in this chunk, maintaining its previous hover state.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": null, + "spatial_logic": "static_hover_near_side_handle", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:top_surface", + "current_status": "contacted" + } + ], + "task_progress": "Left arm has successfully established contact with the top of the bag to prepare for opening or manipulation." + } +} +```` +--- +## 🎬 ChunkAnnotator_15 + +### 👁️ 视觉输入 +![chunkannotator_15_img_0.jpg](./images/chunkannotator_15_img_0.jpg) +![chunkannotator_15_img_1.jpg](./images/chunkannotator_15_img_1.jpg) +![chunkannotator_15_img_2.jpg](./images/chunkannotator_15_img_2.jpg) +![chunkannotator_15_img_3.jpg](./images/chunkannotator_15_img_3.jpg) +![chunkannotator_15_img_4.jpg](./images/chunkannotator_15_img_4.jpg) +![chunkannotator_15_img_5.jpg](./images/chunkannotator_15_img_5.jpg) +![chunkannotator_15_img_6.jpg](./images/chunkannotator_15_img_6.jpg) +![chunkannotator_15_img_7.jpg](./images/chunkannotator_15_img_7.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 4 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:top_surface', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and makes contact with the bag's top surface to stabilize it, while right arm remains idle in a hovering position.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.0, "angle": 4.57, "vel_score": 0.05, "angle_score": 4.0, "vel_fft": [0.005, 0.004, 0.002, 0.001, 0.0, 0.001, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "angle_fft": [4.565, 4.51, 4.385, 4.276, 4.228, 4.229, 4.244, 4.249, 4.238, 4.225, 4.22, 4.221, 4.221, 4.224, 4.23, 4.232, 4.23, 4.23, 4.233, 4.232]}, "right": {"vel": 0.0, "angle": 4.63, "vel_score": 0.03, "angle_score": 4.4, "vel_fft": [0.002, 0.002, 0.001, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "angle_fft": [4.626, 4.534, 4.338, 4.196, 4.184, 4.233, 4.259, 4.252, 4.244, 4.247, 4.25, 4.242, 4.231, 4.227, 4.233, 4.241, 4.243, 4.238, 4.234, 4.237]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.13, "left_arm_rz": 2.75, "left_gripper": 0.23, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.11, "right_arm_ry": 1.11, "right_arm_rz": -2.63, "right_gripper": 0.39}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": -0.084, "left_arm_rx": -3.05, "left_arm_ry": 1.13, "left_arm_rz": 2.75, "left_gripper": 0.23, "right_arm_vel": 0.0, "right_gripper_vel": -0.084, "right_arm_rx": 3.11, "right_arm_ry": 1.11, "right_arm_rz": -2.63, "right_gripper": 0.38}, "2": {"left_arm_vel": 0.004, "left_gripper_vel": -0.105, "left_arm_rx": -3.05, "left_arm_ry": 1.14, "left_arm_rz": 2.76, "left_gripper": 0.23, "right_arm_vel": 0.004, "right_gripper_vel": -0.105, "right_arm_rx": 3.11, "right_arm_ry": 1.11, "right_arm_rz": -2.64, "right_gripper": 0.38}, "3": {"left_arm_vel": 0.008, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.14, "left_arm_rz": 2.85, "left_gripper": 0.23, "right_arm_vel": 0.008, "right_gripper_vel": 0.0, "right_arm_rx": 3.11, "right_arm_ry": 1.11, "right_arm_rz": -2.76, "right_gripper": 0.38}, "4": {"left_arm_vel": 0.009, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.14, "left_arm_rz": 3.07, "left_gripper": 0.23, "right_arm_vel": 0.009, "right_gripper_vel": 0.0, "right_arm_rx": 3.11, "right_arm_ry": 1.11, "right_arm_rz": -3.02, "right_gripper": 0.38}, "5": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.14, "left_arm_rz": -3.07, "left_gripper": 0.23, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 3.11, "right_arm_ry": 1.11, "right_arm_rz": 3.11, "right_gripper": 0.38}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.14, "left_arm_rz": -3.05, "left_gripper": 0.23, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.11, "right_arm_ry": 1.11, "right_arm_rz": 3.09, "right_gripper": 0.38}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.14, "left_arm_rz": -3.05, "left_gripper": 0.23, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.11, "right_arm_ry": 1.11, "right_arm_rz": 3.09, "right_gripper": 0.38}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.00279999990016222, -0.003700000001117587, -0.0003000000142492354], "delta_rot": [0.0012000000569969416, 0.012000000104308128, -5.805699825286865], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0047}, "right": {"delta_pos": [-0.0010999999940395355, 0.0027000000700354576, 0.0], "delta_rot": [-0.002400000113993883, 0.002400000113993883, 5.718999862670898], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.003}} + + [FUTURE HINDSIGHT HINT]: + "End of Trajectory" + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Both arms remain in a static hovering position above the table surface, maintaining a neutral stance with no interaction with the bag.", + "actions": [ + { + "reasoning_cot": "The left arm shows negligible kinematic displacement (delta_pos ~0.002) and zero gripper velocity. Visually, the end-effector remains suspended over the empty table surface to the left of the bag, maintaining a consistent hover height without making contact.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "hover", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "static_hover_left_of_bag", + "topology_change": false + }, + { + "reasoning_cot": "The right arm exhibits minimal movement (delta_pos ~0.001) and stable gripper state. The visual feed confirms the end-effector is stationary in free space above the table, positioned to the right of the bag, with no engagement with any object.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "hover", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": null, + "spatial_logic": "static_hover_right_of_bag", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Arms are holding a static idle position, awaiting further instructions or target acquisition." + } +} +```` +--- +## 🎬 SubtaskAnnotator_0 + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are an expert human observer curating Embodied AI datasets. + Your goal is to synthesize a timeline of low-level robotic micro-actions into a highly logical, human-readable hierarchy of "Macro Chapters" (Subtasks). + + ### 0. GLOBAL CONTEXT + - **Video ID**: video_0005 + - **Total Frames**: 600 + - **Global Task Goal**: "Unknown Task" + + ### 1. INPUT DATA + - **KPM (Micro-Actions Timeline)**: [{"chunk_idx": 0, "start_frame": 0, "end_frame": 65, "chunk_intent": "Right arm approaches and makes contact with the bag's top surface to initiate manipulation, while left arm remains idle.", "micro_actions": [{"verb": "approach", "semantic_verb": null, "subject": "right_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Moving from free space to bag:top_surface"}, {"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_at_initial_position"}]}, {"chunk_idx": 1, "start_frame": 66, "end_frame": 108, "chunk_intent": "Right arm approaches and makes contact with the bag's top surface to initiate manipulation, while left arm remains idle.", "micro_actions": [{"verb": "approach", "semantic_verb": null, "subject": "right_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving from free_space to bag:top_surface"}, {"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_in_free_space"}]}, {"chunk_idx": 2, "start_frame": 109, "end_frame": 147, "chunk_intent": "Left arm approaches and stabilizes the bag's top surface near the zipper, while right arm remains idle.", "micro_actions": [{"verb": "approach", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving from free space to bag:top_surface"}, {"verb": "idle", "semantic_verb": null, "subject": "right_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_hover"}]}, {"chunk_idx": 3, "start_frame": 148, "end_frame": 186, "chunk_intent": "Left arm approaches and stabilizes the bag's top surface near the zipper, while right arm remains idle.", "micro_actions": [{"verb": "grasp", "semantic_verb": null, "subject": "left_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Approaching and contacting bag:top_surface/zipper_pull"}, {"verb": "idle", "semantic_verb": null, "subject": "right_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "Static hover"}]}, {"chunk_idx": 4, "start_frame": 187, "end_frame": 204, "chunk_intent": "Left arm stabilizes the bag by holding the zipper pull, while right arm approaches and makes contact with the top surface near the opening to prepare for manipulation.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_zipper_pull"}, {"verb": "approach", "semantic_verb": "stabilize_top_rim", "subject": "right_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving_from_hover_to_top_surface_contact"}]}, {"chunk_idx": 5, "start_frame": 205, "end_frame": 223, "chunk_intent": "Left arm stabilizes the bag by holding the zipper pull, while right arm approaches and makes contact with the top surface near the opening to prepare for manipulation.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_zipper_pull"}, {"verb": "touch", "semantic_verb": "approach_and_contact", "subject": "right_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving_from_free_space_to_top_surface"}]}, {"chunk_idx": 6, "start_frame": 224, "end_frame": 252, "chunk_intent": "Left arm stabilizes the bag by holding the zipper pull, while right arm approaches and makes contact with the top surface near the opening to prepare for manipulation.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_zipper_pull"}, {"verb": "approach", "semantic_verb": "position_for_opening", "subject": "right_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving_from_hover_to_top_surface_contact"}]}, {"chunk_idx": 7, "start_frame": 253, "end_frame": 262, "chunk_intent": "Left arm stabilizes the bag by holding the top flap, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "stabilizing_at_top_flap"}, {"verb": "approach", "semantic_verb": null, "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving_from_hover_to_zipper_contact"}]}, {"chunk_idx": 8, "start_frame": 263, "end_frame": 310, "chunk_intent": "Left arm stabilizes the bag by holding the top flap, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_top_flap"}, {"verb": "approach", "semantic_verb": "target_zipper_pull", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving_from_free_space_to_zipper_pull"}]}, {"chunk_idx": 9, "start_frame": 311, "end_frame": 365, "chunk_intent": "Left arm stabilizes the bag by holding the top flap, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_top_flap"}, {"verb": "grasp", "semantic_verb": "approach_zipper", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving_from_free_space_to_zipper_pull"}]}, {"chunk_idx": 10, "start_frame": 366, "end_frame": 384, "chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "static_at_top_flap"}, {"verb": "approach", "semantic_verb": null, "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "moving_from_free_space_to_zipper_pull"}]}, {"chunk_idx": 11, "start_frame": 385, "end_frame": 436, "chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_top_flap_interior"}, {"verb": "grasp", "semantic_verb": "target_zipper_pull", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "moving_from_free_space_to_zipper_pull"}]}, {"chunk_idx": 12, "start_frame": 437, "end_frame": 488, "chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_top_flap"}, {"verb": "grasp", "semantic_verb": "engage_zipper", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "moving_from_free_space_to_zipper_pull"}]}, {"chunk_idx": 13, "start_frame": 489, "end_frame": 512, "chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_top_surface"}, {"verb": "grasp", "semantic_verb": "approach_zipper", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving_from_free_space_to_zipper_pull"}]}, {"chunk_idx": 14, "start_frame": 513, "end_frame": 555, "chunk_intent": "Left arm approaches and makes contact with the bag's top surface to stabilize it, while right arm remains idle in a hovering position.", "micro_actions": [{"verb": "touch", "semantic_verb": "stabilize_bag_top", "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving from free_space to bag:top_surface"}, {"verb": "idle", "semantic_verb": null, "subject": "right_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_hover_near_side_handle"}]}, {"chunk_idx": 15, "start_frame": 556, "end_frame": 599, "chunk_intent": "Both arms remain in a static hovering position above the table surface, maintaining a neutral stance with no interaction with the bag.", "micro_actions": [{"verb": "hover", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_hover_left_of_bag"}, {"verb": "hover", "semantic_verb": null, "subject": "right_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_hover_right_of_bag"}]}] + - **WSM (State Memory)**: [{"chunk_idx": 0, "global_frame_range": [0, 65], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "visible"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Right arm approaches and makes contact with the bag's top surface to initiate manipulation, while left arm remains idle.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 1, "global_frame_range": [66, 108], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "visible"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Right arm approaches and makes contact with the bag's top surface to initiate manipulation, while left arm remains idle.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 2, "global_frame_range": [109, 147], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "visible"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and stabilizes the bag's top surface near the zipper, while right arm remains idle.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 3, "global_frame_range": [148, 186], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and stabilizes the bag's top surface near the zipper, while right arm remains idle.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 4, "global_frame_range": [187, 204], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by holding the zipper pull, while right arm approaches and makes contact with the top surface near the opening to prepare for manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 5, "global_frame_range": [205, 223], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by holding the zipper pull, while right arm approaches and makes contact with the top surface near the opening to prepare for manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 6, "global_frame_range": [224, 252], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by holding the zipper pull, while right arm approaches and makes contact with the top surface near the opening to prepare for manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 7, "global_frame_range": [253, 262], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by holding the top flap, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 8, "global_frame_range": [263, 310], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by holding the top flap, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 9, "global_frame_range": [311, 365], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by holding the top flap, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 10, "global_frame_range": [366, 384], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "contacted"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 11, "global_frame_range": [385, 436], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 12, "global_frame_range": [437, 488], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 13, "global_frame_range": [489, 512], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by holding the top flap open, while right arm approaches and makes contact with the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 14, "global_frame_range": [513, 555], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and makes contact with the bag's top surface to stabilize it, while right arm remains idle in a hovering position.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 15, "global_frame_range": [556, 599], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "contacted"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Both arms remain in a static hovering position above the table surface, maintaining a neutral stance with no interaction with the bag.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}] + + ### 2. SYNTHESIS RULES (COMMON SENSE & NATURAL BOUNDARIES) + You must divide the chronological timeline into distinct segments. Instead of following rigid verb rules, use your human common sense to identify when a new phase of the task begins. + + **A natural "Chapter Boundary" (Segment Break) occurs when:** + 1. **Target Object Shift (CRITICAL)**: The robot shifts its focus or interaction from one primary object to another (e.g., finishes pouring into 'cup_A' and moves to 'cup_B', or drops a 'sponge' to pick up a 'towel'). NEVER merge actions directed at different primary targets into the same segment. + 2. **Major State Transition**: As seen in the WSM, a significant physical event occurs (e.g., the gripper transitions from 'none' to 'holding', or an object's topology drastically changes). + 3. **Semantic Goal Shift**: The overarching intent changes (e.g., from the "Approach & Preparation" phase to the "Active Manipulation" phase, and finally to the "Retract & Idle" phase). + + **Grouping Principle:** + - Merge consecutive chunks that serve a single, unified purpose (e.g., multiple chunks of "hover" and "hold" that all serve the continuous intent of "pouring water into the paper cup" should be merged into one segment). + - Ensure chronological integrity: Segments must be contiguous using the `chunk_idx` (e.g., [0, 2], [3, 5]). No gaps, no overlapping chunks. + + ### 3. OUTPUT REQUIREMENT + - `merge_thought`: Explain your logic based on the natural boundaries. Example: "Chunks 2-5 represent the continuous pouring phase into the paper cup. I broke the segment at Chunk 6 because the target shifted to the teal cup." + - `chunk_idx_range`: Output the exact index range `[start, end]`. + - `state_transition.before_anchors`: For the VERY FIRST segment (segment 0), this MUST exactly match these initial anchors: [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "visible"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + + Output ONLY valid JSON. + ```json + { + "$defs": { + "CausalSummary": { + "properties": { + "trigger": { + "description": "Triggered by what topological sequence? (e.g., 'Bimanual pinch & moved from hem to collar')", + "title": "Trigger", + "type": "string" + }, + "effect": { + "description": "Visual effect (e.g., 'Jacket folded in half')", + "title": "Effect", + "type": "string" + } + }, + "required": [ + "trigger", + "effect" + ], + "title": "CausalSummary", + "type": "object" + }, + "SegmentAnnotation": { + "properties": { + "segment_id": { + "minimum": 0, + "title": "Segment Id", + "type": "integer" + }, + "primitive_type": { + "description": "Must be one of: ['Approach', 'Pre-grasp Align', 'Grasp', 'Lift', 'Horizontal Transport', 'Target Hover & Align', 'Lower & Pre-place', 'Compress/Squeeze', 'Shape/Adjust', 'Release', 'Retract', 'Place', 'Idle', 'Hold']", + "title": "Primitive Type", + "type": "string" + }, + "chunk_idx_range": { + "description": "[start_chunk_idx, end_chunk_idx] inclusive. E.g., [2, 5] means merging chunks 2, 3, 4, and 5.", + "items": { + "type": "integer" + }, + "maxItems": 2, + "minItems": 2, + "title": "Chunk Idx Range", + "type": "array" + }, + "subtask": { + "description": "Intent referencing the semantic atlas.", + "title": "Subtask", + "type": "string" + }, + "state_transition": { + "$ref": "#/$defs/StateTransition" + }, + "causal_summary": { + "$ref": "#/$defs/CausalSummary" + } + }, + "required": [ + "segment_id", + "primitive_type", + "chunk_idx_range", + "subtask", + "state_transition", + "causal_summary" + ], + "title": "SegmentAnnotation", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "StateTransition": { + "properties": { + "before_anchors": { + "description": "Status of relevant semantic anchors before segment", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Before Anchors", + "type": "array" + }, + "after_anchors": { + "description": "Status of relevant semantic anchors after segment", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "After Anchors", + "type": "array" + } + }, + "required": [ + "before_anchors", + "after_anchors" + ], + "title": "StateTransition", + "type": "object" + } + }, + "properties": { + "video_id": { + "title": "Video Id", + "type": "string" + }, + "merge_thought": { + "description": "Explain how semantic anchor stability and topology changes guided your chunk merging.", + "title": "Merge Thought", + "type": "string" + }, + "segments": { + "items": { + "$ref": "#/$defs/SegmentAnnotation" + }, + "title": "Segments", + "type": "array" + } + }, + "required": [ + "video_id", + "merge_thought", + "segments" + ], + "title": "SubtaskAnnotation", + "type": "object" +} + ``` + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "video_id": "video_0005", + "merge_thought": "The timeline is divided into three logical macro-chapters based on the shift in robotic intent and target interaction. \n\n1. **Initial Approach & Stabilization (Chunks 0-6)**: The robot begins with the right arm approaching the bag, then switches to the left arm to stabilize the bag's top surface/zipper area. This phase is characterized by establishing a stable base for manipulation. The transition occurs when the left arm secures the zipper pull and the right arm begins its specific approach to the opening mechanism.\n\n2. **Zipper Engagement & Opening Preparation (Chunks 7-13)**: This is the core manipulation phase. The left arm holds the top flap open/stable while the right arm repeatedly approaches, contacts, and grasps the zipper pull. The intent shifts from general stabilization to specific interaction with the 'zipper_pull' anchor to initiate opening. The state of the zipper pull changes from 'visible/contacted' to 'grasped'.\n\n3. **Retraction & Idle (Chunks 14-15)**: After the manipulation attempts, the right arm releases/retracts, and both arms move to a neutral hovering position. The interaction with the bag ceases, marking the end of the active task.", + "segments": [ + { + "segment_id": 0, + "primitive_type": "Approach", + "chunk_idx_range": [ + 0, + 6 + ], + "subtask": "Approach and stabilize bag top surface", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "table:surface_center", + "current_status": "exposed" + }, + { + "anchor_id": "bag:main_body", + "current_status": "upright" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "exposed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "visible" + }, + { + "anchor_id": "bag:side_handle", + "current_status": "accessible" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:top_surface", + "current_status": "contacted" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "contacted" + } + ] + }, + "causal_summary": { + "trigger": "Right arm approaches bag, then left arm stabilizes top surface near zipper", + "effect": "Bag is stabilized, left arm holds zipper pull, right arm positions near opening" + } + }, + { + "segment_id": 1, + "primitive_type": "Grasp", + "chunk_idx_range": [ + 7, + 13 + ], + "subtask": "Engage and grasp zipper pull to open bag", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:top_surface", + "current_status": "contacted" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "contacted" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:top_surface", + "current_status": "contacted" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped" + } + ] + }, + "causal_summary": { + "trigger": "Left arm holds top flap, right arm targets and grasps zipper pull", + "effect": "Right arm secures grasp on zipper pull, preparing to unzip" + } + }, + { + "segment_id": 2, + "primitive_type": "Idle", + "chunk_idx_range": [ + 14, + 15 + ], + "subtask": "Retract arms and return to idle hover", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:top_surface", + "current_status": "contacted" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:top_surface", + "current_status": "contacted" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped" + } + ] + }, + "causal_summary": { + "trigger": "Manipulation complete, arms retract from bag", + "effect": "Both arms hover in neutral position above table" + } + } + ] +} +```` +--- diff --git a/debug/episode_0006/images/chunkannotator_0_img_0.jpg b/debug/episode_0006/images/chunkannotator_0_img_0.jpg new file mode 100644 index 0000000000000000000000000000000000000000..f85b1e49f8fd001f5161eab7c8db4b8729c170ca --- /dev/null +++ b/debug/episode_0006/images/chunkannotator_0_img_0.jpg @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6a141e61a6d1de5555682e3adf553d019a58aa2c6eac927c32605942f8e80f86 +size 16961 diff --git a/debug/episode_0006/images/chunkannotator_0_img_1.jpg 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0000000000000000000000000000000000000000..a7b14113b4b69ae9c4f96333fae6ed4b2e5314b0 --- /dev/null +++ b/debug/episode_0006/images/sceneannotator_0_img_6.jpg @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4c3c8536f1c7585f4730ef9f441c43be3f2d3affe7ee2d59d6358398da7d048d +size 24553 diff --git a/debug/episode_0006/images/sceneannotator_0_img_7.jpg b/debug/episode_0006/images/sceneannotator_0_img_7.jpg new file mode 100644 index 0000000000000000000000000000000000000000..bc7e07b25daf1521321463c45bcc410404a519ea --- /dev/null +++ b/debug/episode_0006/images/sceneannotator_0_img_7.jpg @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:54000d249bc82a432d6e7430518c441dfbc000de452cd9e3f1771d238155449d +size 19383 diff --git a/debug/episode_0006/images/sceneannotator_0_img_8.jpg b/debug/episode_0006/images/sceneannotator_0_img_8.jpg new file mode 100644 index 0000000000000000000000000000000000000000..8862131bbff949799c4c7dd83ff83ac4dd2eb75c --- /dev/null +++ b/debug/episode_0006/images/sceneannotator_0_img_8.jpg @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c4493e44574201a4b77097e1193b23cf7c5954a5812da645255beab5b27cb59c +size 16779 diff --git a/debug/episode_0006/trace_report.md b/debug/episode_0006/trace_report.md new file mode 100644 index 0000000000000000000000000000000000000000..f473fcfb52ef1dde8c56a8efc4deb8088faafdcf --- /dev/null +++ b/debug/episode_0006/trace_report.md @@ -0,0 +1,4137 @@ +# 🤖 Episode_0006 标注追踪报告 + + +# 🌍 全局场景语义理解 +==================== + +## 🎬 SceneAnnotator_0 + +### 👁️ 视觉输入 +![sceneannotator_0_img_0.jpg](./images/sceneannotator_0_img_0.jpg) +![sceneannotator_0_img_1.jpg](./images/sceneannotator_0_img_1.jpg) +![sceneannotator_0_img_2.jpg](./images/sceneannotator_0_img_2.jpg) +![sceneannotator_0_img_3.jpg](./images/sceneannotator_0_img_3.jpg) +![sceneannotator_0_img_4.jpg](./images/sceneannotator_0_img_4.jpg) +![sceneannotator_0_img_5.jpg](./images/sceneannotator_0_img_5.jpg) +![sceneannotator_0_img_6.jpg](./images/sceneannotator_0_img_6.jpg) +![sceneannotator_0_img_7.jpg](./images/sceneannotator_0_img_7.jpg) +![sceneannotator_0_img_8.jpg](./images/sceneannotator_0_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are an Embodied AI Scene Architect. + Your task is to perform a "Global Inventory & Topological Mapping" of the workspace. + + [CONTEXT]: + - Environment: unknown + - Scene: unknown -> unknown + - Target Objects: table, bag + - Task Description: Unknown Task + + [STRICT INSTRUCTIONS]: + 1. **SEMANTIC ANCHOR REGISTRATION (Critical)**: + - 🌟 **Task-Driven Affordance (CRITICAL)**: Analyze the `Task Description` first. ONLY register semantic anchors that are functionally relevant to completing this specific task. Ask yourself: "Which precise parts of the objects will the robot need to grasp, place, align, or avoid?" + - **Functional Decomposition**: Do NOT mindlessly exhaust or grid the object. Identify interaction hotspots. For example: + - If task is "Pour water": register "bottle:cap", "bottle:body", "cup:rim". + - If task is "Fold jacket": register "jacket:left_sleeve", "jacket:collar", "jacket:bottom_hem". + - If task is simply "Move the box": registering "box:main_body" is sufficient; do not invent micro-corners. + - **Naming Convention**: Use `object_name:part_name` (e.g., "jacket:left_sleeve", "table:center_bin"). + - **Scope**: Include essential parts of the target objects AND key functional zones of the workspace (e.g., "workspace:placement_zone"). + - **Initial Status**: Describe the visual topology at the start. ⚠️ DO NOT label main functional parts as "hidden", "unreachable", or "buried" unless absolutely invisible, as this prevents downstream agents from interacting with them. Use neutral terms like "partially_obscured_but_accessible" instead. + + 2. **SPATIAL LAYOUT**: + Provide a one-sentence summary of where the main objects are relative to the robot. + + 3. **SCENE FACTORS**: + Identify environment conditions (lighting, material, clutter) that might affect robot perception or grasp stability. + + 4. **DISTRACTORS**: + List objects that are NOT part of the task but might cause visual noise. Do NOT register them as Semantic Anchors. + + [OUTPUT RULE]: + Return ONLY a JSON object matching the schema. Do not include any explanations. + + [SCHEMA]: + { + "$defs": { + "SceneFactors": { + "additionalProperties": false, + "properties": { + "environment": { + "enum": [ + "kitchen", + "lab", + "outdoor", + "unknown" + ], + "title": "Environment", + "type": "string" + }, + "lighting_type": { + "enum": [ + "bright_indoor", + "dim", + "natural", + "mixed" + ], + "title": "Lighting Type", + "type": "string" + }, + "surface_material": { + "enum": [ + "wood", + "metal", + "plastic", + "tile", + "unknown" + ], + "title": "Surface Material", + "type": "string" + }, + "clutter_level": { + "enum": [ + "low", + "medium", + "high" + ], + "title": "Clutter Level", + "type": "string" + } + }, + "required": [ + "environment", + "lighting_type", + "surface_material", + "clutter_level" + ], + "title": "SceneFactors", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + } + }, + "additionalProperties": false, + "properties": { + "scene_factors": { + "$ref": "#/$defs/SceneFactors" + }, + "spatial_layout": { + "description": "Objective spatial arrangement.", + "title": "Spatial Layout", + "type": "string" + }, + "initial_semantic_anchors": { + "description": "Initial registration of key topological zones for the target objects.", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Initial Semantic Anchors", + "type": "array" + }, + "background_distractors": { + "items": { + "type": "string" + }, + "title": "Background Distractors", + "type": "array" + } + }, + "required": [ + "scene_factors", + "spatial_layout", + "initial_semantic_anchors", + "background_distractors" + ], + "title": "SceneAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "scene_factors": { + "environment": "lab", + "lighting_type": "bright_indoor", + "surface_material": "plastic", + "clutter_level": "low" + }, + "spatial_layout": "A white table surface occupies the immediate workspace, with a beige insulated bag positioned in the center-left area relative to the robot's grippers.", + "initial_semantic_anchors": [ + { + "anchor_id": "table:surface_center", + "current_status": "exposed" + }, + { + "anchor_id": "bag:main_body", + "current_status": "upright_stable" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + }, + { + "anchor_id": "bag:side_handle_ring", + "current_status": "exposed" + } + ], + "background_distractors": [ + "robot_gripper_fingers", + "cables_and_equipment_rack" + ] +} +```` +--- + +# 🤖 动作切片(Chunk) 语义闭环标注 +==================== + +## 🎬 ChunkAnnotator_0 + +### 👁️ 视觉输入 +![chunkannotator_0_img_0.jpg](./images/chunkannotator_0_img_0.jpg) +![chunkannotator_0_img_1.jpg](./images/chunkannotator_0_img_1.jpg) +![chunkannotator_0_img_2.jpg](./images/chunkannotator_0_img_2.jpg) +![chunkannotator_0_img_3.jpg](./images/chunkannotator_0_img_3.jpg) +![chunkannotator_0_img_4.jpg](./images/chunkannotator_0_img_4.jpg) +![chunkannotator_0_img_5.jpg](./images/chunkannotator_0_img_5.jpg) +![chunkannotator_0_img_6.jpg](./images/chunkannotator_0_img_6.jpg) +![chunkannotator_0_img_7.jpg](./images/chunkannotator_0_img_7.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 4 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T0 (Curr Start)] + - Image 3: [T1 (Curr End)] + - Image 4: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "none", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.06, "angle": 0.28, "vel_score": 0.96, "angle_score": 4.66, "vel_fft": [0.057, 0.053, 0.044, 0.031, 0.018, 0.009, 0.008, 0.009, 0.009, 0.007, 0.005, 0.004, 0.005, 0.005, 0.004, 0.004, 0.004, 0.004, 0.004, 0.005], "angle_fft": [0.281, 0.257, 0.197, 0.129, 0.077, 0.054, 0.056, 0.058, 0.05, 0.032, 0.014, 0.012, 0.02, 0.021, 0.011, 0.008, 0.016, 0.018, 0.015, 0.012]}, "right": {"vel": 0.25, "angle": 8.79, "vel_score": 3.26, "angle_score": 140.35, "vel_fft": [0.249, 0.156, 0.021, 0.02, 0.013, 0.011, 0.006, 0.002, 0.007, 0.002, 0.007, 0.008, 0.002, 0.005, 0.003, 0.003, 0.004, 0.001, 0.004, 0.004], "angle_fft": [8.791, 8.035, 6.6, 5.014, 3.265, 2.226, 3.049, 4.486, 5.608, 6.157, 6.014, 5.229, 4.016, 2.63, 1.55, 1.642, 2.314, 2.69, 2.54, 1.967]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.14, "left_arm_rz": -3.05, "left_gripper": 0.23, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.11, "right_arm_ry": 1.12, "right_arm_rz": 3.09, "right_gripper": 0.37}, "1": {"left_arm_vel": 0.474, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.15, "left_arm_rz": -3.05, "left_gripper": 0.23, "right_arm_vel": 0.474, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 1.09, "right_arm_rz": -3.14, "right_gripper": 0.37}, "2": {"left_arm_vel": 0.584, "left_gripper_vel": 0.0, "left_arm_rx": -3.02, "left_arm_ry": 1.14, "left_arm_rz": -3.06, "left_gripper": 0.23, "right_arm_vel": 0.584, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.86, "right_arm_rz": -2.72, "right_gripper": 0.37}, "3": {"left_arm_vel": 0.379, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 1.03, "left_arm_rz": -2.94, "left_gripper": 0.23, "right_arm_vel": 0.379, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.79, "right_arm_rz": -2.37, "right_gripper": 0.37}, "4": {"left_arm_vel": 0.332, "left_gripper_vel": 0.0, "left_arm_rx": -2.64, "left_arm_ry": 0.98, "left_arm_rz": -2.86, "left_gripper": 0.24, "right_arm_vel": 0.332, "right_gripper_vel": 0.0, "right_arm_rx": 2.69, "right_arm_ry": 0.78, "right_arm_rz": -2.34, "right_gripper": 0.37}, "5": {"left_arm_vel": 0.248, "left_gripper_vel": 0.294, "left_arm_rx": -2.55, "left_arm_ry": 0.95, "left_arm_rz": -2.86, "left_gripper": 0.25, "right_arm_vel": 0.248, "right_gripper_vel": 0.294, "right_arm_rx": 2.69, "right_arm_ry": 0.77, "right_arm_rz": -2.32, "right_gripper": 0.39}, "6": {"left_arm_vel": 0.221, "left_gripper_vel": 0.315, "left_arm_rx": -2.55, "left_arm_ry": 0.94, "left_arm_rz": -2.88, "left_gripper": 0.25, "right_arm_vel": 0.221, "right_gripper_vel": 0.315, "right_arm_rx": 2.68, "right_arm_ry": 0.77, "right_arm_rz": -2.31, "right_gripper": 0.4}, "7": {"left_arm_vel": 0.28, "left_gripper_vel": 0.378, "left_arm_rx": -2.54, "left_arm_ry": 0.92, "left_arm_rz": -2.89, "left_gripper": 0.26, "right_arm_vel": 0.28, "right_gripper_vel": 0.378, "right_arm_rx": 2.68, "right_arm_ry": 0.75, "right_arm_rz": -2.31, "right_gripper": 0.42}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.12160000205039978, -0.0364999994635582, 0.00989999994635582], "delta_rot": [0.5, -0.22050000727176666, 0.16519999504089355], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right)", "magnitude": 0.1273}, "right": {"delta_pos": [0.45739999413490295, 0.2264000028371811, -0.026599999517202377], "delta_rot": [-0.43220001459121704, -0.36169999837875366, -5.397200107574463], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and -Z(Down)", "magnitude": 0.511}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.25459998846054077, -0.06040000170469284, -0.04729999974370003], "delta_rot": [0.5964000225067139, -0.31869998574256897, 0.026000000536441803], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.2659}, "right": {"delta_pos": [0.4447000026702881, 0.2687999904155731, -0.07370000332593918], "delta_rot": [-0.4291999936103821, -0.4494999945163727, -5.274400234222412], "gripper_changed": true, "flow_direction": "+X(Forward) and +Y(Left) and -Z(Down)", "magnitude": 0.5248}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Approach and establish contact with the bag's main body using the right arm while the left arm remains idle.", + "actions": [ + { + "reasoning_cot": "The right arm executes a significant forward (+X) and downward (-Z) trajectory (delta_pos magnitude ~0.51), moving from free space to directly over the bag. Visual evidence in T1/T2 confirms the gripper is positioned immediately above the 'bag:main_body'. The gripper signal is stable, indicating an approach or hover phase prior to grasping.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "Moving from table surface zone to bag:main_body anchor", + "topology_change": false + }, + { + "reasoning_cot": "The left arm shows minimal kinematic activity (low velocity, small delta) and remains visually distant from the bag in all frames. It maintains its position in the workspace without interacting with any object.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "Static at initial position", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Right arm has successfully approached and made visual contact with the bag's main body, preparing for manipulation." + } +} +```` +--- +## 🎬 ChunkAnnotator_1 + +### 👁️ 视觉输入 +![chunkannotator_1_img_0.jpg](./images/chunkannotator_1_img_0.jpg) +![chunkannotator_1_img_1.jpg](./images/chunkannotator_1_img_1.jpg) +![chunkannotator_1_img_2.jpg](./images/chunkannotator_1_img_2.jpg) +![chunkannotator_1_img_3.jpg](./images/chunkannotator_1_img_3.jpg) +![chunkannotator_1_img_4.jpg](./images/chunkannotator_1_img_4.jpg) +![chunkannotator_1_img_5.jpg](./images/chunkannotator_1_img_5.jpg) +![chunkannotator_1_img_6.jpg](./images/chunkannotator_1_img_6.jpg) +![chunkannotator_1_img_7.jpg](./images/chunkannotator_1_img_7.jpg) +![chunkannotator_1_img_8.jpg](./images/chunkannotator_1_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Approach and establish contact with the bag's main body using the right arm while the left arm remains idle.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.15, "angle": 0.33, "vel_score": 1.01, "angle_score": 2.28, "vel_fft": [0.146, 0.052, 0.019, 0.018, 0.013, 0.011, 0.008, 0.004, 0.008, 0.007, 0.011, 0.01, 0.009, 0.006, 0.005], "angle_fft": [0.334, 0.093, 0.032, 0.034, 0.039, 0.047, 0.021, 0.025, 0.008, 0.023, 0.031, 0.01, 0.015, 0.025, 0.008]}, "right": {"vel": 0.07, "angle": 0.18, "vel_score": 0.46, "angle_score": 1.27, "vel_fft": [0.068, 0.02, 0.024, 0.018, 0.01, 0.009, 0.007, 0.007, 0.008, 0.005, 0.004, 0.004, 0.003, 0.004, 0.005], "angle_fft": [0.185, 0.045, 0.069, 0.061, 0.029, 0.021, 0.023, 0.022, 0.017, 0.013, 0.012, 0.015, 0.011, 0.009, 0.011]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.54, "left_arm_ry": 0.91, "left_arm_rz": -2.9, "left_gripper": 0.27, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.74, "right_arm_rz": -2.29, "right_gripper": 0.42}, "1": {"left_arm_vel": 0.22, "left_gripper_vel": 0.147, "left_arm_rx": -2.53, "left_arm_ry": 0.91, "left_arm_rz": -2.91, "left_gripper": 0.28, "right_arm_vel": 0.22, "right_gripper_vel": 0.147, "right_arm_rx": 2.68, "right_arm_ry": 0.73, "right_arm_rz": -2.28, "right_gripper": 0.43}, "2": {"left_arm_vel": 0.208, "left_gripper_vel": 0.105, "left_arm_rx": -2.53, "left_arm_ry": 0.89, "left_arm_rz": -2.92, "left_gripper": 0.29, "right_arm_vel": 0.208, "right_gripper_vel": 0.105, "right_arm_rx": 2.68, "right_arm_ry": 0.72, "right_arm_rz": -2.26, "right_gripper": 0.43}, "3": {"left_arm_vel": 0.165, "left_gripper_vel": 0.042, "left_arm_rx": -2.53, "left_arm_ry": 0.87, "left_arm_rz": -2.94, "left_gripper": 0.3, "right_arm_vel": 0.165, "right_gripper_vel": 0.042, "right_arm_rx": 2.69, "right_arm_ry": 0.72, "right_arm_rz": -2.24, "right_gripper": 0.43}, "4": {"left_arm_vel": 0.116, "left_gripper_vel": 0.021, "left_arm_rx": -2.53, "left_arm_ry": 0.85, "left_arm_rz": -2.95, "left_gripper": 0.3, "right_arm_vel": 0.116, "right_gripper_vel": 0.021, "right_arm_rx": 2.69, "right_arm_ry": 0.72, "right_arm_rz": -2.23, "right_gripper": 0.44}, "5": {"left_arm_vel": 0.041, "left_gripper_vel": 0.063, "left_arm_rx": -2.52, "left_arm_ry": 0.82, "left_arm_rz": -2.97, "left_gripper": 0.3, "right_arm_vel": 0.041, "right_gripper_vel": 0.063, "right_arm_rx": 2.69, "right_arm_ry": 0.72, "right_arm_rz": -2.21, "right_gripper": 0.44}, "6": {"left_arm_vel": 0.068, "left_gripper_vel": 0.0, "left_arm_rx": -2.47, "left_arm_ry": 0.81, "left_arm_rz": -2.96, "left_gripper": 0.31, "right_arm_vel": 0.068, "right_gripper_vel": 0.0, "right_arm_rx": 2.69, "right_arm_ry": 0.71, "right_arm_rz": -2.2, "right_gripper": 0.44}, "7": {"left_arm_vel": 0.091, "left_gripper_vel": -0.042, "left_arm_rx": -2.45, "left_arm_ry": 0.81, "left_arm_rz": -2.95, "left_gripper": 0.31, "right_arm_vel": 0.091, "right_gripper_vel": -0.042, "right_arm_rx": 2.67, "right_arm_ry": 0.69, "right_arm_rz": -2.21, "right_gripper": 0.44}, "8": {"left_arm_vel": 0.043, "left_gripper_vel": -0.945, "left_arm_rx": -2.44, "left_arm_ry": 0.81, "left_arm_rz": -2.96, "left_gripper": 0.31, "right_arm_vel": 0.043, "right_gripper_vel": -0.945, "right_arm_rx": 2.67, "right_arm_ry": 0.67, "right_arm_rz": -2.2, "right_gripper": 0.38}, "9": {"left_arm_vel": 0.03, "left_gripper_vel": -1.638, "left_arm_rx": -2.45, "left_arm_ry": 0.81, "left_arm_rz": -2.97, "left_gripper": 0.31, "right_arm_vel": 0.03, "right_gripper_vel": -1.638, "right_arm_rx": 2.67, "right_arm_ry": 0.67, "right_arm_rz": -2.19, "right_gripper": 0.29}, "10": {"left_arm_vel": 0.013, "left_gripper_vel": -1.869, "left_arm_rx": -2.45, "left_arm_ry": 0.82, "left_arm_rz": -2.97, "left_gripper": 0.31, "right_arm_vel": 0.013, "right_gripper_vel": -1.869, "right_arm_rx": 2.68, "right_arm_ry": 0.67, "right_arm_rz": -2.19, "right_gripper": 0.23}, "11": {"left_arm_vel": 0.012, "left_gripper_vel": -2.037, "left_arm_rx": -2.45, "left_arm_ry": 0.82, "left_arm_rz": -2.99, "left_gripper": 0.31, "right_arm_vel": 0.012, "right_gripper_vel": -2.037, "right_arm_rx": 2.68, "right_arm_ry": 0.67, "right_arm_rz": -2.18, "right_gripper": 0.1}, "12": {"left_arm_vel": 0.032, "left_gripper_vel": -1.155, "left_arm_rx": -2.45, "left_arm_ry": 0.83, "left_arm_rz": -2.99, "left_gripper": 0.31, "right_arm_vel": 0.032, "right_gripper_vel": -1.155, "right_arm_rx": 2.68, "right_arm_ry": 0.67, "right_arm_rz": -2.18, "right_gripper": 0.06}, "13": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.45, "left_arm_ry": 0.83, "left_arm_rz": -3.03, "left_gripper": 0.31, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.67, "right_arm_rz": -2.18, "right_gripper": 0.06}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.12200000137090683, -0.021800000220537186, -0.054099999368190765], "delta_rot": [0.0892999991774559, -0.0860000029206276, -0.12770000100135803], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.1352}, "right": {"delta_pos": [-0.011699999682605267, 0.0364999994635582, -0.040699999779462814], "delta_rot": [0.00570000009611249, -0.07680000364780426, 0.11050000041723251], "gripper_changed": true, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.056}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.12240000069141388, -0.0714000016450882, -0.09390000253915787], "delta_rot": [-0.3691999912261963, -0.10369999706745148, 5.394499778747559], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.17}, "right": {"delta_pos": [-0.018300000578165054, 0.04699999839067459, -0.03959999978542328], "delta_rot": [-0.08940000087022781, -0.14010000228881836, -0.015799999237060547], "gripper_changed": true, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.0641}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Approach the bag's main body with the right arm to establish contact, while the left arm remains idle in a hovering position.", + "actions": [ + { + "reasoning_cot": "The right arm executes a forward and downward trajectory (delta_pos -Z, +Y) towards the bag. Visual evidence from T0 to T1 shows the gripper transitioning from free space to making direct contact with the silver reflective panel on the bag's front face. The gripper signal is 'stable' but not yet fully closed for grasping, indicating an approach and initial touch phase.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "Moving from free space to bag:main_body", + "topology_change": false + }, + { + "reasoning_cot": "The left arm exhibits minimal kinematic displacement (low velocity scores) and remains positioned away from the bag in the peripheral view. It does not interact with any object during this chunk.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "static_hover", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Right arm has successfully located and made initial contact with the bag's main body; preparing for grasp or manipulation." + } +} +```` +--- +## 🎬 ChunkAnnotator_2 + +### 👁️ 视觉输入 +![chunkannotator_2_img_0.jpg](./images/chunkannotator_2_img_0.jpg) +![chunkannotator_2_img_1.jpg](./images/chunkannotator_2_img_1.jpg) +![chunkannotator_2_img_2.jpg](./images/chunkannotator_2_img_2.jpg) +![chunkannotator_2_img_3.jpg](./images/chunkannotator_2_img_3.jpg) +![chunkannotator_2_img_4.jpg](./images/chunkannotator_2_img_4.jpg) +![chunkannotator_2_img_5.jpg](./images/chunkannotator_2_img_5.jpg) +![chunkannotator_2_img_6.jpg](./images/chunkannotator_2_img_6.jpg) +![chunkannotator_2_img_7.jpg](./images/chunkannotator_2_img_7.jpg) +![chunkannotator_2_img_8.jpg](./images/chunkannotator_2_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Approach the bag's main body with the right arm to establish contact, while the left arm remains idle in a hovering position.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.11, "angle": 8.62, "vel_score": 1.36, "angle_score": 130.4, "vel_fft": [0.111, 0.047, 0.005, 0.021, 0.017, 0.015, 0.01, 0.008, 0.005, 0.004, 0.002, 0.003, 0.005, 0.001, 0.001, 0.003, 0.004, 0.004, 0.002, 0.002], "angle_fft": [8.623, 4.725, 2.532, 4.415, 2.542, 4.649, 2.323, 5.114, 7.891, 3.85, 3.183, 4.337, 2.747, 4.654, 1.907, 5.721, 7.73, 3.174, 3.637, 4.126]}, "right": {"vel": 0.01, "angle": 0.08, "vel_score": 0.12, "angle_score": 1.07, "vel_fft": [0.006, 0.005, 0.005, 0.005, 0.004, 0.004, 0.003, 0.003, 0.002, 0.001, 0.001, 0.001, 0.0, 0.0, 0.0, 0.0, 0.001, 0.0, 0.0, 0.0], "angle_fft": [0.084, 0.045, 0.027, 0.007, 0.023, 0.012, 0.007, 0.016, 0.017, 0.014, 0.012, 0.012, 0.007, 0.006, 0.005, 0.007, 0.001, 0.007, 0.006, 0.004]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.43, "left_arm_ry": 0.82, "left_arm_rz": -3.03, "left_gripper": 0.31, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.67, "right_arm_rz": -2.18, "right_gripper": 0.06}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.6, "left_arm_ry": 0.84, "left_arm_rz": 2.89, "left_gripper": 0.37, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.67, "right_arm_rz": -2.18, "right_gripper": 0.06}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.14, "left_arm_ry": 0.83, "left_arm_rz": 2.36, "left_gripper": 0.38, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.66, "right_arm_rz": -2.2, "right_gripper": 0.05}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": -0.042, "left_arm_rx": -3.12, "left_arm_ry": 0.84, "left_arm_rz": 2.36, "left_gripper": 0.3, "right_arm_vel": 0.0, "right_gripper_vel": -0.042, "right_arm_rx": 2.67, "right_arm_ry": 0.66, "right_arm_rz": -2.2, "right_gripper": 0.05}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.1, "left_arm_ry": 0.85, "left_arm_rz": 2.35, "left_gripper": 0.18, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.66, "right_arm_rz": -2.2, "right_gripper": 0.05}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.1, "left_arm_ry": 0.86, "left_arm_rz": 2.35, "left_gripper": 0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.66, "right_arm_rz": -2.21, "right_gripper": 0.05}, "6": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": -3.06, "left_arm_ry": 0.84, "left_arm_rz": 2.39, "left_gripper": -0.01, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.62, "right_arm_rz": -2.28, "right_gripper": 0.05}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.91, "left_arm_ry": 0.81, "left_arm_rz": 2.5, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.59, "right_arm_ry": 0.6, "right_arm_rz": -2.31, "right_gripper": 0.05}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.0038999998942017555, -0.04769999906420708, -0.03799999877810478], "delta_rot": [-0.4749999940395355, -0.01209999993443489, 5.529699802398682], "gripper_changed": true, "flow_direction": "-Y(Right) and -Z(Down)", "magnitude": 0.0611}, "right": {"delta_pos": [-0.0066999997943639755, 0.010400000028312206, 0.0008999999845400453], "delta_rot": [-0.09570000320672989, -0.06390000134706497, -0.12680000066757202], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0124}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.043299999088048935, -0.16459999978542328, -0.04569999873638153], "delta_rot": [-0.3709000051021576, -0.08229999989271164, 5.254199981689453], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "magnitude": 0.1763}, "right": {"delta_pos": [-0.004399999976158142, 0.007300000172108412, 0.0010000000474974513], "delta_rot": [-0.1492999941110611, -0.1160999983549118, -0.23330000042915344], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0086}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", + "actions": [ + { + "reasoning_cot": "The left arm is positioned against the side of the bag, providing counter-pressure. The gripper is closed (0.18-0.3 range) and maintains contact to prevent the bag from sliding during the upcoming manipulation by the right arm.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "static_at_side_panel", + "topology_change": false + }, + { + "reasoning_cot": "The right arm moves from a hovering position to make direct contact with the zipper pull tab. Visual evidence in later frames shows the gripper engaging the metal tab, indicating an intent to pull or unzip.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": "engage_zipper", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "approaching_and_grasping_zipper", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "engaged" + } + ], + "task_progress": "Right arm has successfully located and grasped the zipper pull; left arm is stabilizing the bag base." + } +} +```` +--- +## 🎬 ChunkAnnotator_3 + +### 👁️ 视觉输入 +![chunkannotator_3_img_0.jpg](./images/chunkannotator_3_img_0.jpg) +![chunkannotator_3_img_1.jpg](./images/chunkannotator_3_img_1.jpg) +![chunkannotator_3_img_2.jpg](./images/chunkannotator_3_img_2.jpg) +![chunkannotator_3_img_3.jpg](./images/chunkannotator_3_img_3.jpg) +![chunkannotator_3_img_4.jpg](./images/chunkannotator_3_img_4.jpg) +![chunkannotator_3_img_5.jpg](./images/chunkannotator_3_img_5.jpg) +![chunkannotator_3_img_6.jpg](./images/chunkannotator_3_img_6.jpg) +![chunkannotator_3_img_7.jpg](./images/chunkannotator_3_img_7.jpg) +![chunkannotator_3_img_8.jpg](./images/chunkannotator_3_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.12, "angle": 0.67, "vel_score": 0.93, "angle_score": 5.0, "vel_fft": [0.124, 0.026, 0.024, 0.016, 0.016, 0.005, 0.006, 0.007, 0.005, 0.004, 0.003, 0.005, 0.002, 0.003, 0.002, 0.005, 0.003, 0.005], "angle_fft": [0.666, 0.04, 0.081, 0.124, 0.05, 0.007, 0.029, 0.043, 0.012, 0.017, 0.023, 0.05, 0.024, 0.024, 0.01, 0.019, 0.008, 0.051]}, "right": {"vel": 0.0, "angle": 0.11, "vel_score": 0.03, "angle_score": 0.83, "vel_fft": [0.004, 0.001, 0.001, 0.001, 0.0, 0.001, 0.0, 0.002, 0.002, 0.001, 0.0, 0.001, 0.001, 0.0, 0.001, 0.0, 0.002, 0.002], "angle_fft": [0.11, 0.047, 0.02, 0.023, 0.01, 0.005, 0.013, 0.006, 0.01, 0.005, 0.007, 0.01, 0.004, 0.008, 0.006, 0.011, 0.007, 0.012]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.8, "left_arm_rz": 2.51, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.58, "right_arm_ry": 0.6, "right_arm_rz": -2.32, "right_gripper": 0.05}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.81, "left_arm_ry": 0.78, "left_arm_rz": 2.58, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.59, "right_arm_rz": -2.34, "right_gripper": 0.05}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.71, "left_arm_ry": 0.77, "left_arm_rz": 2.57, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.56, "right_arm_ry": 0.58, "right_arm_rz": -2.36, "right_gripper": 0.05}, "3": {"left_arm_vel": 0.018, "left_gripper_vel": 0.0, "left_arm_rx": -2.67, "left_arm_ry": 0.75, "left_arm_rz": 2.54, "left_gripper": -0.01, "right_arm_vel": 0.018, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.57, "right_arm_rz": -2.37, "right_gripper": 0.05}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.65, "left_arm_ry": 0.74, "left_arm_rz": 2.51, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.57, "right_arm_rz": -2.38, "right_gripper": 0.05}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.65, "left_arm_ry": 0.72, "left_arm_rz": 2.46, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.56, "right_arm_rz": -2.39, "right_gripper": 0.05}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.64, "left_arm_ry": 0.69, "left_arm_rz": 2.41, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.56, "right_arm_rz": -2.39, "right_gripper": 0.05}, "7": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": -2.63, "left_arm_ry": 0.68, "left_arm_rz": 2.37, "left_gripper": -0.0, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.56, "right_arm_rz": -2.4, "right_gripper": 0.05}, "8": {"left_arm_vel": 0.015, "left_gripper_vel": 0.0, "left_arm_rx": -2.64, "left_arm_ry": 0.68, "left_arm_rz": 2.36, "left_gripper": -0.0, "right_arm_vel": 0.015, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.56, "right_arm_rz": -2.4, "right_gripper": 0.05}, "9": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.66, "left_arm_ry": 0.69, "left_arm_rz": 2.36, "left_gripper": -0.0, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.55, "right_arm_rz": -2.41, "right_gripper": 0.05}, "10": {"left_arm_vel": 0.018, "left_gripper_vel": 0.0, "left_arm_rx": -2.75, "left_arm_ry": 0.73, "left_arm_rz": 2.33, "left_gripper": -0.0, "right_arm_vel": 0.018, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.55, "right_arm_rz": -2.41, "right_gripper": 0.05}, "11": {"left_arm_vel": 0.013, "left_gripper_vel": 0.0, "left_arm_rx": -2.81, "left_arm_ry": 0.75, "left_arm_rz": 2.25, "left_gripper": -0.0, "right_arm_vel": 0.013, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.55, "right_arm_rz": -2.41, "right_gripper": 0.05}, "12": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.81, "left_arm_ry": 0.74, "left_arm_rz": 2.23, "left_gripper": -0.0, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.55, "right_arm_rz": -2.41, "right_gripper": 0.05}, "13": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.74, "left_arm_rz": 2.22, "left_gripper": -0.0, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.55, "right_arm_rz": -2.42, "right_gripper": 0.05}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.03799999877810478, -0.11620000004768372, -0.006899999920278788], "delta_rot": [0.0803999975323677, -0.06379999965429306, -0.2921000123023987], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.1225}, "right": {"delta_pos": [0.0019000000320374966, -0.0026000000070780516, 9.999999747378752e-05], "delta_rot": [-0.050599999725818634, -0.049400001764297485, -0.10000000149011612], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0032}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.0031999999191612005, -0.015599999576807022, 0.06710000336170197], "delta_rot": [0.13819999992847443, -0.0272000003606081, 0.11640000343322754], "gripper_changed": false, "flow_direction": "+Z(Up)", "magnitude": 0.069}, "right": {"delta_pos": [0.04230000078678131, -0.09719999879598618, 0.02889999933540821], "delta_rot": [-0.15029999613761902, -0.050599999725818634, -0.4397999942302704], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.1098}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", + "actions": [ + { + "reasoning_cot": "The left arm is visually confirmed holding the side of the bag (near the handle ring) to provide stability. Kinematic data shows low velocity but high angle stability, consistent with a static hold during manipulation by the other arm.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:side_handle_ring" + }, + "spatial_logic": "static_at_side_handle", + "topology_change": false + }, + { + "reasoning_cot": "The right arm moves from a hovering position to make contact with the zipper pull tab. Visual sequence shows the gripper closing around the metal pull tab. This is a precise approach and grasp action targeting the specific mechanism for opening.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "touching" + }, + "action_verb": "grasp", + "semantic_action": "engage_zipper_pull", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving_from_hover_to_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "engaged" + } + ], + "task_progress": "Right arm has successfully located and grasped the zipper pull; left arm maintains bag stability." + } +} +```` +--- +## 🎬 ChunkAnnotator_4 + +### 👁️ 视觉输入 +![chunkannotator_4_img_0.jpg](./images/chunkannotator_4_img_0.jpg) +![chunkannotator_4_img_1.jpg](./images/chunkannotator_4_img_1.jpg) +![chunkannotator_4_img_2.jpg](./images/chunkannotator_4_img_2.jpg) +![chunkannotator_4_img_3.jpg](./images/chunkannotator_4_img_3.jpg) +![chunkannotator_4_img_4.jpg](./images/chunkannotator_4_img_4.jpg) +![chunkannotator_4_img_5.jpg](./images/chunkannotator_4_img_5.jpg) +![chunkannotator_4_img_6.jpg](./images/chunkannotator_4_img_6.jpg) +![chunkannotator_4_img_7.jpg](./images/chunkannotator_4_img_7.jpg) +![chunkannotator_4_img_8.jpg](./images/chunkannotator_4_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.16, "angle": 0.63, "vel_score": 1.36, "angle_score": 4.97, "vel_fft": [0.165, 0.098, 0.039, 0.019, 0.012, 0.007, 0.006, 0.011, 0.008, 0.009, 0.01, 0.01, 0.007, 0.008, 0.011, 0.006, 0.003], "angle_fft": [0.628, 0.244, 0.161, 0.151, 0.013, 0.022, 0.031, 0.031, 0.011, 0.036, 0.033, 0.019, 0.011, 0.017, 0.023, 0.01, 0.009]}, "right": {"vel": 0.1, "angle": 0.34, "vel_score": 0.88, "angle_score": 2.84, "vel_fft": [0.101, 0.075, 0.041, 0.032, 0.02, 0.015, 0.011, 0.011, 0.009, 0.012, 0.008, 0.003, 0.004, 0.006, 0.004, 0.006, 0.005], "angle_fft": [0.342, 0.217, 0.061, 0.09, 0.035, 0.039, 0.048, 0.022, 0.018, 0.022, 0.014, 0.014, 0.004, 0.015, 0.009, 0.02, 0.02]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.73, "left_arm_rz": 2.22, "left_gripper": -0.0, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.55, "right_arm_rz": -2.42, "right_gripper": 0.05}, "1": {"left_arm_vel": 0.042, "left_gripper_vel": 0.399, "left_arm_rx": -2.7, "left_arm_ry": 0.66, "left_arm_rz": 2.27, "left_gripper": 0.08, "right_arm_vel": 0.042, "right_gripper_vel": 0.399, "right_arm_rx": 2.53, "right_arm_ry": 0.56, "right_arm_rz": -2.43, "right_gripper": 0.07}, "2": {"left_arm_vel": 0.061, "left_gripper_vel": 1.596, "left_arm_rx": -2.69, "left_arm_ry": 0.62, "left_arm_rz": 2.25, "left_gripper": 0.2, "right_arm_vel": 0.061, "right_gripper_vel": 1.596, "right_arm_rx": 2.52, "right_arm_ry": 0.56, "right_arm_rz": -2.46, "right_gripper": 0.15}, "3": {"left_arm_vel": 0.069, "left_gripper_vel": 1.617, "left_arm_rx": -2.69, "left_arm_ry": 0.6, "left_arm_rz": 2.25, "left_gripper": 0.25, "right_arm_vel": 0.069, "right_gripper_vel": 1.617, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.48, "right_gripper": 0.21}, "4": {"left_arm_vel": 0.107, "left_gripper_vel": 1.764, "left_arm_rx": -2.71, "left_arm_ry": 0.61, "left_arm_rz": 2.28, "left_gripper": 0.31, "right_arm_vel": 0.107, "right_gripper_vel": 1.764, "right_arm_rx": 2.51, "right_arm_ry": 0.58, "right_arm_rz": -2.51, "right_gripper": 0.33}, "5": {"left_arm_vel": 0.177, "left_gripper_vel": 0.504, "left_arm_rx": -2.71, "left_arm_ry": 0.66, "left_arm_rz": 2.36, "left_gripper": 0.33, "right_arm_vel": 0.177, "right_gripper_vel": 0.504, "right_arm_rx": 2.48, "right_arm_ry": 0.58, "right_arm_rz": -2.56, "right_gripper": 0.42}, "6": {"left_arm_vel": 0.342, "left_gripper_vel": 0.063, "left_arm_rx": -2.72, "left_arm_ry": 0.73, "left_arm_rz": 2.49, "left_gripper": 0.34, "right_arm_vel": 0.342, "right_gripper_vel": 0.063, "right_arm_rx": 2.45, "right_arm_ry": 0.55, "right_arm_rz": -2.63, "right_gripper": 0.43}, "7": {"left_arm_vel": 0.375, "left_gripper_vel": -0.189, "left_arm_rx": -2.74, "left_arm_ry": 0.77, "left_arm_rz": 2.63, "left_gripper": 0.34, "right_arm_vel": 0.375, "right_gripper_vel": -0.189, "right_arm_rx": 2.43, "right_arm_ry": 0.55, "right_arm_rz": -2.76, "right_gripper": 0.42}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.03970000147819519, 0.10409999638795853, 0.07699999958276749], "delta_rot": [0.04540000110864639, 0.04600000008940697, 0.40939998626708984], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and +Z(Up)", "magnitude": 0.1354}, "right": {"delta_pos": [0.04039999842643738, -0.09459999948740005, 0.02879999950528145], "delta_rot": [-0.09969999641180038, -0.0012000000569969416, -0.3398999869823456], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.1068}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.20309999585151672, -0.0364999994635582, 0.03290000185370445], "delta_rot": [-0.01119999960064888, -0.10140000283718109, -0.22259999811649323], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.209}, "right": {"delta_pos": [-0.09740000218153, -0.1444000005722046, -0.058800000697374344], "delta_rot": [0.26409998536109924, 0.10939999669790268, -0.27000001072883606], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "magnitude": 0.1839}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", + "actions": [ + { + "reasoning_cot": "The left arm is positioned at the side of the bag, maintaining a grip on the handle ring to prevent the bag from sliding during manipulation. The gripper remains closed (stable) throughout the sequence, indicating a continuous holding action to provide a stable base for the right arm's operation.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:side_handle_ring" + }, + "spatial_logic": "static_at_side_handle", + "topology_change": false + }, + { + "reasoning_cot": "The right arm moves from an open approach position to make contact with the metallic zipper pull. Visual evidence shows the gripper jaws closing around the zipper tab in the later frames (T1/T2), transitioning from 'approach' to 'grasp'. This action secures the zipper pull for the subsequent pulling motion.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": "engage_zipper", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving_from_free_space_to_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "engaged" + } + ], + "task_progress": "Right arm has successfully grasped the zipper pull; left arm maintains bag stability. Ready to unzip." + } +} +```` +--- +## 🎬 ChunkAnnotator_5 + +### 👁️ 视觉输入 +![chunkannotator_5_img_0.jpg](./images/chunkannotator_5_img_0.jpg) +![chunkannotator_5_img_1.jpg](./images/chunkannotator_5_img_1.jpg) +![chunkannotator_5_img_2.jpg](./images/chunkannotator_5_img_2.jpg) +![chunkannotator_5_img_3.jpg](./images/chunkannotator_5_img_3.jpg) +![chunkannotator_5_img_4.jpg](./images/chunkannotator_5_img_4.jpg) +![chunkannotator_5_img_5.jpg](./images/chunkannotator_5_img_5.jpg) +![chunkannotator_5_img_6.jpg](./images/chunkannotator_5_img_6.jpg) +![chunkannotator_5_img_7.jpg](./images/chunkannotator_5_img_7.jpg) +![chunkannotator_5_img_8.jpg](./images/chunkannotator_5_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.12, "angle": 0.38, "vel_score": 1.69, "angle_score": 5.32, "vel_fft": [0.124, 0.096, 0.053, 0.027, 0.017, 0.019, 0.007, 0.008, 0.007, 0.007, 0.006, 0.005, 0.004, 0.004, 0.002, 0.003, 0.001, 0.003, 0.005, 0.005], "angle_fft": [0.381, 0.285, 0.177, 0.109, 0.027, 0.012, 0.022, 0.021, 0.014, 0.007, 0.006, 0.01, 0.01, 0.005, 0.007, 0.004, 0.004, 0.004, 0.009, 0.01]}, "right": {"vel": 0.12, "angle": 0.46, "vel_score": 1.49, "angle_score": 5.21, "vel_fft": [0.123, 0.064, 0.05, 0.016, 0.006, 0.004, 0.015, 0.011, 0.009, 0.01, 0.006, 0.005, 0.006, 0.005, 0.005, 0.007, 0.008, 0.005, 0.001, 0.002], "angle_fft": [0.458, 0.106, 0.179, 0.098, 0.056, 0.04, 0.019, 0.023, 0.025, 0.013, 0.016, 0.01, 0.025, 0.019, 0.021, 0.011, 0.014, 0.027, 0.02, 0.014]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.75, "left_arm_ry": 0.78, "left_arm_rz": 2.64, "left_gripper": 0.34, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.42, "right_arm_ry": 0.55, "right_arm_rz": -2.79, "right_gripper": 0.42}, "1": {"left_arm_vel": 0.307, "left_gripper_vel": -0.063, "left_arm_rx": -2.74, "left_arm_ry": 0.79, "left_arm_rz": 2.62, "left_gripper": 0.34, "right_arm_vel": 0.307, "right_gripper_vel": -0.063, "right_arm_rx": 2.41, "right_arm_ry": 0.54, "right_arm_rz": -2.83, "right_gripper": 0.41}, "2": {"left_arm_vel": 0.276, "left_gripper_vel": 0.0, "left_arm_rx": -2.73, "left_arm_ry": 0.79, "left_arm_rz": 2.55, "left_gripper": 0.34, "right_arm_vel": 0.276, "right_gripper_vel": 0.0, "right_arm_rx": 2.42, "right_arm_ry": 0.52, "right_arm_rz": -2.86, "right_gripper": 0.41}, "3": {"left_arm_vel": 0.361, "left_gripper_vel": -0.021, "left_arm_rx": -2.73, "left_arm_ry": 0.79, "left_arm_rz": 2.49, "left_gripper": 0.34, "right_arm_vel": 0.361, "right_gripper_vel": -0.021, "right_arm_rx": 2.44, "right_arm_ry": 0.52, "right_arm_rz": -2.89, "right_gripper": 0.41}, "4": {"left_arm_vel": 0.381, "left_gripper_vel": 0.0, "left_arm_rx": -2.75, "left_arm_ry": 0.8, "left_arm_rz": 2.41, "left_gripper": 0.35, "right_arm_vel": 0.381, "right_gripper_vel": 0.0, "right_arm_rx": 2.48, "right_arm_ry": 0.55, "right_arm_rz": -2.92, "right_gripper": 0.41}, "5": {"left_arm_vel": 0.296, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.79, "left_arm_rz": 2.27, "left_gripper": 0.36, "right_arm_vel": 0.296, "right_gripper_vel": 0.0, "right_arm_rx": 2.5, "right_arm_ry": 0.6, "right_arm_rz": -2.95, "right_gripper": 0.41}, "6": {"left_arm_vel": 0.23, "left_gripper_vel": -0.021, "left_arm_rx": -2.85, "left_arm_ry": 0.76, "left_arm_rz": 2.12, "left_gripper": 0.36, "right_arm_vel": 0.23, "right_gripper_vel": -0.021, "right_arm_rx": 2.48, "right_arm_ry": 0.61, "right_arm_rz": -2.97, "right_gripper": 0.4}, "7": {"left_arm_vel": 0.164, "left_gripper_vel": -0.042, "left_arm_rx": -2.85, "left_arm_ry": 0.73, "left_arm_rz": 2.04, "left_gripper": 0.36, "right_arm_vel": 0.164, "right_gripper_vel": -0.042, "right_arm_rx": 2.45, "right_arm_ry": 0.59, "right_arm_rz": -3.01, "right_gripper": 0.4}, "8": {"left_arm_vel": 0.004, "left_gripper_vel": -0.042, "left_arm_rx": -2.83, "left_arm_ry": 0.67, "left_arm_rz": 1.98, "left_gripper": 0.36, "right_arm_vel": 0.004, "right_gripper_vel": -0.042, "right_arm_rx": 2.45, "right_arm_ry": 0.61, "right_arm_rz": -3.01, "right_gripper": 0.4}, "9": {"left_arm_vel": 0.018, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.64, "left_arm_rz": 2.01, "left_gripper": 0.25, "right_arm_vel": 0.018, "right_gripper_vel": 0.0, "right_arm_rx": 2.46, "right_arm_ry": 0.61, "right_arm_rz": -2.99, "right_gripper": 0.4}, "10": {"left_arm_vel": 0.036, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.64, "left_arm_rz": 2.0, "left_gripper": 0.11, "right_arm_vel": 0.036, "right_gripper_vel": 0.0, "right_arm_rx": 2.47, "right_arm_ry": 0.6, "right_arm_rz": -2.99, "right_gripper": 0.4}, "11": {"left_arm_vel": 0.04, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.63, "left_arm_rz": 2.0, "left_gripper": 0.04, "right_arm_vel": 0.04, "right_gripper_vel": 0.0, "right_arm_rx": 2.5, "right_arm_ry": 0.6, "right_arm_rz": -2.96, "right_gripper": 0.4}, "12": {"left_arm_vel": 0.12, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.63, "left_arm_rz": 2.0, "left_gripper": 0.04, "right_arm_vel": 0.12, "right_gripper_vel": 0.0, "right_arm_rx": 2.69, "right_arm_ry": 0.69, "right_arm_rz": -2.77, "right_gripper": 0.4}, "13": {"left_arm_vel": 0.019, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.63, "left_arm_rz": 2.0, "left_gripper": 0.04, "right_arm_vel": 0.019, "right_gripper_vel": 0.0, "right_arm_rx": 2.8, "right_arm_ry": 0.66, "right_arm_rz": -2.69, "right_gripper": 0.4}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.15150000154972076, -0.14409999549388885, -0.04820000007748604], "delta_rot": [-0.05260000005364418, -0.15700000524520874, -0.6428999900817871], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.2146}, "right": {"delta_pos": [-0.1386999934911728, -0.03739999979734421, -0.09099999815225601], "delta_rot": [0.3749000132083893, 0.11569999903440475, 0.10339999943971634], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "magnitude": 0.17}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.14270000159740448, -0.1542000025510788, -0.0471000000834465], "delta_rot": [-0.04650000110268593, -0.23829999566078186, -0.5723999738693237], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.2153}, "right": {"delta_pos": [-0.2515000104904175, 0.0763000026345253, -0.05339999869465828], "delta_rot": [0.2069000005722046, 0.1054999977350235, 0.21199999749660492], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left) and -Z(Down)", "magnitude": 0.2682}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", + "actions": [ + { + "reasoning_cot": "The left arm is positioned at the side of the bag, maintaining a steady hold on the handle ring to prevent the bag from shifting. The gripper remains closed (stable) throughout the sequence, confirming a continuous 'hold' action rather than a grasp or release event.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:side_handle_ring" + }, + "spatial_logic": "static_at_side_handle", + "topology_change": false + }, + { + "reasoning_cot": "The right arm moves from a hovering position towards the top edge of the bag. Visual evidence shows the gripper tips making contact with the zipper pull/tab area. The gripper signal indicates a closing motion ('closing') coinciding with this contact, signifying an intent to grasp the zipper mechanism.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "touching" + }, + "action_verb": "grasp", + "semantic_action": "engage_zipper", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "approaching_and_engaging_zipper", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "engaged" + } + ], + "task_progress": "Right arm has successfully located and initiated contact with the zipper pull while the left arm stabilizes the bag base." + } +} +```` +--- +## 🎬 ChunkAnnotator_6 + +### 👁️ 视觉输入 +![chunkannotator_6_img_0.jpg](./images/chunkannotator_6_img_0.jpg) +![chunkannotator_6_img_1.jpg](./images/chunkannotator_6_img_1.jpg) +![chunkannotator_6_img_2.jpg](./images/chunkannotator_6_img_2.jpg) +![chunkannotator_6_img_3.jpg](./images/chunkannotator_6_img_3.jpg) +![chunkannotator_6_img_4.jpg](./images/chunkannotator_6_img_4.jpg) +![chunkannotator_6_img_5.jpg](./images/chunkannotator_6_img_5.jpg) +![chunkannotator_6_img_6.jpg](./images/chunkannotator_6_img_6.jpg) +![chunkannotator_6_img_7.jpg](./images/chunkannotator_6_img_7.jpg) +![chunkannotator_6_img_8.jpg](./images/chunkannotator_6_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.01, "angle": 0.12, "vel_score": 0.12, "angle_score": 1.23, "vel_fft": [0.01, 0.005, 0.006, 0.004, 0.003, 0.003, 0.002, 0.001, 0.0, 0.001, 0.0, 0.0, 0.001, 0.002, 0.002, 0.001, 0.001, 0.001, 0.001, 0.001], "angle_fft": [0.115, 0.041, 0.037, 0.012, 0.029, 0.006, 0.005, 0.006, 0.012, 0.011, 0.013, 0.01, 0.008, 0.006, 0.005, 0.009, 0.006, 0.006, 0.002, 0.004]}, "right": {"vel": 0.15, "angle": 0.32, "vel_score": 1.55, "angle_score": 3.27, "vel_fft": [0.146, 0.04, 0.033, 0.034, 0.011, 0.009, 0.006, 0.006, 0.005, 0.006, 0.004, 0.005, 0.005, 0.002, 0.003, 0.001, 0.003, 0.003, 0.005, 0.003], "angle_fft": [0.317, 0.041, 0.077, 0.018, 0.064, 0.024, 0.02, 0.024, 0.006, 0.011, 0.014, 0.008, 0.005, 0.0, 0.011, 0.008, 0.017, 0.011, 0.008, 0.024]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.63, "left_arm_rz": 2.0, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.79, "right_arm_ry": 0.67, "right_arm_rz": -2.69, "right_gripper": 0.4}, "1": {"left_arm_vel": 0.114, "left_gripper_vel": -0.315, "left_arm_rx": -2.8, "left_arm_ry": 0.63, "left_arm_rz": 2.0, "left_gripper": 0.04, "right_arm_vel": 0.114, "right_gripper_vel": -0.315, "right_arm_rx": 2.76, "right_arm_ry": 0.71, "right_arm_rz": -2.72, "right_gripper": 0.35}, "2": {"left_arm_vel": 0.011, "left_gripper_vel": -2.247, "left_arm_rx": -2.8, "left_arm_ry": 0.63, "left_arm_rz": 2.0, "left_gripper": 0.04, "right_arm_vel": 0.011, "right_gripper_vel": -2.247, "right_arm_rx": 2.74, "right_arm_ry": 0.72, "right_arm_rz": -2.73, "right_gripper": 0.08}, "3": {"left_arm_vel": 0.183, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.62, "left_arm_rz": 2.02, "left_gripper": 0.04, "right_arm_vel": 0.183, "right_gripper_vel": 0.0, "right_arm_rx": 2.73, "right_arm_ry": 0.59, "right_arm_rz": -2.73, "right_gripper": 0.01}, "4": {"left_arm_vel": 0.222, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.59, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.222, "right_gripper_vel": 0.0, "right_arm_rx": 2.69, "right_arm_ry": 0.62, "right_arm_rz": -2.73, "right_gripper": 0.01}, "5": {"left_arm_vel": 0.122, "left_gripper_vel": 0.0, "left_arm_rx": -2.77, "left_arm_ry": 0.57, "left_arm_rz": 2.12, "left_gripper": 0.04, "right_arm_vel": 0.122, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.58, "right_arm_rz": -2.73, "right_gripper": 0.01}, "6": {"left_arm_vel": 0.297, "left_gripper_vel": 0.0, "left_arm_rx": -2.78, "left_arm_ry": 0.56, "left_arm_rz": 2.11, "left_gripper": 0.04, "right_arm_vel": 0.297, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.64, "right_arm_rz": -2.59, "right_gripper": 0.01}, "7": {"left_arm_vel": 0.222, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.55, "left_arm_rz": 2.07, "left_gripper": 0.04, "right_arm_vel": 0.222, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.65, "right_arm_rz": -2.58, "right_gripper": 0.01}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.008899999782443047, -0.010200000368058681, 0.0010999999940395355], "delta_rot": [0.006099999882280827, -0.08129999786615372, 0.07050000131130219], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0135}, "right": {"delta_pos": [-0.11339999735355377, 0.11330000311136246, 0.03750000149011612], "delta_rot": [-0.1647000014781952, -0.01769999973475933, 0.11079999804496765], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1646}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.06109999865293503, 0.05290000140666962, 0.1200999990105629], "delta_rot": [-0.054999999701976776, -0.005900000222027302, 0.4327999949455261], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1447}, "right": {"delta_pos": [-0.16949999332427979, -0.02199999988079071, 0.09769999980926514], "delta_rot": [-0.06350000202655792, -0.2142000049352646, -0.1088000014424324], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.1969}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", + "actions": [ + { + "reasoning_cot": "The left arm is positioned at the side of the bag, maintaining a static hold on the handle ring to stabilize the object against the pulling force of the right arm. Visual evidence shows no significant displacement or gripper change for the left arm.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:side_handle_ring" + }, + "spatial_logic": "static_at_side_handle", + "topology_change": false + }, + { + "reasoning_cot": "The right arm executes a trajectory from free space towards the bag's zipper mechanism. Kinematic data indicates a closing gripper signal (-0.315) coinciding with visual contact on the metal zipper pull tab. The arm then applies a pulling force (delta_pos -X, +Y) to slide the zipper open, changing the bag's topology from closed to partially open.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "pull", + "semantic_action": "unzip", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving_from_hover_to_zipper_pull_then_dragging", + "topology_change": true + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "engaged_and_pulled" + }, + { + "anchor_id": "bag:main_body", + "current_status": "opening" + } + ], + "task_progress": "Initiating bag opening by stabilizing with left hand and pulling zipper with right hand." + } +} +```` +--- +## 🎬 ChunkAnnotator_7 + +### 👁️ 视觉输入 +![chunkannotator_7_img_0.jpg](./images/chunkannotator_7_img_0.jpg) +![chunkannotator_7_img_1.jpg](./images/chunkannotator_7_img_1.jpg) +![chunkannotator_7_img_2.jpg](./images/chunkannotator_7_img_2.jpg) +![chunkannotator_7_img_3.jpg](./images/chunkannotator_7_img_3.jpg) +![chunkannotator_7_img_4.jpg](./images/chunkannotator_7_img_4.jpg) +![chunkannotator_7_img_5.jpg](./images/chunkannotator_7_img_5.jpg) +![chunkannotator_7_img_6.jpg](./images/chunkannotator_7_img_6.jpg) +![chunkannotator_7_img_7.jpg](./images/chunkannotator_7_img_7.jpg) +![chunkannotator_7_img_8.jpg](./images/chunkannotator_7_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "opening"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged_and_pulled"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.18, "angle": 0.52, "vel_score": 1.25, "angle_score": 3.37, "vel_fft": [0.18, 0.102, 0.029, 0.028, 0.019, 0.017, 0.015, 0.021, 0.017, 0.011, 0.013, 0.01, 0.013, 0.006], "angle_fft": [0.52, 0.078, 0.109, 0.07, 0.061, 0.038, 0.028, 0.028, 0.042, 0.022, 0.027, 0.036, 0.032, 0.017]}, "right": {"vel": 0.22, "angle": 0.65, "vel_score": 1.53, "angle_score": 4.33, "vel_fft": [0.223, 0.075, 0.033, 0.002, 0.011, 0.003, 0.007, 0.011, 0.009, 0.009, 0.005, 0.006, 0.011, 0.008], "angle_fft": [0.653, 0.184, 0.065, 0.056, 0.031, 0.056, 0.075, 0.025, 0.032, 0.022, 0.057, 0.024, 0.005, 0.039]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.54, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.65, "right_arm_rz": -2.57, "right_gripper": 0.01}, "1": {"left_arm_vel": 0.094, "left_gripper_vel": 0.714, "left_arm_rx": -2.78, "left_arm_ry": 0.53, "left_arm_rz": 2.1, "left_gripper": 0.05, "right_arm_vel": 0.094, "right_gripper_vel": 0.714, "right_arm_rx": 2.6, "right_arm_ry": 0.58, "right_arm_rz": -2.62, "right_gripper": 0.04}, "2": {"left_arm_vel": 0.174, "left_gripper_vel": 1.638, "left_arm_rx": -2.77, "left_arm_ry": 0.53, "left_arm_rz": 2.13, "left_gripper": 0.1, "right_arm_vel": 0.174, "right_gripper_vel": 1.638, "right_arm_rx": 2.6, "right_arm_ry": 0.51, "right_arm_rz": -2.63, "right_gripper": 0.14}, "3": {"left_arm_vel": 0.2, "left_gripper_vel": 2.394, "left_arm_rx": -2.76, "left_arm_ry": 0.53, "left_arm_rz": 2.16, "left_gripper": 0.15, "right_arm_vel": 0.2, "right_gripper_vel": 2.394, "right_arm_rx": 2.6, "right_arm_ry": 0.47, "right_arm_rz": -2.61, "right_gripper": 0.22}, "4": {"left_arm_vel": 0.325, "left_gripper_vel": 2.478, "left_arm_rx": -2.75, "left_arm_ry": 0.53, "left_arm_rz": 2.19, "left_gripper": 0.19, "right_arm_vel": 0.325, "right_gripper_vel": 2.478, "right_arm_rx": 2.62, "right_arm_ry": 0.45, "right_arm_rz": -2.63, "right_gripper": 0.3}, "5": {"left_arm_vel": 0.39, "left_gripper_vel": 2.037, "left_arm_rx": -2.74, "left_arm_ry": 0.52, "left_arm_rz": 2.21, "left_gripper": 0.22, "right_arm_vel": 0.39, "right_gripper_vel": 2.037, "right_arm_rx": 2.64, "right_arm_ry": 0.45, "right_arm_rz": -2.64, "right_gripper": 0.37}, "6": {"left_arm_vel": 0.376, "left_gripper_vel": 1.113, "left_arm_rx": -2.73, "left_arm_ry": 0.52, "left_arm_rz": 2.23, "left_gripper": 0.23, "right_arm_vel": 0.376, "right_gripper_vel": 1.113, "right_arm_rx": 2.67, "right_arm_ry": 0.45, "right_arm_rz": -2.65, "right_gripper": 0.41}, "7": {"left_arm_vel": 0.369, "left_gripper_vel": 0.777, "left_arm_rx": -2.73, "left_arm_ry": 0.52, "left_arm_rz": 2.25, "left_gripper": 0.23, "right_arm_vel": 0.369, "right_gripper_vel": 0.777, "right_arm_rx": 2.69, "right_arm_ry": 0.46, "right_arm_rz": -2.66, "right_gripper": 0.43}, "8": {"left_arm_vel": 0.39, "left_gripper_vel": 0.462, "left_arm_rx": -2.73, "left_arm_ry": 0.52, "left_arm_rz": 2.27, "left_gripper": 0.23, "right_arm_vel": 0.39, "right_gripper_vel": 0.462, "right_arm_rx": 2.7, "right_arm_ry": 0.48, "right_arm_rz": -2.69, "right_gripper": 0.45}, "9": {"left_arm_vel": 0.35, "left_gripper_vel": 0.231, "left_arm_rx": -2.74, "left_arm_ry": 0.52, "left_arm_rz": 2.28, "left_gripper": 0.23, "right_arm_vel": 0.35, "right_gripper_vel": 0.231, "right_arm_rx": 2.71, "right_arm_ry": 0.49, "right_arm_rz": -2.71, "right_gripper": 0.46}, "10": {"left_arm_vel": 0.315, "left_gripper_vel": 0.063, "left_arm_rx": -2.77, "left_arm_ry": 0.54, "left_arm_rz": 2.32, "left_gripper": 0.23, "right_arm_vel": 0.315, "right_gripper_vel": 0.063, "right_arm_rx": 2.71, "right_arm_ry": 0.5, "right_arm_rz": -2.78, "right_gripper": 0.47}, "11": {"left_arm_vel": 0.26, "left_gripper_vel": 0.021, "left_arm_rx": -2.78, "left_arm_ry": 0.57, "left_arm_rz": 2.36, "left_gripper": 0.23, "right_arm_vel": 0.26, "right_gripper_vel": 0.021, "right_arm_rx": 2.71, "right_arm_ry": 0.49, "right_arm_rz": -2.82, "right_gripper": 0.47}, "12": {"left_arm_vel": 0.247, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.6, "left_arm_rz": 2.41, "left_gripper": 0.21, "right_arm_vel": 0.247, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.46, "right_arm_rz": -2.81, "right_gripper": 0.47}, "13": {"left_arm_vel": 0.259, "left_gripper_vel": 0.0, "left_arm_rx": -2.86, "left_arm_ry": 0.62, "left_arm_rz": 2.43, "left_gripper": 0.2, "right_arm_vel": 0.259, "right_gripper_vel": 0.0, "right_arm_rx": 2.73, "right_arm_ry": 0.45, "right_arm_rz": -2.8, "right_gripper": 0.47}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.05180000141263008, 0.06300000101327896, 0.11909999698400497], "delta_rot": [-0.06239999830722809, 0.07850000262260437, 0.3644999861717224], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1443}, "right": {"delta_pos": [-0.05640000104904175, -0.14090000092983246, 0.06260000169277191], "delta_rot": [0.09960000216960907, -0.19329999387264252, -0.2305999994277954], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.1642}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.4090999960899353, 0.2743000090122223, 0.06260000169277191], "delta_rot": [-0.23270000517368317, 0.5770999789237976, 0.7328000068664551], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.4965}, "right": {"delta_pos": [-0.2298000007867813, -0.2529999911785126, 0.09600000083446503], "delta_rot": [-5.654600143432617, 0.46160000562667847, -0.05790000036358833], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.355}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", + "actions": [ + { + "reasoning_cot": "The left arm is visually confirmed holding the side of the bag (silver mesh panel) to provide stability. The gripper remains closed and stable throughout the sequence, indicating a continuous 'hold' action to counteract forces from the right arm.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:side_handle_ring" + }, + "spatial_logic": "static_at_side_anchor", + "topology_change": false + }, + { + "reasoning_cot": "The right arm moves from a hovering position to make contact with the metal zipper pull. Visual evidence shows the gripper closing around the pull tab (Frames 2-3) and then pulling it backwards/upwards (Frames 4-5), causing the zipper track to separate. This is a clear 'pull' action on the zipper mechanism.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "pull", + "semantic_action": "unzip", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "engaging_and_retracting_zipper", + "topology_change": true + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:main_body", + "current_status": "opening" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "engaged_and_pulled" + } + ], + "task_progress": "Initiating bag opening by stabilizing the base and retracting the zipper." + } +} +```` +--- +## 🎬 ChunkAnnotator_8 + +### 👁️ 视觉输入 +![chunkannotator_8_img_0.jpg](./images/chunkannotator_8_img_0.jpg) +![chunkannotator_8_img_1.jpg](./images/chunkannotator_8_img_1.jpg) +![chunkannotator_8_img_2.jpg](./images/chunkannotator_8_img_2.jpg) +![chunkannotator_8_img_3.jpg](./images/chunkannotator_8_img_3.jpg) +![chunkannotator_8_img_4.jpg](./images/chunkannotator_8_img_4.jpg) +![chunkannotator_8_img_5.jpg](./images/chunkannotator_8_img_5.jpg) +![chunkannotator_8_img_6.jpg](./images/chunkannotator_8_img_6.jpg) +![chunkannotator_8_img_7.jpg](./images/chunkannotator_8_img_7.jpg) +![chunkannotator_8_img_8.jpg](./images/chunkannotator_8_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "opening"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged_and_pulled"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.36, "angle": 10.37, "vel_score": 3.26, "angle_score": 117.13, "vel_fft": [0.356, 0.209, 0.058, 0.033, 0.022, 0.027, 0.017, 0.015, 0.014, 0.017, 0.018, 0.017, 0.008, 0.008, 0.003, 0.01, 0.01, 0.011, 0.014, 0.008], "angle_fft": [10.367, 9.198, 7.7, 5.387, 2.659, 0.495, 3.385, 6.089, 8.1, 9.313, 9.563, 8.773, 7.149, 4.749, 1.897, 1.182, 4.076, 6.656, 8.45, 9.431]}, "right": {"vel": 0.17, "angle": 5.6, "vel_score": 1.48, "angle_score": 7.0, "vel_fft": [0.165, 0.084, 0.034, 0.014, 0.008, 0.008, 0.007, 0.007, 0.007, 0.003, 0.005, 0.012, 0.01, 0.005, 0.001, 0.005, 0.007, 0.004, 0.005, 0.002], "angle_fft": [5.596, 5.014, 4.745, 4.847, 4.749, 4.81, 4.8, 4.804, 4.771, 4.796, 4.848, 4.788, 4.807, 4.81, 4.788, 4.803, 4.803, 4.783, 4.792, 4.814]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.63, "left_arm_rz": 2.46, "left_gripper": 0.18, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.75, "right_arm_ry": 0.45, "right_arm_rz": -2.79, "right_gripper": 0.47}, "1": {"left_arm_vel": 0.456, "left_gripper_vel": 0.0, "left_arm_rx": -2.92, "left_arm_ry": 0.8, "left_arm_rz": 2.6, "left_gripper": 0.17, "right_arm_vel": 0.456, "right_gripper_vel": 0.0, "right_arm_rx": 3.0, "right_arm_ry": 0.53, "right_arm_rz": -2.7, "right_gripper": 0.47}, "2": {"left_arm_vel": 0.311, "left_gripper_vel": 0.0, "left_arm_rx": -2.99, "left_arm_ry": 0.92, "left_arm_rz": 2.6, "left_gripper": 0.24, "right_arm_vel": 0.311, "right_gripper_vel": 0.0, "right_arm_rx": 3.09, "right_arm_ry": 0.58, "right_arm_rz": -2.67, "right_gripper": 0.47}, "3": {"left_arm_vel": 0.249, "left_gripper_vel": 0.0, "left_arm_rx": -3.03, "left_arm_ry": 1.01, "left_arm_rz": 2.6, "left_gripper": 0.34, "right_arm_vel": 0.249, "right_gripper_vel": 0.0, "right_arm_rx": 3.12, "right_arm_ry": 0.66, "right_arm_rz": -2.66, "right_gripper": 0.47}, "4": {"left_arm_vel": 0.159, "left_gripper_vel": 0.0, "left_arm_rx": 3.1, "left_arm_ry": 1.18, "left_arm_rz": 2.56, "left_gripper": 0.36, "right_arm_vel": 0.159, "right_gripper_vel": 0.0, "right_arm_rx": -3.11, "right_arm_ry": 0.92, "right_arm_rz": -2.64, "right_gripper": 0.47}, "5": {"left_arm_vel": 0.102, "left_gripper_vel": -0.252, "left_arm_rx": -3.07, "left_arm_ry": 1.13, "left_arm_rz": 2.69, "left_gripper": 0.35, "right_arm_vel": 0.102, "right_gripper_vel": -0.252, "right_arm_rx": -3.01, "right_arm_ry": 1.08, "right_arm_rz": -2.58, "right_gripper": 0.45}, "6": {"left_arm_vel": 0.017, "left_gripper_vel": -0.273, "left_arm_rx": -3.04, "left_arm_ry": 1.12, "left_arm_rz": 2.76, "left_gripper": 0.34, "right_arm_vel": 0.017, "right_gripper_vel": -0.273, "right_arm_rx": -3.01, "right_arm_ry": 1.11, "right_arm_rz": -2.6, "right_gripper": 0.42}, "7": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -3.03, "left_arm_ry": 1.12, "left_arm_rz": 2.8, "left_gripper": 0.32, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": -3.03, "right_arm_ry": 1.11, "right_arm_rz": -2.62, "right_gripper": 0.4}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.3450999855995178, 0.2029000073671341, -0.05869999900460243], "delta_rot": [-0.15639999508857727, 0.4925999939441681, 0.34119999408721924], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and -Z(Down)", "magnitude": 0.4046}, "right": {"delta_pos": [-0.16779999434947968, -0.10840000212192535, 0.02969999983906746], "delta_rot": [-5.770899772644043, 0.6640999913215637, 0.163100004196167], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.202}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.3465999960899353, 0.19990000128746033, -0.05869999900460243], "delta_rot": [-0.14959999918937683, 0.5134999752044678, -5.5482001304626465], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and -Z(Down)", "magnitude": 0.4044}, "right": {"delta_pos": [-0.16820000112056732, -0.10689999908208847, 0.02969999983906746], "delta_rot": [-5.77209997177124, 0.6668000221252441, -0.17299999296665192], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.2015}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm approaches and makes contact with the bag's top surface to stabilize it, while right arm remains idle in a hovering position.", + "actions": [ + { + "reasoning_cot": "The left arm moves from a neutral position towards the bag (Images 1-3) and establishes visual contact with the top reflective patch (Image 4). The gripper width remains stable (~0.35), indicating no grasp attempt yet, just stabilization/touching. This is a transition from free space to object interaction.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "touch", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "Approaching from above to touch the top surface of the bag.", + "topology_change": false + }, + { + "reasoning_cot": "The right arm shows minimal displacement and remains positioned over the table edge/floor area, away from the bag. It does not interact with any object during this chunk.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": null, + "spatial_logic": "Static hover position, maintaining distance from the workspace.", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:main_body", + "current_status": "touched_and_stabilized" + } + ], + "task_progress": "Initiating physical contact with the bag to prepare for manipulation." + } +} +```` +--- +## 🎬 ChunkAnnotator_9 + +### 👁️ 视觉输入 +![chunkannotator_9_img_0.jpg](./images/chunkannotator_9_img_0.jpg) +![chunkannotator_9_img_1.jpg](./images/chunkannotator_9_img_1.jpg) +![chunkannotator_9_img_2.jpg](./images/chunkannotator_9_img_2.jpg) +![chunkannotator_9_img_3.jpg](./images/chunkannotator_9_img_3.jpg) +![chunkannotator_9_img_4.jpg](./images/chunkannotator_9_img_4.jpg) +![chunkannotator_9_img_5.jpg](./images/chunkannotator_9_img_5.jpg) +![chunkannotator_9_img_6.jpg](./images/chunkannotator_9_img_6.jpg) +![chunkannotator_9_img_7.jpg](./images/chunkannotator_9_img_7.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 4 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged_and_pulled"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and makes contact with the bag's top surface to stabilize it, while right arm remains idle in a hovering position.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.0, "angle": 5.09, "vel_score": 0.04, "angle_score": 3.29, "vel_fft": [0.004, 0.003, 0.002, 0.002, 0.001, 0.001, 0.001, 0.001, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "angle_fft": [5.086, 5.024, 4.888, 4.778, 4.749, 4.772, 4.792, 4.79, 4.78, 4.778, 4.783, 4.79, 4.792, 4.79, 4.784, 4.781, 4.784, 4.789, 4.789, 4.787]}, "right": {"vel": 0.0, "angle": 0.26, "vel_score": 0.02, "angle_score": 3.06, "vel_fft": [0.001, 0.001, 0.001, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "angle_fft": [0.259, 0.23, 0.179, 0.106, 0.049, 0.006, 0.01, 0.012, 0.009, 0.009, 0.006, 0.009, 0.013, 0.009, 0.007, 0.006, 0.005, 0.006, 0.004, 0.005]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.03, "left_arm_ry": 1.12, "left_arm_rz": 2.8, "left_gripper": 0.31, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": -3.03, "right_arm_ry": 1.11, "right_arm_rz": -2.63, "right_gripper": 0.4}, "1": {"left_arm_vel": 0.001, "left_gripper_vel": 0.0, "left_arm_rx": -3.02, "left_arm_ry": 1.12, "left_arm_rz": 2.84, "left_gripper": 0.29, "right_arm_vel": 0.001, "right_gripper_vel": 0.0, "right_arm_rx": -3.03, "right_arm_ry": 1.11, "right_arm_rz": -2.63, "right_gripper": 0.4}, "2": {"left_arm_vel": 0.005, "left_gripper_vel": 0.0, "left_arm_rx": -3.02, "left_arm_ry": 1.14, "left_arm_rz": 2.98, "left_gripper": 0.27, "right_arm_vel": 0.005, "right_gripper_vel": 0.0, "right_arm_rx": -3.02, "right_arm_ry": 1.11, "right_arm_rz": -2.71, "right_gripper": 0.4}, "3": {"left_arm_vel": 0.008, "left_gripper_vel": 0.0, "left_arm_rx": -3.02, "left_arm_ry": 1.14, "left_arm_rz": 3.03, "left_gripper": 0.27, "right_arm_vel": 0.008, "right_gripper_vel": 0.0, "right_arm_rx": -3.02, "right_arm_ry": 1.11, "right_arm_rz": -2.76, "right_gripper": 0.4}, "4": {"left_arm_vel": 0.007, "left_gripper_vel": 0.0, "left_arm_rx": -3.02, "left_arm_ry": 1.14, "left_arm_rz": -3.14, "left_gripper": 0.25, "right_arm_vel": 0.007, "right_gripper_vel": 0.0, "right_arm_rx": -3.02, "right_arm_ry": 1.11, "right_arm_rz": -2.89, "right_gripper": 0.4}, "5": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -3.02, "left_arm_ry": 1.14, "left_arm_rz": -3.1, "left_gripper": 0.24, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": -3.02, "right_arm_ry": 1.11, "right_arm_rz": -2.94, "right_gripper": 0.4}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": -0.042, "left_arm_rx": -3.02, "left_arm_ry": 1.14, "left_arm_rz": -3.09, "left_gripper": 0.23, "right_arm_vel": 0.0, "right_gripper_vel": -0.042, "right_arm_rx": -3.02, "right_arm_ry": 1.11, "right_arm_rz": -2.96, "right_gripper": 0.4}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.02, "left_arm_ry": 1.14, "left_arm_rz": -3.09, "left_gripper": 0.23, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": -3.03, "right_arm_ry": 1.11, "right_arm_rz": -2.96, "right_gripper": 0.4}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.001500000013038516, -0.002899999963119626, -0.0], "delta_rot": [0.006800000090152025, 0.020800000056624413, -5.891300201416016], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0033}, "right": {"delta_pos": [-0.00039999998989515007, 0.001500000013038516, -0.0], "delta_rot": [-0.0, 0.0026000000070780516, -0.33489999175071716], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0016}} + + [FUTURE HINDSIGHT HINT]: + "End of Trajectory" + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Both arms remain in a static hovering state above the table surface, maintaining position without interacting with the bag.", + "actions": [ + { + "reasoning_cot": "The left arm shows negligible kinematic displacement (delta_pos ~0.0015) and zero gripper velocity. Visually, the end-effector remains suspended over the empty table surface to the left of the bag, maintaining a consistent hover height without making contact.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "hover", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "static_hover_left_of_bag", + "topology_change": false + }, + { + "reasoning_cot": "The right arm exhibits minimal movement (delta_pos ~0.0004) and stable gripper status. Visual evidence confirms the end-effector is hovering over the table surface on the right side, with no engagement with the bag or table.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "hover", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": null, + "spatial_logic": "static_hover_right_of_bag", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Arms are holding a static waiting position; no manipulation of the bag or environment is occurring in this chunk." + } +} +```` +--- +## 🎬 SubtaskAnnotator_0 + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are an expert human observer curating Embodied AI datasets. + Your goal is to synthesize a timeline of low-level robotic micro-actions into a highly logical, human-readable hierarchy of "Macro Chapters" (Subtasks). + + ### 0. GLOBAL CONTEXT + - **Video ID**: video_0006 + - **Total Frames**: 463 + - **Global Task Goal**: "Unknown Task" + + ### 1. INPUT DATA + - **KPM (Micro-Actions Timeline)**: [{"chunk_idx": 0, "start_frame": 0, "end_frame": 68, "chunk_intent": "Approach and establish contact with the bag's main body using the right arm while the left arm remains idle.", "micro_actions": [{"verb": "approach", "semantic_verb": null, "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Moving from table surface zone to bag:main_body anchor"}, {"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "Static at initial position"}]}, {"chunk_idx": 1, "start_frame": 69, "end_frame": 97, "chunk_intent": "Approach the bag's main body with the right arm to establish contact, while the left arm remains idle in a hovering position.", "micro_actions": [{"verb": "approach", "semantic_verb": null, "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Moving from free space to bag:main_body"}, {"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_hover"}]}, {"chunk_idx": 2, "start_frame": 98, "end_frame": 168, "chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "static_at_side_panel"}, {"verb": "grasp", "semantic_verb": "engage_zipper", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "approaching_and_grasping_zipper"}]}, {"chunk_idx": 3, "start_frame": 169, "end_frame": 202, "chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:side_handle_ring", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_side_handle"}, {"verb": "grasp", "semantic_verb": "engage_zipper_pull", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving_from_hover_to_zipper_pull"}]}, {"chunk_idx": 4, "start_frame": 203, "end_frame": 235, "chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:side_handle_ring", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_side_handle"}, {"verb": "grasp", "semantic_verb": "engage_zipper", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "moving_from_free_space_to_zipper_pull"}]}, {"chunk_idx": 5, "start_frame": 236, "end_frame": 299, "chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:side_handle_ring", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_side_handle"}, {"verb": "grasp", "semantic_verb": "engage_zipper", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "approaching_and_engaging_zipper"}]}, {"chunk_idx": 6, "start_frame": 300, "end_frame": 357, "chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:side_handle_ring", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_side_handle"}, {"verb": "pull", "semantic_verb": "unzip", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "moving_from_hover_to_zipper_pull_then_dragging"}]}, {"chunk_idx": 7, "start_frame": 358, "end_frame": 384, "chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:side_handle_ring", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_side_anchor"}, {"verb": "pull", "semantic_verb": "unzip", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "engaging_and_retracting_zipper"}]}, {"chunk_idx": 8, "start_frame": 385, "end_frame": 423, "chunk_intent": "Left arm approaches and makes contact with the bag's top surface to stabilize it, while right arm remains idle in a hovering position.", "micro_actions": [{"verb": "touch", "semantic_verb": null, "subject": "left_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Approaching from above to touch the top surface of the bag."}, {"verb": "idle", "semantic_verb": null, "subject": "right_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "Static hover position, maintaining distance from the workspace."}]}, {"chunk_idx": 9, "start_frame": 424, "end_frame": 462, "chunk_intent": "Both arms remain in a static hovering state above the table surface, maintaining position without interacting with the bag.", "micro_actions": [{"verb": "hover", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_hover_left_of_bag"}, {"verb": "hover", "semantic_verb": null, "subject": "right_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_hover_right_of_bag"}]}] + - **WSM (State Memory)**: [{"chunk_idx": 0, "global_frame_range": [0, 68], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}], "short_term_memory": {"last_chunk_intent": "Approach and establish contact with the bag's main body using the right arm while the left arm remains idle.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 1, "global_frame_range": [69, 97], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}], "short_term_memory": {"last_chunk_intent": "Approach the bag's main body with the right arm to establish contact, while the left arm remains idle in a hovering position.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 2, "global_frame_range": [98, 168], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}], "short_term_memory": {"last_chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 3, "global_frame_range": [169, 202], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}], "short_term_memory": {"last_chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 4, "global_frame_range": [203, 235], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}], "short_term_memory": {"last_chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 5, "global_frame_range": [236, 299], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}], "short_term_memory": {"last_chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 6, "global_frame_range": [300, 357], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "opening"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged_and_pulled"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}], "short_term_memory": {"last_chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 7, "global_frame_range": [358, 384], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "opening"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged_and_pulled"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}], "short_term_memory": {"last_chunk_intent": "Stabilize the bag's main body with the left arm while the right arm approaches and engages the zipper pull to initiate opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 8, "global_frame_range": [385, 423], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged_and_pulled"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and makes contact with the bag's top surface to stabilize it, while right arm remains idle in a hovering position.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 9, "global_frame_range": [424, 462], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "engaged_and_pulled"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}], "short_term_memory": {"last_chunk_intent": "Both arms remain in a static hovering state above the table surface, maintaining position without interacting with the bag.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}] + + ### 2. SYNTHESIS RULES (COMMON SENSE & NATURAL BOUNDARIES) + You must divide the chronological timeline into distinct segments. Instead of following rigid verb rules, use your human common sense to identify when a new phase of the task begins. + + **A natural "Chapter Boundary" (Segment Break) occurs when:** + 1. **Target Object Shift (CRITICAL)**: The robot shifts its focus or interaction from one primary object to another (e.g., finishes pouring into 'cup_A' and moves to 'cup_B', or drops a 'sponge' to pick up a 'towel'). NEVER merge actions directed at different primary targets into the same segment. + 2. **Major State Transition**: As seen in the WSM, a significant physical event occurs (e.g., the gripper transitions from 'none' to 'holding', or an object's topology drastically changes). + 3. **Semantic Goal Shift**: The overarching intent changes (e.g., from the "Approach & Preparation" phase to the "Active Manipulation" phase, and finally to the "Retract & Idle" phase). + + **Grouping Principle:** + - Merge consecutive chunks that serve a single, unified purpose (e.g., multiple chunks of "hover" and "hold" that all serve the continuous intent of "pouring water into the paper cup" should be merged into one segment). + - Ensure chronological integrity: Segments must be contiguous using the `chunk_idx` (e.g., [0, 2], [3, 5]). No gaps, no overlapping chunks. + + ### 3. OUTPUT REQUIREMENT + - `merge_thought`: Explain your logic based on the natural boundaries. Example: "Chunks 2-5 represent the continuous pouring phase into the paper cup. I broke the segment at Chunk 6 because the target shifted to the teal cup." + - `chunk_idx_range`: Output the exact index range `[start, end]`. + - `state_transition.before_anchors`: For the VERY FIRST segment (segment 0), this MUST exactly match these initial anchors: [{"anchor_id": "table:surface_center", "current_status": "exposed"}, {"anchor_id": "bag:main_body", "current_status": "upright_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle_ring", "current_status": "exposed"}] + + Output ONLY valid JSON. + ```json + { + "$defs": { + "CausalSummary": { + "properties": { + "trigger": { + "description": "Triggered by what topological sequence? (e.g., 'Bimanual pinch & moved from hem to collar')", + "title": "Trigger", + "type": "string" + }, + "effect": { + "description": "Visual effect (e.g., 'Jacket folded in half')", + "title": "Effect", + "type": "string" + } + }, + "required": [ + "trigger", + "effect" + ], + "title": "CausalSummary", + "type": "object" + }, + "SegmentAnnotation": { + "properties": { + "segment_id": { + "minimum": 0, + "title": "Segment Id", + "type": "integer" + }, + "primitive_type": { + "description": "Must be one of: ['Approach', 'Pre-grasp Align', 'Grasp', 'Lift', 'Horizontal Transport', 'Target Hover & Align', 'Lower & Pre-place', 'Compress/Squeeze', 'Shape/Adjust', 'Release', 'Retract', 'Place', 'Idle', 'Hold']", + "title": "Primitive Type", + "type": "string" + }, + "chunk_idx_range": { + "description": "[start_chunk_idx, end_chunk_idx] inclusive. E.g., [2, 5] means merging chunks 2, 3, 4, and 5.", + "items": { + "type": "integer" + }, + "maxItems": 2, + "minItems": 2, + "title": "Chunk Idx Range", + "type": "array" + }, + "subtask": { + "description": "Intent referencing the semantic atlas.", + "title": "Subtask", + "type": "string" + }, + "state_transition": { + "$ref": "#/$defs/StateTransition" + }, + "causal_summary": { + "$ref": "#/$defs/CausalSummary" + } + }, + "required": [ + "segment_id", + "primitive_type", + "chunk_idx_range", + "subtask", + "state_transition", + "causal_summary" + ], + "title": "SegmentAnnotation", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "StateTransition": { + "properties": { + "before_anchors": { + "description": "Status of relevant semantic anchors before segment", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Before Anchors", + "type": "array" + }, + "after_anchors": { + "description": "Status of relevant semantic anchors after segment", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "After Anchors", + "type": "array" + } + }, + "required": [ + "before_anchors", + "after_anchors" + ], + "title": "StateTransition", + "type": "object" + } + }, + "properties": { + "video_id": { + "title": "Video Id", + "type": "string" + }, + "merge_thought": { + "description": "Explain how semantic anchor stability and topology changes guided your chunk merging.", + "title": "Merge Thought", + "type": "string" + }, + "segments": { + "items": { + "$ref": "#/$defs/SegmentAnnotation" + }, + "title": "Segments", + "type": "array" + } + }, + "required": [ + "video_id", + "merge_thought", + "segments" + ], + "title": "SubtaskAnnotation", + "type": "object" +} + ``` + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "video_id": "video_0006", + "merge_thought": "The timeline is divided into three logical phases based on the interaction with the bag. \n\n1. **Approach Phase (Chunks 0-1)**: The robot approaches the bag with the right arm while the left arm is idle. This is a preparatory phase before any manipulation begins. The state of the bag remains 'upright_stable' and 'accessible'.\n\n2. **Unzipping Phase (Chunks 2-7)**: A clear semantic shift occurs at Chunk 2 where the left arm engages to stabilize the bag (holding the side handle/body) and the right arm grasps the zipper pull. This bimanual coordination continues through Chunk 7, where the zipper is actively pulled ('unzip'). The intent is unified: opening the bag. The state transitions from 'engaged' zipper to 'engaged_and_pulled' and the bag status changes to 'opening'.\n\n3. **Retract/Idle Phase (Chunks 8-9)**: After the unzipping is complete, the robot releases the specific manipulation grasp. In Chunk 8, the left arm touches the top surface briefly, likely as a final stabilization or transition, while the right arm idles. By Chunk 9, both arms are hovering statically, indicating the task is concluded or paused. This represents a shift from active manipulation to a resting state.", + "segments": [ + { + "segment_id": 0, + "primitive_type": "Approach", + "chunk_idx_range": [ + 0, + 1 + ], + "subtask": "Approach bag and establish initial contact readiness", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "table:surface_center", + "current_status": "exposed" + }, + { + "anchor_id": "bag:main_body", + "current_status": "upright_stable" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + }, + { + "anchor_id": "bag:side_handle_ring", + "current_status": "exposed" + } + ], + "after_anchors": [ + { + "anchor_id": "table:surface_center", + "current_status": "exposed" + }, + { + "anchor_id": "bag:main_body", + "current_status": "upright_stable" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + }, + { + "anchor_id": "bag:side_handle_ring", + "current_status": "exposed" + } + ] + }, + "causal_summary": { + "trigger": "Right arm moves from table surface zone to bag main body", + "effect": "Right arm establishes proximity/contact with bag; left arm remains idle" + } + }, + { + "segment_id": 1, + "primitive_type": "Grasp", + "chunk_idx_range": [ + 2, + 7 + ], + "subtask": "Stabilize bag with left arm and unzip with right arm", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "upright_stable" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + }, + { + "anchor_id": "bag:side_handle_ring", + "current_status": "exposed" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "opening" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "engaged_and_pulled" + }, + { + "anchor_id": "bag:side_handle_ring", + "current_status": "exposed" + } + ] + }, + "causal_summary": { + "trigger": "Left arm holds side handle/body for stability; Right arm grasps and pulls zipper", + "effect": "Bag zipper is opened; bag status changes to opening" + } + }, + { + "segment_id": 2, + "primitive_type": "Idle", + "chunk_idx_range": [ + 8, + 9 + ], + "subtask": "Release manipulation and return to idle hover state", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "opening" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "engaged_and_pulled" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "touched_and_stabilized" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "engaged_and_pulled" + } + ] + }, + "causal_summary": { + "trigger": "Completion of unzipping action; arms retract from specific manipulation points", + "effect": "Both arms enter static hover state; task interaction concludes" + } + } + ] +} +```` +--- diff --git a/debug/episode_0007/images/chunkannotator_0_img_0.jpg b/debug/episode_0007/images/chunkannotator_0_img_0.jpg new file mode 100644 index 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/dev/null +++ b/debug/episode_0007/images/sceneannotator_0_img_8.jpg @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:81357c26727d6be3e46ec6e3ef8bd61a3f9c0e881b353d3341ccfee23014f49c +size 16969 diff --git a/debug/episode_0007/trace_report.md b/debug/episode_0007/trace_report.md new file mode 100644 index 0000000000000000000000000000000000000000..1dc8faa1a07a57ba4263adc2d6e3e0b0f747355e --- /dev/null +++ b/debug/episode_0007/trace_report.md @@ -0,0 +1,5569 @@ +# 🤖 Episode_0007 标注追踪报告 + + +# 🌍 全局场景语义理解 +==================== + +## 🎬 SceneAnnotator_0 + +### 👁️ 视觉输入 +![sceneannotator_0_img_0.jpg](./images/sceneannotator_0_img_0.jpg) +![sceneannotator_0_img_1.jpg](./images/sceneannotator_0_img_1.jpg) +![sceneannotator_0_img_2.jpg](./images/sceneannotator_0_img_2.jpg) +![sceneannotator_0_img_3.jpg](./images/sceneannotator_0_img_3.jpg) +![sceneannotator_0_img_4.jpg](./images/sceneannotator_0_img_4.jpg) +![sceneannotator_0_img_5.jpg](./images/sceneannotator_0_img_5.jpg) +![sceneannotator_0_img_6.jpg](./images/sceneannotator_0_img_6.jpg) +![sceneannotator_0_img_7.jpg](./images/sceneannotator_0_img_7.jpg) +![sceneannotator_0_img_8.jpg](./images/sceneannotator_0_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are an Embodied AI Scene Architect. + Your task is to perform a "Global Inventory & Topological Mapping" of the workspace. + + [CONTEXT]: + - Environment: unknown + - Scene: unknown -> unknown + - Target Objects: table, bag + - Task Description: Unknown Task + + [STRICT INSTRUCTIONS]: + 1. **SEMANTIC ANCHOR REGISTRATION (Critical)**: + - 🌟 **Task-Driven Affordance (CRITICAL)**: Analyze the `Task Description` first. ONLY register semantic anchors that are functionally relevant to completing this specific task. Ask yourself: "Which precise parts of the objects will the robot need to grasp, place, align, or avoid?" + - **Functional Decomposition**: Do NOT mindlessly exhaust or grid the object. Identify interaction hotspots. For example: + - If task is "Pour water": register "bottle:cap", "bottle:body", "cup:rim". + - If task is "Fold jacket": register "jacket:left_sleeve", "jacket:collar", "jacket:bottom_hem". + - If task is simply "Move the box": registering "box:main_body" is sufficient; do not invent micro-corners. + - **Naming Convention**: Use `object_name:part_name` (e.g., "jacket:left_sleeve", "table:center_bin"). + - **Scope**: Include essential parts of the target objects AND key functional zones of the workspace (e.g., "workspace:placement_zone"). + - **Initial Status**: Describe the visual topology at the start. ⚠️ DO NOT label main functional parts as "hidden", "unreachable", or "buried" unless absolutely invisible, as this prevents downstream agents from interacting with them. Use neutral terms like "partially_obscured_but_accessible" instead. + + 2. **SPATIAL LAYOUT**: + Provide a one-sentence summary of where the main objects are relative to the robot. + + 3. **SCENE FACTORS**: + Identify environment conditions (lighting, material, clutter) that might affect robot perception or grasp stability. + + 4. **DISTRACTORS**: + List objects that are NOT part of the task but might cause visual noise. Do NOT register them as Semantic Anchors. + + [OUTPUT RULE]: + Return ONLY a JSON object matching the schema. Do not include any explanations. + + [SCHEMA]: + { + "$defs": { + "SceneFactors": { + "additionalProperties": false, + "properties": { + "environment": { + "enum": [ + "kitchen", + "lab", + "outdoor", + "unknown" + ], + "title": "Environment", + "type": "string" + }, + "lighting_type": { + "enum": [ + "bright_indoor", + "dim", + "natural", + "mixed" + ], + "title": "Lighting Type", + "type": "string" + }, + "surface_material": { + "enum": [ + "wood", + "metal", + "plastic", + "tile", + "unknown" + ], + "title": "Surface Material", + "type": "string" + }, + "clutter_level": { + "enum": [ + "low", + "medium", + "high" + ], + "title": "Clutter Level", + "type": "string" + } + }, + "required": [ + "environment", + "lighting_type", + "surface_material", + "clutter_level" + ], + "title": "SceneFactors", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + } + }, + "additionalProperties": false, + "properties": { + "scene_factors": { + "$ref": "#/$defs/SceneFactors" + }, + "spatial_layout": { + "description": "Objective spatial arrangement.", + "title": "Spatial Layout", + "type": "string" + }, + "initial_semantic_anchors": { + "description": "Initial registration of key topological zones for the target objects.", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Initial Semantic Anchors", + "type": "array" + }, + "background_distractors": { + "items": { + "type": "string" + }, + "title": "Background Distractors", + "type": "array" + } + }, + "required": [ + "scene_factors", + "spatial_layout", + "initial_semantic_anchors", + "background_distractors" + ], + "title": "SceneAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "scene_factors": { + "environment": "lab", + "lighting_type": "bright_indoor", + "surface_material": "plastic", + "clutter_level": "low" + }, + "spatial_layout": "A white table occupies the workspace with a beige bag positioned centrally, while black robotic grippers are visible in the immediate foreground.", + "initial_semantic_anchors": [ + { + "anchor_id": "table:surface_center", + "current_status": "clear_and_accessible" + }, + { + "anchor_id": "bag:main_body", + "current_status": "upright_and_stable" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "exposed_and_graspable" + }, + { + "anchor_id": "bag:side_handle_ring", + "current_status": "visible_and_accessible" + } + ], + "background_distractors": [ + "black_robotic_grippers", + "grey_floor_mat_edge" + ] +} +```` +--- + +# 🤖 动作切片(Chunk) 语义闭环标注 +==================== + +## 🎬 ChunkAnnotator_0 + +### 👁️ 视觉输入 +![chunkannotator_0_img_0.jpg](./images/chunkannotator_0_img_0.jpg) +![chunkannotator_0_img_1.jpg](./images/chunkannotator_0_img_1.jpg) +![chunkannotator_0_img_2.jpg](./images/chunkannotator_0_img_2.jpg) +![chunkannotator_0_img_3.jpg](./images/chunkannotator_0_img_3.jpg) +![chunkannotator_0_img_4.jpg](./images/chunkannotator_0_img_4.jpg) +![chunkannotator_0_img_5.jpg](./images/chunkannotator_0_img_5.jpg) +![chunkannotator_0_img_6.jpg](./images/chunkannotator_0_img_6.jpg) +![chunkannotator_0_img_7.jpg](./images/chunkannotator_0_img_7.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 4 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T0 (Curr Start)] + - Image 3: [T1 (Curr End)] + - Image 4: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_and_graspable"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "none", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.03, "angle": 0.23, "vel_score": 0.39, "angle_score": 3.53, "vel_fft": [0.027, 0.025, 0.021, 0.015, 0.009, 0.006, 0.007, 0.008, 0.008, 0.006, 0.004, 0.004, 0.004, 0.004, 0.003, 0.002, 0.003, 0.003, 0.003, 0.003], "angle_fft": [0.232, 0.208, 0.172, 0.139, 0.096, 0.081, 0.084, 0.089, 0.091, 0.075, 0.055, 0.05, 0.042, 0.035, 0.034, 0.025, 0.023, 0.024, 0.024, 0.026]}, "right": {"vel": 0.28, "angle": 3.85, "vel_score": 3.37, "angle_score": 8.2, "vel_fft": [0.278, 0.179, 0.024, 0.019, 0.006, 0.006, 0.011, 0.003, 0.007, 0.01, 0.004, 0.004, 0.005, 0.002, 0.005, 0.003, 0.006, 0.012, 0.011, 0.005], "angle_fft": [3.851, 3.192, 3.156, 3.159, 3.095, 3.143, 3.064, 3.097, 3.132, 3.111, 3.14, 3.099, 3.096, 3.094, 3.108, 3.103, 3.101, 3.044, 3.078, 3.09]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.02, "left_arm_ry": 1.14, "left_arm_rz": -3.09, "left_gripper": 0.23, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": -3.03, "right_arm_ry": 1.11, "right_arm_rz": -2.96, "right_gripper": 0.39}, "1": {"left_arm_vel": 0.483, "left_gripper_vel": 0.0, "left_arm_rx": -3.01, "left_arm_ry": 1.14, "left_arm_rz": -3.09, "left_gripper": 0.23, "right_arm_vel": 0.483, "right_gripper_vel": 0.0, "right_arm_rx": 2.76, "right_arm_ry": 1.14, "right_arm_rz": -3.01, "right_gripper": 0.39}, "2": {"left_arm_vel": 0.685, "left_gripper_vel": 0.0, "left_arm_rx": -3.0, "left_arm_ry": 1.14, "left_arm_rz": -3.08, "left_gripper": 0.23, "right_arm_vel": 0.685, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.87, "right_arm_rz": -2.72, "right_gripper": 0.39}, "3": {"left_arm_vel": 0.504, "left_gripper_vel": -0.021, "left_arm_rx": -3.01, "left_arm_ry": 1.12, "left_arm_rz": -3.09, "left_gripper": 0.23, "right_arm_vel": 0.504, "right_gripper_vel": -0.021, "right_arm_rx": 2.72, "right_arm_ry": 0.83, "right_arm_rz": -2.51, "right_gripper": 0.39}, "4": {"left_arm_vel": 0.525, "left_gripper_vel": 0.0, "left_arm_rx": -3.01, "left_arm_ry": 1.07, "left_arm_rz": -3.09, "left_gripper": 0.24, "right_arm_vel": 0.525, "right_gripper_vel": 0.0, "right_arm_rx": 2.73, "right_arm_ry": 0.83, "right_arm_rz": -2.41, "right_gripper": 0.39}, "5": {"left_arm_vel": 0.371, "left_gripper_vel": 0.0, "left_arm_rx": -3.01, "left_arm_ry": 1.03, "left_arm_rz": -3.09, "left_gripper": 0.24, "right_arm_vel": 0.371, "right_gripper_vel": 0.0, "right_arm_rx": 2.71, "right_arm_ry": 0.82, "right_arm_rz": -2.36, "right_gripper": 0.39}, "6": {"left_arm_vel": 0.291, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.99, "left_arm_rz": -2.96, "left_gripper": 0.24, "right_arm_vel": 0.291, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.8, "right_arm_rz": -2.32, "right_gripper": 0.39}, "7": {"left_arm_vel": 0.241, "left_gripper_vel": 0.0, "left_arm_rx": -2.74, "left_arm_ry": 0.98, "left_arm_rz": -2.92, "left_gripper": 0.24, "right_arm_vel": 0.241, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.8, "right_arm_rz": -2.32, "right_gripper": 0.39}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.049300000071525574, -0.013299999758601189, 0.012500000186264515], "delta_rot": [0.27559998631477356, -0.1565999984741211, 0.16760000586509705], "gripper_changed": false, "flow_direction": "+X(Forward)", "magnitude": 0.0526}, "right": {"delta_pos": [0.4607999920845032, 0.22460000216960907, -0.01489999983459711], "delta_rot": [5.703700065612793, -0.31130000948905945, 0.644599974155426], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left)", "magnitude": 0.5128}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.3041999936103821, -0.0560000017285347, -0.06019999831914902], "delta_rot": [0.6373000144958496, -0.3625999987125397, 0.056699998676776886], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.3151}, "right": {"delta_pos": [0.4456000030040741, 0.2786000072956085, -0.06080000102519989], "delta_rot": [5.730599880218506, -0.4092000126838684, 0.788100004196167], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and -Z(Down)", "magnitude": 0.529}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Right arm approaches and makes contact with the bag's top reflective panel to stabilize or reposition it, while left arm remains idle.", + "actions": [ + { + "reasoning_cot": "The right arm executes a significant forward (+X) and leftward (+Y) trajectory (delta_pos magnitude ~0.51) towards the bag. Visual evidence in frames T1-T2 confirms the gripper tips making contact with the silver reflective patch on the bag's top surface. The gripper remains open (stable signal), indicating a 'touch' or 'press' action rather than a grasp.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "touch", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "top_reflective_panel" + }, + "spatial_logic": "moving from free space to bag:top_reflective_panel", + "topology_change": false + }, + { + "reasoning_cot": "The left arm shows minimal kinematic activity (low velocity, small delta) and remains visually positioned away from the bag in the lower-left quadrant of the workspace. It does not participate in the current interaction.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "static_at_idle_position", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Initiating contact with the bag's top surface using the right end-effector." + } +} +```` +--- +## 🎬 ChunkAnnotator_1 + +### 👁️ 视觉输入 +![chunkannotator_1_img_0.jpg](./images/chunkannotator_1_img_0.jpg) +![chunkannotator_1_img_1.jpg](./images/chunkannotator_1_img_1.jpg) +![chunkannotator_1_img_2.jpg](./images/chunkannotator_1_img_2.jpg) +![chunkannotator_1_img_3.jpg](./images/chunkannotator_1_img_3.jpg) +![chunkannotator_1_img_4.jpg](./images/chunkannotator_1_img_4.jpg) +![chunkannotator_1_img_5.jpg](./images/chunkannotator_1_img_5.jpg) +![chunkannotator_1_img_6.jpg](./images/chunkannotator_1_img_6.jpg) +![chunkannotator_1_img_7.jpg](./images/chunkannotator_1_img_7.jpg) +![chunkannotator_1_img_8.jpg](./images/chunkannotator_1_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_and_graspable"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm approaches and makes contact with the bag's top reflective panel to stabilize or reposition it, while left arm remains idle.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.24, "angle": 0.53, "vel_score": 1.83, "angle_score": 3.81, "vel_fft": [0.243, 0.035, 0.031, 0.009, 0.018, 0.012, 0.003, 0.01, 0.011, 0.006, 0.009, 0.01, 0.004, 0.003, 0.012, 0.004, 0.002], "angle_fft": [0.527, 0.061, 0.023, 0.031, 0.058, 0.026, 0.039, 0.068, 0.08, 0.034, 0.069, 0.028, 0.037, 0.034, 0.044, 0.013, 0.027]}, "right": {"vel": 0.07, "angle": 0.21, "vel_score": 0.61, "angle_score": 1.56, "vel_fft": [0.071, 0.049, 0.025, 0.012, 0.009, 0.002, 0.005, 0.006, 0.005, 0.006, 0.007, 0.004, 0.004, 0.005, 0.002, 0.002, 0.002], "angle_fft": [0.211, 0.06, 0.035, 0.031, 0.032, 0.034, 0.035, 0.01, 0.017, 0.015, 0.007, 0.009, 0.014, 0.01, 0.005, 0.005, 0.003]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.68, "left_arm_ry": 0.98, "left_arm_rz": -2.89, "left_gripper": 0.25, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.8, "right_arm_rz": -2.32, "right_gripper": 0.39}, "1": {"left_arm_vel": 0.175, "left_gripper_vel": 0.0, "left_arm_rx": -2.62, "left_arm_ry": 0.95, "left_arm_rz": -2.89, "left_gripper": 0.25, "right_arm_vel": 0.175, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.78, "right_arm_rz": -2.3, "right_gripper": 0.39}, "2": {"left_arm_vel": 0.239, "left_gripper_vel": 0.0, "left_arm_rx": -2.6, "left_arm_ry": 0.94, "left_arm_rz": -2.9, "left_gripper": 0.25, "right_arm_vel": 0.239, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.76, "right_arm_rz": -2.29, "right_gripper": 0.39}, "3": {"left_arm_vel": 0.182, "left_gripper_vel": 0.0, "left_arm_rx": -2.6, "left_arm_ry": 0.92, "left_arm_rz": -2.91, "left_gripper": 0.27, "right_arm_vel": 0.182, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.75, "right_arm_rz": -2.28, "right_gripper": 0.39}, "4": {"left_arm_vel": 0.161, "left_gripper_vel": 0.0, "left_arm_rx": -2.59, "left_arm_ry": 0.91, "left_arm_rz": -2.92, "left_gripper": 0.28, "right_arm_vel": 0.161, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.74, "right_arm_rz": -2.27, "right_gripper": 0.39}, "5": {"left_arm_vel": 0.136, "left_gripper_vel": 0.0, "left_arm_rx": -2.59, "left_arm_ry": 0.9, "left_arm_rz": -2.93, "left_gripper": 0.29, "right_arm_vel": 0.136, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.74, "right_arm_rz": -2.26, "right_gripper": 0.39}, "6": {"left_arm_vel": 0.115, "left_gripper_vel": 0.0, "left_arm_rx": -2.61, "left_arm_ry": 0.85, "left_arm_rz": -2.95, "left_gripper": 0.3, "right_arm_vel": 0.115, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.74, "right_arm_rz": -2.24, "right_gripper": 0.39}, "7": {"left_arm_vel": 0.045, "left_gripper_vel": 0.0, "left_arm_rx": -2.6, "left_arm_ry": 0.84, "left_arm_rz": -2.97, "left_gripper": 0.31, "right_arm_vel": 0.045, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.73, "right_arm_rz": -2.22, "right_gripper": 0.39}, "8": {"left_arm_vel": 0.014, "left_gripper_vel": 0.0, "left_arm_rx": -2.54, "left_arm_ry": 0.81, "left_arm_rz": -2.99, "left_gripper": 0.31, "right_arm_vel": 0.014, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.73, "right_arm_rz": -2.2, "right_gripper": 0.39}, "9": {"left_arm_vel": 0.01, "left_gripper_vel": -0.063, "left_arm_rx": -2.5, "left_arm_ry": 0.82, "left_arm_rz": -3.0, "left_gripper": 0.31, "right_arm_vel": 0.01, "right_gripper_vel": -0.063, "right_arm_rx": 2.68, "right_arm_ry": 0.72, "right_arm_rz": -2.19, "right_gripper": 0.39}, "10": {"left_arm_vel": 0.012, "left_gripper_vel": -0.399, "left_arm_rx": -2.46, "left_arm_ry": 0.82, "left_arm_rz": -3.02, "left_gripper": 0.31, "right_arm_vel": 0.012, "right_gripper_vel": -0.399, "right_arm_rx": 2.69, "right_arm_ry": 0.71, "right_arm_rz": -2.18, "right_gripper": 0.36}, "11": {"left_arm_vel": 0.011, "left_gripper_vel": -0.399, "left_arm_rx": -2.45, "left_arm_ry": 0.81, "left_arm_rz": -3.03, "left_gripper": 0.31, "right_arm_vel": 0.011, "right_gripper_vel": -0.399, "right_arm_rx": 2.7, "right_arm_ry": 0.71, "right_arm_rz": -2.18, "right_gripper": 0.35}, "12": {"left_arm_vel": 0.01, "left_gripper_vel": -0.21, "left_arm_rx": -2.42, "left_arm_ry": 0.81, "left_arm_rz": -3.04, "left_gripper": 0.31, "right_arm_vel": 0.01, "right_gripper_vel": -0.21, "right_arm_rx": 2.7, "right_arm_ry": 0.71, "right_arm_rz": -2.17, "right_gripper": 0.33}, "13": {"left_arm_vel": 0.0, "left_gripper_vel": -0.042, "left_arm_rx": -2.38, "left_arm_ry": 0.78, "left_arm_rz": -3.04, "left_gripper": 0.31, "right_arm_vel": 0.0, "right_gripper_vel": -0.042, "right_arm_rx": 2.7, "right_arm_ry": 0.7, "right_arm_rz": -2.17, "right_gripper": 0.32}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.24609999358654022, -0.039400000125169754, -0.07500000298023224], "delta_rot": [0.29919999837875366, -0.19689999520778656, -0.14390000700950623], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.2602}, "right": {"delta_pos": [-0.01769999973475933, 0.051100000739097595, -0.04129999876022339], "delta_rot": [0.027699999511241913, -0.09539999812841415, 0.1421000063419342], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.068}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.28439998626708984, -0.08449999988079071, -0.1428000032901764], "delta_rot": [-0.2858000099658966, -0.10620000213384628, 5.39870023727417], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.3293}, "right": {"delta_pos": [-0.01769999973475933, 0.05649999901652336, -0.05620000138878822], "delta_rot": [-0.006800000090152025, -0.1354999989271164, 0.11559999734163284], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.0817}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Right arm approaches and stabilizes the bag's top reflective panel to prevent movement, while left arm remains idle in free space.", + "actions": [ + { + "reasoning_cot": "The right arm executes a forward and downward trajectory (+X, -Z) towards the bag. Visual evidence confirms the gripper makes contact with the silver reflective patch on the bag's top surface. The gripper signal is stable (open), indicating a 'touch' or 'stabilize' action rather than a grasp. This aligns with the kinematic data showing low velocity upon contact.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "touch", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "Approaching from free space to contact the top reflective panel of the bag.", + "topology_change": false + }, + { + "reasoning_cot": "The left arm shows minimal displacement and remains in the lower-left quadrant of the workspace. Visual frames confirm no contact with the bag or table surface. It is effectively idling while the right arm performs the interaction.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "Static position in free space, maintaining clearance from the active zone.", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Right arm has successfully established contact with the bag's main body for stabilization; left arm remains passive." + } +} +```` +--- +## 🎬 ChunkAnnotator_2 + +### 👁️ 视觉输入 +![chunkannotator_2_img_0.jpg](./images/chunkannotator_2_img_0.jpg) +![chunkannotator_2_img_1.jpg](./images/chunkannotator_2_img_1.jpg) +![chunkannotator_2_img_2.jpg](./images/chunkannotator_2_img_2.jpg) +![chunkannotator_2_img_3.jpg](./images/chunkannotator_2_img_3.jpg) +![chunkannotator_2_img_4.jpg](./images/chunkannotator_2_img_4.jpg) +![chunkannotator_2_img_5.jpg](./images/chunkannotator_2_img_5.jpg) +![chunkannotator_2_img_6.jpg](./images/chunkannotator_2_img_6.jpg) +![chunkannotator_2_img_7.jpg](./images/chunkannotator_2_img_7.jpg) +![chunkannotator_2_img_8.jpg](./images/chunkannotator_2_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_and_graspable"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm approaches and stabilizes the bag's top reflective panel to prevent movement, while left arm remains idle in free space.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.08, "angle": 4.3, "vel_score": 0.79, "angle_score": 6.52, "vel_fft": [0.078, 0.028, 0.019, 0.006, 0.009, 0.007, 0.005, 0.005, 0.003, 0.002, 0.002, 0.001, 0.002, 0.002, 0.002, 0.001, 0.004, 0.001, 0.001, 0.001], "angle_fft": [4.296, 3.848, 3.638, 3.621, 3.698, 3.689, 3.636, 3.67, 3.685, 3.645, 3.632, 3.648, 3.654, 3.653, 3.68, 3.665, 3.655, 3.664, 3.647, 3.655]}, "right": {"vel": 0.01, "angle": 0.05, "vel_score": 0.17, "angle_score": 0.51, "vel_fft": [0.011, 0.01, 0.009, 0.006, 0.005, 0.005, 0.004, 0.004, 0.003, 0.002, 0.001, 0.001, 0.001, 0.0, 0.0, 0.001, 0.001, 0.001, 0.001, 0.001], "angle_fft": [0.047, 0.026, 0.02, 0.016, 0.012, 0.009, 0.01, 0.005, 0.005, 0.004, 0.003, 0.001, 0.003, 0.001, 0.003, 0.003, 0.004, 0.003, 0.001, 0.002]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.38, "left_arm_ry": 0.78, "left_arm_rz": -3.04, "left_gripper": 0.31, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 0.7, "right_arm_rz": -2.17, "right_gripper": 0.32}, "1": {"left_arm_vel": 0.05, "left_gripper_vel": -1.197, "left_arm_rx": -2.38, "left_arm_ry": 0.8, "left_arm_rz": -3.04, "left_gripper": 0.31, "right_arm_vel": 0.05, "right_gripper_vel": -1.197, "right_arm_rx": 2.68, "right_arm_ry": 0.68, "right_arm_rz": -2.19, "right_gripper": 0.25}, "2": {"left_arm_vel": 0.021, "left_gripper_vel": -2.289, "left_arm_rx": -2.38, "left_arm_ry": 0.8, "left_arm_rz": -3.06, "left_gripper": 0.31, "right_arm_vel": 0.021, "right_gripper_vel": -2.289, "right_arm_rx": 2.68, "right_arm_ry": 0.67, "right_arm_rz": -2.18, "right_gripper": 0.1}, "3": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": -2.5, "left_arm_ry": 0.84, "left_arm_rz": 3.04, "left_gripper": 0.31, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.67, "right_arm_rz": -2.19, "right_gripper": 0.05}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.64, "left_arm_ry": 0.87, "left_arm_rz": 2.82, "left_gripper": 0.33, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.67, "right_arm_rz": -2.19, "right_gripper": 0.05}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.74, "left_arm_ry": 0.89, "left_arm_rz": 2.71, "left_gripper": 0.36, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.67, "right_arm_rz": -2.19, "right_gripper": 0.05}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.94, "left_arm_ry": 0.89, "left_arm_rz": 2.58, "left_gripper": 0.37, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.67, "right_arm_rz": -2.19, "right_gripper": 0.05}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 0.87, "left_arm_rz": 2.51, "left_gripper": 0.37, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.66, "right_arm_rz": -2.2, "right_gripper": 0.05}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.03700000047683716, -0.04490000009536743, -0.06620000302791595], "delta_rot": [-0.5857999920845032, 0.09160000085830688, 5.543499946594238], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.0882}, "right": {"delta_pos": [-0.0, 0.005499999970197678, -0.01489999983459711], "delta_rot": [-0.03539999946951866, -0.03970000147819519, -0.0272000003606081], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0159}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.060600001364946365, -0.044199999421834946, -0.009700000286102295], "delta_rot": [-0.37709999084472656, -0.052299998700618744, 5.693699836730957], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.0756}, "right": {"delta_pos": [-0.0019000000320374966, 0.009100000374019146, -0.015599999576807022], "delta_rot": [-0.1525000035762787, -0.13699999451637268, -0.2190999984741211], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0181}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Right arm approaches and stabilizes the bag's top reflective panel to prevent movement, while left arm remains idle in free space.", + "actions": [ + { + "reasoning_cot": "The right arm executes a forward (-Z) approach trajectory towards the bag. Visual evidence confirms the gripper makes contact with the silver reflective patch on the bag's top surface. The gripper signal is 'stable' (not closing to grasp), indicating an intent to touch/press for stabilization rather than manipulation.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "touch", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "Approaching from free space to make contact with the top reflective panel of the bag.", + "topology_change": false + }, + { + "reasoning_cot": "The left arm shows negligible kinematic displacement (vel ~0.08) and remains positioned away from the object in the peripheral view. It performs no active interaction during this chunk.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "Stationary in free space, maintaining position while right arm interacts.", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Right arm has successfully established contact with the bag's main body to stabilize it." + } +} +```` +--- +## 🎬 ChunkAnnotator_3 + +### 👁️ 视觉输入 +![chunkannotator_3_img_0.jpg](./images/chunkannotator_3_img_0.jpg) +![chunkannotator_3_img_1.jpg](./images/chunkannotator_3_img_1.jpg) +![chunkannotator_3_img_2.jpg](./images/chunkannotator_3_img_2.jpg) +![chunkannotator_3_img_3.jpg](./images/chunkannotator_3_img_3.jpg) +![chunkannotator_3_img_4.jpg](./images/chunkannotator_3_img_4.jpg) +![chunkannotator_3_img_5.jpg](./images/chunkannotator_3_img_5.jpg) +![chunkannotator_3_img_6.jpg](./images/chunkannotator_3_img_6.jpg) +![chunkannotator_3_img_7.jpg](./images/chunkannotator_3_img_7.jpg) +![chunkannotator_3_img_8.jpg](./images/chunkannotator_3_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_and_graspable"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm approaches and stabilizes the bag's top reflective panel to prevent movement, while left arm remains idle in free space.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.09, "angle": 0.45, "vel_score": 0.87, "angle_score": 4.28, "vel_fft": [0.086, 0.033, 0.023, 0.007, 0.004, 0.005, 0.005, 0.003, 0.001, 0.003, 0.003, 0.002, 0.002, 0.003, 0.002, 0.002, 0.001, 0.001, 0.002, 0.001], "angle_fft": [0.455, 0.079, 0.064, 0.063, 0.03, 0.067, 0.041, 0.015, 0.025, 0.053, 0.039, 0.028, 0.019, 0.01, 0.028, 0.04, 0.029, 0.014, 0.003, 0.016]}, "right": {"vel": 0.01, "angle": 0.16, "vel_score": 0.1, "angle_score": 1.61, "vel_fft": [0.01, 0.005, 0.002, 0.004, 0.002, 0.001, 0.002, 0.002, 0.001, 0.002, 0.001, 0.0, 0.001, 0.002, 0.001, 0.001, 0.0, 0.001, 0.001, 0.001], "angle_fft": [0.16, 0.075, 0.022, 0.006, 0.026, 0.004, 0.013, 0.025, 0.032, 0.013, 0.005, 0.006, 0.008, 0.004, 0.012, 0.013, 0.013, 0.005, 0.007, 0.01]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 0.87, "left_arm_rz": 2.5, "left_gripper": 0.37, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.66, "right_arm_rz": -2.2, "right_gripper": 0.05}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.02, "left_arm_ry": 0.87, "left_arm_rz": 2.43, "left_gripper": 0.22, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.66, "right_arm_rz": -2.2, "right_gripper": 0.05}, "2": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 0.86, "left_arm_rz": 2.39, "left_gripper": 0.02, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.66, "right_arm_rz": -2.2, "right_gripper": 0.05}, "3": {"left_arm_vel": 0.01, "left_gripper_vel": 0.0, "left_arm_rx": -3.01, "left_arm_ry": 0.77, "left_arm_rz": 2.41, "left_gripper": -0.01, "right_arm_vel": 0.01, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.65, "right_arm_rz": -2.22, "right_gripper": 0.05}, "4": {"left_arm_vel": 0.033, "left_gripper_vel": -0.105, "left_arm_rx": -3.01, "left_arm_ry": 0.81, "left_arm_rz": 2.46, "left_gripper": -0.01, "right_arm_vel": 0.033, "right_gripper_vel": -0.105, "right_arm_rx": 2.65, "right_arm_ry": 0.64, "right_arm_rz": -2.23, "right_gripper": 0.05}, "5": {"left_arm_vel": 0.018, "left_gripper_vel": 0.0, "left_arm_rx": -3.01, "left_arm_ry": 0.83, "left_arm_rz": 2.47, "left_gripper": -0.01, "right_arm_vel": 0.018, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.63, "right_arm_rz": -2.26, "right_gripper": 0.04}, "6": {"left_arm_vel": 0.015, "left_gripper_vel": 0.0, "left_arm_rx": -2.86, "left_arm_ry": 0.76, "left_arm_rz": 2.63, "left_gripper": -0.01, "right_arm_vel": 0.015, "right_gripper_vel": 0.0, "right_arm_rx": 2.58, "right_arm_ry": 0.6, "right_arm_rz": -2.33, "right_gripper": 0.04}, "7": {"left_arm_vel": 0.021, "left_gripper_vel": 0.0, "left_arm_rx": -2.76, "left_arm_ry": 0.73, "left_arm_rz": 2.66, "left_gripper": -0.01, "right_arm_vel": 0.021, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.57, "right_arm_rz": -2.39, "right_gripper": 0.04}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.09740000218153, 0.0010999999940395355, 0.05649999901652336], "delta_rot": [0.20970000326633453, -0.1436000019311905, 0.15279999375343323], "gripper_changed": true, "flow_direction": "-X(Backward) and +Z(Up)", "magnitude": 0.1127}, "right": {"delta_pos": [-0.0019000000320374966, 0.0035000001080334187, -0.000699999975040555], "delta_rot": [-0.11710000038146973, -0.09740000218153, -0.19200000166893005], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0041}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.06849999725818634, -0.03420000150799751, 0.11259999871253967], "delta_rot": [0.20810000598430634, -0.09830000251531601, 0.13439999520778656], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.1362}, "right": {"delta_pos": [0.008200000040233135, -0.15289999544620514, 0.057999998331069946], "delta_rot": [-0.10100000351667404, -0.12210000306367874, -0.6053000092506409], "gripper_changed": false, "flow_direction": "-Y(Right) and +Z(Up)", "magnitude": 0.1638}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm approaches and secures the bag's zipper pull to stabilize it, while right arm maintains a static hold on the bag's top reflective panel.", + "actions": [ + { + "reasoning_cot": "The left arm executes a significant approach trajectory (delta_pos X: -0.097) from free space towards the bag. Visual evidence in frames T1-T2 confirms the gripper aligns with and closes around the metal zipper pull ring. This is a clear transition from 'none' to 'grasp'.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "Moving from free space to bag:zipper_pull", + "topology_change": false + }, + { + "reasoning_cot": "The right arm exhibits negligible movement (magnitude 0.0041) and remains in contact with the bag's top surface throughout the sequence. The gripper state is stable. Its role is purely stabilizing the object while the left arm manipulates the zipper.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "hold", + "semantic_action": "stabilize", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "Static hold at bag:main_body", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_and_stabilized" + } + ], + "task_progress": "Left arm has successfully acquired the zipper pull; ready for unzipping or further manipulation." + } +} +```` +--- +## 🎬 ChunkAnnotator_4 + +### 👁️ 视觉输入 +![chunkannotator_4_img_0.jpg](./images/chunkannotator_4_img_0.jpg) +![chunkannotator_4_img_1.jpg](./images/chunkannotator_4_img_1.jpg) +![chunkannotator_4_img_2.jpg](./images/chunkannotator_4_img_2.jpg) +![chunkannotator_4_img_3.jpg](./images/chunkannotator_4_img_3.jpg) +![chunkannotator_4_img_4.jpg](./images/chunkannotator_4_img_4.jpg) +![chunkannotator_4_img_5.jpg](./images/chunkannotator_4_img_5.jpg) +![chunkannotator_4_img_6.jpg](./images/chunkannotator_4_img_6.jpg) +![chunkannotator_4_img_7.jpg](./images/chunkannotator_4_img_7.jpg) +![chunkannotator_4_img_8.jpg](./images/chunkannotator_4_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and secures the bag's zipper pull to stabilize it, while right arm maintains a static hold on the bag's top reflective panel.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.17, "angle": 0.61, "vel_score": 1.71, "angle_score": 5.92, "vel_fft": [0.172, 0.058, 0.039, 0.021, 0.013, 0.007, 0.01, 0.006, 0.005, 0.007, 0.008, 0.005, 0.006, 0.009, 0.006, 0.005, 0.003, 0.003, 0.003, 0.004], "angle_fft": [0.612, 0.191, 0.032, 0.066, 0.066, 0.064, 0.047, 0.012, 0.033, 0.031, 0.031, 0.037, 0.021, 0.021, 0.037, 0.02, 0.003, 0.01, 0.016, 0.03]}, "right": {"vel": 0.11, "angle": 0.27, "vel_score": 1.33, "angle_score": 3.01, "vel_fft": [0.111, 0.088, 0.045, 0.01, 0.016, 0.013, 0.004, 0.003, 0.006, 0.006, 0.007, 0.005, 0.006, 0.008, 0.009, 0.006, 0.001, 0.005, 0.006, 0.005], "angle_fft": [0.269, 0.181, 0.08, 0.049, 0.041, 0.013, 0.011, 0.012, 0.012, 0.003, 0.017, 0.012, 0.001, 0.015, 0.019, 0.008, 0.012, 0.015, 0.016, 0.007]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.73, "left_arm_ry": 0.71, "left_arm_rz": 2.65, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.56, "right_arm_rz": -2.4, "right_gripper": 0.04}, "1": {"left_arm_vel": 0.016, "left_gripper_vel": 0.0, "left_arm_rx": -2.81, "left_arm_ry": 0.71, "left_arm_rz": 2.36, "left_gripper": -0.0, "right_arm_vel": 0.016, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.55, "right_arm_rz": -2.43, "right_gripper": 0.04}, "2": {"left_arm_vel": 0.103, "left_gripper_vel": 0.987, "left_arm_rx": -2.68, "left_arm_ry": 0.68, "left_arm_rz": 2.4, "left_gripper": 0.09, "right_arm_vel": 0.103, "right_gripper_vel": 0.987, "right_arm_rx": 2.54, "right_arm_ry": 0.54, "right_arm_rz": -2.46, "right_gripper": 0.1}, "3": {"left_arm_vel": 0.279, "left_gripper_vel": 2.058, "left_arm_rx": -2.65, "left_arm_ry": 0.65, "left_arm_rz": 2.4, "left_gripper": 0.2, "right_arm_vel": 0.279, "right_gripper_vel": 2.058, "right_arm_rx": 2.53, "right_arm_ry": 0.53, "right_arm_rz": -2.51, "right_gripper": 0.22}, "4": {"left_arm_vel": 0.387, "left_gripper_vel": 1.47, "left_arm_rx": -2.65, "left_arm_ry": 0.65, "left_arm_rz": 2.41, "left_gripper": 0.3, "right_arm_vel": 0.387, "right_gripper_vel": 1.47, "right_arm_rx": 2.54, "right_arm_ry": 0.53, "right_arm_rz": -2.57, "right_gripper": 0.33}, "5": {"left_arm_vel": 0.425, "left_gripper_vel": 0.357, "left_arm_rx": -2.65, "left_arm_ry": 0.67, "left_arm_rz": 2.45, "left_gripper": 0.35, "right_arm_vel": 0.425, "right_gripper_vel": 0.357, "right_arm_rx": 2.55, "right_arm_ry": 0.54, "right_arm_rz": -2.63, "right_gripper": 0.37}, "6": {"left_arm_vel": 0.326, "left_gripper_vel": 0.0, "left_arm_rx": -2.66, "left_arm_ry": 0.75, "left_arm_rz": 2.64, "left_gripper": 0.37, "right_arm_vel": 0.326, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.56, "right_arm_rz": -2.73, "right_gripper": 0.37}, "7": {"left_arm_vel": 0.336, "left_gripper_vel": 0.0, "left_arm_rx": -2.76, "left_arm_ry": 0.77, "left_arm_rz": 2.64, "left_gripper": 0.37, "right_arm_vel": 0.336, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.54, "right_arm_rz": -2.81, "right_gripper": 0.37}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.03220000118017197, -0.0333000011742115, 0.0560000017285347], "delta_rot": [-0.030300000682473183, 0.05869999900460243, -0.006099999882280827], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.0726}, "right": {"delta_pos": [0.009600000455975533, -0.15569999814033508, 0.05869999900460243], "delta_rot": [0.018400000408291817, -0.022099999710917473, -0.40700000524520874], "gripper_changed": false, "flow_direction": "-Y(Right) and +Z(Up)", "magnitude": 0.1666}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.1673000007867813, -0.16009999811649323, 0.032499998807907104], "delta_rot": [-0.1469999998807907, -0.023600000888109207, -0.690500020980835], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.2339}, "right": {"delta_pos": [-0.13359999656677246, -0.19979999959468842, -0.017400000244379044], "delta_rot": [0.09529999643564224, 0.008299999870359898, -0.6532999873161316], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.241}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm approaches and secures the bag's zipper pull to stabilize it, while right arm maintains a static hold on the bag's top reflective panel.", + "actions": [ + { + "reasoning_cot": "The left arm moves from a hovering position (Image 1) towards the side of the bag. In Image 2, the gripper is positioned directly over the metal zipper pull. By Image 3/4, the gripper has closed around the zipper pull, securing it. This matches the 'grasp' action on the specific anchor 'bag:zipper_pull'.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving from free_space to bag:zipper_pull", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains in contact with the top silver reflective panel of the bag throughout the sequence (Images 2-5). The gripper state is stable/closed, and there is no significant displacement relative to the bag's surface. It acts as a stabilizer.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "static_at_bag:main_body", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_and_stabilized" + } + ], + "task_progress": "Stabilizing the bag by grasping the zipper pull with the left arm while holding the main body with the right arm." + } +} +```` +--- +## 🎬 ChunkAnnotator_5 + +### 👁️ 视觉输入 +![chunkannotator_5_img_0.jpg](./images/chunkannotator_5_img_0.jpg) +![chunkannotator_5_img_1.jpg](./images/chunkannotator_5_img_1.jpg) +![chunkannotator_5_img_2.jpg](./images/chunkannotator_5_img_2.jpg) +![chunkannotator_5_img_3.jpg](./images/chunkannotator_5_img_3.jpg) +![chunkannotator_5_img_4.jpg](./images/chunkannotator_5_img_4.jpg) +![chunkannotator_5_img_5.jpg](./images/chunkannotator_5_img_5.jpg) +![chunkannotator_5_img_6.jpg](./images/chunkannotator_5_img_6.jpg) +![chunkannotator_5_img_7.jpg](./images/chunkannotator_5_img_7.jpg) +![chunkannotator_5_img_8.jpg](./images/chunkannotator_5_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and secures the bag's zipper pull to stabilize it, while right arm maintains a static hold on the bag's top reflective panel.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.32, "angle": 1.13, "vel_score": 1.73, "angle_score": 6.16, "vel_fft": [0.325, 0.052, 0.034, 0.022, 0.012, 0.017, 0.017, 0.013, 0.018, 0.022], "angle_fft": [1.129, 0.288, 0.116, 0.038, 0.047, 0.022, 0.055, 0.03, 0.056, 0.041]}, "right": {"vel": 0.26, "angle": 0.53, "vel_score": 1.42, "angle_score": 2.83, "vel_fft": [0.261, 0.104, 0.038, 0.027, 0.012, 0.028, 0.009, 0.006, 0.016, 0.017], "angle_fft": [0.531, 0.133, 0.053, 0.019, 0.032, 0.012, 0.054, 0.048, 0.041, 0.023]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.76, "left_arm_ry": 0.77, "left_arm_rz": 2.61, "left_gripper": 0.37, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.58, "right_arm_ry": 0.55, "right_arm_rz": -2.83, "right_gripper": 0.37}, "1": {"left_arm_vel": 0.457, "left_gripper_vel": 0.021, "left_arm_rx": -2.77, "left_arm_ry": 0.78, "left_arm_rz": 2.56, "left_gripper": 0.37, "right_arm_vel": 0.457, "right_gripper_vel": 0.021, "right_arm_rx": 2.59, "right_arm_ry": 0.54, "right_arm_rz": -2.85, "right_gripper": 0.37}, "2": {"left_arm_vel": 0.492, "left_gripper_vel": 0.0, "left_arm_rx": -2.77, "left_arm_ry": 0.78, "left_arm_rz": 2.53, "left_gripper": 0.37, "right_arm_vel": 0.492, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.53, "right_arm_rz": -2.86, "right_gripper": 0.37}, "3": {"left_arm_vel": 0.386, "left_gripper_vel": -0.042, "left_arm_rx": -2.78, "left_arm_ry": 0.8, "left_arm_rz": 2.51, "left_gripper": 0.37, "right_arm_vel": 0.386, "right_gripper_vel": -0.042, "right_arm_rx": 2.62, "right_arm_ry": 0.55, "right_arm_rz": -2.87, "right_gripper": 0.36}, "4": {"left_arm_vel": 0.484, "left_gripper_vel": 0.0, "left_arm_rx": -2.78, "left_arm_ry": 0.81, "left_arm_rz": 2.47, "left_gripper": 0.38, "right_arm_vel": 0.484, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.55, "right_arm_rz": -2.88, "right_gripper": 0.36}, "5": {"left_arm_vel": 0.455, "left_gripper_vel": 0.0, "left_arm_rx": -2.77, "left_arm_ry": 0.8, "left_arm_rz": 2.44, "left_gripper": 0.38, "right_arm_vel": 0.455, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.55, "right_arm_rz": -2.9, "right_gripper": 0.36}, "6": {"left_arm_vel": 0.335, "left_gripper_vel": 0.0, "left_arm_rx": -2.76, "left_arm_ry": 0.79, "left_arm_rz": 2.4, "left_gripper": 0.38, "right_arm_vel": 0.335, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.57, "right_arm_rz": -2.91, "right_gripper": 0.36}, "7": {"left_arm_vel": 0.403, "left_gripper_vel": 0.0, "left_arm_rx": -2.77, "left_arm_ry": 0.8, "left_arm_rz": 2.35, "left_gripper": 0.38, "right_arm_vel": 0.403, "right_gripper_vel": 0.0, "right_arm_rx": 2.69, "right_arm_ry": 0.58, "right_arm_rz": -2.93, "right_gripper": 0.36}, "8": {"left_arm_vel": 0.352, "left_gripper_vel": 0.0, "left_arm_rx": -2.77, "left_arm_ry": 0.79, "left_arm_rz": 2.31, "left_gripper": 0.39, "right_arm_vel": 0.352, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 0.58, "right_arm_rz": -2.94, "right_gripper": 0.36}, "9": {"left_arm_vel": 0.287, "left_gripper_vel": 0.0, "left_arm_rx": -2.78, "left_arm_ry": 0.77, "left_arm_rz": 2.26, "left_gripper": 0.39, "right_arm_vel": 0.287, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 0.58, "right_arm_rz": -2.97, "right_gripper": 0.36}, "10": {"left_arm_vel": 0.18, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.75, "left_arm_rz": 2.21, "left_gripper": 0.39, "right_arm_vel": 0.18, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 0.59, "right_arm_rz": -2.99, "right_gripper": 0.36}, "11": {"left_arm_vel": 0.217, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.75, "left_arm_rz": 2.15, "left_gripper": 0.39, "right_arm_vel": 0.217, "right_gripper_vel": 0.0, "right_arm_rx": 2.69, "right_arm_ry": 0.58, "right_arm_rz": -3.0, "right_gripper": 0.36}, "12": {"left_arm_vel": 0.142, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.71, "left_arm_rz": 2.06, "left_gripper": 0.39, "right_arm_vel": 0.142, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.57, "right_arm_rz": -3.02, "right_gripper": 0.36}, "13": {"left_arm_vel": 0.019, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.69, "left_arm_rz": 1.95, "left_gripper": 0.39, "right_arm_vel": 0.019, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.57, "right_arm_rz": -3.05, "right_gripper": 0.36}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.12280000001192093, -0.12210000306367874, -0.02710000053048134], "delta_rot": [-0.11159999668598175, -0.08169999718666077, -0.6583999991416931], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.1753}, "right": {"delta_pos": [-0.13519999384880066, -0.038600001484155655, -0.07509999722242355], "delta_rot": [0.06629999727010727, 0.021400000900030136, -0.22679999470710754], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "magnitude": 0.1594}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.12319999933242798, -0.1396999955177307, -0.052799999713897705], "delta_rot": [-0.1307000070810318, -0.1420000046491623, -0.6922000050544739], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.1936}, "right": {"delta_pos": [-0.12210000306367874, 0.0031999999191612005, -0.1023000031709671], "delta_rot": [0.10660000145435333, 0.07289999723434448, -0.09600000083446503], "gripper_changed": false, "flow_direction": "-X(Backward) and -Z(Down)", "magnitude": 0.1593}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm approaches the bag's zipper pull to stabilize it, while right arm maintains a static hold on the bag's top reflective panel.", + "actions": [ + { + "reasoning_cot": "The left arm is moving forward and downward (+X, -Z) towards the bag. Visual evidence in frames T0-T1 shows the gripper aligning with the metal zipper pull ring. The motion is an approach to establish a grasp for stabilization.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving from free space to bag:zipper_pull", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains stationary relative to the bag's top surface. The visual input confirms the gripper is already in contact with the reflective panel, maintaining a hold to keep the bag upright while the left arm operates.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "static_at_bag:main_body", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Initiating two-handed manipulation: Right arm stabilizes bag body, Left arm targets zipper pull for next interaction." + } +} +```` +--- +## 🎬 ChunkAnnotator_6 + +### 👁️ 视觉输入 +![chunkannotator_6_img_0.jpg](./images/chunkannotator_6_img_0.jpg) +![chunkannotator_6_img_1.jpg](./images/chunkannotator_6_img_1.jpg) +![chunkannotator_6_img_2.jpg](./images/chunkannotator_6_img_2.jpg) +![chunkannotator_6_img_3.jpg](./images/chunkannotator_6_img_3.jpg) +![chunkannotator_6_img_4.jpg](./images/chunkannotator_6_img_4.jpg) +![chunkannotator_6_img_5.jpg](./images/chunkannotator_6_img_5.jpg) +![chunkannotator_6_img_6.jpg](./images/chunkannotator_6_img_6.jpg) +![chunkannotator_6_img_7.jpg](./images/chunkannotator_6_img_7.jpg) +![chunkannotator_6_img_8.jpg](./images/chunkannotator_6_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches the bag's zipper pull to stabilize it, while right arm maintains a static hold on the bag's top reflective panel.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.03, "angle": 0.15, "vel_score": 0.23, "angle_score": 1.33, "vel_fft": [0.025, 0.017, 0.006, 0.006, 0.006, 0.004, 0.004, 0.005, 0.002, 0.002, 0.004, 0.003, 0.001, 0.003, 0.003, 0.001, 0.002, 0.003, 0.003, 0.002], "angle_fft": [0.147, 0.061, 0.057, 0.053, 0.052, 0.028, 0.015, 0.01, 0.015, 0.004, 0.012, 0.008, 0.002, 0.009, 0.009, 0.005, 0.006, 0.009, 0.011, 0.009]}, "right": {"vel": 0.05, "angle": 0.35, "vel_score": 0.49, "angle_score": 3.03, "vel_fft": [0.055, 0.015, 0.025, 0.001, 0.006, 0.005, 0.002, 0.002, 0.004, 0.0, 0.002, 0.001, 0.001, 0.002, 0.002, 0.001, 0.002, 0.001, 0.002, 0.0], "angle_fft": [0.351, 0.112, 0.093, 0.05, 0.021, 0.011, 0.032, 0.003, 0.009, 0.01, 0.002, 0.004, 0.006, 0.011, 0.021, 0.001, 0.012, 0.009, 0.005, 0.009]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.69, "left_arm_rz": 1.94, "left_gripper": 0.39, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.57, "right_arm_rz": -3.06, "right_gripper": 0.36}, "1": {"left_arm_vel": 0.043, "left_gripper_vel": 0.0, "left_arm_rx": -2.92, "left_arm_ry": 0.64, "left_arm_rz": 1.87, "left_gripper": 0.39, "right_arm_vel": 0.043, "right_gripper_vel": 0.0, "right_arm_rx": 2.61, "right_arm_ry": 0.59, "right_arm_rz": -3.05, "right_gripper": 0.36}, "2": {"left_arm_vel": 0.153, "left_gripper_vel": -0.021, "left_arm_rx": -2.9, "left_arm_ry": 0.63, "left_arm_rz": 1.89, "left_gripper": 0.38, "right_arm_vel": 0.153, "right_gripper_vel": -0.021, "right_arm_rx": 2.59, "right_arm_ry": 0.59, "right_arm_rz": -2.99, "right_gripper": 0.36}, "3": {"left_arm_vel": 0.155, "left_gripper_vel": -0.042, "left_arm_rx": -2.9, "left_arm_ry": 0.63, "left_arm_rz": 1.89, "left_gripper": 0.3, "right_arm_vel": 0.155, "right_gripper_vel": -0.042, "right_arm_rx": 2.61, "right_arm_ry": 0.6, "right_arm_rz": -2.95, "right_gripper": 0.36}, "4": {"left_arm_vel": 0.08, "left_gripper_vel": 0.0, "left_arm_rx": -2.91, "left_arm_ry": 0.63, "left_arm_rz": 1.89, "left_gripper": 0.13, "right_arm_vel": 0.08, "right_gripper_vel": 0.0, "right_arm_rx": 2.65, "right_arm_ry": 0.61, "right_arm_rz": -2.92, "right_gripper": 0.36}, "5": {"left_arm_vel": 0.047, "left_gripper_vel": 0.0, "left_arm_rx": -2.91, "left_arm_ry": 0.63, "left_arm_rz": 1.89, "left_gripper": 0.06, "right_arm_vel": 0.047, "right_gripper_vel": 0.0, "right_arm_rx": 2.69, "right_arm_ry": 0.62, "right_arm_rz": -2.91, "right_gripper": 0.36}, "6": {"left_arm_vel": 0.081, "left_gripper_vel": 0.0, "left_arm_rx": -2.89, "left_arm_ry": 0.63, "left_arm_rz": 1.92, "left_gripper": 0.05, "right_arm_vel": 0.081, "right_gripper_vel": 0.0, "right_arm_rx": 2.76, "right_arm_ry": 0.66, "right_arm_rz": -2.91, "right_gripper": 0.36}, "7": {"left_arm_vel": 0.032, "left_gripper_vel": 0.0, "left_arm_rx": -2.9, "left_arm_ry": 0.63, "left_arm_rz": 1.92, "left_gripper": 0.05, "right_arm_vel": 0.032, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.62, "right_arm_rz": -2.92, "right_gripper": 0.36}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0015999999595806003, -0.01269999984651804, -0.02459999918937683], "delta_rot": [-0.01489999983459711, -0.06239999830722809, -0.016899999231100082], "gripper_changed": false, "flow_direction": "-Z(Down)", "magnitude": 0.0278}, "right": {"delta_pos": [0.013299999758601189, 0.04170000180602074, -0.027400000020861626], "delta_rot": [0.04450000077486038, 0.04989999905228615, 0.13459999859333038], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.0516}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.00839999970048666, -0.006099999882280827, -0.025299999862909317], "delta_rot": [0.09229999780654907, -0.11940000206232071, 0.23240000009536743], "gripper_changed": true, "flow_direction": "-Z(Down)", "magnitude": 0.0273}, "right": {"delta_pos": [-0.08079999685287476, 0.12520000338554382, 0.0024999999441206455], "delta_rot": [0.014399999752640724, 0.06120000034570694, 0.4023999869823456], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left)", "magnitude": 0.149}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm approaches and stabilizes the bag's top reflective panel to prepare for manipulation, while right arm maintains a static hold on the side handle ring.", + "actions": [ + { + "reasoning_cot": "The left arm moves from a hovering position towards the bag's top surface. Visual evidence in frames T0-T1 shows the gripper descending and making contact with the silver reflective patch. The kinematic data confirms a downward (-Z) trajectory followed by stabilization. This is an approach and touch action to secure the object.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": "stabilize_top_panel", + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "moving from free_space to bag:main_body (reflective_panel)", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains stationary relative to the bag's side handle ring throughout the sequence. Visuals confirm the gripper is already engaged with the metal ring. Kinematic data shows negligible delta, indicating a holding state to provide counter-tension for the left arm's actions.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:side_handle_ring" + }, + "spatial_logic": "static_at_side_handle_ring", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:main_body", + "current_status": "touched_and_stabilized" + } + ], + "task_progress": "Establishing dual-point contact: Right arm holds side handle, Left arm secures top panel." + } +} +```` +--- +## 🎬 ChunkAnnotator_7 + +### 👁️ 视觉输入 +![chunkannotator_7_img_0.jpg](./images/chunkannotator_7_img_0.jpg) +![chunkannotator_7_img_1.jpg](./images/chunkannotator_7_img_1.jpg) +![chunkannotator_7_img_2.jpg](./images/chunkannotator_7_img_2.jpg) +![chunkannotator_7_img_3.jpg](./images/chunkannotator_7_img_3.jpg) +![chunkannotator_7_img_4.jpg](./images/chunkannotator_7_img_4.jpg) +![chunkannotator_7_img_5.jpg](./images/chunkannotator_7_img_5.jpg) +![chunkannotator_7_img_6.jpg](./images/chunkannotator_7_img_6.jpg) +![chunkannotator_7_img_7.jpg](./images/chunkannotator_7_img_7.jpg) +![chunkannotator_7_img_8.jpg](./images/chunkannotator_7_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and stabilizes the bag's top reflective panel to prepare for manipulation, while right arm maintains a static hold on the side handle ring.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.01, "angle": 0.19, "vel_score": 0.07, "angle_score": 1.84, "vel_fft": [0.007, 0.003, 0.003, 0.003, 0.002, 0.001, 0.001, 0.001, 0.001, 0.0, 0.001, 0.001, 0.0, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001], "angle_fft": [0.194, 0.083, 0.015, 0.023, 0.016, 0.029, 0.014, 0.019, 0.016, 0.006, 0.013, 0.011, 0.009, 0.014, 0.003, 0.006, 0.008, 0.005, 0.003, 0.008]}, "right": {"vel": 0.13, "angle": 0.38, "vel_score": 1.21, "angle_score": 3.52, "vel_fft": [0.129, 0.032, 0.013, 0.026, 0.015, 0.005, 0.004, 0.003, 0.001, 0.002, 0.003, 0.003, 0.002, 0.006, 0.004, 0.002, 0.003, 0.002, 0.002, 0.002], "angle_fft": [0.38, 0.116, 0.066, 0.013, 0.032, 0.031, 0.022, 0.034, 0.033, 0.039, 0.015, 0.022, 0.023, 0.028, 0.011, 0.005, 0.003, 0.009, 0.011, 0.006]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.9, "left_arm_ry": 0.63, "left_arm_rz": 1.92, "left_gripper": 0.05, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.62, "right_arm_rz": -2.92, "right_gripper": 0.36}, "1": {"left_arm_vel": 0.102, "left_gripper_vel": -1.512, "left_arm_rx": -2.9, "left_arm_ry": 0.62, "left_arm_rz": 1.92, "left_gripper": 0.05, "right_arm_vel": 0.102, "right_gripper_vel": -1.512, "right_arm_rx": 2.71, "right_arm_ry": 0.63, "right_arm_rz": -2.91, "right_gripper": 0.28}, "2": {"left_arm_vel": 0.059, "left_gripper_vel": -2.835, "left_arm_rx": -2.9, "left_arm_ry": 0.63, "left_arm_rz": 1.92, "left_gripper": 0.05, "right_arm_vel": 0.059, "right_gripper_vel": -2.835, "right_arm_rx": 2.71, "right_arm_ry": 0.63, "right_arm_rz": -2.93, "right_gripper": 0.12}, "3": {"left_arm_vel": 0.017, "left_gripper_vel": -0.84, "left_arm_rx": -2.9, "left_arm_ry": 0.63, "left_arm_rz": 1.92, "left_gripper": 0.05, "right_arm_vel": 0.017, "right_gripper_vel": -0.84, "right_arm_rx": 2.7, "right_arm_ry": 0.63, "right_arm_rz": -2.93, "right_gripper": 0.03}, "4": {"left_arm_vel": 0.076, "left_gripper_vel": 0.0, "left_arm_rx": -2.89, "left_arm_ry": 0.62, "left_arm_rz": 1.94, "left_gripper": 0.05, "right_arm_vel": 0.076, "right_gripper_vel": 0.0, "right_arm_rx": 2.71, "right_arm_ry": 0.59, "right_arm_rz": -2.91, "right_gripper": 0.01}, "5": {"left_arm_vel": 0.12, "left_gripper_vel": 0.0, "left_arm_rx": -2.89, "left_arm_ry": 0.62, "left_arm_rz": 1.95, "left_gripper": 0.04, "right_arm_vel": 0.12, "right_gripper_vel": 0.0, "right_arm_rx": 2.71, "right_arm_ry": 0.58, "right_arm_rz": -2.9, "right_gripper": 0.01}, "6": {"left_arm_vel": 0.161, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.61, "left_arm_rz": 1.99, "left_gripper": 0.04, "right_arm_vel": 0.161, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 0.57, "right_arm_rz": -2.88, "right_gripper": 0.01}, "7": {"left_arm_vel": 0.21, "left_gripper_vel": 0.0, "left_arm_rx": -2.86, "left_arm_ry": 0.61, "left_arm_rz": 2.01, "left_gripper": 0.04, "right_arm_vel": 0.21, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 0.58, "right_arm_rz": -2.89, "right_gripper": 0.01}, "8": {"left_arm_vel": 0.198, "left_gripper_vel": 0.0, "left_arm_rx": -2.84, "left_arm_ry": 0.61, "left_arm_rz": 2.03, "left_gripper": 0.04, "right_arm_vel": 0.198, "right_gripper_vel": 0.0, "right_arm_rx": 2.69, "right_arm_ry": 0.6, "right_arm_rz": -2.89, "right_gripper": 0.01}, "9": {"left_arm_vel": 0.148, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.6, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.148, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.59, "right_arm_rz": -2.86, "right_gripper": 0.01}, "10": {"left_arm_vel": 0.143, "left_gripper_vel": 0.0, "left_arm_rx": -2.81, "left_arm_ry": 0.59, "left_arm_rz": 2.1, "left_gripper": 0.04, "right_arm_vel": 0.143, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.59, "right_arm_rz": -2.77, "right_gripper": 0.01}, "11": {"left_arm_vel": 0.2, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.58, "left_arm_rz": 2.13, "left_gripper": 0.04, "right_arm_vel": 0.2, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.58, "right_arm_rz": -2.68, "right_gripper": 0.01}, "12": {"left_arm_vel": 0.252, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.57, "left_arm_rz": 2.15, "left_gripper": 0.04, "right_arm_vel": 0.252, "right_gripper_vel": 0.0, "right_arm_rx": 2.61, "right_arm_ry": 0.58, "right_arm_rz": -2.62, "right_gripper": 0.01}, "13": {"left_arm_vel": 0.15, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.57, "left_arm_rz": 2.17, "left_gripper": 0.04, "right_arm_vel": 0.15, "right_gripper_vel": 0.0, "right_arm_rx": 2.65, "right_arm_ry": 0.64, "right_arm_rz": -2.65, "right_gripper": 0.01}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0066999997943639755, 0.0066999997943639755, -0.0008999999845400453], "delta_rot": [0.10769999772310257, -0.057500001043081284, 0.2493000030517578], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0095}, "right": {"delta_pos": [-0.09390000253915787, 0.08320000022649765, 0.03009999915957451], "delta_rot": [-0.026499999687075615, 0.013399999588727951, 0.2669999897480011], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.129}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.010200000368058681, 0.0071000000461936, -0.0006000000284984708], "delta_rot": [0.1111999973654747, -0.05339999869465828, 0.3068000078201294], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0125}, "right": {"delta_pos": [-0.07660000026226044, 0.147599995136261, 0.026000000536441803], "delta_rot": [-0.02669999934732914, 0.07479999959468842, 0.27709999680519104], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1683}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag's top reflective panel while right arm approaches and secures a grasp on the side handle ring to prepare for manipulation.", + "actions": [ + { + "reasoning_cot": "The left arm maintains a static position with gripper closed, visually confirmed touching the silver reflective top panel of the bag. This action provides stability (anchoring) while the other arm operates, preventing the bag from sliding during the upcoming pull.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_reflective_panel" + }, + "spatial_logic": "static_at_top_panel", + "topology_change": false + }, + { + "reasoning_cot": "The right arm executes a significant trajectory shift (-X, +Y, +Z) moving from a neutral position towards the bag's side. Visual evidence in frames T1/T2 shows the gripper jaws closing around the metal D-ring/handle attachment point. The kinematic data confirms a 'gripper_changed' event (closing), transitioning from approach to a secured hold.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:side_handle_ring" + }, + "spatial_logic": "moving_from_free_space_to_side_handle_ring", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:side_handle_ring", + "current_status": "grasped_and_stabilized" + } + ], + "task_progress": "Right arm has successfully acquired the side handle anchor; left arm is maintaining bag stability. Ready for coordinated pull or rotation." + } +} +```` +--- +## 🎬 ChunkAnnotator_8 + +### 👁️ 视觉输入 +![chunkannotator_8_img_0.jpg](./images/chunkannotator_8_img_0.jpg) +![chunkannotator_8_img_1.jpg](./images/chunkannotator_8_img_1.jpg) +![chunkannotator_8_img_2.jpg](./images/chunkannotator_8_img_2.jpg) +![chunkannotator_8_img_3.jpg](./images/chunkannotator_8_img_3.jpg) +![chunkannotator_8_img_4.jpg](./images/chunkannotator_8_img_4.jpg) +![chunkannotator_8_img_5.jpg](./images/chunkannotator_8_img_5.jpg) +![chunkannotator_8_img_6.jpg](./images/chunkannotator_8_img_6.jpg) +![chunkannotator_8_img_7.jpg](./images/chunkannotator_8_img_7.jpg) +![chunkannotator_8_img_8.jpg](./images/chunkannotator_8_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "grasped_and_stabilized"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag's top reflective panel while right arm approaches and secures a grasp on the side handle ring to prepare for manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_reflective_panel"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.01, "angle": 0.16, "vel_score": 0.03, "angle_score": 0.52, "vel_fft": [0.011, 0.002, 0.002, 0.002, 0.001, 0.001], "angle_fft": [0.16, 0.049, 0.024, 0.015, 0.01, 0.023]}, "right": {"vel": 0.2, "angle": 0.3, "vel_score": 0.65, "angle_score": 0.95, "vel_fft": [0.195, 0.047, 0.013, 0.02, 0.014, 0.02], "angle_fft": [0.298, 0.016, 0.051, 0.063, 0.051, 0.055]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.57, "left_arm_rz": 2.18, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.65, "right_arm_rz": -2.67, "right_gripper": 0.01}, "1": {"left_arm_vel": 0.157, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.57, "left_arm_rz": 2.19, "left_gripper": 0.04, "right_arm_vel": 0.157, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.67, "right_arm_rz": -2.69, "right_gripper": 0.01}, "2": {"left_arm_vel": 0.202, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.57, "left_arm_rz": 2.2, "left_gripper": 0.04, "right_arm_vel": 0.202, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.68, "right_arm_rz": -2.68, "right_gripper": 0.01}, "3": {"left_arm_vel": 0.204, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.57, "left_arm_rz": 2.21, "left_gripper": 0.04, "right_arm_vel": 0.204, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.68, "right_arm_rz": -2.68, "right_gripper": 0.01}, "4": {"left_arm_vel": 0.281, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.58, "left_arm_rz": 2.21, "left_gripper": 0.04, "right_arm_vel": 0.281, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.69, "right_arm_rz": -2.67, "right_gripper": 0.01}, "5": {"left_arm_vel": 0.29, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.57, "left_arm_rz": 2.22, "left_gripper": 0.04, "right_arm_vel": 0.29, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.7, "right_arm_rz": -2.66, "right_gripper": 0.01}, "6": {"left_arm_vel": 0.227, "left_gripper_vel": 0.0, "left_arm_rx": -2.78, "left_arm_ry": 0.57, "left_arm_rz": 2.23, "left_gripper": 0.04, "right_arm_vel": 0.227, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.7, "right_arm_rz": -2.65, "right_gripper": 0.01}, "7": {"left_arm_vel": 0.204, "left_gripper_vel": 0.0, "left_arm_rx": -2.78, "left_arm_ry": 0.57, "left_arm_rz": 2.23, "left_gripper": 0.04, "right_arm_vel": 0.204, "right_gripper_vel": 0.0, "right_arm_rx": 2.65, "right_arm_ry": 0.7, "right_arm_rz": -2.64, "right_gripper": 0.01}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0031999999191612005, 0.0005000000237487257, 0.0003000000142492354], "delta_rot": [0.003599999938160181, 0.003599999938160181, 0.05119999870657921], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0032}, "right": {"delta_pos": [0.018300000578165054, 0.060499999672174454, -0.0044999998062849045], "delta_rot": [-0.006200000178068876, 0.04800000041723251, 0.028999999165534973], "gripper_changed": false, "flow_direction": "+Y(Left)", "magnitude": 0.0633}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.02590000070631504, 0.0494999997317791, 0.09539999812841415], "delta_rot": [-0.006099999882280827, 0.002099999925121665, 0.30079999566078186], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1106}, "right": {"delta_pos": [-0.0, -0.09799999743700027, 0.04500000178813934], "delta_rot": [0.02810000069439411, -0.26989999413490295, -0.1995999962091446], "gripper_changed": true, "flow_direction": "-Y(Right) and +Z(Up)", "magnitude": 0.1078}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag's top reflective panel while right arm approaches and secures a grasp on the side handle ring to prepare for manipulation.", + "actions": [ + { + "reasoning_cot": "The left arm is visually confirmed pressing against the silver reflective interior panel of the bag. Kinematic data shows minimal velocity (0.01) and stable gripper state, indicating a static holding action to stabilize the object against the force applied by the right arm.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_reflective_panel" + }, + "spatial_logic": "static_at_top_reflective_panel", + "topology_change": false + }, + { + "reasoning_cot": "The right arm executes a precise approach trajectory (+Y direction) towards the metal D-ring on the bag's side. Visual sequence confirms the gripper jaws align with and close around the ring. The high angle score (0.95) and subsequent grip stability confirm successful acquisition of the handle anchor.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:side_handle_ring" + }, + "spatial_logic": "approaching_and_grasping_side_handle_ring", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:side_handle_ring", + "current_status": "grasped_and_stabilized" + } + ], + "task_progress": "Right arm has successfully secured the side handle ring while left arm maintains stabilization on the top panel; ready for lifting or repositioning." + } +} +```` +--- +## 🎬 ChunkAnnotator_9 + +### 👁️ 视觉输入 +![chunkannotator_9_img_0.jpg](./images/chunkannotator_9_img_0.jpg) +![chunkannotator_9_img_1.jpg](./images/chunkannotator_9_img_1.jpg) +![chunkannotator_9_img_2.jpg](./images/chunkannotator_9_img_2.jpg) +![chunkannotator_9_img_3.jpg](./images/chunkannotator_9_img_3.jpg) +![chunkannotator_9_img_4.jpg](./images/chunkannotator_9_img_4.jpg) +![chunkannotator_9_img_5.jpg](./images/chunkannotator_9_img_5.jpg) +![chunkannotator_9_img_6.jpg](./images/chunkannotator_9_img_6.jpg) +![chunkannotator_9_img_7.jpg](./images/chunkannotator_9_img_7.jpg) +![chunkannotator_9_img_8.jpg](./images/chunkannotator_9_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "grasped_and_stabilized"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag's top reflective panel while right arm approaches and secures a grasp on the side handle ring to prepare for manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_reflective_panel"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.16, "angle": 0.42, "vel_score": 1.02, "angle_score": 2.56, "vel_fft": [0.158, 0.093, 0.03, 0.016, 0.018, 0.011, 0.014, 0.015, 0.016, 0.011, 0.008, 0.009, 0.01], "angle_fft": [0.416, 0.147, 0.076, 0.039, 0.05, 0.031, 0.02, 0.026, 0.032, 0.009, 0.011, 0.011, 0.021]}, "right": {"vel": 0.22, "angle": 0.73, "vel_score": 1.43, "angle_score": 4.47, "vel_fft": [0.223, 0.083, 0.014, 0.004, 0.006, 0.002, 0.0, 0.009, 0.007, 0.008, 0.005, 0.005, 0.006], "angle_fft": [0.73, 0.117, 0.117, 0.052, 0.034, 0.004, 0.029, 0.006, 0.034, 0.04, 0.02, 0.022, 0.046]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.78, "left_arm_ry": 0.58, "left_arm_rz": 2.23, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.69, "right_arm_rz": -2.65, "right_gripper": 0.01}, "1": {"left_arm_vel": 0.112, "left_gripper_vel": 1.05, "left_arm_rx": -2.77, "left_arm_ry": 0.57, "left_arm_rz": 2.25, "left_gripper": 0.06, "right_arm_vel": 0.112, "right_gripper_vel": 1.05, "right_arm_rx": 2.61, "right_arm_ry": 0.61, "right_arm_rz": -2.67, "right_gripper": 0.08}, "2": {"left_arm_vel": 0.17, "left_gripper_vel": 1.932, "left_arm_rx": -2.77, "left_arm_ry": 0.58, "left_arm_rz": 2.26, "left_gripper": 0.09, "right_arm_vel": 0.17, "right_gripper_vel": 1.932, "right_arm_rx": 2.61, "right_arm_ry": 0.59, "right_arm_rz": -2.66, "right_gripper": 0.14}, "3": {"left_arm_vel": 0.197, "left_gripper_vel": 2.415, "left_arm_rx": -2.77, "left_arm_ry": 0.58, "left_arm_rz": 2.27, "left_gripper": 0.13, "right_arm_vel": 0.197, "right_gripper_vel": 2.415, "right_arm_rx": 2.63, "right_arm_ry": 0.56, "right_arm_rz": -2.65, "right_gripper": 0.22}, "4": {"left_arm_vel": 0.251, "left_gripper_vel": 2.037, "left_arm_rx": -2.76, "left_arm_ry": 0.58, "left_arm_rz": 2.29, "left_gripper": 0.19, "right_arm_vel": 0.251, "right_gripper_vel": 2.037, "right_arm_rx": 2.64, "right_arm_ry": 0.53, "right_arm_rz": -2.65, "right_gripper": 0.29}, "5": {"left_arm_vel": 0.318, "left_gripper_vel": 2.037, "left_arm_rx": -2.75, "left_arm_ry": 0.58, "left_arm_rz": 2.31, "left_gripper": 0.23, "right_arm_vel": 0.318, "right_gripper_vel": 2.037, "right_arm_rx": 2.67, "right_arm_ry": 0.51, "right_arm_rz": -2.63, "right_gripper": 0.36}, "6": {"left_arm_vel": 0.357, "left_gripper_vel": 1.323, "left_arm_rx": -2.74, "left_arm_ry": 0.57, "left_arm_rz": 2.33, "left_gripper": 0.26, "right_arm_vel": 0.357, "right_gripper_vel": 1.323, "right_arm_rx": 2.7, "right_arm_ry": 0.49, "right_arm_rz": -2.63, "right_gripper": 0.4}, "7": {"left_arm_vel": 0.339, "left_gripper_vel": 0.777, "left_arm_rx": -2.73, "left_arm_ry": 0.56, "left_arm_rz": 2.36, "left_gripper": 0.27, "right_arm_vel": 0.339, "right_gripper_vel": 0.777, "right_arm_rx": 2.72, "right_arm_ry": 0.47, "right_arm_rz": -2.63, "right_gripper": 0.43}, "8": {"left_arm_vel": 0.379, "left_gripper_vel": 0.399, "left_arm_rx": -2.72, "left_arm_ry": 0.55, "left_arm_rz": 2.39, "left_gripper": 0.27, "right_arm_vel": 0.379, "right_gripper_vel": 0.399, "right_arm_rx": 2.73, "right_arm_ry": 0.46, "right_arm_rz": -2.64, "right_gripper": 0.44}, "9": {"left_arm_vel": 0.394, "left_gripper_vel": 0.315, "left_arm_rx": -2.71, "left_arm_ry": 0.55, "left_arm_rz": 2.41, "left_gripper": 0.26, "right_arm_vel": 0.394, "right_gripper_vel": 0.315, "right_arm_rx": 2.74, "right_arm_ry": 0.45, "right_arm_rz": -2.66, "right_gripper": 0.45}, "10": {"left_arm_vel": 0.365, "left_gripper_vel": 0.084, "left_arm_rx": -2.72, "left_arm_ry": 0.55, "left_arm_rz": 2.43, "left_gripper": 0.24, "right_arm_vel": 0.365, "right_gripper_vel": 0.084, "right_arm_rx": 2.74, "right_arm_ry": 0.43, "right_arm_rz": -2.7, "right_gripper": 0.46}, "11": {"left_arm_vel": 0.328, "left_gripper_vel": 0.063, "left_arm_rx": -2.75, "left_arm_ry": 0.56, "left_arm_rz": 2.44, "left_gripper": 0.23, "right_arm_vel": 0.328, "right_gripper_vel": 0.063, "right_arm_rx": 2.72, "right_arm_ry": 0.41, "right_arm_rz": -2.75, "right_gripper": 0.46}, "12": {"left_arm_vel": 0.24, "left_gripper_vel": 0.0, "left_arm_rx": -2.78, "left_arm_ry": 0.56, "left_arm_rz": 2.45, "left_gripper": 0.23, "right_arm_vel": 0.24, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 0.38, "right_arm_rz": -2.83, "right_gripper": 0.46}, "13": {"left_arm_vel": 0.158, "left_gripper_vel": -0.084, "left_arm_rx": -2.79, "left_arm_ry": 0.57, "left_arm_rz": 2.48, "left_gripper": 0.22, "right_arm_vel": 0.158, "right_gripper_vel": -0.084, "right_arm_rx": 2.69, "right_arm_ry": 0.38, "right_arm_rz": -2.87, "right_gripper": 0.46}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.029100000858306885, 0.04910000041127205, 0.09510000050067902], "delta_rot": [-0.011300000362098217, -0.0017000000225380063, 0.24619999527931213], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1109}, "right": {"delta_pos": [-0.019500000402331352, -0.16200000047683716, 0.05000000074505806], "delta_rot": [0.04600000008940697, -0.3138999938964844, -0.22120000422000885], "gripper_changed": true, "flow_direction": "-Y(Right) and +Z(Up)", "magnitude": 0.1706}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.42170000076293945, 0.2782999873161316, 0.06840000301599503], "delta_rot": [-0.2732999920845032, 0.590399980545044, 0.47679999470710754], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.5099}, "right": {"delta_pos": [-0.25099998712539673, -0.27549999952316284, 0.09700000286102295], "delta_rot": [-5.773799896240234, 0.424699991941452, -0.08590000122785568], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.3851}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag's top reflective panel while right arm approaches and secures a grasp on the side handle ring to prepare for manipulation.", + "actions": [ + { + "reasoning_cot": "The left arm maintains a static position, pinching the top edge of the bag near the reflective panel. This provides necessary counter-tension and stability for the object while the other arm interacts with it. The gripper remains closed (stable) throughout the sequence.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_reflective_panel" + }, + "spatial_logic": "static_at_top_edge", + "topology_change": false + }, + { + "reasoning_cot": "The right arm executes a precise approach trajectory towards the metal side handle ring. Visual evidence shows the gripper jaws aligning with the ring structure. Following the approach, the gripper closes to secure the handle, transitioning from free space to a secured grasp state.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:side_handle_ring" + }, + "spatial_logic": "approach_and_grasp_side_handle", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:side_handle_ring", + "current_status": "grasped_and_stabilized" + } + ], + "task_progress": "Established dual-point contact: Left arm holding top panel, Right arm grasping side handle ring." + } +} +```` +--- +## 🎬 ChunkAnnotator_10 + +### 👁️ 视觉输入 +![chunkannotator_10_img_0.jpg](./images/chunkannotator_10_img_0.jpg) +![chunkannotator_10_img_1.jpg](./images/chunkannotator_10_img_1.jpg) +![chunkannotator_10_img_2.jpg](./images/chunkannotator_10_img_2.jpg) +![chunkannotator_10_img_3.jpg](./images/chunkannotator_10_img_3.jpg) +![chunkannotator_10_img_4.jpg](./images/chunkannotator_10_img_4.jpg) +![chunkannotator_10_img_5.jpg](./images/chunkannotator_10_img_5.jpg) +![chunkannotator_10_img_6.jpg](./images/chunkannotator_10_img_6.jpg) +![chunkannotator_10_img_7.jpg](./images/chunkannotator_10_img_7.jpg) +![chunkannotator_10_img_8.jpg](./images/chunkannotator_10_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "grasped_and_stabilized"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag's top reflective panel while right arm approaches and secures a grasp on the side handle ring to prepare for manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_reflective_panel"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.4, "angle": 0.69, "vel_score": 3.58, "angle_score": 5.77, "vel_fft": [0.395, 0.206, 0.041, 0.018, 0.021, 0.009, 0.01, 0.018, 0.012, 0.006, 0.022, 0.021, 0.003, 0.001, 0.007, 0.009, 0.008, 0.009, 0.012, 0.009], "angle_fft": [0.693, 0.204, 0.055, 0.057, 0.06, 0.039, 0.016, 0.056, 0.006, 0.025, 0.071, 0.089, 0.022, 0.024, 0.022, 0.027, 0.01, 0.009, 0.008, 0.028]}, "right": {"vel": 0.22, "angle": 5.68, "vel_score": 1.96, "angle_score": 7.62, "vel_fft": [0.224, 0.094, 0.022, 0.009, 0.011, 0.007, 0.006, 0.008, 0.004, 0.002, 0.006, 0.013, 0.007, 0.005, 0.005, 0.003, 0.003, 0.007, 0.003, 0.006], "angle_fft": [5.678, 4.846, 4.87, 4.699, 4.854, 4.831, 4.819, 4.747, 4.788, 4.771, 4.798, 4.831, 4.772, 4.783, 4.804, 4.783, 4.783, 4.799, 4.781, 4.797]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.81, "left_arm_ry": 0.58, "left_arm_rz": 2.48, "left_gripper": 0.21, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.69, "right_arm_ry": 0.38, "right_arm_rz": -2.88, "right_gripper": 0.46}, "1": {"left_arm_vel": 0.272, "left_gripper_vel": -0.105, "left_arm_rx": -2.89, "left_arm_ry": 0.61, "left_arm_rz": 2.52, "left_gripper": 0.19, "right_arm_vel": 0.272, "right_gripper_vel": -0.105, "right_arm_rx": 2.72, "right_arm_ry": 0.37, "right_arm_rz": -2.86, "right_gripper": 0.44}, "2": {"left_arm_vel": 0.419, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.77, "left_arm_rz": 2.64, "left_gripper": 0.19, "right_arm_vel": 0.419, "right_gripper_vel": 0.0, "right_arm_rx": 2.91, "right_arm_ry": 0.44, "right_arm_rz": -2.78, "right_gripper": 0.44}, "3": {"left_arm_vel": 0.323, "left_gripper_vel": 0.0, "left_arm_rx": -3.0, "left_arm_ry": 0.89, "left_arm_rz": 2.66, "left_gripper": 0.24, "right_arm_vel": 0.323, "right_gripper_vel": 0.0, "right_arm_rx": 2.94, "right_arm_ry": 0.55, "right_arm_rz": -2.77, "right_gripper": 0.44}, "4": {"left_arm_vel": 0.339, "left_gripper_vel": -0.021, "left_arm_rx": -3.04, "left_arm_ry": 0.95, "left_arm_rz": 2.62, "left_gripper": 0.38, "right_arm_vel": 0.339, "right_gripper_vel": -0.021, "right_arm_rx": 2.95, "right_arm_ry": 0.66, "right_arm_rz": -2.76, "right_gripper": 0.44}, "5": {"left_arm_vel": 0.226, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.07, "left_arm_rz": 2.67, "left_gripper": 0.45, "right_arm_vel": 0.226, "right_gripper_vel": 0.0, "right_arm_rx": 3.03, "right_arm_ry": 0.79, "right_arm_rz": -2.73, "right_gripper": 0.44}, "6": {"left_arm_vel": 0.052, "left_gripper_vel": -0.042, "left_arm_rx": -3.07, "left_arm_ry": 1.18, "left_arm_rz": 2.69, "left_gripper": 0.42, "right_arm_vel": 0.052, "right_gripper_vel": -0.042, "right_arm_rx": -3.08, "right_arm_ry": 1.07, "right_arm_rz": -2.62, "right_gripper": 0.44}, "7": {"left_arm_vel": 0.008, "left_gripper_vel": -0.042, "left_arm_rx": -3.06, "left_arm_ry": 1.17, "left_arm_rz": 2.71, "left_gripper": 0.38, "right_arm_vel": 0.008, "right_gripper_vel": -0.042, "right_arm_rx": -3.13, "right_arm_ry": 1.12, "right_arm_rz": -2.74, "right_gripper": 0.43}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.3817000091075897, 0.22450000047683716, -0.033900000154972076], "delta_rot": [-0.24469999969005585, 0.5856000185012817, 0.2273000031709671], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and -Z(Down)", "magnitude": 0.4441}, "right": {"delta_pos": [-0.2287999987602234, -0.11089999973773956, 0.04280000180006027], "delta_rot": [-5.822199821472168, 0.7383000254631042, 0.1412999927997589], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.2578}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.3799000084400177, 0.21950000524520874, -0.03660000115633011], "delta_rot": [-0.23739999532699585, 0.5698000192642212, 0.6607999801635742], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and -Z(Down)", "magnitude": 0.4403}, "right": {"delta_pos": [-0.226500004529953, -0.10849999636411667, 0.042100001126527786], "delta_rot": [0.4392000138759613, 0.7397000193595886, -0.20980000495910645], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.2547}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm approaches and stabilizes the bag's top reflective panel while right arm hovers nearby, preparing for manipulation.", + "actions": [ + { + "reasoning_cot": "The left arm moves from a neutral position to make direct contact with the silver reflective patch on the bag's lid. The gripper is open but the end-effector presses down to stabilize the object, indicated by the 'touching' status and lack of grasp closure.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "touch", + "semantic_action": "stabilize_top_panel", + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_reflective_panel" + }, + "spatial_logic": "Approaching and contacting the top surface of the bag to establish a stable reference point.", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains in a hovering state above the table surface near the bag's side handle. It does not make contact or change its gripper state, serving as a passive observer or waiting for the next step in the sequence.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "hover", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": null, + "spatial_logic": "Maintaining position in free space adjacent to the bag's side handle.", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:top_reflective_panel", + "current_status": "touched_and_stabilized" + } + ], + "task_progress": "Initial stabilization of the bag achieved via left arm contact with the top panel." + } +} +```` +--- +## 🎬 ChunkAnnotator_11 + +### 👁️ 视觉输入 +![chunkannotator_11_img_0.jpg](./images/chunkannotator_11_img_0.jpg) +![chunkannotator_11_img_1.jpg](./images/chunkannotator_11_img_1.jpg) +![chunkannotator_11_img_2.jpg](./images/chunkannotator_11_img_2.jpg) +![chunkannotator_11_img_3.jpg](./images/chunkannotator_11_img_3.jpg) +![chunkannotator_11_img_4.jpg](./images/chunkannotator_11_img_4.jpg) +![chunkannotator_11_img_5.jpg](./images/chunkannotator_11_img_5.jpg) +![chunkannotator_11_img_6.jpg](./images/chunkannotator_11_img_6.jpg) +![chunkannotator_11_img_7.jpg](./images/chunkannotator_11_img_7.jpg) +![chunkannotator_11_img_8.jpg](./images/chunkannotator_11_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:top_reflective_panel", "current_status": "touched_and_stabilized"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring', 'bag:top_reflective_panel'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and stabilizes the bag's top reflective panel while right arm hovers nearby, preparing for manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_reflective_panel"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.0, "angle": 9.75, "vel_score": 0.04, "angle_score": 121.36, "vel_fft": [0.005, 0.003, 0.002, 0.002, 0.001, 0.001, 0.001, 0.0, 0.0, 0.001, 0.001, 0.0, 0.001, 0.0, 0.001, 0.001, 0.0, 0.0, 0.0, 0.0], "angle_fft": [9.752, 9.039, 7.445, 5.442, 2.918, 0.023, 2.901, 5.526, 7.622, 8.965, 9.415, 8.943, 7.605, 5.539, 2.919, 0.008, 2.91, 5.531, 7.617, 8.966]}, "right": {"vel": 0.0, "angle": 4.97, "vel_score": 0.03, "angle_score": 2.78, "vel_fft": [0.003, 0.002, 0.001, 0.001, 0.0, 0.001, 0.001, 0.001, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0], "angle_fft": [4.965, 4.533, 4.76, 4.737, 4.674, 4.712, 4.714, 4.705, 4.707, 4.71, 4.703, 4.712, 4.699, 4.702, 4.716, 4.694, 4.716, 4.708, 4.709, 4.705]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.06, "left_arm_ry": 1.16, "left_arm_rz": 2.71, "left_gripper": 0.38, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": -3.14, "right_arm_ry": 1.12, "right_arm_rz": -2.74, "right_gripper": 0.43}, "1": {"left_arm_vel": 0.01, "left_gripper_vel": 0.0, "left_arm_rx": -3.06, "left_arm_ry": 1.16, "left_arm_rz": 2.71, "left_gripper": 0.37, "right_arm_vel": 0.01, "right_gripper_vel": 0.0, "right_arm_rx": 3.14, "right_arm_ry": 1.12, "right_arm_rz": -2.75, "right_gripper": 0.43}, "2": {"left_arm_vel": 0.002, "left_gripper_vel": -0.021, "left_arm_rx": -3.06, "left_arm_ry": 1.15, "left_arm_rz": 2.71, "left_gripper": 0.36, "right_arm_vel": 0.002, "right_gripper_vel": -0.021, "right_arm_rx": 3.14, "right_arm_ry": 1.12, "right_arm_rz": -2.75, "right_gripper": 0.43}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 2.71, "left_gripper": 0.36, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.14, "right_arm_ry": 1.12, "right_arm_rz": -2.75, "right_gripper": 0.43}, "4": {"left_arm_vel": 0.006, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 2.81, "left_gripper": 0.35, "right_arm_vel": 0.006, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -2.82, "right_gripper": 0.43}, "5": {"left_arm_vel": 0.011, "left_gripper_vel": -0.021, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.02, "left_gripper": 0.35, "right_arm_vel": 0.011, "right_gripper_vel": -0.021, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -2.99, "right_gripper": 0.43}, "6": {"left_arm_vel": 0.01, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.07, "left_gripper": 0.35, "right_arm_vel": 0.01, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.03, "right_gripper": 0.43}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.00139999995008111, -0.004800000227987766, -0.00139999995008111], "delta_rot": [0.008100000210106373, -0.00860000029206276, 0.4343999922275543], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0052}, "right": {"delta_pos": [0.0020000000949949026, 0.002400000113993883, -0.0005000000237487257], "delta_rot": [6.2657999992370605, 0.0008999999845400453, -0.3452000021934509], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0032}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.00139999995008111, -0.004800000227987766, -0.00139999995008111], "delta_rot": [0.008100000210106373, -0.00860000029206276, 0.4343999922275543], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0052}, "right": {"delta_pos": [0.0020000000949949026, 0.002400000113993883, -0.0005000000237487257], "delta_rot": [6.2657999992370605, 0.0013000000035390258, -0.3452000021934509], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0032}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Both arms maintain a static hovering position above the table surface, observing the bag without initiating contact or manipulation.", + "actions": [ + { + "reasoning_cot": "The left arm remains stationary in the foreground with grippers open. Visual evidence confirms no contact with the bag or table. Kinematic data shows near-zero velocity, indicating an idle state while waiting for the next instruction or stabilizing before approach.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "static_hover_left_of_bag", + "topology_change": false + }, + { + "reasoning_cot": "The right arm mirrors the left, maintaining a fixed position in the foreground with open grippers. There is no visual interaction with the bag's side handle or main body. The arm is effectively idling in free space.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": null, + "spatial_logic": "static_hover_right_of_bag", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Robot is in a pre-manipulation holding pattern; both end-effectors are positioned and ready but currently inactive." + } +} +```` +--- +## 🎬 ChunkAnnotator_12 + +### 👁️ 视觉输入 +![chunkannotator_12_img_0.jpg](./images/chunkannotator_12_img_0.jpg) +![chunkannotator_12_img_1.jpg](./images/chunkannotator_12_img_1.jpg) +![chunkannotator_12_img_2.jpg](./images/chunkannotator_12_img_2.jpg) +![chunkannotator_12_img_3.jpg](./images/chunkannotator_12_img_3.jpg) +![chunkannotator_12_img_4.jpg](./images/chunkannotator_12_img_4.jpg) +![chunkannotator_12_img_5.jpg](./images/chunkannotator_12_img_5.jpg) +![chunkannotator_12_img_6.jpg](./images/chunkannotator_12_img_6.jpg) +![chunkannotator_12_img_7.jpg](./images/chunkannotator_12_img_7.jpg) +![chunkannotator_12_img_8.jpg](./images/chunkannotator_12_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:top_reflective_panel", "current_status": "touched_and_stabilized"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring', 'bag:top_reflective_panel'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Both arms maintain a static hovering position above the table surface, observing the bag without initiating contact or manipulation.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.0, "angle": 0.0, "vel_score": 0.0, "angle_score": 0.0, "vel_fft": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "angle_fft": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]}, "right": {"vel": 0.0, "angle": 0.0, "vel_score": 0.0, "angle_score": 0.0, "vel_fft": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "angle_fft": [0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}, "1": {"left_arm_vel": 0.001, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.001, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": -0.021, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": -0.021, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.021, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.021, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}, "8": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}, "9": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}, "10": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}, "11": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}, "12": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}, "13": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0, 0.0, 0.0], "delta_rot": [0.0, 0.0, 0.0], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0}, "right": {"delta_pos": [0.0, -0.0, 0.0], "delta_rot": [0.0, 0.00039999998989515007, -0.0], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.0, 0.0, 0.0], "delta_rot": [0.0, 0.0, 0.0], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0}, "right": {"delta_pos": [0.0, -0.0, 0.0], "delta_rot": [0.0, 0.00039999998989515007, -0.0], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Both arms maintain a static hovering position above the table surface, observing the bag without initiating contact or manipulation.", + "actions": [ + { + "reasoning_cot": "The left arm remains stationary in a hovering state above the table. Visual evidence from T0 to T1 shows no displacement of the gripper relative to the bag or table surface. Kinematic data confirms zero velocity and stable gripper width. No interaction is occurring.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "hover", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "static_hover_above_table", + "topology_change": false + }, + { + "reasoning_cot": "The right arm mirrors the left, maintaining a fixed hovering position. There is no visual change in the gap between the gripper and the table/bag across the sequence. The arm is idle, waiting for a command or visual trigger.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "hover", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": null, + "spatial_logic": "static_hover_above_table", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Observation phase: Arms are positioned and holding steady above the workspace, awaiting initiation of manipulation." + } +} +```` +--- +## 🎬 ChunkAnnotator_13 + +### 👁️ 视觉输入 +![chunkannotator_13_img_0.jpg](./images/chunkannotator_13_img_0.jpg) +![chunkannotator_13_img_1.jpg](./images/chunkannotator_13_img_1.jpg) +![chunkannotator_13_img_2.jpg](./images/chunkannotator_13_img_2.jpg) +![chunkannotator_13_img_3.jpg](./images/chunkannotator_13_img_3.jpg) +![chunkannotator_13_img_4.jpg](./images/chunkannotator_13_img_4.jpg) +![chunkannotator_13_img_5.jpg](./images/chunkannotator_13_img_5.jpg) +![chunkannotator_13_img_6.jpg](./images/chunkannotator_13_img_6.jpg) +![chunkannotator_13_img_7.jpg](./images/chunkannotator_13_img_7.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 4 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:top_reflective_panel", "current_status": "touched_and_stabilized"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle_ring', 'bag:top_reflective_panel'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Both arms maintain a static hovering position above the table surface, observing the bag without initiating contact or manipulation.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0, 0.0, 0.0], "delta_rot": [0.0, 0.0, 0.0], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0}, "right": {"delta_pos": [0.0, 0.0, 0.0], "delta_rot": [0.0, 0.0, 0.0], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0}} + + [FUTURE HINDSIGHT HINT]: + "End of Trajectory" + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Both arms maintain a static hovering position above the table surface, observing the bag without initiating contact or manipulation.", + "actions": [ + { + "reasoning_cot": "Visual evidence from both wrist cameras shows the end-effectors remain in a fixed spatial configuration relative to the table and the bag. There is no change in gripper state (open) and no displacement in X/Y/Z coordinates. The robot is in an idle observation phase.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "static_hover_above_table", + "topology_change": false + }, + { + "reasoning_cot": "Visual evidence confirms the right arm is also stationary with open grippers. No interaction with the 'bag:main_body' or any other anchor is occurring. The state is identical to the previous chunk, indicating a continued pause or wait state.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": null, + "spatial_logic": "static_hover_above_table", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Maintaining pre-manipulation hover state; awaiting next instruction to engage with bag anchors." + } +} +```` +--- +## 🎬 SubtaskAnnotator_0 + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are an expert human observer curating Embodied AI datasets. + Your goal is to synthesize a timeline of low-level robotic micro-actions into a highly logical, human-readable hierarchy of "Macro Chapters" (Subtasks). + + ### 0. GLOBAL CONTEXT + - **Video ID**: video_0007 + - **Total Frames**: 485 + - **Global Task Goal**: "Unknown Task" + + ### 1. INPUT DATA + - **KPM (Micro-Actions Timeline)**: [{"chunk_idx": 0, "start_frame": 0, "end_frame": 59, "chunk_intent": "Right arm approaches and makes contact with the bag's top reflective panel to stabilize or reposition it, while left arm remains idle.", "micro_actions": [{"verb": "touch", "semantic_verb": null, "subject": "right_arm", "target": "top_reflective_panel", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving from free space to bag:top_reflective_panel"}, {"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_at_idle_position"}]}, {"chunk_idx": 1, "start_frame": 60, "end_frame": 92, "chunk_intent": "Right arm approaches and stabilizes the bag's top reflective panel to prevent movement, while left arm remains idle in free space.", "micro_actions": [{"verb": "touch", "semantic_verb": null, "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Approaching from free space to contact the top reflective panel of the bag."}, {"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "Static position in free space, maintaining clearance from the active zone."}]}, {"chunk_idx": 2, "start_frame": 93, "end_frame": 143, "chunk_intent": "Right arm approaches and stabilizes the bag's top reflective panel to prevent movement, while left arm remains idle in free space.", "micro_actions": [{"verb": "touch", "semantic_verb": null, "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Approaching from free space to make contact with the top reflective panel of the bag."}, {"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "Stationary in free space, maintaining position while right arm interacts."}]}, {"chunk_idx": 3, "start_frame": 144, "end_frame": 194, "chunk_intent": "Left arm approaches and secures the bag's zipper pull to stabilize it, while right arm maintains a static hold on the bag's top reflective panel.", "micro_actions": [{"verb": "grasp", "semantic_verb": null, "subject": "left_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "Moving from free space to bag:zipper_pull"}, {"verb": "hold", "semantic_verb": "stabilize", "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Static hold at bag:main_body"}]}, {"chunk_idx": 4, "start_frame": 195, "end_frame": 246, "chunk_intent": "Left arm approaches and secures the bag's zipper pull to stabilize it, while right arm maintains a static hold on the bag's top reflective panel.", "micro_actions": [{"verb": "grasp", "semantic_verb": null, "subject": "left_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "moving from free_space to bag:zipper_pull"}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "static_at_bag:main_body"}]}, {"chunk_idx": 5, "start_frame": 247, "end_frame": 265, "chunk_intent": "Left arm approaches the bag's zipper pull to stabilize it, while right arm maintains a static hold on the bag's top reflective panel.", "micro_actions": [{"verb": "approach", "semantic_verb": null, "subject": "left_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "moving from free space to bag:zipper_pull"}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_bag:main_body"}]}, {"chunk_idx": 6, "start_frame": 266, "end_frame": 305, "chunk_intent": "Left arm approaches and stabilizes the bag's top reflective panel to prepare for manipulation, while right arm maintains a static hold on the side handle ring.", "micro_actions": [{"verb": "approach", "semantic_verb": "stabilize_top_panel", "subject": "left_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving from free_space to bag:main_body (reflective_panel)"}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:side_handle_ring", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_side_handle_ring"}]}, {"chunk_idx": 7, "start_frame": 306, "end_frame": 352, "chunk_intent": "Left arm stabilizes the bag's top reflective panel while right arm approaches and secures a grasp on the side handle ring to prepare for manipulation.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_reflective_panel", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "static_at_top_panel"}, {"verb": "grasp", "semantic_verb": null, "subject": "right_arm", "target": "bag:side_handle_ring", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "moving_from_free_space_to_side_handle_ring"}]}, {"chunk_idx": 8, "start_frame": 353, "end_frame": 362, "chunk_intent": "Left arm stabilizes the bag's top reflective panel while right arm approaches and secures a grasp on the side handle ring to prepare for manipulation.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_reflective_panel", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "static_at_top_reflective_panel"}, {"verb": "grasp", "semantic_verb": null, "subject": "right_arm", "target": "bag:side_handle_ring", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "approaching_and_grasping_side_handle_ring"}]}, {"chunk_idx": 9, "start_frame": 363, "end_frame": 386, "chunk_intent": "Left arm stabilizes the bag's top reflective panel while right arm approaches and secures a grasp on the side handle ring to prepare for manipulation.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_reflective_panel", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_top_edge"}, {"verb": "grasp", "semantic_verb": null, "subject": "right_arm", "target": "bag:side_handle_ring", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "approach_and_grasp_side_handle"}]}, {"chunk_idx": 10, "start_frame": 387, "end_frame": 425, "chunk_intent": "Left arm approaches and stabilizes the bag's top reflective panel while right arm hovers nearby, preparing for manipulation.", "micro_actions": [{"verb": "touch", "semantic_verb": "stabilize_top_panel", "subject": "left_arm", "target": "bag:top_reflective_panel", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Approaching and contacting the top surface of the bag to establish a stable reference point."}, {"verb": "hover", "semantic_verb": null, "subject": "right_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "Maintaining position in free space adjacent to the bag's side handle."}]}, {"chunk_idx": 11, "start_frame": 426, "end_frame": 465, "chunk_intent": "Both arms maintain a static hovering position above the table surface, observing the bag without initiating contact or manipulation.", "micro_actions": [{"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_hover_left_of_bag"}, {"verb": "idle", "semantic_verb": null, "subject": "right_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_hover_right_of_bag"}]}, {"chunk_idx": 12, "start_frame": 466, "end_frame": 483, "chunk_intent": "Both arms maintain a static hovering position above the table surface, observing the bag without initiating contact or manipulation.", "micro_actions": [{"verb": "hover", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_hover_above_table"}, {"verb": "hover", "semantic_verb": null, "subject": "right_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_hover_above_table"}]}, {"chunk_idx": 13, "start_frame": 484, "end_frame": 484, "chunk_intent": "Both arms maintain a static hovering position above the table surface, observing the bag without initiating contact or manipulation.", "micro_actions": [{"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_hover_above_table"}, {"verb": "idle", "semantic_verb": null, "subject": "right_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_hover_above_table"}]}] + - **WSM (State Memory)**: [{"chunk_idx": 0, "global_frame_range": [0, 59], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_and_graspable"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}], "short_term_memory": {"last_chunk_intent": "Right arm approaches and makes contact with the bag's top reflective panel to stabilize or reposition it, while left arm remains idle.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 1, "global_frame_range": [60, 92], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_and_graspable"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}], "short_term_memory": {"last_chunk_intent": "Right arm approaches and stabilizes the bag's top reflective panel to prevent movement, while left arm remains idle in free space.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 2, "global_frame_range": [93, 143], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_and_graspable"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}], "short_term_memory": {"last_chunk_intent": "Right arm approaches and stabilizes the bag's top reflective panel to prevent movement, while left arm remains idle in free space.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 3, "global_frame_range": [144, 194], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and secures the bag's zipper pull to stabilize it, while right arm maintains a static hold on the bag's top reflective panel.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 4, "global_frame_range": [195, 246], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and secures the bag's zipper pull to stabilize it, while right arm maintains a static hold on the bag's top reflective panel.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 5, "global_frame_range": [247, 265], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches the bag's zipper pull to stabilize it, while right arm maintains a static hold on the bag's top reflective panel.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 6, "global_frame_range": [266, 305], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and stabilizes the bag's top reflective panel to prepare for manipulation, while right arm maintains a static hold on the side handle ring.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 7, "global_frame_range": [306, 352], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "grasped_and_stabilized"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag's top reflective panel while right arm approaches and secures a grasp on the side handle ring to prepare for manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_reflective_panel"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 8, "global_frame_range": [353, 362], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "grasped_and_stabilized"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag's top reflective panel while right arm approaches and secures a grasp on the side handle ring to prepare for manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_reflective_panel"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 9, "global_frame_range": [363, 386], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "grasped_and_stabilized"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag's top reflective panel while right arm approaches and secures a grasp on the side handle ring to prepare for manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_reflective_panel"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 10, "global_frame_range": [387, 425], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:top_reflective_panel", "current_status": "touched_and_stabilized"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and stabilizes the bag's top reflective panel while right arm hovers nearby, preparing for manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_reflective_panel"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle_ring"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 11, "global_frame_range": [426, 465], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:top_reflective_panel", "current_status": "touched_and_stabilized"}], "short_term_memory": {"last_chunk_intent": "Both arms maintain a static hovering position above the table surface, observing the bag without initiating contact or manipulation.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 12, "global_frame_range": [466, 483], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:top_reflective_panel", "current_status": "touched_and_stabilized"}], "short_term_memory": {"last_chunk_intent": "Both arms maintain a static hovering position above the table surface, observing the bag without initiating contact or manipulation.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 13, "global_frame_range": [484, 484], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "touched_and_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:side_handle_ring", "current_status": "grasped_and_stabilized"}, {"anchor_id": "bag:top_reflective_panel", "current_status": "touched_and_stabilized"}], "short_term_memory": {"last_chunk_intent": "Both arms maintain a static hovering position above the table surface, observing the bag without initiating contact or manipulation.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}] + + ### 2. SYNTHESIS RULES (COMMON SENSE & NATURAL BOUNDARIES) + You must divide the chronological timeline into distinct segments. Instead of following rigid verb rules, use your human common sense to identify when a new phase of the task begins. + + **A natural "Chapter Boundary" (Segment Break) occurs when:** + 1. **Target Object Shift (CRITICAL)**: The robot shifts its focus or interaction from one primary object to another (e.g., finishes pouring into 'cup_A' and moves to 'cup_B', or drops a 'sponge' to pick up a 'towel'). NEVER merge actions directed at different primary targets into the same segment. + 2. **Major State Transition**: As seen in the WSM, a significant physical event occurs (e.g., the gripper transitions from 'none' to 'holding', or an object's topology drastically changes). + 3. **Semantic Goal Shift**: The overarching intent changes (e.g., from the "Approach & Preparation" phase to the "Active Manipulation" phase, and finally to the "Retract & Idle" phase). + + **Grouping Principle:** + - Merge consecutive chunks that serve a single, unified purpose (e.g., multiple chunks of "hover" and "hold" that all serve the continuous intent of "pouring water into the paper cup" should be merged into one segment). + - Ensure chronological integrity: Segments must be contiguous using the `chunk_idx` (e.g., [0, 2], [3, 5]). No gaps, no overlapping chunks. + + ### 3. OUTPUT REQUIREMENT + - `merge_thought`: Explain your logic based on the natural boundaries. Example: "Chunks 2-5 represent the continuous pouring phase into the paper cup. I broke the segment at Chunk 6 because the target shifted to the teal cup." + - `chunk_idx_range`: Output the exact index range `[start, end]`. + - `state_transition.before_anchors`: For the VERY FIRST segment (segment 0), this MUST exactly match these initial anchors: [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_and_graspable"}, {"anchor_id": "bag:side_handle_ring", "current_status": "visible_and_accessible"}] + + Output ONLY valid JSON. + ```json + { + "$defs": { + "CausalSummary": { + "properties": { + "trigger": { + "description": "Triggered by what topological sequence? (e.g., 'Bimanual pinch & moved from hem to collar')", + "title": "Trigger", + "type": "string" + }, + "effect": { + "description": "Visual effect (e.g., 'Jacket folded in half')", + "title": "Effect", + "type": "string" + } + }, + "required": [ + "trigger", + "effect" + ], + "title": "CausalSummary", + "type": "object" + }, + "SegmentAnnotation": { + "properties": { + "segment_id": { + "minimum": 0, + "title": "Segment Id", + "type": "integer" + }, + "primitive_type": { + "description": "Must be one of: ['Approach', 'Pre-grasp Align', 'Grasp', 'Lift', 'Horizontal Transport', 'Target Hover & Align', 'Lower & Pre-place', 'Compress/Squeeze', 'Shape/Adjust', 'Release', 'Retract', 'Place', 'Idle', 'Hold']", + "title": "Primitive Type", + "type": "string" + }, + "chunk_idx_range": { + "description": "[start_chunk_idx, end_chunk_idx] inclusive. E.g., [2, 5] means merging chunks 2, 3, 4, and 5.", + "items": { + "type": "integer" + }, + "maxItems": 2, + "minItems": 2, + "title": "Chunk Idx Range", + "type": "array" + }, + "subtask": { + "description": "Intent referencing the semantic atlas.", + "title": "Subtask", + "type": "string" + }, + "state_transition": { + "$ref": "#/$defs/StateTransition" + }, + "causal_summary": { + "$ref": "#/$defs/CausalSummary" + } + }, + "required": [ + "segment_id", + "primitive_type", + "chunk_idx_range", + "subtask", + "state_transition", + "causal_summary" + ], + "title": "SegmentAnnotation", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "StateTransition": { + "properties": { + "before_anchors": { + "description": "Status of relevant semantic anchors before segment", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Before Anchors", + "type": "array" + }, + "after_anchors": { + "description": "Status of relevant semantic anchors after segment", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "After Anchors", + "type": "array" + } + }, + "required": [ + "before_anchors", + "after_anchors" + ], + "title": "StateTransition", + "type": "object" + } + }, + "properties": { + "video_id": { + "title": "Video Id", + "type": "string" + }, + "merge_thought": { + "description": "Explain how semantic anchor stability and topology changes guided your chunk merging.", + "title": "Merge Thought", + "type": "string" + }, + "segments": { + "items": { + "$ref": "#/$defs/SegmentAnnotation" + }, + "title": "Segments", + "type": "array" + } + }, + "required": [ + "video_id", + "merge_thought", + "segments" + ], + "title": "SubtaskAnnotation", + "type": "object" +} + ``` + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "video_id": "video_0007", + "merge_thought": "The timeline is divided into four logical segments based on the shifting focus of the robotic arms and the state of the bag. \n\n1. **Segment 0 (Chunks 0-2)**: The right arm establishes initial contact with the bag's top panel for stabilization while the left arm is idle. This represents the 'Approach & Initial Stabilization' phase.\n2. **Segment 1 (Chunks 3-5)**: A clear shift occurs as the left arm engages the zipper pull to grasp/stabilize it, while the right arm maintains its hold on the main body. This is a distinct 'Bimanual Stabilization' phase focused on the zipper area.\n3. **Segment 2 (Chunks 6-10)**: The interaction topology changes significantly. The right arm releases the main body to grasp the side handle ring, while the left arm shifts to stabilize the top reflective panel. This represents a 'Re-grasp & Handle Preparation' phase, preparing the bag for potential lifting or opening via the handle.\n4. **Segment 3 (Chunks 11-13)**: Both arms release all contacts and enter a static hovering/idle state above the table. This is the final 'Retract & Observe' phase.", + "segments": [ + { + "segment_id": 0, + "primitive_type": "Approach", + "chunk_idx_range": [ + 0, + 2 + ], + "subtask": "Right arm approaches and stabilizes the bag's top reflective panel", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "table:surface_center", + "current_status": "clear_and_accessible" + }, + { + "anchor_id": "bag:main_body", + "current_status": "upright_and_stable" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "exposed_and_graspable" + }, + { + "anchor_id": "bag:side_handle_ring", + "current_status": "visible_and_accessible" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "touched_and_stabilized" + }, + { + "anchor_id": "bag:top_reflective_panel", + "current_status": "touched_and_stabilized" + } + ] + }, + "causal_summary": { + "trigger": "Right arm moves from free space to contact bag:top_reflective_panel", + "effect": "Bag top panel stabilized by right arm" + } + }, + { + "segment_id": 1, + "primitive_type": "Grasp", + "chunk_idx_range": [ + 3, + 5 + ], + "subtask": "Left arm grasps zipper pull while right arm holds main body", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "touched_and_stabilized" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "exposed_and_graspable" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_and_stabilized" + }, + { + "anchor_id": "bag:main_body", + "current_status": "held_by_right_arm" + } + ] + }, + "causal_summary": { + "trigger": "Left arm approaches and secures grasp on bag:zipper_pull", + "effect": "Zipper pull secured; bimanual stabilization established" + } + }, + { + "segment_id": 2, + "primitive_type": "Pre-grasp Align", + "chunk_idx_range": [ + 6, + 10 + ], + "subtask": "Right arm grasps side handle ring while left arm stabilizes top panel", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_and_stabilized" + }, + { + "anchor_id": "bag:side_handle_ring", + "current_status": "visible_and_accessible" + }, + { + "anchor_id": "bag:top_reflective_panel", + "current_status": "touched_and_stabilized" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:side_handle_ring", + "current_status": "grasped_and_stabilized" + }, + { + "anchor_id": "bag:top_reflective_panel", + "current_status": "stabilized_by_left_arm" + } + ] + }, + "causal_summary": { + "trigger": "Right arm shifts from main body to grasp bag:side_handle_ring; Left arm shifts to top panel", + "effect": "Bag stabilized via top panel (left) and side handle (right)" + } + }, + { + "segment_id": 3, + "primitive_type": "Idle", + "chunk_idx_range": [ + 11, + 13 + ], + "subtask": "Both arms retract to hovering position above table", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:side_handle_ring", + "current_status": "grasped_and_stabilized" + }, + { + "anchor_id": "bag:top_reflective_panel", + "current_status": "stabilized_by_left_arm" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "static_on_table" + }, + { + "anchor_id": "table:surface_center", + "current_status": "clear_and_accessible" + } + ] + }, + "causal_summary": { + "trigger": "Both arms release contact and move to free space", + "effect": "Robot enters idle observation state; bag remains on table" + } + } + ] +} +```` +--- diff --git a/debug/episode_0008/images/chunkannotator_0_img_0.jpg b/debug/episode_0008/images/chunkannotator_0_img_0.jpg new file mode 100644 index 0000000000000000000000000000000000000000..a58be8a6f897cda6f309094d03f64e184d5fe008 --- /dev/null +++ b/debug/episode_0008/images/chunkannotator_0_img_0.jpg @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:eb62b121e6e50b3be71bf6a5bbfd85a47e53a920e5b7962b5e7cc3367f932265 +size 17347 diff --git 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index 0000000000000000000000000000000000000000..2ad1a2ea58bb4b982eed6321fb9088930ea603bd --- /dev/null +++ b/debug/episode_0008/trace_report.md @@ -0,0 +1,5604 @@ +# 🤖 Episode_0008 标注追踪报告 + + +# 🌍 全局场景语义理解 +==================== + +## 🎬 SceneAnnotator_0 + +### 👁️ 视觉输入 +![sceneannotator_0_img_0.jpg](./images/sceneannotator_0_img_0.jpg) +![sceneannotator_0_img_1.jpg](./images/sceneannotator_0_img_1.jpg) +![sceneannotator_0_img_2.jpg](./images/sceneannotator_0_img_2.jpg) +![sceneannotator_0_img_3.jpg](./images/sceneannotator_0_img_3.jpg) +![sceneannotator_0_img_4.jpg](./images/sceneannotator_0_img_4.jpg) +![sceneannotator_0_img_5.jpg](./images/sceneannotator_0_img_5.jpg) +![sceneannotator_0_img_6.jpg](./images/sceneannotator_0_img_6.jpg) +![sceneannotator_0_img_7.jpg](./images/sceneannotator_0_img_7.jpg) +![sceneannotator_0_img_8.jpg](./images/sceneannotator_0_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are an Embodied AI Scene Architect. + Your task is to perform a "Global Inventory & Topological Mapping" of the workspace. + + [CONTEXT]: + - Environment: unknown + - Scene: unknown -> unknown + - Target Objects: table, bag + - Task Description: Unknown Task + + [STRICT INSTRUCTIONS]: + 1. **SEMANTIC ANCHOR REGISTRATION (Critical)**: + - 🌟 **Task-Driven Affordance (CRITICAL)**: Analyze the `Task Description` first. ONLY register semantic anchors that are functionally relevant to completing this specific task. Ask yourself: "Which precise parts of the objects will the robot need to grasp, place, align, or avoid?" + - **Functional Decomposition**: Do NOT mindlessly exhaust or grid the object. Identify interaction hotspots. For example: + - If task is "Pour water": register "bottle:cap", "bottle:body", "cup:rim". + - If task is "Fold jacket": register "jacket:left_sleeve", "jacket:collar", "jacket:bottom_hem". + - If task is simply "Move the box": registering "box:main_body" is sufficient; do not invent micro-corners. + - **Naming Convention**: Use `object_name:part_name` (e.g., "jacket:left_sleeve", "table:center_bin"). + - **Scope**: Include essential parts of the target objects AND key functional zones of the workspace (e.g., "workspace:placement_zone"). + - **Initial Status**: Describe the visual topology at the start. ⚠️ DO NOT label main functional parts as "hidden", "unreachable", or "buried" unless absolutely invisible, as this prevents downstream agents from interacting with them. Use neutral terms like "partially_obscured_but_accessible" instead. + + 2. **SPATIAL LAYOUT**: + Provide a one-sentence summary of where the main objects are relative to the robot. + + 3. **SCENE FACTORS**: + Identify environment conditions (lighting, material, clutter) that might affect robot perception or grasp stability. + + 4. **DISTRACTORS**: + List objects that are NOT part of the task but might cause visual noise. Do NOT register them as Semantic Anchors. + + [OUTPUT RULE]: + Return ONLY a JSON object matching the schema. Do not include any explanations. + + [SCHEMA]: + { + "$defs": { + "SceneFactors": { + "additionalProperties": false, + "properties": { + "environment": { + "enum": [ + "kitchen", + "lab", + "outdoor", + "unknown" + ], + "title": "Environment", + "type": "string" + }, + "lighting_type": { + "enum": [ + "bright_indoor", + "dim", + "natural", + "mixed" + ], + "title": "Lighting Type", + "type": "string" + }, + "surface_material": { + "enum": [ + "wood", + "metal", + "plastic", + "tile", + "unknown" + ], + "title": "Surface Material", + "type": "string" + }, + "clutter_level": { + "enum": [ + "low", + "medium", + "high" + ], + "title": "Clutter Level", + "type": "string" + } + }, + "required": [ + "environment", + "lighting_type", + "surface_material", + "clutter_level" + ], + "title": "SceneFactors", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + } + }, + "additionalProperties": false, + "properties": { + "scene_factors": { + "$ref": "#/$defs/SceneFactors" + }, + "spatial_layout": { + "description": "Objective spatial arrangement.", + "title": "Spatial Layout", + "type": "string" + }, + "initial_semantic_anchors": { + "description": "Initial registration of key topological zones for the target objects.", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Initial Semantic Anchors", + "type": "array" + }, + "background_distractors": { + "items": { + "type": "string" + }, + "title": "Background Distractors", + "type": "array" + } + }, + "required": [ + "scene_factors", + "spatial_layout", + "initial_semantic_anchors", + "background_distractors" + ], + "title": "SceneAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "scene_factors": { + "environment": "lab", + "lighting_type": "bright_indoor", + "surface_material": "plastic", + "clutter_level": "low" + }, + "spatial_layout": "A white table occupies the central workspace with a beige insulated bag positioned in the middle-right area, while black robotic grippers are visible in the immediate foreground.", + "initial_semantic_anchors": [ + { + "anchor_id": "table:surface_center", + "current_status": "clear_and_accessible" + }, + { + "anchor_id": "bag:main_body", + "current_status": "upright_and_stable" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "exposed_for_grasping" + }, + { + "anchor_id": "bag:side_handle", + "current_status": "accessible" + } + ], + "background_distractors": [ + "robotic_gripper_fingers", + "cables_in_background" + ] +} +```` +--- + +# 🤖 动作切片(Chunk) 语义闭环标注 +==================== + +## 🎬 ChunkAnnotator_0 + +### 👁️ 视觉输入 +![chunkannotator_0_img_0.jpg](./images/chunkannotator_0_img_0.jpg) +![chunkannotator_0_img_1.jpg](./images/chunkannotator_0_img_1.jpg) +![chunkannotator_0_img_2.jpg](./images/chunkannotator_0_img_2.jpg) +![chunkannotator_0_img_3.jpg](./images/chunkannotator_0_img_3.jpg) +![chunkannotator_0_img_4.jpg](./images/chunkannotator_0_img_4.jpg) +![chunkannotator_0_img_5.jpg](./images/chunkannotator_0_img_5.jpg) +![chunkannotator_0_img_6.jpg](./images/chunkannotator_0_img_6.jpg) +![chunkannotator_0_img_7.jpg](./images/chunkannotator_0_img_7.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 4 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T0 (Curr Start)] + - Image 3: [T1 (Curr End)] + - Image 4: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_for_grasping"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "none", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.01, "angle": 4.45, "vel_score": 0.16, "angle_score": 2.9, "vel_fft": [0.014, 0.013, 0.013, 0.012, 0.012, 0.011, 0.009, 0.008, 0.007, 0.006, 0.005, 0.005, 0.004, 0.004, 0.004, 0.004, 0.004, 0.004, 0.004, 0.004], "angle_fft": [4.445, 4.429, 4.387, 4.327, 4.264, 4.213, 4.186, 4.187, 4.21, 4.247, 4.285, 4.311, 4.32, 4.312, 4.291, 4.266, 4.247, 4.241, 4.249, 4.268]}, "right": {"vel": 0.03, "angle": 4.47, "vel_score": 0.4, "angle_score": 2.95, "vel_fft": [0.033, 0.031, 0.028, 0.023, 0.017, 0.013, 0.01, 0.008, 0.007, 0.007, 0.006, 0.006, 0.006, 0.006, 0.006, 0.005, 0.005, 0.004, 0.004, 0.004], "angle_fft": [4.468, 4.449, 4.401, 4.341, 4.284, 4.242, 4.226, 4.233, 4.246, 4.257, 4.263, 4.261, 4.252, 4.246, 4.25, 4.26, 4.27, 4.278, 4.277, 4.262]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.12, "right_arm_rz": -3.09, "right_gripper": 0.43}, "1": {"left_arm_vel": 0.096, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 3.14, "left_gripper": 0.35, "right_arm_vel": 0.096, "right_gripper_vel": 0.0, "right_arm_rx": 3.02, "right_arm_ry": 1.12, "right_arm_rz": 3.13, "right_gripper": 0.43}, "2": {"left_arm_vel": 0.157, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.15, "left_arm_rz": -3.14, "left_gripper": 0.35, "right_arm_vel": 0.157, "right_gripper_vel": 0.0, "right_arm_rx": 2.99, "right_arm_ry": 1.12, "right_arm_rz": 3.13, "right_gripper": 0.43}, "3": {"left_arm_vel": 0.23, "left_gripper_vel": 0.0, "left_arm_rx": -2.98, "left_arm_ry": 1.14, "left_arm_rz": -3.1, "left_gripper": 0.31, "right_arm_vel": 0.23, "right_gripper_vel": 0.0, "right_arm_rx": 2.91, "right_arm_ry": 1.12, "right_arm_rz": 3.12, "right_gripper": 0.43}, "4": {"left_arm_vel": 0.296, "left_gripper_vel": 0.0, "left_arm_rx": -2.92, "left_arm_ry": 1.15, "left_arm_rz": -3.05, "left_gripper": 0.29, "right_arm_vel": 0.296, "right_gripper_vel": 0.0, "right_arm_rx": 2.89, "right_arm_ry": 1.13, "right_arm_rz": 3.13, "right_gripper": 0.43}, "5": {"left_arm_vel": 0.34, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 1.14, "left_arm_rz": -3.0, "left_gripper": 0.26, "right_arm_vel": 0.34, "right_gripper_vel": 0.0, "right_arm_rx": 2.85, "right_arm_ry": 1.14, "right_arm_rz": 3.13, "right_gripper": 0.43}, "6": {"left_arm_vel": 0.34, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 1.14, "left_arm_rz": -3.0, "left_gripper": 0.26, "right_arm_vel": 0.34, "right_gripper_vel": 0.0, "right_arm_rx": 2.85, "right_arm_ry": 1.14, "right_arm_rz": 3.13, "right_gripper": 0.43}, "7": {"left_arm_vel": 0.34, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 1.14, "left_arm_rz": -3.0, "left_gripper": 0.26, "right_arm_vel": 0.34, "right_gripper_vel": 0.0, "right_arm_rx": 2.85, "right_arm_ry": 1.14, "right_arm_rz": 3.13, "right_gripper": 0.43}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.014600000344216824, -0.006399999838322401, 0.01140000019222498], "delta_rot": [0.19580000638961792, -0.005499999970197678, -6.138800144195557], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0196}, "right": {"delta_pos": [0.03449999913573265, 0.02019999921321869, 0.023000000044703484], "delta_rot": [-0.2809000015258789, 0.020999999716877937, 6.223700046539307], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and +Z(Up)", "magnitude": 0.0461}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.28369998931884766, -0.06300000101327896, -0.1193000003695488], "delta_rot": [0.5996999740600586, -0.39259999990463257, -6.270999908447266], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.3141}, "right": {"delta_pos": [0.4636000096797943, 0.24899999797344208, -0.043699998408555984], "delta_rot": [-0.3434999883174896, -0.3452000021934509, 0.9376999735832214], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and -Z(Down)", "magnitude": 0.5281}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Hovering and stabilizing position above the table surface near the bag, preparing for interaction.", + "actions": [ + { + "reasoning_cot": "The left arm shows minimal kinematic displacement (delta_pos magnitude ~0.02) and maintains a constant gripper width (0.35 -> 0.26 closing slightly but not grasping). Visually, the gripper remains in free space above the table, to the left of the bag. It is effectively holding its position or making micro-adjustments while hovering.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "hover", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "static_hover_left_of_bag", + "topology_change": false + }, + { + "reasoning_cot": "The right arm exhibits a small forward and upward drift (delta_pos magnitude ~0.046) with no gripper state change (width constant at 0.43). Visually, the gripper is open and moving through free space on the right side of the workspace. No contact with the bag or table is observed. This is a positioning/hovering maneuver.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "hover", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": null, + "spatial_logic": "drifting_forward_right_zone", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Arms are positioned in free space near the target object (bag), establishing a stable hover state before initiating contact." + } +} +```` +--- +## 🎬 ChunkAnnotator_1 + +### 👁️ 视觉输入 +![chunkannotator_1_img_0.jpg](./images/chunkannotator_1_img_0.jpg) +![chunkannotator_1_img_1.jpg](./images/chunkannotator_1_img_1.jpg) +![chunkannotator_1_img_2.jpg](./images/chunkannotator_1_img_2.jpg) +![chunkannotator_1_img_3.jpg](./images/chunkannotator_1_img_3.jpg) +![chunkannotator_1_img_4.jpg](./images/chunkannotator_1_img_4.jpg) +![chunkannotator_1_img_5.jpg](./images/chunkannotator_1_img_5.jpg) +![chunkannotator_1_img_6.jpg](./images/chunkannotator_1_img_6.jpg) +![chunkannotator_1_img_7.jpg](./images/chunkannotator_1_img_7.jpg) +![chunkannotator_1_img_8.jpg](./images/chunkannotator_1_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_for_grasping"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Hovering and stabilizing position above the table surface near the bag, preparing for interaction.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.27, "angle": 0.86, "vel_score": 2.14, "angle_score": 6.55, "vel_fft": [0.271, 0.08, 0.042, 0.014, 0.016, 0.017, 0.007, 0.01, 0.014, 0.01, 0.009, 0.011, 0.01, 0.002, 0.005, 0.01, 0.009, 0.004, 0.005], "angle_fft": [0.859, 0.258, 0.021, 0.102, 0.176, 0.11, 0.063, 0.094, 0.124, 0.065, 0.045, 0.086, 0.049, 0.016, 0.099, 0.074, 0.054, 0.035, 0.029]}, "right": {"vel": 0.45, "angle": 1.1, "vel_score": 3.54, "angle_score": 8.87, "vel_fft": [0.445, 0.112, 0.027, 0.021, 0.012, 0.011, 0.016, 0.013, 0.006, 0.01, 0.018, 0.01, 0.012, 0.002, 0.008, 0.018, 0.004, 0.01, 0.004], "angle_fft": [1.101, 0.414, 0.138, 0.157, 0.063, 0.055, 0.024, 0.024, 0.006, 0.057, 0.064, 0.058, 0.065, 0.058, 0.013, 0.02, 0.056, 0.003, 0.034]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.78, "left_arm_ry": 1.13, "left_arm_rz": -2.95, "left_gripper": 0.25, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.82, "right_arm_ry": 1.16, "right_arm_rz": -3.14, "right_gripper": 0.43}, "1": {"left_arm_vel": 0.435, "left_gripper_vel": 0.0, "left_arm_rx": -2.63, "left_arm_ry": 1.07, "left_arm_rz": -2.82, "left_gripper": 0.24, "right_arm_vel": 0.435, "right_gripper_vel": 0.0, "right_arm_rx": 2.75, "right_arm_ry": 1.17, "right_arm_rz": -3.12, "right_gripper": 0.43}, "2": {"left_arm_vel": 0.514, "left_gripper_vel": 0.0, "left_arm_rx": -2.56, "left_arm_ry": 1.01, "left_arm_rz": -2.79, "left_gripper": 0.26, "right_arm_vel": 0.514, "right_gripper_vel": 0.0, "right_arm_rx": 2.75, "right_arm_ry": 1.09, "right_arm_rz": -3.04, "right_gripper": 0.43}, "3": {"left_arm_vel": 0.459, "left_gripper_vel": 0.0, "left_arm_rx": -2.56, "left_arm_ry": 0.99, "left_arm_rz": -2.81, "left_gripper": 0.27, "right_arm_vel": 0.459, "right_gripper_vel": 0.0, "right_arm_rx": 2.74, "right_arm_ry": 1.07, "right_arm_rz": -3.02, "right_gripper": 0.43}, "4": {"left_arm_vel": 0.546, "left_gripper_vel": 0.0, "left_arm_rx": -2.52, "left_arm_ry": 0.93, "left_arm_rz": -2.81, "left_gripper": 0.29, "right_arm_vel": 0.546, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.98, "right_arm_rz": -2.98, "right_gripper": 0.43}, "5": {"left_arm_vel": 0.501, "left_gripper_vel": 0.0, "left_arm_rx": -2.53, "left_arm_ry": 0.89, "left_arm_rz": -2.84, "left_gripper": 0.3, "right_arm_vel": 0.501, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.97, "right_arm_rz": -2.95, "right_gripper": 0.43}, "6": {"left_arm_vel": 0.62, "left_gripper_vel": 0.0, "left_arm_rx": -2.57, "left_arm_ry": 0.82, "left_arm_rz": -2.94, "left_gripper": 0.31, "right_arm_vel": 0.62, "right_gripper_vel": 0.0, "right_arm_rx": 2.69, "right_arm_ry": 0.91, "right_arm_rz": -2.9, "right_gripper": 0.43}, "7": {"left_arm_vel": 0.622, "left_gripper_vel": 0.0, "left_arm_rx": -2.52, "left_arm_ry": 0.78, "left_arm_rz": -2.98, "left_gripper": 0.32, "right_arm_vel": 0.622, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.88, "right_arm_rz": -2.77, "right_gripper": 0.43}, "8": {"left_arm_vel": 0.627, "left_gripper_vel": 0.0, "left_arm_rx": -2.49, "left_arm_ry": 0.78, "left_arm_rz": -3.02, "left_gripper": 0.32, "right_arm_vel": 0.627, "right_gripper_vel": 0.0, "right_arm_rx": 2.75, "right_arm_ry": 0.86, "right_arm_rz": -2.55, "right_gripper": 0.43}, "9": {"left_arm_vel": 0.495, "left_gripper_vel": 0.0, "left_arm_rx": -2.46, "left_arm_ry": 0.77, "left_arm_rz": -3.04, "left_gripper": 0.34, "right_arm_vel": 0.495, "right_gripper_vel": 0.0, "right_arm_rx": 2.81, "right_arm_ry": 0.83, "right_arm_rz": -2.35, "right_gripper": 0.43}, "10": {"left_arm_vel": 0.531, "left_gripper_vel": 0.0, "left_arm_rx": -2.45, "left_arm_ry": 0.78, "left_arm_rz": -3.04, "left_gripper": 0.37, "right_arm_vel": 0.531, "right_gripper_vel": 0.0, "right_arm_rx": 2.79, "right_arm_ry": 0.79, "right_arm_rz": -2.29, "right_gripper": 0.43}, "11": {"left_arm_vel": 0.4, "left_gripper_vel": 0.0, "left_arm_rx": -2.43, "left_arm_ry": 0.78, "left_arm_rz": -3.03, "left_gripper": 0.38, "right_arm_vel": 0.4, "right_gripper_vel": 0.0, "right_arm_rx": 2.8, "right_arm_ry": 0.78, "right_arm_rz": -2.26, "right_gripper": 0.43}, "12": {"left_arm_vel": 0.381, "left_gripper_vel": 0.0, "left_arm_rx": -2.4, "left_arm_ry": 0.77, "left_arm_rz": -3.0, "left_gripper": 0.39, "right_arm_vel": 0.381, "right_gripper_vel": 0.0, "right_arm_rx": 2.78, "right_arm_ry": 0.74, "right_arm_rz": -2.19, "right_gripper": 0.43}, "13": {"left_arm_vel": 0.095, "left_gripper_vel": 0.0, "left_arm_rx": -2.45, "left_arm_ry": 0.76, "left_arm_rz": -3.13, "left_gripper": 0.39, "right_arm_vel": 0.095, "right_gripper_vel": 0.0, "right_arm_rx": 2.79, "right_arm_ry": 0.77, "right_arm_rz": -2.15, "right_gripper": 0.43}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.25940001010894775, -0.054499998688697815, -0.13449999690055847], "delta_rot": [0.33899998664855957, -0.37790000438690186, -0.18140000104904175], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.2973}, "right": {"delta_pos": [0.42010000348091125, 0.22540000081062317, -0.07079999893903732], "delta_rot": [-0.030899999663233757, -0.384799987077713, 0.9879999756813049], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and -Z(Down)", "magnitude": 0.4819}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.2757999897003174, -0.05570000037550926, -0.12280000001192093], "delta_rot": [0.3319999873638153, -0.30390000343322754, 6.0756001472473145], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.307}, "right": {"delta_pos": [0.4113999903202057, 0.249099999666214, -0.09669999778270721], "delta_rot": [-0.07320000231266022, -0.46950000524520874, 0.9726999998092651], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and -Z(Down)", "magnitude": 0.4906}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Approaching the bag from a distance to establish contact with the top surface/zipper area.", + "actions": [ + { + "reasoning_cot": "The left arm is moving forward (+X) and downward (-Z) towards the bag. Visual evidence in frames 4-5 shows the gripper arriving at the bag's location near the zipper/side handle, transitioning from free space to close proximity. No grasp has occurred yet.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:side_handle" + }, + "spatial_logic": "moving from table:surface_center approach vector to bag:side_handle proximity", + "topology_change": false + }, + { + "reasoning_cot": "The right arm mirrors the left arm's trajectory, moving forward and down towards the bag. It arrives at the opposite side of the bag's top surface. The gripper remains open, indicating an intent to grasp or stabilize rather than push.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "moving from table:surface_center approach vector to bag:main_body proximity", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Initiating interaction by approaching the bag with both arms positioned for a potential two-handed grasp or stabilization." + } +} +```` +--- +## 🎬 ChunkAnnotator_2 + +### 👁️ 视觉输入 +![chunkannotator_2_img_0.jpg](./images/chunkannotator_2_img_0.jpg) +![chunkannotator_2_img_1.jpg](./images/chunkannotator_2_img_1.jpg) +![chunkannotator_2_img_2.jpg](./images/chunkannotator_2_img_2.jpg) +![chunkannotator_2_img_3.jpg](./images/chunkannotator_2_img_3.jpg) +![chunkannotator_2_img_4.jpg](./images/chunkannotator_2_img_4.jpg) +![chunkannotator_2_img_5.jpg](./images/chunkannotator_2_img_5.jpg) +![chunkannotator_2_img_6.jpg](./images/chunkannotator_2_img_6.jpg) +![chunkannotator_2_img_7.jpg](./images/chunkannotator_2_img_7.jpg) +![chunkannotator_2_img_8.jpg](./images/chunkannotator_2_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_for_grasping"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Approaching the bag from a distance to establish contact with the top surface/zipper area.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.06, "angle": 17.32, "vel_score": 0.22, "angle_score": 0.93, "vel_fft": [0.059, 0.018, 0.004, 0.004, 0.002, 0.005], "angle_fft": [17.317, 17.06, 17.093, 17.102, 17.102, 17.123]}, "right": {"vel": 0.12, "angle": 0.32, "vel_score": 0.43, "angle_score": 1.15, "vel_fft": [0.117, 0.014, 0.014, 0.01, 0.009, 0.015], "angle_fft": [0.321, 0.085, 0.041, 0.031, 0.026, 0.046]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.45, "left_arm_ry": 0.76, "left_arm_rz": -3.14, "left_gripper": 0.39, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.78, "right_arm_ry": 0.77, "right_arm_rz": -2.15, "right_gripper": 0.43}, "1": {"left_arm_vel": 0.121, "left_gripper_vel": 0.0, "left_arm_rx": -2.46, "left_arm_ry": 0.77, "left_arm_rz": 3.13, "left_gripper": 0.39, "right_arm_vel": 0.121, "right_gripper_vel": 0.0, "right_arm_rx": 2.78, "right_arm_ry": 0.76, "right_arm_rz": -2.14, "right_gripper": 0.43}, "2": {"left_arm_vel": 0.118, "left_gripper_vel": 0.0, "left_arm_rx": -2.46, "left_arm_ry": 0.78, "left_arm_rz": 3.13, "left_gripper": 0.39, "right_arm_vel": 0.118, "right_gripper_vel": 0.0, "right_arm_rx": 2.77, "right_arm_ry": 0.76, "right_arm_rz": -2.14, "right_gripper": 0.43}, "3": {"left_arm_vel": 0.155, "left_gripper_vel": 0.0, "left_arm_rx": -2.45, "left_arm_ry": 0.79, "left_arm_rz": 3.13, "left_gripper": 0.39, "right_arm_vel": 0.155, "right_gripper_vel": 0.0, "right_arm_rx": 2.76, "right_arm_ry": 0.75, "right_arm_rz": -2.14, "right_gripper": 0.43}, "4": {"left_arm_vel": 0.1, "left_gripper_vel": 0.0, "left_arm_rx": -2.45, "left_arm_ry": 0.8, "left_arm_rz": 3.13, "left_gripper": 0.39, "right_arm_vel": 0.1, "right_gripper_vel": 0.0, "right_arm_rx": 2.75, "right_arm_ry": 0.74, "right_arm_rz": -2.14, "right_gripper": 0.43}, "5": {"left_arm_vel": 0.156, "left_gripper_vel": 0.0, "left_arm_rx": -2.45, "left_arm_ry": 0.82, "left_arm_rz": 3.13, "left_gripper": 0.39, "right_arm_vel": 0.156, "right_gripper_vel": 0.0, "right_arm_rx": 2.74, "right_arm_ry": 0.72, "right_arm_rz": -2.16, "right_gripper": 0.43}, "6": {"left_arm_vel": 0.116, "left_gripper_vel": 0.0, "left_arm_rx": -2.45, "left_arm_ry": 0.82, "left_arm_rz": 3.13, "left_gripper": 0.39, "right_arm_vel": 0.116, "right_gripper_vel": 0.0, "right_arm_rx": 2.74, "right_arm_ry": 0.71, "right_arm_rz": -2.16, "right_gripper": 0.43}, "7": {"left_arm_vel": 0.117, "left_gripper_vel": 0.0, "left_arm_rx": -2.45, "left_arm_ry": 0.83, "left_arm_rz": 3.13, "left_gripper": 0.39, "right_arm_vel": 0.117, "right_gripper_vel": 0.0, "right_arm_rx": 2.74, "right_arm_ry": 0.69, "right_arm_rz": -2.17, "right_gripper": 0.43}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.015799999237060547, -0.00139999995008111, 0.013399999588727951], "delta_rot": [-0.0003000000142492354, 0.07280000299215317, 6.267399787902832], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0208}, "right": {"delta_pos": [-0.007400000002235174, 0.020400000736117363, -0.025100000202655792], "delta_rot": [-0.03750000149011612, -0.08179999887943268, -0.015300000086426735], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.0332}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.05640000104904175, -0.017100000753998756, -0.01769999973475933], "delta_rot": [-0.6586999893188477, 0.25859999656677246, 5.3597002029418945], "gripper_changed": false, "flow_direction": "+X(Forward)", "magnitude": 0.0615}, "right": {"delta_pos": [-0.008100000210106373, 0.020099999383091927, -0.029200000688433647], "delta_rot": [-0.035999998450279236, -0.11699999868869781, -0.023800000548362732], "gripper_changed": true, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.0364}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Approaching the bag to establish contact with the top surface/zipper area.", + "actions": [ + { + "reasoning_cot": "The left arm is moving forward and downward towards the bag, transitioning from free space to a hovering position near the bag's side. The gripper remains open (stable), indicating an approach phase rather than a grasp.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "side_handle" + }, + "spatial_logic": "moving from free_space to bag:side_handle", + "topology_change": false + }, + { + "reasoning_cot": "The right arm is moving downward and slightly leftward, positioning itself directly over the top reflective patch of the bag. The gripper is open and stable, consistent with an approach maneuver to prepare for interaction with the bag's main body or zipper.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "moving from free_space to bag:main_body", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Initiating contact sequence with the bag; both arms are approaching their respective target zones (side handle and main body) without yet making physical contact." + } +} +```` +--- +## 🎬 ChunkAnnotator_3 + +### 👁️ 视觉输入 +![chunkannotator_3_img_0.jpg](./images/chunkannotator_3_img_0.jpg) +![chunkannotator_3_img_1.jpg](./images/chunkannotator_3_img_1.jpg) +![chunkannotator_3_img_2.jpg](./images/chunkannotator_3_img_2.jpg) +![chunkannotator_3_img_3.jpg](./images/chunkannotator_3_img_3.jpg) +![chunkannotator_3_img_4.jpg](./images/chunkannotator_3_img_4.jpg) +![chunkannotator_3_img_5.jpg](./images/chunkannotator_3_img_5.jpg) +![chunkannotator_3_img_6.jpg](./images/chunkannotator_3_img_6.jpg) +![chunkannotator_3_img_7.jpg](./images/chunkannotator_3_img_7.jpg) +![chunkannotator_3_img_8.jpg](./images/chunkannotator_3_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_for_grasping"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Approaching the bag to establish contact with the top surface/zipper area.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.08, "angle": 1.6, "vel_score": 0.49, "angle_score": 9.89, "vel_fft": [0.085, 0.004, 0.009, 0.006, 0.006, 0.005, 0.005, 0.004, 0.003, 0.004, 0.003, 0.002], "angle_fft": [1.597, 0.941, 0.508, 0.332, 0.133, 0.063, 0.075, 0.135, 0.093, 0.094, 0.118, 0.112]}, "right": {"vel": 0.0, "angle": 0.06, "vel_score": 0.02, "angle_score": 0.35, "vel_fft": [0.004, 0.003, 0.001, 0.001, 0.001, 0.001, 0.0, 0.001, 0.0, 0.001, 0.001, 0.002], "angle_fft": [0.064, 0.032, 0.009, 0.017, 0.025, 0.012, 0.005, 0.012, 0.014, 0.008, 0.008, 0.012]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.45, "left_arm_ry": 0.83, "left_arm_rz": 3.12, "left_gripper": 0.39, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.74, "right_arm_ry": 0.68, "right_arm_rz": -2.17, "right_gripper": 0.43}, "1": {"left_arm_vel": 0.004, "left_gripper_vel": -0.252, "left_arm_rx": -2.45, "left_arm_ry": 0.83, "left_arm_rz": 3.13, "left_gripper": 0.39, "right_arm_vel": 0.004, "right_gripper_vel": -0.252, "right_arm_rx": 2.74, "right_arm_ry": 0.67, "right_arm_rz": -2.18, "right_gripper": 0.42}, "2": {"left_arm_vel": 0.006, "left_gripper_vel": -1.953, "left_arm_rx": -2.45, "left_arm_ry": 0.82, "left_arm_rz": 3.13, "left_gripper": 0.39, "right_arm_vel": 0.006, "right_gripper_vel": -1.953, "right_arm_rx": 2.74, "right_arm_ry": 0.67, "right_arm_rz": -2.18, "right_gripper": 0.32}, "3": {"left_arm_vel": 0.012, "left_gripper_vel": -2.31, "left_arm_rx": -2.45, "left_arm_ry": 0.82, "left_arm_rz": 3.12, "left_gripper": 0.39, "right_arm_vel": 0.012, "right_gripper_vel": -2.31, "right_arm_rx": 2.74, "right_arm_ry": 0.67, "right_arm_rz": -2.18, "right_gripper": 0.25}, "4": {"left_arm_vel": 0.019, "left_gripper_vel": -3.003, "left_arm_rx": -2.45, "left_arm_ry": 0.82, "left_arm_rz": 3.12, "left_gripper": 0.39, "right_arm_vel": 0.019, "right_gripper_vel": -3.003, "right_arm_rx": 2.74, "right_arm_ry": 0.66, "right_arm_rz": -2.18, "right_gripper": 0.15}, "5": {"left_arm_vel": 0.011, "left_gripper_vel": -1.848, "left_arm_rx": -2.46, "left_arm_ry": 0.83, "left_arm_rz": 3.11, "left_gripper": 0.39, "right_arm_vel": 0.011, "right_gripper_vel": -1.848, "right_arm_rx": 2.74, "right_arm_ry": 0.66, "right_arm_rz": -2.17, "right_gripper": 0.09}, "6": {"left_arm_vel": 0.009, "left_gripper_vel": -0.882, "left_arm_rx": -2.47, "left_arm_ry": 0.84, "left_arm_rz": 3.09, "left_gripper": 0.39, "right_arm_vel": 0.009, "right_gripper_vel": -0.882, "right_arm_rx": 2.74, "right_arm_ry": 0.66, "right_arm_rz": -2.17, "right_gripper": 0.06}, "7": {"left_arm_vel": 0.002, "left_gripper_vel": -0.042, "left_arm_rx": -2.49, "left_arm_ry": 0.86, "left_arm_rz": 3.06, "left_gripper": 0.39, "right_arm_vel": 0.002, "right_gripper_vel": -0.042, "right_arm_rx": 2.75, "right_arm_ry": 0.66, "right_arm_rz": -2.17, "right_gripper": 0.06}, "8": {"left_arm_vel": 0.015, "left_gripper_vel": 0.0, "left_arm_rx": -2.51, "left_arm_ry": 0.88, "left_arm_rz": 3.01, "left_gripper": 0.39, "right_arm_vel": 0.015, "right_gripper_vel": 0.0, "right_arm_rx": 2.75, "right_arm_ry": 0.66, "right_arm_rz": -2.17, "right_gripper": 0.06}, "9": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.54, "left_arm_ry": 0.9, "left_arm_rz": 2.98, "left_gripper": 0.39, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.75, "right_arm_ry": 0.66, "right_arm_rz": -2.17, "right_gripper": 0.06}, "10": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.59, "left_arm_ry": 0.93, "left_arm_rz": 2.9, "left_gripper": 0.39, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.75, "right_arm_ry": 0.66, "right_arm_rz": -2.17, "right_gripper": 0.06}, "11": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.75, "left_arm_ry": 0.99, "left_arm_rz": 2.68, "left_gripper": 0.39, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.75, "right_arm_ry": 0.66, "right_arm_rz": -2.17, "right_gripper": 0.06}, "12": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 1.02, "left_arm_rz": 2.42, "left_gripper": 0.39, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.75, "right_arm_ry": 0.65, "right_arm_rz": -2.17, "right_gripper": 0.06}, "13": {"left_arm_vel": 0.0, "left_gripper_vel": -0.021, "left_arm_rx": -3.11, "left_arm_ry": 1.02, "left_arm_rz": 2.22, "left_gripper": 0.39, "right_arm_vel": 0.0, "right_gripper_vel": -0.021, "right_arm_rx": 2.74, "right_arm_ry": 0.65, "right_arm_rz": -2.18, "right_gripper": 0.05}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.039400000125169754, -0.015599999576807022, -0.031099999323487282], "delta_rot": [-0.6577000021934509, 0.18440000712871552, -0.9067999720573425], "gripper_changed": false, "flow_direction": "+X(Forward) and -Z(Down)", "magnitude": 0.0526}, "right": {"delta_pos": [-0.0012000000569969416, 0.0, -0.001500000013038516], "delta_rot": [0.0017999999690800905, -0.024399999529123306, -0.0026000000070780516], "gripper_changed": true, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0019}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.01720000058412552, -0.037700001150369644, 0.00279999990016222], "delta_rot": [5.360899925231934, 0.07620000094175339, -1.0260000228881836], "gripper_changed": true, "flow_direction": "-Y(Right)", "magnitude": 0.0415}, "right": {"delta_pos": [-0.0010000000474974513, -0.0003000000142492354, -0.002400000113993883], "delta_rot": [-0.04360000044107437, -0.05909999832510948, -0.08500000089406967], "gripper_changed": true, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0026}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Approaching the bag to establish contact with the top surface/zipper area.", + "actions": [ + { + "reasoning_cot": "The left arm is moving forward (+X) and downward (-Z) towards the bag, as indicated by the kinematic delta. Visually, the gripper transitions from hovering above the table to making contact with the side/top edge of the bag near the zipper pull. The gripper remains open (stable signal), indicating an approach or touch phase rather than a grasp.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving from free space to bag:zipper_pull", + "topology_change": false + }, + { + "reasoning_cot": "The right arm shows negligible movement (magnitude 0.0019) and remains in a hovering position above the bag's main body. There is no visual evidence of contact or significant trajectory change. It acts as a passive observer or stabilizer in this chunk.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "hovering over bag:main_body", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Left arm has successfully located and made initial contact with the bag's zipper area; right arm remains stationary." + } +} +```` +--- +## 🎬 ChunkAnnotator_4 + +### 👁️ 视觉输入 +![chunkannotator_4_img_0.jpg](./images/chunkannotator_4_img_0.jpg) +![chunkannotator_4_img_1.jpg](./images/chunkannotator_4_img_1.jpg) +![chunkannotator_4_img_2.jpg](./images/chunkannotator_4_img_2.jpg) +![chunkannotator_4_img_3.jpg](./images/chunkannotator_4_img_3.jpg) +![chunkannotator_4_img_4.jpg](./images/chunkannotator_4_img_4.jpg) +![chunkannotator_4_img_5.jpg](./images/chunkannotator_4_img_5.jpg) +![chunkannotator_4_img_6.jpg](./images/chunkannotator_4_img_6.jpg) +![chunkannotator_4_img_7.jpg](./images/chunkannotator_4_img_7.jpg) +![chunkannotator_4_img_8.jpg](./images/chunkannotator_4_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_for_grasping"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Approaching the bag to establish contact with the top surface/zipper area.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.08, "angle": 0.53, "vel_score": 0.92, "angle_score": 5.96, "vel_fft": [0.084, 0.029, 0.018, 0.017, 0.013, 0.012, 0.007, 0.007, 0.004, 0.003, 0.002, 0.001, 0.002, 0.002, 0.002, 0.001, 0.004, 0.004, 0.004, 0.005], "angle_fft": [0.534, 0.188, 0.087, 0.177, 0.155, 0.065, 0.087, 0.054, 0.037, 0.006, 0.04, 0.047, 0.032, 0.016, 0.014, 0.011, 0.016, 0.023, 0.03, 0.033]}, "right": {"vel": 0.0, "angle": 0.05, "vel_score": 0.01, "angle_score": 0.67, "vel_fft": [0.001, 0.001, 0.0, 0.001, 0.001, 0.0, 0.001, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "angle_fft": [0.054, 0.038, 0.022, 0.01, 0.005, 0.01, 0.012, 0.012, 0.004, 0.002, 0.005, 0.002, 0.005, 0.006, 0.002, 0.002, 0.004, 0.006, 0.005, 0.003]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 3.12, "left_arm_ry": 1.01, "left_arm_rz": 2.15, "left_gripper": 0.39, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.74, "right_arm_ry": 0.65, "right_arm_rz": -2.18, "right_gripper": 0.05}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.91, "left_arm_ry": 1.02, "left_arm_rz": 1.92, "left_gripper": 0.39, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.74, "right_arm_ry": 0.66, "right_arm_rz": -2.18, "right_gripper": 0.05}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.83, "left_arm_ry": 0.96, "left_arm_rz": 1.85, "left_gripper": 0.34, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.73, "right_arm_ry": 0.66, "right_arm_rz": -2.18, "right_gripper": 0.05}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.8, "left_arm_ry": 0.94, "left_arm_rz": 1.8, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.73, "right_arm_ry": 0.66, "right_arm_rz": -2.18, "right_gripper": 0.05}, "4": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": 2.78, "left_arm_ry": 0.92, "left_arm_rz": 1.78, "left_gripper": 0.09, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.73, "right_arm_ry": 0.65, "right_arm_rz": -2.19, "right_gripper": 0.05}, "5": {"left_arm_vel": 0.006, "left_gripper_vel": -0.021, "left_arm_rx": 2.86, "left_arm_ry": 0.91, "left_arm_rz": 1.93, "left_gripper": -0.01, "right_arm_vel": 0.006, "right_gripper_vel": -0.021, "right_arm_rx": 2.73, "right_arm_ry": 0.65, "right_arm_rz": -2.19, "right_gripper": 0.05}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.97, "left_arm_ry": 0.89, "left_arm_rz": 2.11, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.63, "right_arm_rz": -2.22, "right_gripper": 0.05}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.91, "left_arm_ry": 0.91, "left_arm_rz": 2.1, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 0.62, "right_arm_rz": -2.26, "right_gripper": 0.05}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.022600000724196434, -0.01940000057220459, 0.03550000116229057], "delta_rot": [-0.21310000121593475, -0.1062999963760376, -0.0494999997317791], "gripper_changed": true, "flow_direction": "-X(Backward) and +Z(Up)", "magnitude": 0.0463}, "right": {"delta_pos": [0.00019999999494757503, -0.0003000000142492354, -0.0008999999845400453], "delta_rot": [-0.04540000110864639, -0.034699998795986176, -0.08229999989271164], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.001}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.14990000426769257, -0.07540000230073929, 0.045099999755620956], "delta_rot": [-6.0131001472473145, -0.13490000367164612, 0.13670000433921814], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.1738}, "right": {"delta_pos": [-0.004100000020116568, 0.007300000172108412, -0.0010999999940395355], "delta_rot": [-0.16949999332427979, -0.09109999984502792, -0.2354000061750412], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0084}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm approaches and grasps the bag's side handle to stabilize it, while right arm hovers near the zipper pull.", + "actions": [ + { + "reasoning_cot": "The left arm moves from a free-space position towards the bag, specifically targeting the side handle. The gripper closes (delta_gripper negative) and secures the handle, establishing a stable hold for subsequent manipulation.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:side_handle" + }, + "spatial_logic": "Approaching from table surface to bag side handle", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains relatively stationary near the top of the bag, hovering over the zipper area without making significant contact or changing state. It acts as a passive observer or preparatory agent.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "hover", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "Hovering above zipper pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:side_handle", + "current_status": "grasped_by_left_arm" + } + ], + "task_progress": "Stabilizing the bag by grasping the side handle with the left arm." + } +} +```` +--- +## 🎬 ChunkAnnotator_5 + +### 👁️ 视觉输入 +![chunkannotator_5_img_0.jpg](./images/chunkannotator_5_img_0.jpg) +![chunkannotator_5_img_1.jpg](./images/chunkannotator_5_img_1.jpg) +![chunkannotator_5_img_2.jpg](./images/chunkannotator_5_img_2.jpg) +![chunkannotator_5_img_3.jpg](./images/chunkannotator_5_img_3.jpg) +![chunkannotator_5_img_4.jpg](./images/chunkannotator_5_img_4.jpg) +![chunkannotator_5_img_5.jpg](./images/chunkannotator_5_img_5.jpg) +![chunkannotator_5_img_6.jpg](./images/chunkannotator_5_img_6.jpg) +![chunkannotator_5_img_7.jpg](./images/chunkannotator_5_img_7.jpg) +![chunkannotator_5_img_8.jpg](./images/chunkannotator_5_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_for_grasping"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and grasps the bag's side handle to stabilize it, while right arm hovers near the zipper pull.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.1, "angle": 3.67, "vel_score": 1.09, "angle_score": 6.96, "vel_fft": [0.102, 0.02, 0.007, 0.016, 0.018, 0.005, 0.004, 0.004, 0.003, 0.004, 0.004, 0.002, 0.002, 0.003, 0.002, 0.004, 0.001, 0.004, 0.005, 0.002], "angle_fft": [3.668, 3.18, 3.152, 3.124, 3.047, 3.119, 3.059, 3.008, 3.037, 3.042, 3.033, 3.075, 3.034, 3.017, 3.033, 3.05, 3.055, 3.059, 3.065, 3.049]}, "right": {"vel": 0.01, "angle": 0.1, "vel_score": 0.08, "angle_score": 1.17, "vel_fft": [0.006, 0.004, 0.003, 0.003, 0.002, 0.003, 0.002, 0.002, 0.001, 0.001, 0.001, 0.0, 0.001, 0.001, 0.0, 0.001, 0.001, 0.001, 0.0, 0.001], "angle_fft": [0.102, 0.045, 0.045, 0.024, 0.023, 0.018, 0.017, 0.016, 0.016, 0.01, 0.007, 0.009, 0.014, 0.003, 0.006, 0.007, 0.007, 0.006, 0.006, 0.008]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.91, "left_arm_ry": 0.92, "left_arm_rz": 2.11, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.69, "right_arm_ry": 0.62, "right_arm_rz": -2.26, "right_gripper": 0.05}, "1": {"left_arm_vel": 0.033, "left_gripper_vel": 0.0, "left_arm_rx": 2.92, "left_arm_ry": 0.91, "left_arm_rz": 2.21, "left_gripper": -0.01, "right_arm_vel": 0.033, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.61, "right_arm_rz": -2.28, "right_gripper": 0.04}, "2": {"left_arm_vel": 0.005, "left_gripper_vel": 0.0, "left_arm_rx": 3.07, "left_arm_ry": 0.92, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.005, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.6, "right_arm_rz": -2.33, "right_gripper": 0.04}, "3": {"left_arm_vel": 0.01, "left_gripper_vel": -0.021, "left_arm_rx": -2.92, "left_arm_ry": 0.94, "left_arm_rz": 2.46, "left_gripper": -0.01, "right_arm_vel": 0.01, "right_gripper_vel": -0.021, "right_arm_rx": 2.6, "right_arm_ry": 0.59, "right_arm_rz": -2.36, "right_gripper": 0.04}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.9, "left_arm_rz": 2.47, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.59, "right_arm_rz": -2.37, "right_gripper": 0.04}, "5": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -2.89, "left_arm_ry": 0.88, "left_arm_rz": 2.41, "left_gripper": -0.0, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.59, "right_arm_ry": 0.58, "right_arm_rz": -2.38, "right_gripper": 0.04}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.02, "left_arm_ry": 0.88, "left_arm_rz": 2.28, "left_gripper": -0.0, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.59, "right_arm_ry": 0.57, "right_arm_rz": -2.39, "right_gripper": 0.04}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.89, "left_arm_ry": 0.88, "left_arm_rz": 2.29, "left_gripper": -0.0, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.56, "right_arm_rz": -2.41, "right_gripper": 0.04}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.12319999933242798, -0.0568000003695488, 0.004600000102072954], "delta_rot": [-5.798600196838379, -0.04010000079870224, 0.17990000545978546], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.1358}, "right": {"delta_pos": [-0.00430000014603138, 0.007499999832361937, -0.0003000000142492354], "delta_rot": [-0.11890000104904175, -0.05530000105500221, -0.14650000631809235], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0086}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.10980000346899033, -0.10649999976158142, 0.0215000007301569], "delta_rot": [-5.655099868774414, -0.07900000363588333, 0.17329999804496765], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.1545}, "right": {"delta_pos": [0.000699999975040555, -9.999999747378752e-05, -0.00019999999494757503], "delta_rot": [-0.13359999656677246, -0.07720000296831131, -0.20100000500679016], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0007}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", + "actions": [ + { + "reasoning_cot": "The left arm is visually confirmed to be holding the side handle of the bag. The kinematic data shows low velocity (0.1) and stable gripper state (-0.01), indicating a static hold to anchor the object against the table surface.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "side_handle" + }, + "spatial_logic": "static_at_side_handle", + "topology_change": false + }, + { + "reasoning_cot": "The right arm transitions from hovering near the bag to making contact with the zipper pull. Visual evidence in frames T1-T2 shows the gripper jaws closing around the metal zipper tab. This is a precise grasp action to gain control of the zipper mechanism.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "zipper_pull" + }, + "spatial_logic": "approaching_and_grasping_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:side_handle", + "current_status": "grasped_by_left_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_right_arm" + } + ], + "task_progress": "Bag stabilized and zipper engaged; ready to unzip." + } +} +```` +--- +## 🎬 ChunkAnnotator_6 + +### 👁️ 视觉输入 +![chunkannotator_6_img_0.jpg](./images/chunkannotator_6_img_0.jpg) +![chunkannotator_6_img_1.jpg](./images/chunkannotator_6_img_1.jpg) +![chunkannotator_6_img_2.jpg](./images/chunkannotator_6_img_2.jpg) +![chunkannotator_6_img_3.jpg](./images/chunkannotator_6_img_3.jpg) +![chunkannotator_6_img_4.jpg](./images/chunkannotator_6_img_4.jpg) +![chunkannotator_6_img_5.jpg](./images/chunkannotator_6_img_5.jpg) +![chunkannotator_6_img_6.jpg](./images/chunkannotator_6_img_6.jpg) +![chunkannotator_6_img_7.jpg](./images/chunkannotator_6_img_7.jpg) +![chunkannotator_6_img_8.jpg](./images/chunkannotator_6_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:side_handle"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.13, "angle": 0.47, "vel_score": 0.7, "angle_score": 2.56, "vel_fft": [0.129, 0.051, 0.026, 0.011, 0.009, 0.008, 0.007, 0.011, 0.012, 0.011, 0.008], "angle_fft": [0.471, 0.079, 0.147, 0.022, 0.073, 0.031, 0.016, 0.03, 0.034, 0.028, 0.0]}, "right": {"vel": 0.01, "angle": 0.1, "vel_score": 0.07, "angle_score": 0.6, "vel_fft": [0.014, 0.008, 0.006, 0.006, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.002], "angle_fft": [0.102, 0.075, 0.049, 0.028, 0.011, 0.016, 0.013, 0.014, 0.015, 0.009, 0.005]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.88, "left_arm_rz": 2.29, "left_gripper": -0.0, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.56, "right_arm_rz": -2.41, "right_gripper": 0.04}, "1": {"left_arm_vel": 0.001, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.9, "left_arm_rz": 2.25, "left_gripper": -0.0, "right_arm_vel": 0.001, "right_gripper_vel": 0.0, "right_arm_rx": 2.58, "right_arm_ry": 0.56, "right_arm_rz": -2.41, "right_gripper": 0.04}, "2": {"left_arm_vel": 0.016, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.91, "left_arm_rz": 2.19, "left_gripper": -0.0, "right_arm_vel": 0.016, "right_gripper_vel": 0.0, "right_arm_rx": 2.58, "right_arm_ry": 0.56, "right_arm_rz": -2.41, "right_gripper": 0.04}, "3": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -2.86, "left_arm_ry": 0.9, "left_arm_rz": 2.18, "left_gripper": -0.0, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.58, "right_arm_ry": 0.56, "right_arm_rz": -2.41, "right_gripper": 0.04}, "4": {"left_arm_vel": 0.015, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.88, "left_arm_rz": 2.26, "left_gripper": 0.03, "right_arm_vel": 0.015, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.56, "right_arm_rz": -2.42, "right_gripper": 0.04}, "5": {"left_arm_vel": 0.027, "left_gripper_vel": 0.042, "left_arm_rx": -2.78, "left_arm_ry": 0.88, "left_arm_rz": 2.26, "left_gripper": 0.06, "right_arm_vel": 0.027, "right_gripper_vel": 0.042, "right_arm_rx": 2.57, "right_arm_ry": 0.55, "right_arm_rz": -2.44, "right_gripper": 0.04}, "6": {"left_arm_vel": 0.032, "left_gripper_vel": 0.42, "left_arm_rx": -2.77, "left_arm_ry": 0.87, "left_arm_rz": 2.26, "left_gripper": 0.12, "right_arm_vel": 0.032, "right_gripper_vel": 0.42, "right_arm_rx": 2.57, "right_arm_ry": 0.55, "right_arm_rz": -2.45, "right_gripper": 0.06}, "7": {"left_arm_vel": 0.059, "left_gripper_vel": 1.05, "left_arm_rx": -2.76, "left_arm_ry": 0.85, "left_arm_rz": 2.27, "left_gripper": 0.19, "right_arm_vel": 0.059, "right_gripper_vel": 1.05, "right_arm_rx": 2.56, "right_arm_ry": 0.54, "right_arm_rz": -2.46, "right_gripper": 0.09}, "8": {"left_arm_vel": 0.067, "left_gripper_vel": 1.386, "left_arm_rx": -2.75, "left_arm_ry": 0.84, "left_arm_rz": 2.28, "left_gripper": 0.27, "right_arm_vel": 0.067, "right_gripper_vel": 1.386, "right_arm_rx": 2.56, "right_arm_ry": 0.54, "right_arm_rz": -2.46, "right_gripper": 0.14}, "9": {"left_arm_vel": 0.067, "left_gripper_vel": 1.386, "left_arm_rx": -2.75, "left_arm_ry": 0.84, "left_arm_rz": 2.28, "left_gripper": 0.27, "right_arm_vel": 0.067, "right_gripper_vel": 1.386, "right_arm_rx": 2.56, "right_arm_ry": 0.54, "right_arm_rz": -2.46, "right_gripper": 0.14}, "10": {"left_arm_vel": 0.067, "left_gripper_vel": 1.386, "left_arm_rx": -2.75, "left_arm_ry": 0.84, "left_arm_rz": 2.28, "left_gripper": 0.27, "right_arm_vel": 0.067, "right_gripper_vel": 1.386, "right_arm_rx": 2.56, "right_arm_ry": 0.54, "right_arm_rz": -2.46, "right_gripper": 0.14}, "11": {"left_arm_vel": 0.067, "left_gripper_vel": 1.386, "left_arm_rx": -2.75, "left_arm_ry": 0.84, "left_arm_rz": 2.28, "left_gripper": 0.27, "right_arm_vel": 0.067, "right_gripper_vel": 1.386, "right_arm_rx": 2.56, "right_arm_ry": 0.54, "right_arm_rz": -2.46, "right_gripper": 0.14}, "12": {"left_arm_vel": 0.067, "left_gripper_vel": 1.386, "left_arm_rx": -2.75, "left_arm_ry": 0.84, "left_arm_rz": 2.28, "left_gripper": 0.27, "right_arm_vel": 0.067, "right_gripper_vel": 1.386, "right_arm_rx": 2.56, "right_arm_ry": 0.54, "right_arm_rz": -2.46, "right_gripper": 0.14}, "13": {"left_arm_vel": 0.067, "left_gripper_vel": 1.386, "left_arm_rx": -2.75, "left_arm_ry": 0.84, "left_arm_rz": 2.28, "left_gripper": 0.27, "right_arm_vel": 0.067, "right_gripper_vel": 1.386, "right_arm_rx": 2.56, "right_arm_ry": 0.54, "right_arm_rz": -2.46, "right_gripper": 0.14}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.012199999764561653, -0.04490000009536743, 0.01769999973475933], "delta_rot": [0.13050000369548798, -0.039000000804662704, -0.00930000003427267], "gripper_changed": false, "flow_direction": "-Y(Right)", "magnitude": 0.0497}, "right": {"delta_pos": [0.004900000058114529, -0.007600000128149986, 0.00019999999494757503], "delta_rot": [-0.014700000174343586, -0.021900000050663948, -0.054499998688697815], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.009}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.07559999823570251, 0.031700000166893005, 0.07890000194311142], "delta_rot": [0.04659999907016754, 0.047600001096725464, 0.2903999984264374], "gripper_changed": true, "flow_direction": "+X(Forward) and +Y(Left) and +Z(Up)", "magnitude": 0.1138}, "right": {"delta_pos": [0.04129999876022339, -0.11509999632835388, 0.05620000138878822], "delta_rot": [-0.07810000330209732, 0.0357000008225441, -0.36399999260902405], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.1345}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", + "actions": [ + { + "reasoning_cot": "The left arm is visually confirmed to be holding the side handle of the bag. The gripper signal shows an increase in width (opening) from 0.0 to 0.27, which indicates the robot is actively applying force to maintain the grasp against the bag's resistance or adjusting its hold, rather than releasing. The spatial logic is 'static_at_handle' as it provides stability for the right arm's operation.", + "causal_trace": { + "gripper_signal": "opening", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "side_handle" + }, + "spatial_logic": "static_at_handle", + "topology_change": false + }, + { + "reasoning_cot": "The right arm has moved from a hovering position to making direct contact with the zipper pull. The visual sequence shows the gripper closing around the metal tab. The gripper signal transitions from open (0.04) to partially closed (0.14), confirming the execution of a grasp action to secure the zipper for manipulation.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "zipper_pull" + }, + "spatial_logic": "approach_and_grasp_zipper", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_right_arm" + } + ], + "task_progress": "Bag stabilized by left arm; right arm has successfully acquired grasp on zipper pull." + } +} +```` +--- +## 🎬 ChunkAnnotator_7 + +### 👁️ 视觉输入 +![chunkannotator_7_img_0.jpg](./images/chunkannotator_7_img_0.jpg) +![chunkannotator_7_img_1.jpg](./images/chunkannotator_7_img_1.jpg) +![chunkannotator_7_img_2.jpg](./images/chunkannotator_7_img_2.jpg) +![chunkannotator_7_img_3.jpg](./images/chunkannotator_7_img_3.jpg) +![chunkannotator_7_img_4.jpg](./images/chunkannotator_7_img_4.jpg) +![chunkannotator_7_img_5.jpg](./images/chunkannotator_7_img_5.jpg) +![chunkannotator_7_img_6.jpg](./images/chunkannotator_7_img_6.jpg) +![chunkannotator_7_img_7.jpg](./images/chunkannotator_7_img_7.jpg) +![chunkannotator_7_img_8.jpg](./images/chunkannotator_7_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:side_handle"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.26, "angle": 0.73, "vel_score": 1.12, "angle_score": 3.18, "vel_fft": [0.262, 0.029, 0.02, 0.017, 0.021, 0.018, 0.025, 0.02], "angle_fft": [0.729, 0.207, 0.048, 0.032, 0.044, 0.035, 0.046, 0.027]}, "right": {"vel": 0.27, "angle": 0.68, "vel_score": 1.16, "angle_score": 2.91, "vel_fft": [0.271, 0.064, 0.022, 0.018, 0.027, 0.011, 0.015, 0.012], "angle_fft": [0.685, 0.08, 0.079, 0.061, 0.06, 0.034, 0.048, 0.039]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.75, "left_arm_ry": 0.84, "left_arm_rz": 2.29, "left_gripper": 0.32, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.54, "right_arm_rz": -2.48, "right_gripper": 0.21}, "1": {"left_arm_vel": 0.116, "left_gripper_vel": 2.268, "left_arm_rx": -2.75, "left_arm_ry": 0.83, "left_arm_rz": 2.3, "left_gripper": 0.36, "right_arm_vel": 0.116, "right_gripper_vel": 2.268, "right_arm_rx": 2.55, "right_arm_ry": 0.54, "right_arm_rz": -2.49, "right_gripper": 0.28}, "2": {"left_arm_vel": 0.168, "left_gripper_vel": 1.638, "left_arm_rx": -2.76, "left_arm_ry": 0.82, "left_arm_rz": 2.32, "left_gripper": 0.39, "right_arm_vel": 0.168, "right_gripper_vel": 1.638, "right_arm_rx": 2.55, "right_arm_ry": 0.53, "right_arm_rz": -2.51, "right_gripper": 0.34}, "3": {"left_arm_vel": 0.217, "left_gripper_vel": 0.567, "left_arm_rx": -2.78, "left_arm_ry": 0.83, "left_arm_rz": 2.36, "left_gripper": 0.41, "right_arm_vel": 0.217, "right_gripper_vel": 0.567, "right_arm_rx": 2.54, "right_arm_ry": 0.53, "right_arm_rz": -2.56, "right_gripper": 0.4}, "4": {"left_arm_vel": 0.325, "left_gripper_vel": -0.021, "left_arm_rx": -2.79, "left_arm_ry": 0.86, "left_arm_rz": 2.42, "left_gripper": 0.42, "right_arm_vel": 0.325, "right_gripper_vel": -0.021, "right_arm_rx": 2.53, "right_arm_ry": 0.54, "right_arm_rz": -2.61, "right_gripper": 0.4}, "5": {"left_arm_vel": 0.383, "left_gripper_vel": -0.021, "left_arm_rx": -2.8, "left_arm_ry": 0.88, "left_arm_rz": 2.49, "left_gripper": 0.42, "right_arm_vel": 0.383, "right_gripper_vel": -0.021, "right_arm_rx": 2.53, "right_arm_ry": 0.55, "right_arm_rz": -2.65, "right_gripper": 0.4}, "6": {"left_arm_vel": 0.315, "left_gripper_vel": -0.021, "left_arm_rx": -2.82, "left_arm_ry": 0.91, "left_arm_rz": 2.57, "left_gripper": 0.4, "right_arm_vel": 0.315, "right_gripper_vel": -0.021, "right_arm_rx": 2.52, "right_arm_ry": 0.59, "right_arm_rz": -2.73, "right_gripper": 0.4}, "7": {"left_arm_vel": 0.321, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.93, "left_arm_rz": 2.58, "left_gripper": 0.4, "right_arm_vel": 0.321, "right_gripper_vel": 0.0, "right_arm_rx": 2.5, "right_arm_ry": 0.6, "right_arm_rz": -2.77, "right_gripper": 0.4}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0649000033736229, 0.07249999791383743, 0.05559999868273735], "delta_rot": [-0.08500000089406967, 0.09239999949932098, 0.2897999882698059], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and +Z(Up)", "magnitude": 0.1121}, "right": {"delta_pos": [0.035100001841783524, -0.10540000349283218, 0.0551999993622303], "delta_rot": [-0.0568000003695488, 0.0568000003695488, -0.29750001430511475], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.1241}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.2150000035762787, -0.0348999984562397, 0.04309999942779541], "delta_rot": [-0.12020000070333481, -0.007899999618530273, -0.20110000669956207], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.222}, "right": {"delta_pos": [-0.09589999914169312, -0.19509999454021454, -0.025699999183416367], "delta_rot": [-0.004600000102072954, 0.14300000667572021, -0.4772000014781952], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "magnitude": 0.2189}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", + "actions": [ + { + "reasoning_cot": "The left arm is visually confirmed to be holding the side handle of the bag. The gripper width remains stable (approx 0.42) throughout the sequence, indicating a static hold to stabilize the object against the forces applied by the right arm.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "side_handle" + }, + "spatial_logic": "static_at_side_handle", + "topology_change": false + }, + { + "reasoning_cot": "The right arm moves from an approach position to make contact with the zipper pull tab. Visual evidence shows the gripper jaws closing around the metal ring of the zipper pull. This establishes a secure grasp necessary for the subsequent unzipping action.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "zipper_pull" + }, + "spatial_logic": "approaching_and_grasping_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_right_arm" + } + ], + "task_progress": "Right arm has successfully secured the zipper pull; left arm maintains stability. Ready to initiate unzipping motion." + } +} +```` +--- +## 🎬 ChunkAnnotator_8 + +### 👁️ 视觉输入 +![chunkannotator_8_img_0.jpg](./images/chunkannotator_8_img_0.jpg) +![chunkannotator_8_img_1.jpg](./images/chunkannotator_8_img_1.jpg) +![chunkannotator_8_img_2.jpg](./images/chunkannotator_8_img_2.jpg) +![chunkannotator_8_img_3.jpg](./images/chunkannotator_8_img_3.jpg) +![chunkannotator_8_img_4.jpg](./images/chunkannotator_8_img_4.jpg) +![chunkannotator_8_img_5.jpg](./images/chunkannotator_8_img_5.jpg) +![chunkannotator_8_img_6.jpg](./images/chunkannotator_8_img_6.jpg) +![chunkannotator_8_img_7.jpg](./images/chunkannotator_8_img_7.jpg) +![chunkannotator_8_img_8.jpg](./images/chunkannotator_8_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:side_handle"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.3, "angle": 0.88, "vel_score": 1.61, "angle_score": 4.88, "vel_fft": [0.298, 0.055, 0.026, 0.019, 0.015, 0.006, 0.016, 0.014, 0.02, 0.018, 0.015], "angle_fft": [0.876, 0.291, 0.146, 0.035, 0.032, 0.053, 0.025, 0.058, 0.015, 0.058, 0.002]}, "right": {"vel": 0.3, "angle": 0.64, "vel_score": 1.64, "angle_score": 3.47, "vel_fft": [0.3, 0.054, 0.02, 0.016, 0.013, 0.018, 0.013, 0.01, 0.014, 0.016, 0.011], "angle_fft": [0.641, 0.138, 0.033, 0.083, 0.022, 0.019, 0.02, 0.024, 0.099, 0.048, 0.035]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.94, "left_arm_rz": 2.57, "left_gripper": 0.39, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.59, "right_arm_rz": -2.79, "right_gripper": 0.4}, "1": {"left_arm_vel": 0.301, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.95, "left_arm_rz": 2.55, "left_gripper": 0.39, "right_arm_vel": 0.301, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.58, "right_arm_rz": -2.81, "right_gripper": 0.4}, "2": {"left_arm_vel": 0.31, "left_gripper_vel": 0.0, "left_arm_rx": -2.81, "left_arm_ry": 0.96, "left_arm_rz": 2.52, "left_gripper": 0.39, "right_arm_vel": 0.31, "right_gripper_vel": 0.0, "right_arm_rx": 2.48, "right_arm_ry": 0.55, "right_arm_rz": -2.83, "right_gripper": 0.4}, "3": {"left_arm_vel": 0.319, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.96, "left_arm_rz": 2.5, "left_gripper": 0.39, "right_arm_vel": 0.319, "right_gripper_vel": 0.0, "right_arm_rx": 2.48, "right_arm_ry": 0.53, "right_arm_rz": -2.84, "right_gripper": 0.4}, "4": {"left_arm_vel": 0.37, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.96, "left_arm_rz": 2.47, "left_gripper": 0.39, "right_arm_vel": 0.37, "right_gripper_vel": 0.0, "right_arm_rx": 2.48, "right_arm_ry": 0.51, "right_arm_rz": -2.87, "right_gripper": 0.4}, "5": {"left_arm_vel": 0.401, "left_gripper_vel": 0.0, "left_arm_rx": -2.78, "left_arm_ry": 0.96, "left_arm_rz": 2.43, "left_gripper": 0.39, "right_arm_vel": 0.401, "right_gripper_vel": 0.0, "right_arm_rx": 2.5, "right_arm_ry": 0.54, "right_arm_rz": -2.9, "right_gripper": 0.4}, "6": {"left_arm_vel": 0.341, "left_gripper_vel": -0.021, "left_arm_rx": -2.78, "left_arm_ry": 0.95, "left_arm_rz": 2.4, "left_gripper": 0.39, "right_arm_vel": 0.341, "right_gripper_vel": -0.021, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.92, "right_gripper": 0.4}, "7": {"left_arm_vel": 0.419, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.95, "left_arm_rz": 2.35, "left_gripper": 0.39, "right_arm_vel": 0.419, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.59, "right_arm_rz": -2.93, "right_gripper": 0.4}, "8": {"left_arm_vel": 0.412, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.94, "left_arm_rz": 2.31, "left_gripper": 0.39, "right_arm_vel": 0.412, "right_gripper_vel": 0.0, "right_arm_rx": 2.56, "right_arm_ry": 0.61, "right_arm_rz": -2.93, "right_gripper": 0.4}, "9": {"left_arm_vel": 0.316, "left_gripper_vel": 0.0, "left_arm_rx": -2.84, "left_arm_ry": 0.92, "left_arm_rz": 2.26, "left_gripper": 0.39, "right_arm_vel": 0.316, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.64, "right_arm_rz": -2.93, "right_gripper": 0.4}, "10": {"left_arm_vel": 0.399, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.91, "left_arm_rz": 2.21, "left_gripper": 0.39, "right_arm_vel": 0.399, "right_gripper_vel": 0.0, "right_arm_rx": 2.59, "right_arm_ry": 0.66, "right_arm_rz": -2.93, "right_gripper": 0.4}, "11": {"left_arm_vel": 0.351, "left_gripper_vel": 0.0, "left_arm_rx": -2.89, "left_arm_ry": 0.9, "left_arm_rz": 2.17, "left_gripper": 0.39, "right_arm_vel": 0.351, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.67, "right_arm_rz": -2.93, "right_gripper": 0.4}, "12": {"left_arm_vel": 0.228, "left_gripper_vel": 0.0, "left_arm_rx": -2.9, "left_arm_ry": 0.86, "left_arm_rz": 2.12, "left_gripper": 0.39, "right_arm_vel": 0.228, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.68, "right_arm_rz": -2.95, "right_gripper": 0.4}, "13": {"left_arm_vel": 0.128, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.83, "left_arm_rz": 2.09, "left_gripper": 0.39, "right_arm_vel": 0.128, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.69, "right_arm_rz": -2.95, "right_gripper": 0.4}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.13940000534057617, -0.10540000349283218, -0.018300000578165054], "delta_rot": [-0.03290000185370445, -0.11180000007152557, -0.4799000024795532], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right)", "magnitude": 0.1757}, "right": {"delta_pos": [-0.1307000070810318, -0.08160000294446945, -0.08229999989271164], "delta_rot": [0.060499999672174454, 0.0917000025510788, -0.1597999930381775], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "magnitude": 0.1747}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.1421000063419342, -0.11649999767541885, -0.05169999971985817], "delta_rot": [-0.01850000023841858, -0.24469999969005585, -0.5081999897956848], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.1909}, "right": {"delta_pos": [-0.1234000027179718, -0.03970000147819519, -0.10580000281333923], "delta_rot": [0.5234000086784363, 0.2232999950647354, 0.39590001106262207], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "magnitude": 0.1673}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", + "actions": [ + { + "reasoning_cot": "The left arm is maintaining a static hold on the bag's side handle to provide stability. Visual evidence shows the gripper is closed around the fabric loop/handle area, preventing the bag from sliding during the right arm's manipulation.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "side_handle" + }, + "spatial_logic": "static_at_side_handle", + "topology_change": false + }, + { + "reasoning_cot": "The right arm has moved from a hovering position to make direct contact with the zipper pull tab. The gripper is closing to secure the metal ring/tab, transitioning from approach to grasp to enable the subsequent unzipping action.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "touching" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "zipper_pull" + }, + "spatial_logic": "approaching_and_grasping_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_right_arm" + } + ], + "task_progress": "Right arm has successfully located and grasped the zipper pull; left arm maintains bag stability." + } +} +```` +--- +## 🎬 ChunkAnnotator_9 + +### 👁️ 视觉输入 +![chunkannotator_9_img_0.jpg](./images/chunkannotator_9_img_0.jpg) +![chunkannotator_9_img_1.jpg](./images/chunkannotator_9_img_1.jpg) +![chunkannotator_9_img_2.jpg](./images/chunkannotator_9_img_2.jpg) +![chunkannotator_9_img_3.jpg](./images/chunkannotator_9_img_3.jpg) +![chunkannotator_9_img_4.jpg](./images/chunkannotator_9_img_4.jpg) +![chunkannotator_9_img_5.jpg](./images/chunkannotator_9_img_5.jpg) +![chunkannotator_9_img_6.jpg](./images/chunkannotator_9_img_6.jpg) +![chunkannotator_9_img_7.jpg](./images/chunkannotator_9_img_7.jpg) +![chunkannotator_9_img_8.jpg](./images/chunkannotator_9_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:side_handle"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.03, "angle": 0.16, "vel_score": 0.25, "angle_score": 1.45, "vel_fft": [0.027, 0.022, 0.012, 0.005, 0.004, 0.007, 0.006, 0.002, 0.002, 0.003, 0.003, 0.002, 0.001, 0.002, 0.002, 0.002, 0.001, 0.003, 0.004, 0.003], "angle_fft": [0.156, 0.105, 0.053, 0.035, 0.035, 0.036, 0.034, 0.014, 0.005, 0.001, 0.004, 0.007, 0.007, 0.015, 0.011, 0.004, 0.009, 0.01, 0.006, 0.004]}, "right": {"vel": 0.05, "angle": 0.62, "vel_score": 0.46, "angle_score": 5.38, "vel_fft": [0.051, 0.031, 0.012, 0.008, 0.006, 0.003, 0.002, 0.003, 0.002, 0.001, 0.001, 0.004, 0.002, 0.001, 0.001, 0.002, 0.001, 0.001, 0.001, 0.003], "angle_fft": [0.622, 0.286, 0.128, 0.066, 0.006, 0.035, 0.031, 0.004, 0.025, 0.005, 0.01, 0.029, 0.015, 0.023, 0.017, 0.015, 0.014, 0.017, 0.004, 0.022]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.86, "left_arm_ry": 0.82, "left_arm_rz": 2.08, "left_gripper": 0.39, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.7, "right_arm_rz": -2.94, "right_gripper": 0.4}, "1": {"left_arm_vel": 0.001, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.72, "left_arm_rz": 2.04, "left_gripper": 0.39, "right_arm_vel": 0.001, "right_gripper_vel": 0.0, "right_arm_rx": 2.58, "right_arm_ry": 0.77, "right_arm_rz": -2.9, "right_gripper": 0.4}, "2": {"left_arm_vel": 0.004, "left_gripper_vel": 0.0, "left_arm_rx": -2.84, "left_arm_ry": 0.71, "left_arm_rz": 2.06, "left_gripper": 0.27, "right_arm_vel": 0.004, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.79, "right_arm_rz": -2.87, "right_gripper": 0.39}, "3": {"left_arm_vel": 0.019, "left_gripper_vel": 0.021, "left_arm_rx": -2.85, "left_arm_ry": 0.7, "left_arm_rz": 2.06, "left_gripper": 0.12, "right_arm_vel": 0.019, "right_gripper_vel": 0.021, "right_arm_rx": 2.64, "right_arm_ry": 0.8, "right_arm_rz": -2.82, "right_gripper": 0.39}, "4": {"left_arm_vel": 0.021, "left_gripper_vel": -0.021, "left_arm_rx": -2.85, "left_arm_ry": 0.7, "left_arm_rz": 2.06, "left_gripper": 0.05, "right_arm_vel": 0.021, "right_gripper_vel": -0.021, "right_arm_rx": 2.68, "right_arm_ry": 0.81, "right_arm_rz": -2.76, "right_gripper": 0.39}, "5": {"left_arm_vel": 0.153, "left_gripper_vel": 0.021, "left_arm_rx": -2.85, "left_arm_ry": 0.7, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.153, "right_gripper_vel": 0.021, "right_arm_rx": 2.79, "right_arm_ry": 0.82, "right_arm_rz": -2.57, "right_gripper": 0.39}, "6": {"left_arm_vel": 0.087, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.7, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.087, "right_gripper_vel": 0.0, "right_arm_rx": 2.96, "right_arm_ry": 0.79, "right_arm_rz": -2.43, "right_gripper": 0.39}, "7": {"left_arm_vel": 0.06, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.06, "right_gripper_vel": 0.0, "right_arm_rx": 3.01, "right_arm_ry": 0.82, "right_arm_rz": -2.4, "right_gripper": 0.39}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0024999999441206455, -0.007499999832361937, -0.029999999329447746], "delta_rot": [0.006599999964237213, -0.12290000170469284, -0.020500000566244125], "gripper_changed": true, "flow_direction": "-Z(Down)", "magnitude": 0.0311}, "right": {"delta_pos": [0.008100000210106373, 0.041600000113248825, -0.022299999371170998], "delta_rot": [0.460099995136261, 0.11429999768733978, 0.5461999773979187], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.0479}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.0015999999595806003, -0.01080000028014183, -0.029600000008940697], "delta_rot": [0.04699999839067459, -0.1454000025987625, 0.06849999725818634], "gripper_changed": true, "flow_direction": "-Z(Down)", "magnitude": 0.0315}, "right": {"delta_pos": [-0.06350000202655792, 0.05299999937415123, 0.00839999970048666], "delta_rot": [0.13179999589920044, -0.07859999686479568, 0.426800012588501], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left)", "magnitude": 0.0831}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by grasping the top-left corner, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", + "actions": [ + { + "reasoning_cot": "The left arm moves from a hovering position to make contact with the top-left corner of the bag. The gripper closes (delta_gripper negative) to secure this hold, providing stability for the upcoming manipulation by the right arm.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "top_left_corner" + }, + "spatial_logic": "moving from free space to bag:top_left_corner", + "topology_change": false + }, + { + "reasoning_cot": "The right arm approaches the side of the bag where the zipper pull is located. It aligns with the metal ring of the zipper pull and closes its gripper to secure it, preparing to unzip the bag.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "zipper_pull" + }, + "spatial_logic": "approaching and grasping bag:zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:top_left_corner", + "current_status": "grasped_by_left_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_right_arm" + } + ], + "task_progress": "Both arms have established stable grasps on the bag; left arm holds the body, right arm holds the zipper pull, ready for the unzipping action." + } +} +```` +--- +## 🎬 ChunkAnnotator_10 + +### 👁️ 视觉输入 +![chunkannotator_10_img_0.jpg](./images/chunkannotator_10_img_0.jpg) +![chunkannotator_10_img_1.jpg](./images/chunkannotator_10_img_1.jpg) +![chunkannotator_10_img_2.jpg](./images/chunkannotator_10_img_2.jpg) +![chunkannotator_10_img_3.jpg](./images/chunkannotator_10_img_3.jpg) +![chunkannotator_10_img_4.jpg](./images/chunkannotator_10_img_4.jpg) +![chunkannotator_10_img_5.jpg](./images/chunkannotator_10_img_5.jpg) +![chunkannotator_10_img_6.jpg](./images/chunkannotator_10_img_6.jpg) +![chunkannotator_10_img_7.jpg](./images/chunkannotator_10_img_7.jpg) +![chunkannotator_10_img_8.jpg](./images/chunkannotator_10_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}, {"anchor_id": "bag:top_left_corner", "current_status": "grasped_by_left_arm"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'bag:top_left_corner'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by grasping the top-left corner, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:top_left_corner"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.01, "angle": 0.09, "vel_score": 0.05, "angle_score": 0.84, "vel_fft": [0.006, 0.003, 0.001, 0.001, 0.001, 0.0, 0.0, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.001, 0.001, 0.0, 0.001, 0.001], "angle_fft": [0.091, 0.054, 0.035, 0.014, 0.006, 0.014, 0.012, 0.013, 0.01, 0.007, 0.007, 0.007, 0.007, 0.003, 0.001, 0.006, 0.003, 0.003, 0.005, 0.008]}, "right": {"vel": 0.11, "angle": 0.46, "vel_score": 0.91, "angle_score": 3.83, "vel_fft": [0.108, 0.034, 0.02, 0.008, 0.003, 0.005, 0.004, 0.005, 0.005, 0.004, 0.005, 0.004, 0.005, 0.006, 0.003, 0.003, 0.002, 0.003, 0.004, 0.005], "angle_fft": [0.457, 0.084, 0.137, 0.102, 0.041, 0.023, 0.05, 0.009, 0.023, 0.007, 0.02, 0.015, 0.041, 0.016, 0.035, 0.009, 0.032, 0.018, 0.014, 0.02]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.01, "right_arm_ry": 0.82, "right_arm_rz": -2.4, "right_gripper": 0.39}, "1": {"left_arm_vel": 0.084, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.084, "right_gripper_vel": 0.0, "right_arm_rx": 3.0, "right_arm_ry": 0.81, "right_arm_rz": -2.4, "right_gripper": 0.39}, "2": {"left_arm_vel": 0.06, "left_gripper_vel": -0.84, "left_arm_rx": -2.86, "left_arm_ry": 0.69, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.06, "right_gripper_vel": -0.84, "right_arm_rx": 3.02, "right_arm_ry": 0.83, "right_arm_rz": -2.38, "right_gripper": 0.35}, "3": {"left_arm_vel": 0.038, "left_gripper_vel": -1.953, "left_arm_rx": -2.86, "left_arm_ry": 0.69, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.038, "right_gripper_vel": -1.953, "right_arm_rx": 3.02, "right_arm_ry": 0.83, "right_arm_rz": -2.38, "right_gripper": 0.28}, "4": {"left_arm_vel": 0.029, "left_gripper_vel": -2.604, "left_arm_rx": -2.86, "left_arm_ry": 0.69, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.029, "right_gripper_vel": -2.604, "right_arm_rx": 3.03, "right_arm_ry": 0.83, "right_arm_rz": -2.37, "right_gripper": 0.1}, "5": {"left_arm_vel": 0.027, "left_gripper_vel": -0.861, "left_arm_rx": -2.86, "left_arm_ry": 0.69, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.027, "right_gripper_vel": -0.861, "right_arm_rx": 3.02, "right_arm_ry": 0.81, "right_arm_rz": -2.38, "right_gripper": 0.02}, "6": {"left_arm_vel": 0.048, "left_gripper_vel": -0.021, "left_arm_rx": -2.86, "left_arm_ry": 0.69, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.048, "right_gripper_vel": -0.021, "right_arm_rx": 2.94, "right_arm_ry": 0.75, "right_arm_rz": -2.45, "right_gripper": 0.01}, "7": {"left_arm_vel": 0.146, "left_gripper_vel": -0.021, "left_arm_rx": -2.86, "left_arm_ry": 0.69, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.146, "right_gripper_vel": -0.021, "right_arm_rx": 2.92, "right_arm_ry": 0.71, "right_arm_rz": -2.49, "right_gripper": 0.01}, "8": {"left_arm_vel": 0.21, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 2.06, "left_gripper": 0.04, "right_arm_vel": 0.21, "right_gripper_vel": 0.0, "right_arm_rx": 2.9, "right_arm_ry": 0.7, "right_arm_rz": -2.54, "right_gripper": 0.01}, "9": {"left_arm_vel": 0.201, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 2.07, "left_gripper": 0.04, "right_arm_vel": 0.201, "right_gripper_vel": 0.0, "right_arm_rx": 2.89, "right_arm_ry": 0.7, "right_arm_rz": -2.54, "right_gripper": 0.01}, "10": {"left_arm_vel": 0.165, "left_gripper_vel": 0.021, "left_arm_rx": -2.84, "left_arm_ry": 0.68, "left_arm_rz": 2.1, "left_gripper": 0.04, "right_arm_vel": 0.165, "right_gripper_vel": 0.021, "right_arm_rx": 2.84, "right_arm_ry": 0.7, "right_arm_rz": -2.53, "right_gripper": 0.01}, "11": {"left_arm_vel": 0.112, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.68, "left_arm_rz": 2.12, "left_gripper": 0.04, "right_arm_vel": 0.112, "right_gripper_vel": 0.0, "right_arm_rx": 2.77, "right_arm_ry": 0.67, "right_arm_rz": -2.54, "right_gripper": 0.01}, "12": {"left_arm_vel": 0.1, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.68, "left_arm_rz": 2.14, "left_gripper": 0.04, "right_arm_vel": 0.1, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.65, "right_arm_rz": -2.54, "right_gripper": 0.01}, "13": {"left_arm_vel": 0.188, "left_gripper_vel": 0.0, "left_arm_rx": -2.81, "left_arm_ry": 0.67, "left_arm_rz": 2.15, "left_gripper": 0.04, "right_arm_vel": 0.188, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.62, "right_arm_rz": -2.52, "right_gripper": 0.01}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.0008999999845400453, -0.0032999999821186066, 0.0005000000237487257], "delta_rot": [0.041200000792741776, -0.02199999988079071, 0.08969999849796295], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0035}, "right": {"delta_pos": [-0.0729999989271164, 0.01119999960064888, 0.031700000166893005], "delta_rot": [-0.3271999955177307, -0.19249999523162842, -0.11659999936819077], "gripper_changed": true, "flow_direction": "-X(Backward) and +Z(Up)", "magnitude": 0.0804}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.0017000000225380063, -0.006500000134110451, 0.007499999832361937], "delta_rot": [0.09019999951124191, -0.08969999849796295, 0.4018000066280365], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.01}, "right": {"delta_pos": [-0.10440000146627426, 0.13210000097751617, 0.050700001418590546], "delta_rot": [-0.2815000116825104, -0.20839999616146088, -0.17910000681877136], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1759}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Left arm stabilizes the bag by grasping the top-left corner, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", + "actions": [ + { + "reasoning_cot": "The left arm maintains a static position with gripper closed (0.04) throughout the sequence. Visual evidence confirms it is holding the top-left corner of the bag to provide stability against the forces applied by the right arm.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_left_corner" + }, + "spatial_logic": "static_at_top_left_corner", + "topology_change": false + }, + { + "reasoning_cot": "The right arm executes a significant approach trajectory (-X, +Z) towards the zipper mechanism. The gripper closes from open (0.39) to fully closed (0.01), visually confirming the transition from approaching to securing a grasp on the metal zipper pull ring.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving_from_free_space_to_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_right_arm" + } + ], + "task_progress": "Right arm has successfully acquired the zipper pull; left arm is stabilizing the bag body." + } +} +```` +--- +## 🎬 ChunkAnnotator_11 + +### 👁️ 视觉输入 +![chunkannotator_11_img_0.jpg](./images/chunkannotator_11_img_0.jpg) +![chunkannotator_11_img_1.jpg](./images/chunkannotator_11_img_1.jpg) +![chunkannotator_11_img_2.jpg](./images/chunkannotator_11_img_2.jpg) +![chunkannotator_11_img_3.jpg](./images/chunkannotator_11_img_3.jpg) +![chunkannotator_11_img_4.jpg](./images/chunkannotator_11_img_4.jpg) +![chunkannotator_11_img_5.jpg](./images/chunkannotator_11_img_5.jpg) +![chunkannotator_11_img_6.jpg](./images/chunkannotator_11_img_6.jpg) +![chunkannotator_11_img_7.jpg](./images/chunkannotator_11_img_7.jpg) +![chunkannotator_11_img_8.jpg](./images/chunkannotator_11_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}, {"anchor_id": "bag:top_left_corner", "current_status": "grasped_by_left_arm"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'bag:top_left_corner'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag by grasping the top-left corner, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_left_corner"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.02, "angle": 0.33, "vel_score": 0.19, "angle_score": 3.27, "vel_fft": [0.02, 0.007, 0.004, 0.007, 0.0, 0.002, 0.002, 0.001, 0.001, 0.0, 0.0, 0.001, 0.001, 0.001, 0.002, 0.001, 0.002, 0.001, 0.0, 0.002], "angle_fft": [0.331, 0.183, 0.088, 0.053, 0.027, 0.016, 0.036, 0.032, 0.022, 0.005, 0.022, 0.011, 0.013, 0.021, 0.015, 0.012, 0.007, 0.009, 0.005, 0.005]}, "right": {"vel": 0.13, "angle": 0.48, "vel_score": 1.26, "angle_score": 4.18, "vel_fft": [0.135, 0.025, 0.043, 0.045, 0.028, 0.002, 0.011, 0.006, 0.005, 0.006, 0.004, 0.002, 0.004, 0.007, 0.006, 0.008, 0.005, 0.003, 0.004, 0.006], "angle_fft": [0.478, 0.056, 0.053, 0.078, 0.07, 0.043, 0.044, 0.02, 0.026, 0.032, 0.014, 0.014, 0.021, 0.023, 0.003, 0.022, 0.011, 0.009, 0.027, 0.026]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.81, "left_arm_ry": 0.67, "left_arm_rz": 2.15, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.62, "right_arm_rz": -2.49, "right_gripper": 0.01}, "1": {"left_arm_vel": 0.246, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.65, "left_arm_rz": 2.16, "left_gripper": 0.04, "right_arm_vel": 0.246, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.64, "right_arm_rz": -2.42, "right_gripper": 0.01}, "2": {"left_arm_vel": 0.018, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.62, "left_arm_rz": 2.12, "left_gripper": 0.04, "right_arm_vel": 0.018, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.68, "right_arm_rz": -2.49, "right_gripper": 0.01}, "3": {"left_arm_vel": 0.115, "left_gripper_vel": 0.0, "left_arm_rx": -2.77, "left_arm_ry": 0.6, "left_arm_rz": 2.3, "left_gripper": 0.04, "right_arm_vel": 0.115, "right_gripper_vel": 0.0, "right_arm_rx": 2.73, "right_arm_ry": 0.59, "right_arm_rz": -2.55, "right_gripper": 0.01}, "4": {"left_arm_vel": 0.187, "left_gripper_vel": 0.0, "left_arm_rx": -2.77, "left_arm_ry": 0.61, "left_arm_rz": 2.39, "left_gripper": 0.04, "right_arm_vel": 0.187, "right_gripper_vel": 0.0, "right_arm_rx": 2.77, "right_arm_ry": 0.54, "right_arm_rz": -2.58, "right_gripper": 0.01}, "5": {"left_arm_vel": 0.206, "left_gripper_vel": 0.0, "left_arm_rx": -2.75, "left_arm_ry": 0.62, "left_arm_rz": 2.48, "left_gripper": 0.04, "right_arm_vel": 0.206, "right_gripper_vel": 0.0, "right_arm_rx": 2.77, "right_arm_ry": 0.59, "right_arm_rz": -2.61, "right_gripper": 0.01}, "6": {"left_arm_vel": 0.026, "left_gripper_vel": 0.399, "left_arm_rx": -2.76, "left_arm_ry": 0.6, "left_arm_rz": 2.46, "left_gripper": 0.04, "right_arm_vel": 0.026, "right_gripper_vel": 0.399, "right_arm_rx": 2.75, "right_arm_ry": 0.63, "right_arm_rz": -2.57, "right_gripper": 0.03}, "7": {"left_arm_vel": 0.028, "left_gripper_vel": 1.071, "left_arm_rx": -2.76, "left_arm_ry": 0.6, "left_arm_rz": 2.46, "left_gripper": 0.04, "right_arm_vel": 0.028, "right_gripper_vel": 1.071, "right_arm_rx": 2.73, "right_arm_ry": 0.61, "right_arm_rz": -2.58, "right_gripper": 0.06}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0024999999441206455, -0.003100000089034438, 0.007000000216066837], "delta_rot": [0.045499999076128006, -0.0658000037074089, 0.30630001425743103], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0081}, "right": {"delta_pos": [-0.026799999177455902, 0.1128000020980835, 0.019099999219179153], "delta_rot": [0.05009999871253967, -0.007699999958276749, -0.08590000122785568], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left)", "magnitude": 0.1175}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.4499000012874603, 0.2770000100135803, 0.10689999908208847], "delta_rot": [-0.15960000455379486, 0.5077000260353088, 0.7328000068664551], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.539}, "right": {"delta_pos": [-0.26409998536109924, -0.12099999934434891, 0.0957999974489212], "delta_rot": [0.27649998664855957, 0.16040000319480896, -0.26409998536109924], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.3058}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Right arm executes a pulling motion on the zipper pull to open the bag, while the left arm maintains a stabilizing hold on the bag's top-left corner.", + "actions": [ + { + "reasoning_cot": "The right arm is visually confirmed to be grasping the metal zipper pull. The kinematic data shows a significant velocity (0.13) and displacement (-X, +Y), indicating an active pulling motion away from the initial position to slide the zipper open. This is a topology-changing action as it alters the state of the bag's opening.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "pull", + "semantic_action": "unzip_bag", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving from static_grasp to pulling_along_zipper_track", + "topology_change": true + }, + { + "reasoning_cot": "The left arm remains in contact with the silver mesh/corner area of the bag. Kinematic data shows near-zero velocity (0.02) and minimal displacement, confirming its role is purely stabilization to counteract the force applied by the right arm. No topology change is induced by this arm.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_left_corner" + }, + "spatial_logic": "static_stabilization_at_anchor", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_track", + "current_status": "partially_opened" + } + ], + "task_progress": "Executing the unzipping sequence; right arm pulling zipper while left arm stabilizes." + } +} +```` +--- +## 🎬 ChunkAnnotator_12 + +### 👁️ 视觉输入 +![chunkannotator_12_img_0.jpg](./images/chunkannotator_12_img_0.jpg) +![chunkannotator_12_img_1.jpg](./images/chunkannotator_12_img_1.jpg) +![chunkannotator_12_img_2.jpg](./images/chunkannotator_12_img_2.jpg) +![chunkannotator_12_img_3.jpg](./images/chunkannotator_12_img_3.jpg) +![chunkannotator_12_img_4.jpg](./images/chunkannotator_12_img_4.jpg) +![chunkannotator_12_img_5.jpg](./images/chunkannotator_12_img_5.jpg) +![chunkannotator_12_img_6.jpg](./images/chunkannotator_12_img_6.jpg) +![chunkannotator_12_img_7.jpg](./images/chunkannotator_12_img_7.jpg) +![chunkannotator_12_img_8.jpg](./images/chunkannotator_12_img_8.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 5 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Image 5: [T2 (Next Start)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}, {"anchor_id": "bag:top_left_corner", "current_status": "grasped_by_left_arm"}, {"anchor_id": "bag:zipper_track", "current_status": "partially_opened"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'bag:top_left_corner', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm executes a pulling motion on the zipper pull to open the bag, while the left arm maintains a stabilizing hold on the bag's top-left corner.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_left_corner"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.46, "angle": 0.8, "vel_score": 4.0, "angle_score": 6.65, "vel_fft": [0.461, 0.17, 0.019, 0.018, 0.014, 0.009, 0.011, 0.015, 0.007, 0.005, 0.012, 0.021, 0.009, 0.008, 0.003, 0.006, 0.005, 0.009, 0.008, 0.004], "angle_fft": [0.797, 0.228, 0.035, 0.073, 0.061, 0.016, 0.066, 0.084, 0.056, 0.009, 0.036, 0.049, 0.025, 0.014, 0.012, 0.02, 0.024, 0.028, 0.016, 0.01]}, "right": {"vel": 0.29, "angle": 0.63, "vel_score": 2.41, "angle_score": 5.12, "vel_fft": [0.288, 0.062, 0.029, 0.019, 0.005, 0.003, 0.008, 0.006, 0.001, 0.003, 0.006, 0.009, 0.006, 0.008, 0.003, 0.006, 0.007, 0.006, 0.005, 0.005], "angle_fft": [0.628, 0.118, 0.045, 0.014, 0.004, 0.07, 0.023, 0.047, 0.039, 0.018, 0.04, 0.005, 0.047, 0.041, 0.027, 0.038, 0.034, 0.016, 0.024, 0.032]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.76, "left_arm_ry": 0.61, "left_arm_rz": 2.46, "left_gripper": 0.05, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.71, "right_arm_ry": 0.58, "right_arm_rz": -2.59, "right_gripper": 0.12}, "1": {"left_arm_vel": 0.134, "left_gripper_vel": 2.268, "left_arm_rx": -2.77, "left_arm_ry": 0.62, "left_arm_rz": 2.48, "left_gripper": 0.13, "right_arm_vel": 0.134, "right_gripper_vel": 2.268, "right_arm_rx": 2.67, "right_arm_ry": 0.52, "right_arm_rz": -2.6, "right_gripper": 0.28}, "2": {"left_arm_vel": 0.167, "left_gripper_vel": 2.478, "left_arm_rx": -2.77, "left_arm_ry": 0.63, "left_arm_rz": 2.49, "left_gripper": 0.19, "right_arm_vel": 0.167, "right_gripper_vel": 2.478, "right_arm_rx": 2.67, "right_arm_ry": 0.49, "right_arm_rz": -2.61, "right_gripper": 0.37}, "3": {"left_arm_vel": 0.232, "left_gripper_vel": 1.638, "left_arm_rx": -2.76, "left_arm_ry": 0.64, "left_arm_rz": 2.5, "left_gripper": 0.23, "right_arm_vel": 0.232, "right_gripper_vel": 1.638, "right_arm_rx": 2.67, "right_arm_ry": 0.46, "right_arm_rz": -2.61, "right_gripper": 0.42}, "4": {"left_arm_vel": 0.272, "left_gripper_vel": 0.756, "left_arm_rx": -2.76, "left_arm_ry": 0.65, "left_arm_rz": 2.52, "left_gripper": 0.27, "right_arm_vel": 0.272, "right_gripper_vel": 0.756, "right_arm_rx": 2.69, "right_arm_ry": 0.45, "right_arm_rz": -2.61, "right_gripper": 0.45}, "5": {"left_arm_vel": 0.356, "left_gripper_vel": 0.231, "left_arm_rx": -2.74, "left_arm_ry": 0.66, "left_arm_rz": 2.56, "left_gripper": 0.29, "right_arm_vel": 0.356, "right_gripper_vel": 0.231, "right_arm_rx": 2.73, "right_arm_ry": 0.43, "right_arm_rz": -2.64, "right_gripper": 0.47}, "6": {"left_arm_vel": 0.442, "left_gripper_vel": 0.021, "left_arm_rx": -2.73, "left_arm_ry": 0.68, "left_arm_rz": 2.6, "left_gripper": 0.27, "right_arm_vel": 0.442, "right_gripper_vel": 0.021, "right_arm_rx": 2.79, "right_arm_ry": 0.47, "right_arm_rz": -2.7, "right_gripper": 0.48}, "7": {"left_arm_vel": 0.343, "left_gripper_vel": 0.0, "left_arm_rx": -2.74, "left_arm_ry": 0.73, "left_arm_rz": 2.64, "left_gripper": 0.27, "right_arm_vel": 0.343, "right_gripper_vel": 0.0, "right_arm_rx": 2.81, "right_arm_ry": 0.52, "right_arm_rz": -2.74, "right_gripper": 0.48}, "8": {"left_arm_vel": 0.383, "left_gripper_vel": 0.0, "left_arm_rx": -2.77, "left_arm_ry": 0.83, "left_arm_rz": 2.72, "left_gripper": 0.27, "right_arm_vel": 0.383, "right_gripper_vel": 0.0, "right_arm_rx": 2.86, "right_arm_ry": 0.51, "right_arm_rz": -2.72, "right_gripper": 0.48}, "9": {"left_arm_vel": 0.382, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.92, "left_arm_rz": 2.8, "left_gripper": 0.27, "right_arm_vel": 0.382, "right_gripper_vel": 0.0, "right_arm_rx": 2.87, "right_arm_ry": 0.51, "right_arm_rz": -2.7, "right_gripper": 0.48}, "10": {"left_arm_vel": 0.293, "left_gripper_vel": 0.0, "left_arm_rx": -2.78, "left_arm_ry": 1.03, "left_arm_rz": 2.91, "left_gripper": 0.27, "right_arm_vel": 0.293, "right_gripper_vel": 0.0, "right_arm_rx": 2.85, "right_arm_ry": 0.57, "right_arm_rz": -2.75, "right_gripper": 0.48}, "11": {"left_arm_vel": 0.221, "left_gripper_vel": 0.0, "left_arm_rx": -2.93, "left_arm_ry": 1.03, "left_arm_rz": 2.87, "left_gripper": 0.28, "right_arm_vel": 0.221, "right_gripper_vel": 0.0, "right_arm_rx": 2.87, "right_arm_ry": 0.65, "right_arm_rz": -2.77, "right_gripper": 0.48}, "12": {"left_arm_vel": 0.186, "left_gripper_vel": 0.0, "left_arm_rx": -2.99, "left_arm_ry": 1.09, "left_arm_rz": 2.86, "left_gripper": 0.33, "right_arm_vel": 0.186, "right_gripper_vel": 0.0, "right_arm_rx": 2.92, "right_arm_ry": 0.71, "right_arm_rz": -2.76, "right_gripper": 0.48}, "13": {"left_arm_vel": 0.16, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 1.18, "left_arm_rz": 2.89, "left_gripper": 0.36, "right_arm_vel": 0.16, "right_gripper_vel": 0.0, "right_arm_rx": 2.96, "right_arm_ry": 0.78, "right_arm_rz": -2.76, "right_gripper": 0.48}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.453000009059906, 0.27970001101493835, 0.09989999979734421], "delta_rot": [-0.20399999618530273, 0.5720000267028809, 0.4228000044822693], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.5417}, "right": {"delta_pos": [-0.23680000007152557, -0.23240000009536743, 0.07649999856948853], "delta_rot": [0.24580000340938568, 0.19429999589920044, -0.16769999265670776], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.3405}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.4223000109195709, 0.25450000166893005, 0.0551999993622303], "delta_rot": [-0.19939999282360077, 0.5365999937057495, -5.474899768829346], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.4961}, "right": {"delta_pos": [-0.26429998874664307, -0.25360000133514404, 0.07240000367164612], "delta_rot": [0.29269999265670776, 0.5263000130653381, 5.56879997253418], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.3734}} + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Right arm releases the bag's zipper pull and retreats to a neutral position, while the left arm maintains a stabilizing hold on the bag's top-left corner.", + "actions": [ + { + "reasoning_cot": "The right arm gripper is observed opening (gripper width increases from ~0.12 to ~0.48) and the arm moves backward and upward away from the bag. Visual evidence in frames T1-T2 confirms the gripper jaws separate from the zipper pull, indicating a release action followed by a retreat.", + "causal_trace": { + "gripper_signal": "opening", + "visual_contact": "none" + }, + "action_verb": "release", + "semantic_action": "release_and_retreat", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving from bag:zipper_pull to free_space", + "topology_change": false + }, + { + "reasoning_cot": "The left arm remains in contact with the top-left corner of the bag throughout the sequence. While there is minor positional adjustment (delta_pos indicates slight movement), the primary function is maintaining stability while the right arm operates. The gripper state is stable/closed around the fabric.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": "stabilize", + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_left_corner" + }, + "spatial_logic": "static_at_bag:top_left_corner", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "released_by_right_arm" + } + ], + "task_progress": "Right arm has completed the pulling motion on the zipper and released the handle; left arm continues to stabilize the bag." + } +} +```` +--- +## 🎬 ChunkAnnotator_13 + +### 👁️ 视觉输入 +![chunkannotator_13_img_0.jpg](./images/chunkannotator_13_img_0.jpg) +![chunkannotator_13_img_1.jpg](./images/chunkannotator_13_img_1.jpg) +![chunkannotator_13_img_2.jpg](./images/chunkannotator_13_img_2.jpg) +![chunkannotator_13_img_3.jpg](./images/chunkannotator_13_img_3.jpg) +![chunkannotator_13_img_4.jpg](./images/chunkannotator_13_img_4.jpg) +![chunkannotator_13_img_5.jpg](./images/chunkannotator_13_img_5.jpg) +![chunkannotator_13_img_6.jpg](./images/chunkannotator_13_img_6.jpg) +![chunkannotator_13_img_7.jpg](./images/chunkannotator_13_img_7.jpg) + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are the robot's "Inner Monologue", acting as a highly capable visual-semantic grounder. + Analyze the spatial logic, visual sequence, and physical outcomes to output a highly structured JSON. + + [GLOBAL TASK]: Unknown Task + ========================================= + 👀 [VISUAL INPUT STRUCTURE] (CRITICAL) + ========================================= + You are provided with a sequence of discrete, high-resolution images in chronological order. + + 1. THE FIRST 4 IMAGES form the "Macro Context Timeline": + - Image 1: [T_base (Scene)] + - Image 2: [T-1 (Prev End)] + - Image 3: [T0 (Curr Start)] + - Image 4: [T1 (Curr End)] + - Use these heavily for Textureless/Black objects. Compare [T0] to [T1] to track the "flow" of the black mass, and use [T_base] to confirm if the arm has crossed into a new topological zone (e.g., from left to right side). + + 2. THE SUBSEQUENT IMAGES are intra-chunk sequential samples (Micro Execution). + - These show the exact continuous movement between [T0] and [T1]. + - Use these to determine the precise moment of gripper state changes (e.g., exact contact point for 'grasp', or release point for 'drop') and the fine-grained trajectory path. + ========================================= + 🧠 [COGNITIVE MEMORY (L1 Semantic State & Context)] + ========================================= + 1. SPATIAL ATLAS (Your known topological zones): + [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "released_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}, {"anchor_id": "bag:top_left_corner", "current_status": "grasped_by_left_arm"}, {"anchor_id": "bag:zipper_track", "current_status": "partially_opened"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['table:surface_center', 'bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'bag:top_left_corner', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm releases the bag's zipper pull and retreats to a neutral position, while the left arm maintains a stabilizing hold on the bag's top-left corner.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_left_corner"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}} + ⚠️ CONTEXT RULE: If your 'left_end_effector' grasp_status was "holding" a "cup" in the last chunk, and in THIS chunk the gripper opens, you are "releasing/placing", NOT "approaching". Use this memory to resolve visual ambiguities. + ⚠️ BEWARE OF TARGET SHIFT (Visual Override): Do not blindly inherit the 'contact_target' from memory! If the robot recently performed a 'retreat' or 'hover', it is almost certainly shifting to a NEW part of the object. ALWAYS trust your current visual evidence over the memory text. If the gripper is visually over the 'right_sleeve', output 'right_sleeve' immediately. + ========================================= + 🛡️ [L0 PHYSICAL GROUND TRUTH] + ========================================= + [KINEMATIC STATISTICS]: + {"left": {"vel": 0.03, "angle": 2.95, "vel_score": 0.46, "angle_score": 4.43, "vel_fft": [0.028, 0.022, 0.019, 0.015, 0.012, 0.013, 0.011, 0.01, 0.006, 0.002, 0.002, 0.002, 0.002, 0.001, 0.002, 0.003, 0.004, 0.003, 0.002, 0.001], "angle_fft": [2.954, 2.769, 2.803, 2.797, 2.721, 2.7, 2.657, 2.678, 2.647, 2.641, 2.668, 2.659, 2.639, 2.668, 2.641, 2.669, 2.618, 2.677, 2.645, 2.645]}, "right": {"vel": 0.02, "angle": 3.03, "vel_score": 0.33, "angle_score": 5.52, "vel_fft": [0.019, 0.016, 0.015, 0.012, 0.008, 0.006, 0.004, 0.003, 0.003, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.001, 0.001], "angle_fft": [3.027, 2.765, 2.863, 2.824, 2.697, 2.734, 2.642, 2.658, 2.629, 2.635, 2.634, 2.662, 2.624, 2.66, 2.643, 2.653, 2.633, 2.659, 2.648, 2.649]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.98, "left_arm_ry": 1.17, "left_arm_rz": 2.88, "left_gripper": 0.36, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.96, "right_arm_ry": 0.81, "right_arm_rz": -2.76, "right_gripper": 0.48}, "1": {"left_arm_vel": 0.14, "left_gripper_vel": -0.063, "left_arm_rx": -3.01, "left_arm_ry": 1.14, "left_arm_rz": 2.86, "left_gripper": 0.37, "right_arm_vel": 0.14, "right_gripper_vel": -0.063, "right_arm_rx": 2.95, "right_arm_ry": 0.86, "right_arm_rz": -2.77, "right_gripper": 0.47}, "2": {"left_arm_vel": 0.139, "left_gripper_vel": -0.189, "left_arm_rx": -2.98, "left_arm_ry": 1.15, "left_arm_rz": 2.87, "left_gripper": 0.37, "right_arm_vel": 0.139, "right_gripper_vel": -0.189, "right_arm_rx": 2.95, "right_arm_ry": 0.95, "right_arm_rz": -2.77, "right_gripper": 0.46}, "3": {"left_arm_vel": 0.107, "left_gripper_vel": -0.315, "left_arm_rx": -2.94, "left_arm_ry": 1.16, "left_arm_rz": 2.9, "left_gripper": 0.37, "right_arm_vel": 0.107, "right_gripper_vel": -0.315, "right_arm_rx": 2.95, "right_arm_ry": 1.02, "right_arm_rz": -2.79, "right_gripper": 0.44}, "4": {"left_arm_vel": 0.054, "left_gripper_vel": -0.357, "left_arm_rx": -2.94, "left_arm_ry": 1.17, "left_arm_rz": 2.88, "left_gripper": 0.37, "right_arm_vel": 0.054, "right_gripper_vel": -0.357, "right_arm_rx": 2.95, "right_arm_ry": 1.07, "right_arm_rz": -2.79, "right_gripper": 0.42}, "5": {"left_arm_vel": 0.054, "left_gripper_vel": -0.168, "left_arm_rx": -2.94, "left_arm_ry": 1.18, "left_arm_rz": 2.86, "left_gripper": 0.37, "right_arm_vel": 0.054, "right_gripper_vel": -0.168, "right_arm_rx": 2.97, "right_arm_ry": 1.09, "right_arm_rz": -2.78, "right_gripper": 0.41}, "6": {"left_arm_vel": 0.009, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 1.14, "left_arm_rz": 3.07, "left_gripper": 0.37, "right_arm_vel": 0.009, "right_gripper_vel": 0.0, "right_arm_rx": 3.0, "right_arm_ry": 1.11, "right_arm_rz": -3.06, "right_gripper": 0.4}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 1.14, "left_arm_rz": -3.01, "left_gripper": 0.37, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.0, "right_arm_ry": 1.11, "right_arm_rz": 2.98, "right_gripper": 0.39}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.031099999323487282, -0.026100000366568565, -0.03880000114440918], "delta_rot": [0.020400000736117363, -0.03009999915957451, -5.888599872589111], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.0562}, "right": {"delta_pos": [-0.02370000071823597, -0.017999999225139618, -0.004000000189989805], "delta_rot": [0.042399998754262924, 0.30250000953674316, 5.737400054931641], "gripper_changed": false, "flow_direction": "-X(Backward)", "magnitude": 0.03}} + + [FUTURE HINDSIGHT HINT]: + "End of Trajectory" + + ========================================= + [STRICT INSTRUCTIONS] + ========================================= + 1. ZERO-TRUST ANCHOR EVALUATION (ANTI-LAZINESS - CRITICAL): + - DO NOT lazily inherit the `CURRENT ACTIVE ZONES` or `SHORT-TERM MEMORY`. Treat the STM as a *historical reference*, NOT the current truth. + - For EVERY chunk, you MUST independently scan the visual frames to verify the end-effector's exact location against the `KNOWN ANCHOR CANDIDATES`. + - If the robot is manipulating an extremity of the clothing (e.g., grasping to fold), you MUST select the highly specific `anchor_id` (e.g., 'left_sleeve', 'right_sleeve', 'collar'). + - PROHIBITED: You are strictly FORBIDDEN from defaulting to 'front_panel' or 'jacket' if the visual evidence clearly shows interaction with the sleeves, collar, or hem. + + 2. KINEMATIC-TRIGGERED TOPOLOGY SHIFTS: + - Use the [KINEMATIC STATISTICS] as an attention trigger. If the arms show significant spatial displacement (e.g., large delta in X/Y plane) followed by a `gripper_changed` event, this is a mathematically guaranteed shift to a NEW semantic anchor. + - Your `reasoning_cot` MUST explicitly state: "Moving from [Old Anchor] to [New Anchor] because..." + + 3. VISUAL AUTHORITY & FLEXIBLE INTERACTION: + - You have the final say on contact. If touching a deformable object, actions like "drag" or "fold_over" are valid even if the gripper is not fully closed. + - NO HALLUCINATION: If `hindsight_flow` is zero, `topology_change` MUST be false. + + 4. SEMANTIC DELTA & DYNAMIC DISCOVERY (CRITICAL): + - If the robot's action creates a new topological feature (e.g., 'new_folded_crease'), use it as your `interaction_target.anchor_id`. + - You MUST simultaneously register this new anchor in `semantic_delta.anchor_updates`: `[{ "anchor_id": "new_folded_crease", "current_status": "just_created" }]`. + - Set `topology_change: true` whenever structure changes or new anchors are created. + 5. INDEPENDENT ARM EVALUATION (CRITICAL): + - The `subject` MUST strictly be either "left_arm" or "right_arm". You are FORBIDDEN from using "both_arms". + - Cross-reference the [VISUAL INPUT ALIGNMENT] watermarks with the [HINDSIGHT ACHIEVED FLOW] independently for each arm. + - Output TWO separate action objects in the `actions` list for EVERY chunk. + - If one arm is moving and the other is not, the stationary arm should be marked as `action_verb: "idle"` with `visual_contact: "none"` (or "touching" if resting on an object). + - Example: + [{ + "subject": "right_arm", + "action_verb": "fold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "left_sleeve"} + }, + { + "subject": "left_arm", + "action_verb": "hold", + "interaction_target": {"parent_object": "jacket", "anchor_id": "collar"} + }] + + 6. OVERCOMING SCHEMA LIMITATIONS (DUAL-VERB ESCAPE HATCH - CRITICAL): + - If the robot is performing a complex or continuous interaction (like pouring, wiping, unscrewing) that is NOT in the rigid `action_verb` list, you MUST: + a) Select the closest physical primitive (e.g., 'hold', 'hover', 'reach') for the `action_verb` field. + b) Output the TRUE continuous semantic meaning in the `semantic_action` field (e.g., 'pour', 'wipe'). + 7. SENSOR CONFLICT RESOLUTION (STRUCTURAL OBSERVATION > QUANTITATIVE DATA): + - Quantitative metrics (delta/velocity/signals) can sometimes average out to near-zero over time or suffer from sensor desync/noise. + - If the Temporal Comparison (T0 vs T1) shows a CLEAR MORPHOLOGICAL OR TOPOLOGICAL CHANGE, this OBSERVATIONAL EVIDENCE STRICTLY OVERRIDES low numeric deltas. + - DO NOT default to 'static', 'idle', or 'no-change' if you can observe the subject's state or geometry actively evolving. Trust the observed evolution over the 0.0 metrics. + Output ONLY valid JSON strictly following the schema below. + ```json + { + "$defs": { + "ActionAnnotation": { + "properties": { + "reasoning_cot": { + "description": "Brief reasoning combining spatial_logic (trajectory) and visual evidence.", + "title": "Reasoning Cot", + "type": "string" + }, + "causal_trace": { + "$ref": "#/$defs/CausalTrace" + }, + "action_verb": { + "description": "Micro-action verb. Must be exactly one of: ['reach', 'approach', 'retreat', 'idle', 'hover', 'hold', 'touch', 'press', 'smooth', 'grasp', 'release', 'pick', 'place', 'fold', 'fold_over', 'pinch', 'drag', 'pull', 'push']", + "title": "Action Verb", + "type": "string" + }, + "semantic_action": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The open-vocabulary, continuous human-semantic action (e.g., 'pour', 'lift', 'wipe', 'unscrew'). Use this if action_verb is too restrictive.", + "title": "Semantic Action" + }, + "subject": { + "description": "Executing agent. MUST be evaluated independently.", + "enum": [ + "left_arm", + "right_arm" + ], + "title": "Subject", + "type": "string" + }, + "interaction_target": { + "anyOf": [ + { + "$ref": "#/$defs/InteractionEntity" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The object and anchor being acted upon. None if moving in free space." + }, + "spatial_logic": { + "description": "Topological movement, e.g., 'moving from hem to collar' or 'static_at_handle'", + "title": "Spatial Logic", + "type": "string" + }, + "topology_change": { + "default": false, + "description": "True ONLY IF this action structurally altered the object (e.g., folded, opened)", + "title": "Topology Change", + "type": "boolean" + } + }, + "required": [ + "reasoning_cot", + "causal_trace", + "action_verb", + "subject", + "spatial_logic" + ], + "title": "ActionAnnotation", + "type": "object" + }, + "CausalTrace": { + "description": "\u57fa\u4e8e\u89c6\u89c9-\u62d3\u6251\u7684\u56e0\u679c\u8ffd\u8e2a (\u66ff\u6362\u6b7b\u677f\u7684\u7269\u7406\u53d7\u529b\u53cd\u9988)", + "properties": { + "gripper_signal": { + "description": "Hardware intent from robot sensors", + "enum": [ + "opening", + "closing", + "stable" + ], + "title": "Gripper Signal", + "type": "string" + }, + "visual_contact": { + "description": "VLM's visual confirmation of contact. 'touching' is sufficient for soft-body interactions.", + "enum": [ + "none", + "touching", + "secured" + ], + "title": "Visual Contact", + "type": "string" + } + }, + "required": [ + "gripper_signal", + "visual_contact" + ], + "title": "CausalTrace", + "type": "object" + }, + "InteractionEntity": { + "properties": { + "parent_object": { + "description": "The macro object, e.g., 'jacket_01'", + "title": "Parent Object", + "type": "string" + }, + "anchor_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The specific semantic zone, e.g., 'left_sleeve'. Can be None for global moves.", + "title": "Anchor Id" + } + }, + "required": [ + "parent_object" + ], + "title": "InteractionEntity", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "SemanticStateDelta": { + "description": "\u8bb0\u5f55\u5c40\u90e8 Chunk \u9020\u6210\u7684 L1 \u5c42\u8bed\u4e49\u589e\u91cf", + "properties": { + "anchor_updates": { + "description": "Update the status of semantic zones if they changed (e.g., sleeve became 'folded')", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Anchor Updates", + "type": "array" + }, + "task_progress": { + "description": "Short summary of current subtask intent.", + "title": "Task Progress", + "type": "string" + } + }, + "required": [ + "task_progress" + ], + "title": "SemanticStateDelta", + "type": "object" + } + }, + "properties": { + "chunk_intent": { + "description": "Immediate physical intent, referencing semantic anchors.", + "title": "Chunk Intent", + "type": "string" + }, + "actions": { + "items": { + "$ref": "#/$defs/ActionAnnotation" + }, + "title": "Actions", + "type": "array" + }, + "semantic_delta": { + "$ref": "#/$defs/SemanticStateDelta" + } + }, + "required": [ + "chunk_intent", + "actions", + "semantic_delta" + ], + "title": "ChunkAnnotation", + "type": "object" +} + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "chunk_intent": "Both arms maintain a static, idle state in free space above the table surface. The left arm hovers near the bag while the right arm remains retracted over the floor area; no physical interaction or topological change occurs.", + "actions": [ + { + "reasoning_cot": "The left arm is positioned directly above the white bag but maintains a consistent vertical gap throughout the sequence. Kinematic data shows negligible velocity (0.03 m/s) and zero gripper change. Visually, the gripper jaws are open and not contacting the object. This is a 'hover' state, likely waiting for the next instruction or stabilizing before an approach.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "hover", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "main_body" + }, + "spatial_logic": "static_hover_above_bag", + "topology_change": false + }, + { + "reasoning_cot": "The right arm is located in the bottom-right quadrant of the workspace, visually distinct from the bag (which is on the left/center). The camera view shows the floor/carpet below, indicating the arm is retracted or hovering over the edge. There is no movement towards the bag or any other object. It remains completely idle in free space.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": null, + "spatial_logic": "static_in_free_space_right_zone", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Arms are in a holding pattern; left arm is pre-positioned near the bag, right arm is retracted. No manipulation has occurred in this chunk." + } +} +```` +--- +## 🎬 SubtaskAnnotator_0 + +### 🧠 组装 Prompt +
👉 点击展开 + +````text +You are an expert human observer curating Embodied AI datasets. + Your goal is to synthesize a timeline of low-level robotic micro-actions into a highly logical, human-readable hierarchy of "Macro Chapters" (Subtasks). + + ### 0. GLOBAL CONTEXT + - **Video ID**: video_0008 + - **Total Frames**: 521 + - **Global Task Goal**: "Unknown Task" + + ### 1. INPUT DATA + - **KPM (Micro-Actions Timeline)**: [{"chunk_idx": 0, "start_frame": 0, "end_frame": 43, "chunk_intent": "Hovering and stabilizing position above the table surface near the bag, preparing for interaction.", "micro_actions": [{"verb": "hover", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_hover_left_of_bag"}, {"verb": "hover", "semantic_verb": null, "subject": "right_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "drifting_forward_right_zone"}]}, {"chunk_idx": 1, "start_frame": 44, "end_frame": 79, "chunk_intent": "Approaching the bag from a distance to establish contact with the top surface/zipper area.", "micro_actions": [{"verb": "approach", "semantic_verb": null, "subject": "left_arm", "target": "bag:side_handle", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "moving from table:surface_center approach vector to bag:side_handle proximity"}, {"verb": "approach", "semantic_verb": null, "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "moving from table:surface_center approach vector to bag:main_body proximity"}]}, {"chunk_idx": 2, "start_frame": 80, "end_frame": 90, "chunk_intent": "Approaching the bag to establish contact with the top surface/zipper area.", "micro_actions": [{"verb": "approach", "semantic_verb": null, "subject": "left_arm", "target": "side_handle", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "moving from free_space to bag:side_handle"}, {"verb": "approach", "semantic_verb": null, "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "moving from free_space to bag:main_body"}]}, {"chunk_idx": 3, "start_frame": 91, "end_frame": 112, "chunk_intent": "Approaching the bag to establish contact with the top surface/zipper area.", "micro_actions": [{"verb": "approach", "semantic_verb": null, "subject": "left_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving from free space to bag:zipper_pull"}, {"verb": "idle", "semantic_verb": null, "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "hovering over bag:main_body"}]}, {"chunk_idx": 4, "start_frame": 113, "end_frame": 173, "chunk_intent": "Left arm approaches and grasps the bag's side handle to stabilize it, while right arm hovers near the zipper pull.", "micro_actions": [{"verb": "grasp", "semantic_verb": null, "subject": "left_arm", "target": "bag:side_handle", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "Approaching from table surface to bag side handle"}, {"verb": "hover", "semantic_verb": null, "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "Hovering above zipper pull"}]}, {"chunk_idx": 5, "start_frame": 174, "end_frame": 234, "chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "side_handle", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_side_handle"}, {"verb": "grasp", "semantic_verb": null, "subject": "right_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "approaching_and_grasping_zipper_pull"}]}, {"chunk_idx": 6, "start_frame": 235, "end_frame": 254, "chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "side_handle", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_handle"}, {"verb": "grasp", "semantic_verb": null, "subject": "right_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "approach_and_grasp_zipper"}]}, {"chunk_idx": 7, "start_frame": 255, "end_frame": 268, "chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "side_handle", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_side_handle"}, {"verb": "grasp", "semantic_verb": null, "subject": "right_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "approaching_and_grasping_zipper_pull"}]}, {"chunk_idx": 8, "start_frame": 269, "end_frame": 288, "chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "side_handle", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_side_handle"}, {"verb": "grasp", "semantic_verb": null, "subject": "right_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "approaching_and_grasping_zipper_pull"}]}, {"chunk_idx": 9, "start_frame": 289, "end_frame": 326, "chunk_intent": "Left arm stabilizes the bag by grasping the top-left corner, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "micro_actions": [{"verb": "grasp", "semantic_verb": null, "subject": "left_arm", "target": "top_left_corner", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "moving from free space to bag:top_left_corner"}, {"verb": "grasp", "semantic_verb": null, "subject": "right_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "approaching and grasping bag:zipper_pull"}]}, {"chunk_idx": 10, "start_frame": 327, "end_frame": 366, "chunk_intent": "Left arm stabilizes the bag by grasping the top-left corner, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_left_corner", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_top_left_corner"}, {"verb": "grasp", "semantic_verb": null, "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "moving_from_free_space_to_zipper_pull"}]}, {"chunk_idx": 11, "start_frame": 367, "end_frame": 411, "chunk_intent": "Right arm executes a pulling motion on the zipper pull to open the bag, while the left arm maintains a stabilizing hold on the bag's top-left corner.", "micro_actions": [{"verb": "pull", "semantic_verb": "unzip_bag", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "moving from static_grasp to pulling_along_zipper_track"}, {"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_left_corner", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_stabilization_at_anchor"}]}, {"chunk_idx": 12, "start_frame": 412, "end_frame": 450, "chunk_intent": "Right arm releases the bag's zipper pull and retreats to a neutral position, while the left arm maintains a stabilizing hold on the bag's top-left corner.", "micro_actions": [{"verb": "release", "semantic_verb": "release_and_retreat", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "moving from bag:zipper_pull to free_space"}, {"verb": "hold", "semantic_verb": "stabilize", "subject": "left_arm", "target": "bag:top_left_corner", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_bag:top_left_corner"}]}, {"chunk_idx": 13, "start_frame": 451, "end_frame": 520, "chunk_intent": "Both arms maintain a static, idle state in free space above the table surface. The left arm hovers near the bag while the right arm remains retracted over the floor area; no physical interaction or topological change occurs.", "micro_actions": [{"verb": "hover", "semantic_verb": null, "subject": "left_arm", "target": "main_body", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "static_hover_above_bag"}, {"verb": "idle", "semantic_verb": null, "subject": "right_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_in_free_space_right_zone"}]}] + - **WSM (State Memory)**: [{"chunk_idx": 0, "global_frame_range": [0, 43], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_for_grasping"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Hovering and stabilizing position above the table surface near the bag, preparing for interaction.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 1, "global_frame_range": [44, 79], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_for_grasping"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Approaching the bag from a distance to establish contact with the top surface/zipper area.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 2, "global_frame_range": [80, 90], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_for_grasping"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Approaching the bag to establish contact with the top surface/zipper area.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 3, "global_frame_range": [91, 112], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_for_grasping"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}], "short_term_memory": {"last_chunk_intent": "Approaching the bag to establish contact with the top surface/zipper area.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 4, "global_frame_range": [113, 173], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_for_grasping"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and grasps the bag's side handle to stabilize it, while right arm hovers near the zipper pull.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 5, "global_frame_range": [174, 234], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:side_handle"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 6, "global_frame_range": [235, 254], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:side_handle"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 7, "global_frame_range": [255, 268], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:side_handle"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 8, "global_frame_range": [269, 288], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by grasping the side handle, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:side_handle"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 9, "global_frame_range": [289, 326], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}, {"anchor_id": "bag:top_left_corner", "current_status": "grasped_by_left_arm"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by grasping the top-left corner, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:top_left_corner"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 10, "global_frame_range": [327, 366], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}, {"anchor_id": "bag:top_left_corner", "current_status": "grasped_by_left_arm"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag by grasping the top-left corner, while right arm approaches and secures a grasp on the zipper pull to prepare for opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_left_corner"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 11, "global_frame_range": [367, 411], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}, {"anchor_id": "bag:top_left_corner", "current_status": "grasped_by_left_arm"}, {"anchor_id": "bag:zipper_track", "current_status": "partially_opened"}], "short_term_memory": {"last_chunk_intent": "Right arm executes a pulling motion on the zipper pull to open the bag, while the left arm maintains a stabilizing hold on the bag's top-left corner.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_left_corner"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 12, "global_frame_range": [412, 450], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "released_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}, {"anchor_id": "bag:top_left_corner", "current_status": "grasped_by_left_arm"}, {"anchor_id": "bag:zipper_track", "current_status": "partially_opened"}], "short_term_memory": {"last_chunk_intent": "Right arm releases the bag's zipper pull and retreats to a neutral position, while the left arm maintains a stabilizing hold on the bag's top-left corner.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_left_corner"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:zipper_pull"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 13, "global_frame_range": [451, 520], "world_state": {"spatial_atlas": [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "released_by_right_arm"}, {"anchor_id": "bag:side_handle", "current_status": "grasped_by_left_arm"}, {"anchor_id": "bag:top_left_corner", "current_status": "grasped_by_left_arm"}, {"anchor_id": "bag:zipper_track", "current_status": "partially_opened"}], "short_term_memory": {"last_chunk_intent": "Both arms maintain a static, idle state in free space above the table surface. The left arm hovers near the bag while the right arm remains retracted over the floor area; no physical interaction or topological change occurs.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_left_corner"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}] + + ### 2. SYNTHESIS RULES (COMMON SENSE & NATURAL BOUNDARIES) + You must divide the chronological timeline into distinct segments. Instead of following rigid verb rules, use your human common sense to identify when a new phase of the task begins. + + **A natural "Chapter Boundary" (Segment Break) occurs when:** + 1. **Target Object Shift (CRITICAL)**: The robot shifts its focus or interaction from one primary object to another (e.g., finishes pouring into 'cup_A' and moves to 'cup_B', or drops a 'sponge' to pick up a 'towel'). NEVER merge actions directed at different primary targets into the same segment. + 2. **Major State Transition**: As seen in the WSM, a significant physical event occurs (e.g., the gripper transitions from 'none' to 'holding', or an object's topology drastically changes). + 3. **Semantic Goal Shift**: The overarching intent changes (e.g., from the "Approach & Preparation" phase to the "Active Manipulation" phase, and finally to the "Retract & Idle" phase). + + **Grouping Principle:** + - Merge consecutive chunks that serve a single, unified purpose (e.g., multiple chunks of "hover" and "hold" that all serve the continuous intent of "pouring water into the paper cup" should be merged into one segment). + - Ensure chronological integrity: Segments must be contiguous using the `chunk_idx` (e.g., [0, 2], [3, 5]). No gaps, no overlapping chunks. + + ### 3. OUTPUT REQUIREMENT + - `merge_thought`: Explain your logic based on the natural boundaries. Example: "Chunks 2-5 represent the continuous pouring phase into the paper cup. I broke the segment at Chunk 6 because the target shifted to the teal cup." + - `chunk_idx_range`: Output the exact index range `[start, end]`. + - `state_transition.before_anchors`: For the VERY FIRST segment (segment 0), this MUST exactly match these initial anchors: [{"anchor_id": "table:surface_center", "current_status": "clear_and_accessible"}, {"anchor_id": "bag:main_body", "current_status": "upright_and_stable"}, {"anchor_id": "bag:zipper_pull", "current_status": "exposed_for_grasping"}, {"anchor_id": "bag:side_handle", "current_status": "accessible"}] + + Output ONLY valid JSON. + ```json + { + "$defs": { + "CausalSummary": { + "properties": { + "trigger": { + "description": "Triggered by what topological sequence? (e.g., 'Bimanual pinch & moved from hem to collar')", + "title": "Trigger", + "type": "string" + }, + "effect": { + "description": "Visual effect (e.g., 'Jacket folded in half')", + "title": "Effect", + "type": "string" + } + }, + "required": [ + "trigger", + "effect" + ], + "title": "CausalSummary", + "type": "object" + }, + "SegmentAnnotation": { + "properties": { + "segment_id": { + "minimum": 0, + "title": "Segment Id", + "type": "integer" + }, + "primitive_type": { + "description": "Must be one of: ['Approach', 'Pre-grasp Align', 'Grasp', 'Lift', 'Horizontal Transport', 'Target Hover & Align', 'Lower & Pre-place', 'Compress/Squeeze', 'Shape/Adjust', 'Release', 'Retract', 'Place', 'Idle', 'Hold']", + "title": "Primitive Type", + "type": "string" + }, + "chunk_idx_range": { + "description": "[start_chunk_idx, end_chunk_idx] inclusive. E.g., [2, 5] means merging chunks 2, 3, 4, and 5.", + "items": { + "type": "integer" + }, + "maxItems": 2, + "minItems": 2, + "title": "Chunk Idx Range", + "type": "array" + }, + "subtask": { + "description": "Intent referencing the semantic atlas.", + "title": "Subtask", + "type": "string" + }, + "state_transition": { + "$ref": "#/$defs/StateTransition" + }, + "causal_summary": { + "$ref": "#/$defs/CausalSummary" + } + }, + "required": [ + "segment_id", + "primitive_type", + "chunk_idx_range", + "subtask", + "state_transition", + "causal_summary" + ], + "title": "SegmentAnnotation", + "type": "object" + }, + "SemanticAnchor": { + "description": "\u52a8\u6001\u8bed\u4e49\u951a\u70b9\uff1a\u4ee3\u66ff\u7edd\u5bf9 XYZ \u5750\u6807\uff0c\u5b9a\u4e49\u7269\u4f53\u6216\u5de5\u4f5c\u7a7a\u95f4\u7684\u903b\u8f91\u529f\u80fd\u533a", + "properties": { + "anchor_id": { + "description": "Unique topological zone ID, e.g., 'left_sleeve', 'collar', 'drawer_handle'", + "title": "Anchor Id", + "type": "string" + }, + "current_status": { + "description": "Visual status of this zone, e.g., 'exposed', 'folded_over', 'open'", + "title": "Current Status", + "type": "string" + } + }, + "required": [ + "anchor_id", + "current_status" + ], + "title": "SemanticAnchor", + "type": "object" + }, + "StateTransition": { + "properties": { + "before_anchors": { + "description": "Status of relevant semantic anchors before segment", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "Before Anchors", + "type": "array" + }, + "after_anchors": { + "description": "Status of relevant semantic anchors after segment", + "items": { + "$ref": "#/$defs/SemanticAnchor" + }, + "title": "After Anchors", + "type": "array" + } + }, + "required": [ + "before_anchors", + "after_anchors" + ], + "title": "StateTransition", + "type": "object" + } + }, + "properties": { + "video_id": { + "title": "Video Id", + "type": "string" + }, + "merge_thought": { + "description": "Explain how semantic anchor stability and topology changes guided your chunk merging.", + "title": "Merge Thought", + "type": "string" + }, + "segments": { + "items": { + "$ref": "#/$defs/SegmentAnnotation" + }, + "title": "Segments", + "type": "array" + } + }, + "required": [ + "video_id", + "merge_thought", + "segments" + ], + "title": "SubtaskAnnotation", + "type": "object" +} + ``` + +```` +
+ +### 🗣️ 输出结果 +````json +{ + "video_id": "video_0008", + "merge_thought": "I have segmented the timeline into four logical macro-chapters based on the shift in robotic intent and object interaction states. \n\n1. **Approach Phase (Chunks 0-3)**: The robot transitions from hovering to approaching the bag. Although there are multiple approach chunks, they all serve the unified goal of establishing initial proximity and contact with the bag's zipper area without yet securing a functional grasp for manipulation. The boundary is drawn at Chunk 4 where the left arm secures a grasp.\n\n2. **Stabilization & Grasp Acquisition (Chunks 4-10)**: This long segment represents the 'Pre-grasp Align' and 'Grasp' phases. The left arm first grasps the side handle (Chunk 4), then switches to the top-left corner (Chunk 9) to better stabilize the bag while the right arm secures the zipper pull. These actions are merged because they constitute the continuous setup required before the actual opening action can begin. The state remains 'preparing to open' throughout.\n\n3. **Execution: Unzipping (Chunk 11)**: This is a distinct 'Active Manipulation' phase. The topology of the bag changes (zipper track opens). This is a clear semantic goal shift from preparation to execution.\n\n4. **Release & Idle (Chunks 12-13)**: After unzipping, the right arm releases and retreats, and both arms enter an idle/hover state. This represents the conclusion of the task sequence.", + "segments": [ + { + "segment_id": 0, + "primitive_type": "Approach", + "chunk_idx_range": [ + 0, + 3 + ], + "subtask": "Approach bag and establish initial contact with zipper area", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "table:surface_center", + "current_status": "clear_and_accessible" + }, + { + "anchor_id": "bag:main_body", + "current_status": "upright_and_stable" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "exposed_for_grasping" + }, + { + "anchor_id": "bag:side_handle", + "current_status": "accessible" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "touched_by_left_arm" + }, + { + "anchor_id": "bag:side_handle", + "current_status": "accessible" + } + ] + }, + "causal_summary": { + "trigger": "Robot hovers then moves arms from free space to bag proximity", + "effect": "Left arm touches zipper pull, right arm hovers near main body" + } + }, + { + "segment_id": 1, + "primitive_type": "Grasp", + "chunk_idx_range": [ + 4, + 10 + ], + "subtask": "Stabilize bag with left arm and grasp zipper pull with right arm", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "touched_by_left_arm" + }, + { + "anchor_id": "bag:side_handle", + "current_status": "accessible" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:top_left_corner", + "current_status": "grasped_by_left_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_right_arm" + } + ] + }, + "causal_summary": { + "trigger": "Left arm secures hold on bag corner; Right arm secures hold on zipper", + "effect": "Bag is stabilized and zipper pull is ready for pulling" + } + }, + { + "segment_id": 2, + "primitive_type": "Compress/Squeeze", + "chunk_idx_range": [ + 11, + 11 + ], + "subtask": "Execute unzipping motion", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:top_left_corner", + "current_status": "grasped_by_left_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_right_arm" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:zipper_track", + "current_status": "partially_opened" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_right_arm" + } + ] + }, + "causal_summary": { + "trigger": "Right arm pulls zipper pull along track while left arm holds bag", + "effect": "Bag zipper opens partially" + } + }, + { + "segment_id": 3, + "primitive_type": "Release", + "chunk_idx_range": [ + 12, + 13 + ], + "subtask": "Release zipper and return to idle state", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:zipper_track", + "current_status": "partially_opened" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_right_arm" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "released_by_right_arm" + }, + { + "anchor_id": 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