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index 0000000000000000000000000000000000000000..21772e24278bc71b117b3686ccecb465eddfcdbb --- /dev/null +++ b/debug/episode_0033/trace_report.md @@ -0,0 +1,8898 @@ +# 🤖 Episode_0033 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 beige insulated bag is positioned centrally on a white table surface, directly within the robot's forward reach zone.", + "initial_semantic_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "exposed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "exposed" + }, + { + "anchor_id": "table:center_zone", + "current_status": "occupied_by_bag" + } + ], + "background_distractors": [] +} +```` +--- + +# 🤖 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone'] + + 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": 0.0, "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, 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, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]}, "right": {"vel": 0.08, "angle": 0.5, "vel_score": 0.75, "angle_score": 4.62, "vel_fft": [0.082, 0.073, 0.053, 0.034, 0.023, 0.016, 0.013, 0.012, 0.009, 0.008, 0.01, 0.011, 0.01, 0.01, 0.01, 0.011, 0.011], "angle_fft": [0.501, 0.422, 0.236, 0.057, 0.054, 0.057, 0.051, 0.051, 0.02, 0.034, 0.056, 0.052, 0.041, 0.018, 0.016, 0.04, 0.046]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.01, "left_arm_ry": 1.14, "left_arm_rz": -3.14, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.02, "right_arm_ry": 1.11, "right_arm_rz": 3.1, "right_gripper": 0.34}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": -0.063, "left_arm_rx": -3.01, "left_arm_ry": 1.14, "left_arm_rz": -3.14, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": -0.063, "right_arm_rx": 3.02, "right_arm_ry": 1.11, "right_arm_rz": 3.1, "right_gripper": 0.34}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.01, "left_arm_ry": 1.14, "left_arm_rz": -3.14, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.02, "right_arm_ry": 1.11, "right_arm_rz": 3.1, "right_gripper": 0.34}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": -0.021, "left_arm_rx": -3.01, "left_arm_ry": 1.14, "left_arm_rz": -3.14, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": -0.021, "right_arm_rx": 3.02, "right_arm_ry": 1.11, "right_arm_rz": 3.1, "right_gripper": 0.34}, "4": {"left_arm_vel": 0.046, "left_gripper_vel": 0.0, "left_arm_rx": -3.01, "left_arm_ry": 1.14, "left_arm_rz": -3.14, "left_gripper": 0.24, "right_arm_vel": 0.046, "right_gripper_vel": 0.0, "right_arm_rx": 2.95, "right_arm_ry": 1.1, "right_arm_rz": 3.06, "right_gripper": 0.34}, "5": {"left_arm_vel": 0.176, "left_gripper_vel": -0.042, "left_arm_rx": -3.01, "left_arm_ry": 1.14, "left_arm_rz": -3.14, "left_gripper": 0.24, "right_arm_vel": 0.176, "right_gripper_vel": -0.042, "right_arm_rx": 2.78, "right_arm_ry": 1.14, "right_arm_rz": 2.97, "right_gripper": 0.34}, "6": {"left_arm_vel": 0.383, "left_gripper_vel": 0.0, "left_arm_rx": -3.01, "left_arm_ry": 1.14, "left_arm_rz": -3.14, "left_gripper": 0.24, "right_arm_vel": 0.383, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 1.18, "right_arm_rz": 3.02, "right_gripper": 0.34}, "7": {"left_arm_vel": 0.524, "left_gripper_vel": 0.0, "left_arm_rx": -3.01, "left_arm_ry": 1.14, "left_arm_rz": -3.14, "left_gripper": 0.24, "right_arm_vel": 0.524, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 1.18, "right_arm_rz": 3.14, "right_gripper": 0.34}}} + + [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": [0.05999999865889549, 0.04670000076293945, 0.03350000083446503], "delta_rot": [-0.38989999890327454, 0.06960000097751617, 0.0340999998152256], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and +Z(Up)", "magnitude": 0.0831}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.012500000186264515, -0.0020000000949949026, 0.00039999998989515007], "delta_rot": [-0.007300000172108412, -0.07460000365972519, 6.267399787902832], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0127}, "right": {"delta_pos": [0.44909998774528503, 0.26089999079704285, -0.03880000114440918], "delta_rot": [-0.2538999915122986, -0.2526000142097473, -5.321400165557861], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and -Z(Down)", "magnitude": 0.5208}} + + ========================================= + [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 hovering position to initiate interaction.", + "actions": [ + { + "reasoning_cot": "The left arm remains stationary in the foreground with no change in gripper state or position relative to the scene. It is effectively idle while waiting for the right arm to engage.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "static_at_foreground", + "topology_change": false + }, + { + "reasoning_cot": "The right arm exhibits forward (+X) and upward (+Z) displacement towards the bag's location. The gripper is open (0.34), indicating an approach phase rather than a grasp. Visual evidence confirms the end-effector is moving into the proximity of the 'bag:main_body' but has not yet made contact.", + "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_center", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Initiating approach sequence towards the bag." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Approaching the bag from a hovering position to initiate 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": 0.02, "angle": 7.63, "vel_score": 0.1, "angle_score": 0.82, "vel_fft": [0.016, 0.012, 0.006, 0.005, 0.006, 0.004, 0.003, 0.004, 0.003, 0.002, 0.003, 0.002, 0.002], "angle_fft": [7.625, 7.564, 7.511, 7.512, 7.513, 7.517, 7.519, 7.528, 7.507, 7.5, 7.515, 7.505, 7.508]}, "right": {"vel": 0.54, "angle": 1.32, "vel_score": 3.49, "angle_score": 8.44, "vel_fft": [0.541, 0.122, 0.034, 0.026, 0.021, 0.014, 0.012, 0.004, 0.022, 0.02, 0.018, 0.028, 0.018], "angle_fft": [1.315, 0.37, 0.025, 0.081, 0.078, 0.098, 0.034, 0.058, 0.062, 0.063, 0.082, 0.052, 0.053]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.01, "left_arm_ry": 1.14, "left_arm_rz": -3.14, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 1.17, "right_arm_rz": -3.1, "right_gripper": 0.34}, "1": {"left_arm_vel": 0.579, "left_gripper_vel": -0.021, "left_arm_rx": -3.01, "left_arm_ry": 1.14, "left_arm_rz": -3.14, "left_gripper": 0.24, "right_arm_vel": 0.579, "right_gripper_vel": -0.021, "right_arm_rx": 2.66, "right_arm_ry": 1.14, "right_arm_rz": -3.05, "right_gripper": 0.33}, "2": {"left_arm_vel": 0.521, "left_gripper_vel": -0.021, "left_arm_rx": -3.01, "left_arm_ry": 1.14, "left_arm_rz": -3.14, "left_gripper": 0.24, "right_arm_vel": 0.521, "right_gripper_vel": -0.021, "right_arm_rx": 2.68, "right_arm_ry": 1.14, "right_arm_rz": -2.99, "right_gripper": 0.33}, "3": {"left_arm_vel": 0.641, "left_gripper_vel": 0.021, "left_arm_rx": -3.0, "left_arm_ry": 1.14, "left_arm_rz": -3.14, "left_gripper": 0.24, "right_arm_vel": 0.641, "right_gripper_vel": 0.021, "right_arm_rx": 2.7, "right_arm_ry": 1.12, "right_arm_rz": -2.94, "right_gripper": 0.33}, "4": {"left_arm_vel": 0.708, "left_gripper_vel": 0.0, "left_arm_rx": -3.0, "left_arm_ry": 1.14, "left_arm_rz": -3.13, "left_gripper": 0.24, "right_arm_vel": 0.708, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 1.09, "right_arm_rz": -2.9, "right_gripper": 0.33}, "5": {"left_arm_vel": 0.608, "left_gripper_vel": 0.0, "left_arm_rx": -3.0, "left_arm_ry": 1.14, "left_arm_rz": -3.13, "left_gripper": 0.24, "right_arm_vel": 0.608, "right_gripper_vel": 0.0, "right_arm_rx": 2.71, "right_arm_ry": 1.08, "right_arm_rz": -2.86, "right_gripper": 0.33}, "6": {"left_arm_vel": 0.747, "left_gripper_vel": 0.0, "left_arm_rx": -3.0, "left_arm_ry": 1.14, "left_arm_rz": -3.13, "left_gripper": 0.24, "right_arm_vel": 0.747, "right_gripper_vel": 0.0, "right_arm_rx": 2.79, "right_arm_ry": 1.02, "right_arm_rz": -2.7, "right_gripper": 0.33}, "7": {"left_arm_vel": 0.766, "left_gripper_vel": 0.0, "left_arm_rx": -2.99, "left_arm_ry": 1.14, "left_arm_rz": -3.13, "left_gripper": 0.24, "right_arm_vel": 0.766, "right_gripper_vel": 0.0, "right_arm_rx": 2.85, "right_arm_ry": 0.99, "right_arm_rz": -2.57, "right_gripper": 0.33}, "8": {"left_arm_vel": 0.771, "left_gripper_vel": 0.0, "left_arm_rx": -2.99, "left_arm_ry": 1.14, "left_arm_rz": -3.13, "left_gripper": 0.24, "right_arm_vel": 0.771, "right_gripper_vel": 0.0, "right_arm_rx": 2.88, "right_arm_ry": 0.98, "right_arm_rz": -2.51, "right_gripper": 0.33}, "9": {"left_arm_vel": 0.672, "left_gripper_vel": 0.0, "left_arm_rx": -2.99, "left_arm_ry": 1.14, "left_arm_rz": -3.13, "left_gripper": 0.24, "right_arm_vel": 0.672, "right_gripper_vel": 0.0, "right_arm_rx": 2.9, "right_arm_ry": 0.98, "right_arm_rz": -2.46, "right_gripper": 0.33}, "10": {"left_arm_vel": 0.651, "left_gripper_vel": 0.0, "left_arm_rx": -2.99, "left_arm_ry": 1.14, "left_arm_rz": -3.13, "left_gripper": 0.24, "right_arm_vel": 0.651, "right_gripper_vel": 0.0, "right_arm_rx": 2.89, "right_arm_ry": 0.95, "right_arm_rz": -2.33, "right_gripper": 0.33}, "11": {"left_arm_vel": 0.479, "left_gripper_vel": 0.0, "left_arm_rx": -2.99, "left_arm_ry": 1.13, "left_arm_rz": -3.13, "left_gripper": 0.24, "right_arm_vel": 0.479, "right_gripper_vel": 0.0, "right_arm_rx": 2.81, "right_arm_ry": 0.92, "right_arm_rz": -2.29, "right_gripper": 0.33}, "12": {"left_arm_vel": 0.28, "left_gripper_vel": 0.0, "left_arm_rx": -3.0, "left_arm_ry": 1.1, "left_arm_rz": -3.14, "left_gripper": 0.24, "right_arm_vel": 0.28, "right_gripper_vel": 0.0, "right_arm_rx": 2.8, "right_arm_ry": 0.88, "right_arm_rz": -2.24, "right_gripper": 0.33}, "13": {"left_arm_vel": 0.27, "left_gripper_vel": 0.0, "left_arm_rx": -3.02, "left_arm_ry": 1.07, "left_arm_rz": 3.13, "left_gripper": 0.24, "right_arm_vel": 0.27, "right_gripper_vel": 0.0, "right_arm_rx": 2.77, "right_arm_ry": 0.86, "right_arm_rz": -2.22, "right_gripper": 0.33}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.012500000186264515, -0.0020000000949949026, 0.00039999998989515007], "delta_rot": [-0.007300000172108412, -0.07460000365972519, 6.267399787902832], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0127}, "right": {"delta_pos": [0.3714999854564667, 0.20819999277591705, -0.07410000264644623], "delta_rot": [0.1274999976158142, -0.31150001287460327, 0.8773000240325928], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and -Z(Down)", "magnitude": 0.4323}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.08820000290870667, -0.022199999541044235, 0.02199999988079071], "delta_rot": [0.04969999939203262, -0.13009999692440033, 6.15749979019165], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.0936}, "right": {"delta_pos": [0.36160001158714294, 0.2362000048160553, -0.10490000247955322], "delta_rot": [0.06769999861717224, -0.48500001430511475, 0.9280999898910522], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and -Z(Down)", "magnitude": 0.4445}} + + ========================================= + [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 top surface of the bag to initiate manipulation, while left arm remains idle.", + "actions": [ + { + "reasoning_cot": "The right arm executes a significant forward (+X) and downward (-Z) trajectory (delta_pos magnitude 0.43), transitioning from free space to direct contact with the bag's top reflective patch. The gripper remains stable/open, indicating an approach or touch action rather than a grasp. The left arm shows negligible movement and no visual interaction.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "top_surface" + }, + "spatial_logic": "Moving from hovering position to contact with bag:top_surface", + "topology_change": false + }, + { + "reasoning_cot": "The left arm maintains a static position with near-zero velocity and delta displacement. Visual input confirms no contact with the bag or table. It is effectively idling while the right arm performs the primary task.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "Static hover in free space", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Initiating interaction with the bag by establishing contact on the top surface with the right end-effector." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm approaches and makes contact with the top surface of the bag 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": 0.18, "angle": 0.59, "vel_score": 0.75, "angle_score": 2.4, "vel_fft": [0.185, 0.033, 0.025, 0.023, 0.013, 0.016, 0.011], "angle_fft": [0.586, 0.036, 0.122, 0.075, 0.04, 0.05, 0.058]}, "right": {"vel": 0.1, "angle": 0.51, "vel_score": 0.41, "angle_score": 2.1, "vel_fft": [0.098, 0.049, 0.017, 0.014, 0.008, 0.01, 0.006], "angle_fft": [0.509, 0.12, 0.054, 0.046, 0.044, 0.025, 0.036]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.02, "left_arm_ry": 1.04, "left_arm_rz": 3.12, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.75, "right_arm_ry": 0.85, "right_arm_rz": -2.22, "right_gripper": 0.33}, "1": {"left_arm_vel": 0.211, "left_gripper_vel": 0.042, "left_arm_rx": -3.06, "left_arm_ry": 0.98, "left_arm_rz": 3.08, "left_gripper": 0.24, "right_arm_vel": 0.211, "right_gripper_vel": 0.042, "right_arm_rx": 2.7, "right_arm_ry": 0.82, "right_arm_rz": -2.2, "right_gripper": 0.34}, "2": {"left_arm_vel": 0.131, "left_gripper_vel": 0.042, "left_arm_rx": -3.06, "left_arm_ry": 0.96, "left_arm_rz": 3.05, "left_gripper": 0.24, "right_arm_vel": 0.131, "right_gripper_vel": 0.042, "right_arm_rx": 2.68, "right_arm_ry": 0.78, "right_arm_rz": -2.2, "right_gripper": 0.34}, "3": {"left_arm_vel": 0.061, "left_gripper_vel": 0.021, "left_arm_rx": -3.05, "left_arm_ry": 0.98, "left_arm_rz": 3.03, "left_gripper": 0.24, "right_arm_vel": 0.061, "right_gripper_vel": 0.021, "right_arm_rx": 2.67, "right_arm_ry": 0.74, "right_arm_rz": -2.19, "right_gripper": 0.34}, "4": {"left_arm_vel": 0.036, "left_gripper_vel": 0.021, "left_arm_rx": -3.02, "left_arm_ry": 1.01, "left_arm_rz": 3.03, "left_gripper": 0.24, "right_arm_vel": 0.036, "right_gripper_vel": 0.021, "right_arm_rx": 2.69, "right_arm_ry": 0.72, "right_arm_rz": -2.19, "right_gripper": 0.35}, "5": {"left_arm_vel": 0.029, "left_gripper_vel": -0.063, "left_arm_rx": -2.97, "left_arm_ry": 1.01, "left_arm_rz": 3.03, "left_gripper": 0.25, "right_arm_vel": 0.029, "right_gripper_vel": -0.063, "right_arm_rx": 2.7, "right_arm_ry": 0.7, "right_arm_rz": -2.18, "right_gripper": 0.34}, "6": {"left_arm_vel": 0.036, "left_gripper_vel": -0.399, "left_arm_rx": -2.96, "left_arm_ry": 1.01, "left_arm_rz": 3.02, "left_gripper": 0.25, "right_arm_vel": 0.036, "right_gripper_vel": -0.399, "right_arm_rx": 2.71, "right_arm_ry": 0.68, "right_arm_rz": -2.17, "right_gripper": 0.33}, "7": {"left_arm_vel": 0.036, "left_gripper_vel": -0.399, "left_arm_rx": -2.96, "left_arm_ry": 1.01, "left_arm_rz": 3.02, "left_gripper": 0.25, "right_arm_vel": 0.036, "right_gripper_vel": -0.399, "right_arm_rx": 2.71, "right_arm_ry": 0.68, "right_arm_rz": -2.17, "right_gripper": 0.33}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.07180000096559525, -0.019899999722838402, 0.02160000056028366], "delta_rot": [0.060100000351667404, -0.03319999948143959, -0.10740000009536743], "gripper_changed": false, "flow_direction": "+X(Forward) and +Z(Up)", "magnitude": 0.0776}, "right": {"delta_pos": [-0.010499999858438969, 0.020400000736117363, -0.027699999511241913], "delta_rot": [-0.042100001126527786, -0.16590000689029694, 0.04729999974370003], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.036}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.2565999925136566, -0.05719999969005585, -0.05130000039935112], "delta_rot": [5.9430999755859375, -0.2287999987602234, -0.9366000294685364], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.2679}, "right": {"delta_pos": [-0.012900000438094139, 0.020999999716877937, -0.029200000688433647], "delta_rot": [-0.03539999946951866, -0.19120000302791595, 0.061900001019239426], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.0382}} + + ========================================= + [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 establishes contact with the top surface of the bag to initiate manipulation, while left arm remains idle.", + "actions": [ + { + "reasoning_cot": "The right arm executes a forward (+X) and downward (-Z) trajectory, transitioning from free space to direct physical contact with the bag's upper reflective patch. The gripper remains open (stable signal), indicating an approach or touch action rather than a grasp. Visual evidence confirms the end-effector is positioned over the 'top_surface' anchor.", + "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 hover to contact at bag:top_surface", + "topology_change": false + }, + { + "reasoning_cot": "The left arm shows negligible kinematic displacement (low velocity scores) and maintains its position in the peripheral workspace. It does not interact with the bag or any other 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_in_peripheral_zone", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Initiating contact with the bag's top surface using the right arm." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm approaches and establishes contact with the top surface of the bag 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": 0.36, "angle": 13.4, "vel_score": 1.7, "angle_score": 9.34, "vel_fft": [0.362, 0.049, 0.03, 0.009, 0.022, 0.023, 0.021, 0.029, 0.015], "angle_fft": [13.402, 11.935, 11.296, 11.648, 11.721, 11.472, 11.667, 11.726, 11.531]}, "right": {"vel": 0.01, "angle": 0.06, "vel_score": 0.03, "angle_score": 0.24, "vel_fft": [0.006, 0.004, 0.003, 0.002, 0.001, 0.001, 0.001, 0.001, 0.001], "angle_fft": [0.057, 0.037, 0.023, 0.015, 0.02, 0.015, 0.009, 0.011, 0.011]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 1.01, "left_arm_rz": 3.0, "left_gripper": 0.26, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.68, "right_arm_rz": -2.16, "right_gripper": 0.29}, "1": {"left_arm_vel": 0.027, "left_gripper_vel": -2.352, "left_arm_rx": -2.95, "left_arm_ry": 1.01, "left_arm_rz": 2.99, "left_gripper": 0.28, "right_arm_vel": 0.027, "right_gripper_vel": -2.352, "right_arm_rx": 2.72, "right_arm_ry": 0.67, "right_arm_rz": -2.16, "right_gripper": 0.21}, "2": {"left_arm_vel": 0.018, "left_gripper_vel": -2.646, "left_arm_rx": -2.96, "left_arm_ry": 1.0, "left_arm_rz": 2.96, "left_gripper": 0.29, "right_arm_vel": 0.018, "right_gripper_vel": -2.646, "right_arm_rx": 2.72, "right_arm_ry": 0.67, "right_arm_rz": -2.15, "right_gripper": 0.12}, "3": {"left_arm_vel": 0.021, "left_gripper_vel": -1.323, "left_arm_rx": -2.98, "left_arm_ry": 1.0, "left_arm_rz": 2.93, "left_gripper": 0.31, "right_arm_vel": 0.021, "right_gripper_vel": -1.323, "right_arm_rx": 2.72, "right_arm_ry": 0.66, "right_arm_rz": -2.15, "right_gripper": 0.07}, "4": {"left_arm_vel": 0.012, "left_gripper_vel": -0.798, "left_arm_rx": -3.01, "left_arm_ry": 0.99, "left_arm_rz": 2.89, "left_gripper": 0.33, "right_arm_vel": 0.012, "right_gripper_vel": -0.798, "right_arm_rx": 2.72, "right_arm_ry": 0.66, "right_arm_rz": -2.15, "right_gripper": 0.05}, "5": {"left_arm_vel": 0.003, "left_gripper_vel": -0.084, "left_arm_rx": -3.04, "left_arm_ry": 0.97, "left_arm_rz": 2.84, "left_gripper": 0.35, "right_arm_vel": 0.003, "right_gripper_vel": -0.084, "right_arm_rx": 2.72, "right_arm_ry": 0.66, "right_arm_rz": -2.15, "right_gripper": 0.05}, "6": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -3.06, "left_arm_ry": 0.94, "left_arm_rz": 2.81, "left_gripper": 0.37, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.66, "right_arm_rz": -2.15, "right_gripper": 0.05}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.09, "left_arm_ry": 0.92, "left_arm_rz": 2.75, "left_gripper": 0.39, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.66, "right_arm_rz": -2.15, "right_gripper": 0.05}, "8": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -3.11, "left_arm_ry": 0.9, "left_arm_rz": 2.7, "left_gripper": 0.4, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.66, "right_arm_rz": -2.15, "right_gripper": 0.05}, "9": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": -3.13, "left_arm_ry": 0.88, "left_arm_rz": 2.65, "left_gripper": 0.41, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.66, "right_arm_rz": -2.15, "right_gripper": 0.05}, "10": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 3.13, "left_arm_ry": 0.86, "left_arm_rz": 2.59, "left_gripper": 0.42, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.66, "right_arm_rz": -2.15, "right_gripper": 0.05}, "11": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 3.11, "left_arm_ry": 0.85, "left_arm_rz": 2.53, "left_gripper": 0.42, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.66, "right_arm_rz": -2.15, "right_gripper": 0.05}, "12": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 3.07, "left_arm_ry": 0.85, "left_arm_rz": 2.45, "left_gripper": 0.42, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.66, "right_arm_rz": -2.15, "right_gripper": 0.05}, "13": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.92, "left_arm_ry": 0.81, "left_arm_rz": 2.19, "left_gripper": 0.43, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.71, "right_arm_ry": 0.66, "right_arm_rz": -2.15, "right_gripper": 0.04}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.17389999330043793, -0.03449999913573265, -0.0722000002861023], "delta_rot": [5.871399879455566, -0.19339999556541443, -0.8181999921798706], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.1914}, "right": {"delta_pos": [-0.002300000051036477, 0.0013000000035390258, -0.0007999999797903001], "delta_rot": [-0.0019000000320374966, -0.016100000590085983, 0.007499999832361937], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0028}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.12839999794960022, -0.094200000166893, -0.06769999861717224], "delta_rot": [-0.18940000236034393, -0.535099983215332, -0.9764000177383423], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.173}, "right": {"delta_pos": [-0.008799999952316284, 0.008899999782443047, -0.0007999999797903001], "delta_rot": [-0.1128000020980835, -0.08460000157356262, -0.1273999959230423], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0125}} + + ========================================= + [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 establishes contact with the top surface of the bag 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 0.1914) towards the bag. Visual evidence confirms the gripper makes contact with the silver reflective patch on the bag's top flap. The gripper signal is 'stable' but visual contact transitions from 'none' to 'touching', indicating an approach and initial touch phase rather than a full grasp yet.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "top_surface" + }, + "spatial_logic": "Moving from free space to contact with bag:top_surface", + "topology_change": false + }, + { + "reasoning_cot": "The left arm exhibits negligible kinematic displacement (delta_mag 0.0028) and remains in a static hover position away from the object. Visual frames confirm no interaction with the bag or table.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "Static hover in free space", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Right arm has successfully located and touched the top surface of the bag; left arm is standby." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm approaches and establishes contact with the top surface of the bag 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": 0.1, "angle": 3.08, "vel_score": 1.21, "angle_score": 6.77, "vel_fft": [0.101, 0.032, 0.023, 0.005, 0.011, 0.005, 0.005, 0.01, 0.003, 0.002, 0.003, 0.003, 0.003, 0.004, 0.004, 0.003, 0.004, 0.004, 0.004, 0.004], "angle_fft": [3.08, 2.589, 2.441, 2.539, 2.557, 2.536, 2.514, 2.578, 2.556, 2.524, 2.466, 2.544, 2.547, 2.499, 2.531, 2.533, 2.563, 2.535, 2.508, 2.532]}, "right": {"vel": 0.01, "angle": 0.09, "vel_score": 0.08, "angle_score": 1.11, "vel_fft": [0.005, 0.003, 0.003, 0.003, 0.002, 0.004, 0.001, 0.002, 0.002, 0.002, 0.002, 0.0, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001], "angle_fft": [0.087, 0.046, 0.014, 0.027, 0.007, 0.011, 0.013, 0.018, 0.003, 0.016, 0.009, 0.006, 0.008, 0.007, 0.007, 0.008, 0.008, 0.005, 0.004, 0.007]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.88, "left_arm_ry": 0.79, "left_arm_rz": 2.11, "left_gripper": 0.43, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.71, "right_arm_ry": 0.66, "right_arm_rz": -2.15, "right_gripper": 0.04}, "1": {"left_arm_vel": 0.002, "left_gripper_vel": -0.105, "left_arm_rx": 2.78, "left_arm_ry": 0.67, "left_arm_rz": 1.82, "left_gripper": 0.43, "right_arm_vel": 0.002, "right_gripper_vel": -0.105, "right_arm_rx": 2.71, "right_arm_ry": 0.66, "right_arm_rz": -2.16, "right_gripper": 0.04}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.75, "left_arm_ry": 0.61, "left_arm_rz": 1.71, "left_gripper": 0.28, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.71, "right_arm_ry": 0.66, "right_arm_rz": -2.16, "right_gripper": 0.04}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.74, "left_arm_ry": 0.59, "left_arm_rz": 1.68, "left_gripper": 0.06, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.71, "right_arm_ry": 0.66, "right_arm_rz": -2.16, "right_gripper": 0.04}, "4": {"left_arm_vel": 0.007, "left_gripper_vel": 0.0, "left_arm_rx": 2.79, "left_arm_ry": 0.51, "left_arm_rz": 1.76, "left_gripper": 0.01, "right_arm_vel": 0.007, "right_gripper_vel": 0.0, "right_arm_rx": 2.69, "right_arm_ry": 0.65, "right_arm_rz": -2.19, "right_gripper": 0.04}, "5": {"left_arm_vel": 0.016, "left_gripper_vel": 0.0, "left_arm_rx": 3.11, "left_arm_ry": 0.46, "left_arm_rz": 2.01, "left_gripper": -0.01, "right_arm_vel": 0.016, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.64, "right_arm_rz": -2.23, "right_gripper": 0.04}, "6": {"left_arm_vel": 0.006, "left_gripper_vel": 0.0, "left_arm_rx": -3.1, "left_arm_ry": 0.4, "left_arm_rz": 2.01, "left_gripper": -0.01, "right_arm_vel": 0.006, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.61, "right_arm_rz": -2.28, "right_gripper": 0.04}, "7": {"left_arm_vel": 0.058, "left_gripper_vel": 0.0, "left_arm_rx": -3.14, "left_arm_ry": 0.47, "left_arm_rz": 2.03, "left_gripper": -0.01, "right_arm_vel": 0.058, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.59, "right_arm_rz": -2.29, "right_gripper": 0.04}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.05310000106692314, -0.05590000003576279, 0.009999999776482582], "delta_rot": [-6.022200107574463, -0.31929999589920044, -0.08240000158548355], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.0778}, "right": {"delta_pos": [-0.006500000134110451, 0.007499999832361937, -9.999999747378752e-05], "delta_rot": [-0.10980000346899033, -0.06889999657869339, -0.13410000503063202], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0099}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.011699999682605267, -0.05270000174641609, -0.030500000342726707], "delta_rot": [-0.09700000286102295, -0.20739999413490295, -0.11620000004768372], "gripper_changed": true, "flow_direction": "-Y(Right) and -Z(Down)", "magnitude": 0.062}, "right": {"delta_pos": [0.00039999998989515007, 0.0031999999191612005, -0.0006000000284984708], "delta_rot": [-0.09510000050067902, -0.06889999657869339, -0.19179999828338623], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0033}} + + ========================================= + [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 zipper pull of the bag to initiate opening, while right arm stabilizes the bag body.", + "actions": [ + { + "reasoning_cot": "The left arm moves from a hovering position towards the bag's zipper area. Visual evidence in frames 4-8 shows the gripper closing around the metal zipper pull tab. The kinematic data confirms a significant delta in position (-X, -Y) followed by a gripper change event (closing). This indicates a transition from approach to grasp on the specific 'zipper_pull' anchor.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "zipper_pull" + }, + "spatial_logic": "moving from free space to zipper_pull", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains relatively stationary, maintaining contact with the top surface/body of the bag to provide stability while the left arm manipulates the zipper. The visual input shows the right gripper pressing against the silver reflective patch on the bag's top. Kinematics show minimal movement (hovering/stabilizing).", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "hold", + "semantic_action": "stabilize", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "top_surface" + }, + "spatial_logic": "static_at_top_surface", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "zipper_pull", + "current_status": "grasped" + } + ], + "task_progress": "Initiating bag opening by securing the zipper pull." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and grasps the zipper pull of the bag to initiate opening, while right arm stabilizes the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "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": 0.13, "angle": 6.2, "vel_score": 0.95, "angle_score": 6.07, "vel_fft": [0.13, 0.025, 0.03, 0.025, 0.016, 0.012, 0.013, 0.01, 0.009, 0.009, 0.008, 0.005, 0.006, 0.005, 0.005, 0.008, 0.006, 0.006], "angle_fft": [6.196, 5.689, 5.572, 5.592, 5.556, 5.369, 5.495, 5.495, 5.39, 5.443, 5.486, 5.431, 5.463, 5.469, 5.446, 5.466, 5.462, 5.442]}, "right": {"vel": 0.01, "angle": 0.05, "vel_score": 0.07, "angle_score": 0.51, "vel_fft": [0.007, 0.007, 0.006, 0.005, 0.004, 0.003, 0.003, 0.002, 0.002, 0.002, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.002], "angle_fft": [0.054, 0.05, 0.04, 0.029, 0.02, 0.011, 0.007, 0.01, 0.012, 0.011, 0.009, 0.009, 0.008, 0.004, 0.005, 0.008, 0.009, 0.008]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.12, "left_arm_ry": 0.46, "left_arm_rz": 2.02, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.61, "right_arm_ry": 0.59, "right_arm_rz": -2.29, "right_gripper": 0.04}, "1": {"left_arm_vel": 0.068, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 0.42, "left_arm_rz": 2.01, "left_gripper": -0.01, "right_arm_vel": 0.068, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.6, "right_arm_rz": -2.31, "right_gripper": 0.04}, "2": {"left_arm_vel": 0.057, "left_gripper_vel": -0.021, "left_arm_rx": -3.03, "left_arm_ry": 0.41, "left_arm_rz": 2.0, "left_gripper": -0.01, "right_arm_vel": 0.057, "right_gripper_vel": -0.021, "right_arm_rx": 2.62, "right_arm_ry": 0.6, "right_arm_rz": -2.32, "right_gripper": 0.04}, "3": {"left_arm_vel": 0.024, "left_gripper_vel": 0.0, "left_arm_rx": -3.03, "left_arm_ry": 0.42, "left_arm_rz": 2.0, "left_gripper": -0.01, "right_arm_vel": 0.024, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.6, "right_arm_rz": -2.33, "right_gripper": 0.04}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.1, "left_arm_ry": 0.51, "left_arm_rz": 2.02, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.35, "right_gripper": 0.04}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 3.05, "left_arm_ry": 0.61, "left_arm_rz": 2.01, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.35, "right_gripper": 0.04}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.99, "left_arm_ry": 0.63, "left_arm_rz": 2.0, "left_gripper": 0.11, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.35, "right_gripper": 0.04}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.95, "left_arm_ry": 0.65, "left_arm_rz": 1.99, "left_gripper": 0.2, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.35, "right_gripper": 0.04}, "8": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.92, "left_arm_ry": 0.66, "left_arm_rz": 1.99, "left_gripper": 0.3, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.35, "right_gripper": 0.04}, "9": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.89, "left_arm_ry": 0.67, "left_arm_rz": 1.99, "left_gripper": 0.38, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.35, "right_gripper": 0.04}, "10": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.88, "left_arm_ry": 0.67, "left_arm_rz": 2.01, "left_gripper": 0.46, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.35, "right_gripper": 0.04}, "11": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.87, "left_arm_ry": 0.64, "left_arm_rz": 2.02, "left_gripper": 0.51, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.35, "right_gripper": 0.04}, "12": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.88, "left_arm_ry": 0.55, "left_arm_rz": 2.01, "left_gripper": 0.48, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.35, "right_gripper": 0.04}, "13": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.78, "left_arm_ry": 0.58, "left_arm_rz": 1.99, "left_gripper": 0.45, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.35, "right_gripper": 0.04}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.050200000405311584, 0.0031999999191612005, -0.039000000804662704], "delta_rot": [5.9028000831604, 0.12290000170469284, -0.02800000086426735], "gripper_changed": true, "flow_direction": "+X(Forward) and -Z(Down)", "magnitude": 0.0636}, "right": {"delta_pos": [0.006500000134110451, -0.004999999888241291, -0.00039999998989515007], "delta_rot": [0.008799999952316284, -0.002099999925121665, -0.05339999869465828], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0082}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.06650000065565109, -0.017000000923871994, -0.0568000003695488], "delta_rot": [5.8933000564575195, 0.1412999927997589, -0.0357000008225441], "gripper_changed": true, "flow_direction": "+X(Forward) and -Z(Down)", "magnitude": 0.0891}, "right": {"delta_pos": [0.007699999958276749, -0.005499999970197678, -0.0008999999845400453], "delta_rot": [0.02630000002682209, 0.002300000051036477, -0.04910000041127205], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0095}} + + ========================================= + [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 retreats from the bag zipper area to clear space, while right arm maintains a stabilizing hold on the bag body.", + "actions": [ + { + "reasoning_cot": "The left arm is observed moving away from the bag (visible in frames 7-8) after previously interacting with the zipper. The gripper is open and remains open, indicating a retreat motion rather than a grasp or release. This clears the workspace for subsequent actions.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "retreat", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "moving away from bag:zipper_pull to free space", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains stationary with its gripper jaws closed around the side of the bag (visible in all frames). This provides necessary stabilization for the bag while the left arm operates or retreats. No movement or state change is detected.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": "stabilize", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "static_at_bag_side", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Left arm has cleared the immediate vicinity of the zipper; right arm continues to stabilize the bag." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm retreats from the bag zipper area to clear space, while right arm maintains a stabilizing hold on the bag body.", "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": 0.15, "vel_score": 0.3, "angle_score": 1.35, "vel_fft": [0.032, 0.007, 0.001, 0.012, 0.004, 0.005, 0.002, 0.003, 0.002, 0.002, 0.001, 0.003, 0.002, 0.001, 0.002, 0.0, 0.001, 0.001, 0.001, 0.001], "angle_fft": [0.148, 0.02, 0.048, 0.026, 0.035, 0.012, 0.019, 0.017, 0.01, 0.01, 0.004, 0.001, 0.003, 0.004, 0.003, 0.003, 0.008, 0.005, 0.005, 0.008]}, "right": {"vel": 0.0, "angle": 0.02, "vel_score": 0.01, "angle_score": 0.15, "vel_fft": [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, 0.0], "angle_fft": [0.015, 0.01, 0.007, 0.005, 0.006, 0.001, 0.001, 0.004, 0.005, 0.005, 0.001, 0.003, 0.002, 0.001, 0.001, 0.002, 0.002, 0.001, 0.003, 0.001]}, "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": 1.99, "left_gripper": 0.45, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.35, "right_gripper": 0.04}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.78, "left_arm_ry": 0.59, "left_arm_rz": 2.03, "left_gripper": 0.4, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.35, "right_gripper": 0.04}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.81, "left_arm_ry": 0.59, "left_arm_rz": 2.06, "left_gripper": 0.37, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.34, "right_gripper": 0.04}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.8, "left_arm_ry": 0.61, "left_arm_rz": 2.05, "left_gripper": 0.32, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.35, "right_gripper": 0.04}, "4": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": 2.79, "left_arm_ry": 0.61, "left_arm_rz": 2.01, "left_gripper": 0.28, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.59, "right_arm_rz": -2.34, "right_gripper": 0.04}, "5": {"left_arm_vel": 0.006, "left_gripper_vel": 0.0, "left_arm_rx": 2.79, "left_arm_ry": 0.6, "left_arm_rz": 2.0, "left_gripper": 0.16, "right_arm_vel": 0.006, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.59, "right_arm_rz": -2.35, "right_gripper": 0.04}, "6": {"left_arm_vel": 0.004, "left_gripper_vel": 0.0, "left_arm_rx": 2.79, "left_arm_ry": 0.6, "left_arm_rz": 1.99, "left_gripper": 0.04, "right_arm_vel": 0.004, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.6, "right_arm_rz": -2.34, "right_gripper": 0.04}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.77, "left_arm_ry": 0.6, "left_arm_rz": 1.99, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.6, "right_arm_rz": -2.34, "right_gripper": 0.04}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.01549999974668026, -0.019999999552965164, -0.016699999570846558], "delta_rot": [-0.007799999788403511, 0.01940000057220459, -0.007799999788403511], "gripper_changed": true, "flow_direction": "-Y(Right)", "magnitude": 0.0303}, "right": {"delta_pos": [0.0012000000569969416, -0.0005000000237487257, -0.0005000000237487257], "delta_rot": [0.017500000074505806, 0.004399999976158142, 0.004399999976158142], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0014}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.061500001698732376, 0.013299999758601189, 0.041999999433755875], "delta_rot": [0.33410000801086426, -0.030300000682473183, 0.20329999923706055], "gripper_changed": true, "flow_direction": "-X(Backward) and +Z(Up)", "magnitude": 0.0757}, "right": {"delta_pos": [-0.012500000186264515, 0.012600000016391277, 0.0008999999845400453], "delta_rot": [-0.125900000333786, -0.11249999701976776, -0.12729999423027039], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0178}} + + ========================================= + [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 zipper pull to initiate grasping, while right arm maintains a stabilizing hold on the bag body.", + "actions": [ + { + "reasoning_cot": "The left arm moves from a hovering position towards the bag's zipper area. Visual evidence in frames T0-T1 shows the gripper aligning with the zipper pull. The gripper signal indicates 'closing' (delta from 0.45 to -0.01), confirming an intent to grasp the zipper pull.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "touching" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "zipper_pull" + }, + "spatial_logic": "moving from hover to zipper_pull", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains stationary relative to the bag body, providing stability. Kinematic data shows near-zero velocity and no gripper change. It is maintaining contact with the bag surface to prevent movement while the left arm operates.", + "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_body", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "zipper_pull", + "current_status": "being_grasped" + } + ], + "task_progress": "Initiating interaction with bag zipper." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "being_grasped"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches the bag zipper pull to initiate grasping, while right arm maintains a stabilizing hold on the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "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": 0.09, "angle": 0.35, "vel_score": 0.82, "angle_score": 3.19, "vel_fft": [0.088, 0.017, 0.026, 0.012, 0.0, 0.004, 0.003, 0.001, 0.001, 0.001, 0.002, 0.001, 0.001, 0.001, 0.002, 0.002, 0.001, 0.001, 0.001, 0.0], "angle_fft": [0.35, 0.091, 0.051, 0.074, 0.024, 0.037, 0.011, 0.015, 0.024, 0.008, 0.009, 0.008, 0.012, 0.009, 0.008, 0.015, 0.001, 0.01, 0.007, 0.008]}, "right": {"vel": 0.01, "angle": 0.16, "vel_score": 0.13, "angle_score": 1.41, "vel_fft": [0.014, 0.006, 0.004, 0.004, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.002, 0.002, 0.0, 0.001, 0.001, 0.0, 0.001, 0.001, 0.001, 0.0], "angle_fft": [0.163, 0.04, 0.03, 0.026, 0.026, 0.036, 0.028, 0.024, 0.02, 0.029, 0.019, 0.015, 0.016, 0.015, 0.011, 0.01, 0.005, 0.007, 0.002, 0.017]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.78, "left_arm_ry": 0.6, "left_arm_rz": 1.99, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.6, "right_arm_rz": -2.34, "right_gripper": 0.04}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.88, "left_arm_ry": 0.6, "left_arm_rz": 2.1, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.59, "right_arm_rz": -2.34, "right_gripper": 0.04}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.95, "left_arm_ry": 0.6, "left_arm_rz": 2.12, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.59, "right_arm_rz": -2.36, "right_gripper": 0.04}, "3": {"left_arm_vel": 0.045, "left_gripper_vel": 0.0, "left_arm_rx": 3.04, "left_arm_ry": 0.58, "left_arm_rz": 2.14, "left_gripper": -0.01, "right_arm_vel": 0.045, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.57, "right_arm_rz": -2.37, "right_gripper": 0.04}, "4": {"left_arm_vel": 0.011, "left_gripper_vel": 0.0, "left_arm_rx": 3.11, "left_arm_ry": 0.57, "left_arm_rz": 2.15, "left_gripper": -0.01, "right_arm_vel": 0.011, "right_gripper_vel": 0.0, "right_arm_rx": 2.58, "right_arm_ry": 0.55, "right_arm_rz": -2.39, "right_gripper": 0.04}, "5": {"left_arm_vel": 0.04, "left_gripper_vel": 0.0, "left_arm_rx": 3.11, "left_arm_ry": 0.55, "left_arm_rz": 2.16, "left_gripper": -0.01, "right_arm_vel": 0.04, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.53, "right_arm_rz": -2.41, "right_gripper": 0.04}, "6": {"left_arm_vel": 0.045, "left_gripper_vel": 0.0, "left_arm_rx": 3.12, "left_arm_ry": 0.55, "left_arm_rz": 2.17, "left_gripper": -0.01, "right_arm_vel": 0.045, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.51, "right_arm_rz": -2.43, "right_gripper": 0.04}, "7": {"left_arm_vel": 0.007, "left_gripper_vel": 0.0, "left_arm_rx": 3.12, "left_arm_ry": 0.55, "left_arm_rz": 2.2, "left_gripper": -0.01, "right_arm_vel": 0.007, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.48, "right_arm_rz": -2.47, "right_gripper": 0.04}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.07689999788999557, 0.032999999821186066, 0.05900000035762787], "delta_rot": [0.33799999952316284, -0.04780000075697899, 0.20890000462532043], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1024}, "right": {"delta_pos": [-0.013799999840557575, 0.013100000098347664, 0.00139999995008111], "delta_rot": [-0.14470000565052032, -0.11659999936819077, -0.13249999284744263], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.019}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.01979999989271164, 0.027699999511241913, 0.045899998396635056], "delta_rot": [0.32659998536109924, -0.029500000178813934, 0.3301999866962433], "gripper_changed": false, "flow_direction": "+Y(Left) and +Z(Up)", "magnitude": 0.0571}, "right": {"delta_pos": [0.010599999688565731, -0.01209999993443489, 0.0020000000949949026], "delta_rot": [-0.04529999941587448, 0.00570000009611249, -0.10379999876022339], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0162}} + + ========================================= + [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 executes a precise grasp on the bag's zipper pull to initiate opening, while the right arm maintains a stabilizing hold on the bag body.", + "actions": [ + { + "reasoning_cot": "The left arm approaches the zipper pull (visible in T0) and closes its gripper around it (T1-T2). The kinematic data shows a small but deliberate movement (-X, +Y) consistent with aligning with the pull tab. Visual evidence confirms the gripper jaws are closing around the metal ring of the 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": "zipper_pull" + }, + "spatial_logic": "Approaching and securing grip on zipper_pull from free space", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains stationary relative to the bag body throughout the sequence. It is visually confirmed to be holding the side/corner of the bag to provide counter-tension for the left arm's upcoming pull action. No significant movement or state change occurs.", + "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 stabilization at bag:main_body", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "zipper_pull", + "current_status": "grasped" + } + ], + "task_progress": "Left arm has successfully grasped the zipper pull; ready to unzip." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm executes a precise grasp on the bag's zipper pull to initiate opening, while the right arm maintains a stabilizing hold on the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "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": 0.08, "angle": 0.42, "vel_score": 0.57, "angle_score": 2.8, "vel_fft": [0.08, 0.049, 0.008, 0.007, 0.003, 0.001, 0.002, 0.001, 0.002, 0.004, 0.002, 0.002, 0.002], "angle_fft": [0.418, 0.187, 0.075, 0.084, 0.021, 0.016, 0.008, 0.025, 0.008, 0.023, 0.006, 0.007, 0.019]}, "right": {"vel": 0.04, "angle": 0.52, "vel_score": 0.31, "angle_score": 3.24, "vel_fft": [0.044, 0.023, 0.015, 0.007, 0.002, 0.003, 0.002, 0.002, 0.0, 0.0, 0.001, 0.002, 0.002], "angle_fft": [0.518, 0.061, 0.042, 0.106, 0.032, 0.029, 0.032, 0.04, 0.025, 0.036, 0.027, 0.025, 0.015]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 3.12, "left_arm_ry": 0.56, "left_arm_rz": 2.21, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.47, "right_arm_rz": -2.49, "right_gripper": 0.04}, "1": {"left_arm_vel": 0.089, "left_gripper_vel": 0.0, "left_arm_rx": 3.08, "left_arm_ry": 0.6, "left_arm_rz": 2.21, "left_gripper": -0.01, "right_arm_vel": 0.089, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.45, "right_arm_rz": -2.55, "right_gripper": 0.04}, "2": {"left_arm_vel": 0.113, "left_gripper_vel": 0.0, "left_arm_rx": 3.06, "left_arm_ry": 0.62, "left_arm_rz": 2.22, "left_gripper": -0.01, "right_arm_vel": 0.113, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.44, "right_arm_rz": -2.57, "right_gripper": 0.04}, "3": {"left_arm_vel": 0.117, "left_gripper_vel": 0.0, "left_arm_rx": 3.03, "left_arm_ry": 0.67, "left_arm_rz": 2.26, "left_gripper": -0.01, "right_arm_vel": 0.117, "right_gripper_vel": 0.0, "right_arm_rx": 2.48, "right_arm_ry": 0.44, "right_arm_rz": -2.62, "right_gripper": 0.04}, "4": {"left_arm_vel": 0.075, "left_gripper_vel": 0.0, "left_arm_rx": 3.03, "left_arm_ry": 0.67, "left_arm_rz": 2.29, "left_gripper": -0.01, "right_arm_vel": 0.075, "right_gripper_vel": 0.0, "right_arm_rx": 2.48, "right_arm_ry": 0.44, "right_arm_rz": -2.63, "right_gripper": 0.04}, "5": {"left_arm_vel": 0.061, "left_gripper_vel": 0.0, "left_arm_rx": 3.04, "left_arm_ry": 0.65, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.061, "right_gripper_vel": 0.0, "right_arm_rx": 2.5, "right_arm_ry": 0.46, "right_arm_rz": -2.61, "right_gripper": 0.04}, "6": {"left_arm_vel": 0.027, "left_gripper_vel": -0.021, "left_arm_rx": 3.07, "left_arm_ry": 0.62, "left_arm_rz": 2.32, "left_gripper": -0.01, "right_arm_vel": 0.027, "right_gripper_vel": -0.021, "right_arm_rx": 2.53, "right_arm_ry": 0.49, "right_arm_rz": -2.57, "right_gripper": 0.04}, "7": {"left_arm_vel": 0.008, "left_gripper_vel": -0.042, "left_arm_rx": 3.09, "left_arm_ry": 0.59, "left_arm_rz": 2.32, "left_gripper": -0.01, "right_arm_vel": 0.008, "right_gripper_vel": -0.042, "right_arm_rx": 2.55, "right_arm_ry": 0.5, "right_arm_rz": -2.54, "right_gripper": 0.04}, "8": {"left_arm_vel": 0.01, "left_gripper_vel": 0.147, "left_arm_rx": 3.1, "left_arm_ry": 0.58, "left_arm_rz": 2.32, "left_gripper": -0.01, "right_arm_vel": 0.01, "right_gripper_vel": 0.147, "right_arm_rx": 2.56, "right_arm_ry": 0.52, "right_arm_rz": -2.52, "right_gripper": 0.04}, "9": {"left_arm_vel": 0.006, "left_gripper_vel": 0.567, "left_arm_rx": 3.1, "left_arm_ry": 0.58, "left_arm_rz": 2.32, "left_gripper": -0.01, "right_arm_vel": 0.006, "right_gripper_vel": 0.567, "right_arm_rx": 2.57, "right_arm_ry": 0.53, "right_arm_rz": -2.5, "right_gripper": 0.06}, "10": {"left_arm_vel": 0.037, "left_gripper_vel": 1.491, "left_arm_rx": 3.1, "left_arm_ry": 0.57, "left_arm_rz": 2.32, "left_gripper": -0.01, "right_arm_vel": 0.037, "right_gripper_vel": 1.491, "right_arm_rx": 2.58, "right_arm_ry": 0.56, "right_arm_rz": -2.48, "right_gripper": 0.15}, "11": {"left_arm_vel": 0.041, "left_gripper_vel": 2.142, "left_arm_rx": 3.1, "left_arm_ry": 0.57, "left_arm_rz": 2.32, "left_gripper": -0.01, "right_arm_vel": 0.041, "right_gripper_vel": 2.142, "right_arm_rx": 2.59, "right_arm_ry": 0.58, "right_arm_rz": -2.46, "right_gripper": 0.22}, "12": {"left_arm_vel": 0.034, "left_gripper_vel": 2.058, "left_arm_rx": 3.1, "left_arm_ry": 0.57, "left_arm_rz": 2.32, "left_gripper": -0.01, "right_arm_vel": 0.034, "right_gripper_vel": 2.058, "right_arm_rx": 2.59, "right_arm_ry": 0.6, "right_arm_rz": -2.45, "right_gripper": 0.29}, "13": {"left_arm_vel": 0.034, "left_gripper_vel": 2.058, "left_arm_rx": 3.1, "left_arm_ry": 0.57, "left_arm_rz": 2.32, "left_gripper": -0.01, "right_arm_vel": 0.034, "right_gripper_vel": 2.058, "right_arm_rx": 2.59, "right_arm_ry": 0.6, "right_arm_rz": -2.45, "right_gripper": 0.29}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.05730000138282776, -0.004999999888241291, -0.013199999928474426], "delta_rot": [-0.019300000742077827, 0.013700000010430813, 0.11169999837875366], "gripper_changed": false, "flow_direction": "+X(Forward)", "magnitude": 0.059}, "right": {"delta_pos": [0.02410000003874302, -0.02500000037252903, 0.0007999999797903001], "delta_rot": [0.10159999877214432, 0.13099999725818634, 0.040800001472234726], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right)", "magnitude": 0.0348}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.05730000138282776, -0.004600000102072954, -0.013399999588727951], "delta_rot": [-0.026000000536441803, 0.00989999994635582, 0.10400000214576721], "gripper_changed": false, "flow_direction": "+X(Forward)", "magnitude": 0.059}, "right": {"delta_pos": [0.019999999552965164, -0.006500000134110451, 0.008899999782443047], "delta_rot": [0.13249999284744263, 0.31850001215934753, 0.17479999363422394], "gripper_changed": true, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0228}} + + ========================================= + [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 executes a precise grasp on the bag's zipper pull to initiate opening, while the right arm maintains a stabilizing hold on the bag body.", + "actions": [ + { + "reasoning_cot": "The left arm approaches and secures the metal zipper pull tab. Visual evidence shows the gripper closing around the tab (Frames 2-4) and maintaining a secure hold to apply tension for unzipping. The spatial logic involves moving from an approach vector to a secured grasp on the specific 'zipper_pull' anchor.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "zipper_pull" + }, + "spatial_logic": "approaching and grasping zipper_pull", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains stationary relative to the bag's main body, providing counter-tension. The gripper is closed and holding the fabric firmly to prevent the bag from sliding while the left arm manipulates the zipper. No significant movement or state change occurs for this arm.", + "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_hold_on_bag_body", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "zipper_pull", + "current_status": "grasped" + } + ], + "task_progress": "Initiating bag opening by securing the zipper pull with the left arm while stabilizing the bag with the right." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm executes a precise grasp on the bag's zipper pull to initiate opening, while the right arm maintains a stabilizing hold on the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "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": 0.0, "angle": 0.03, "vel_score": 0.01, "angle_score": 0.12, "vel_fft": [0.002, 0.001, 0.0, 0.0, 0.001, 0.001], "angle_fft": [0.034, 0.004, 0.007, 0.002, 0.009, 0.015]}, "right": {"vel": 0.06, "angle": 0.56, "vel_score": 0.22, "angle_score": 1.99, "vel_fft": [0.061, 0.016, 0.005, 0.007, 0.006, 0.009], "angle_fft": [0.559, 0.118, 0.067, 0.053, 0.072, 0.075]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 3.1, "left_arm_ry": 0.57, "left_arm_rz": 2.32, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.63, "right_arm_rz": -2.42, "right_gripper": 0.34}, "1": {"left_arm_vel": 0.039, "left_gripper_vel": 1.029, "left_arm_rx": 3.1, "left_arm_ry": 0.57, "left_arm_rz": 2.32, "left_gripper": -0.01, "right_arm_vel": 0.039, "right_gripper_vel": 1.029, "right_arm_rx": 2.61, "right_arm_ry": 0.65, "right_arm_rz": -2.4, "right_gripper": 0.37}, "2": {"left_arm_vel": 0.046, "left_gripper_vel": 0.567, "left_arm_rx": 3.11, "left_arm_ry": 0.57, "left_arm_rz": 2.32, "left_gripper": -0.01, "right_arm_vel": 0.046, "right_gripper_vel": 0.567, "right_arm_rx": 2.61, "right_arm_ry": 0.67, "right_arm_rz": -2.39, "right_gripper": 0.39}, "3": {"left_arm_vel": 0.04, "left_gripper_vel": 0.315, "left_arm_rx": 3.1, "left_arm_ry": 0.57, "left_arm_rz": 2.32, "left_gripper": -0.01, "right_arm_vel": 0.04, "right_gripper_vel": 0.315, "right_arm_rx": 2.61, "right_arm_ry": 0.7, "right_arm_rz": -2.38, "right_gripper": 0.4}, "4": {"left_arm_vel": 0.044, "left_gripper_vel": 0.168, "left_arm_rx": 3.1, "left_arm_ry": 0.57, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.044, "right_gripper_vel": 0.168, "right_arm_rx": 2.62, "right_arm_ry": 0.71, "right_arm_rz": -2.36, "right_gripper": 0.4}, "5": {"left_arm_vel": 0.087, "left_gripper_vel": 0.084, "left_arm_rx": 3.1, "left_arm_ry": 0.57, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.087, "right_gripper_vel": 0.084, "right_arm_rx": 2.6, "right_arm_ry": 0.75, "right_arm_rz": -2.34, "right_gripper": 0.41}, "6": {"left_arm_vel": 0.1, "left_gripper_vel": 0.021, "left_arm_rx": 3.1, "left_arm_ry": 0.57, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.1, "right_gripper_vel": 0.021, "right_arm_rx": 2.61, "right_arm_ry": 0.77, "right_arm_rz": -2.32, "right_gripper": 0.41}, "7": {"left_arm_vel": 0.101, "left_gripper_vel": 0.0, "left_arm_rx": 3.1, "left_arm_ry": 0.57, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.101, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.79, "right_arm_rz": -2.31, "right_gripper": 0.41}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [9.999999747378752e-05, 0.0003000000142492354, -9.999999747378752e-05], "delta_rot": [-0.006399999838322401, -0.002199999988079071, -0.006399999838322401], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0003}, "right": {"delta_pos": [-0.005200000014156103, 0.01889999955892563, 0.007600000128149986], "delta_rot": [0.01979999989271164, 0.16290000081062317, 0.11110000312328339], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.021}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.0017000000225380063, 0.0010999999940395355, 0.0005000000237487257], "delta_rot": [-0.017500000074505806, 0.008899999782443047, -0.004000000189989805], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0021}, "right": {"delta_pos": [-0.007699999958276749, 0.0340999998152256, -0.015399999916553497], "delta_rot": [0.035100001841783524, 0.12160000205039978, 0.10130000114440918], "gripper_changed": false, "flow_direction": "+Y(Left)", "magnitude": 0.0382}} + + ========================================= + [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 maintains a precise grasp on the bag's zipper pull to initiate opening, while the right arm stabilizes the bag body by holding the top surface.", + "actions": [ + { + "reasoning_cot": "The left end-effector is visually confirmed to be grasping the metal zipper pull. Kinematic data shows minimal positional change but stable gripper closure (gripper value -0.01), indicating a 'hold' action to maintain tension or prepare for a pull. The target is specifically the zipper mechanism.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "zipper_pull" + }, + "spatial_logic": "static_at_zipper_pull", + "topology_change": false + }, + { + "reasoning_cot": "The right end-effector is pressing against the silver textured top surface of the bag. This provides counter-force/stabilization for the left arm's operation on the zipper. The gripper is slightly open/pressing (value ~0.4), consistent with a stabilizing touch rather than a lift.", + "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:top_surface" + }, + "spatial_logic": "static_at_top_surface", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Arms are positioned and secured on the bag; left arm holds zipper pull, right arm stabilizes body. Ready to execute zipper opening." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm maintains a precise grasp on the bag's zipper pull to initiate opening, while the right arm stabilizes the bag body by holding the top surface.", "left_end_effector": {"grasp_status": "holding", "contact_target": "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": 0.0, "angle": 0.02, "vel_score": 0.01, "angle_score": 0.12, "vel_fft": [0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.001, 0.0, 0.001, 0.001, 0.001], "angle_fft": [0.02, 0.0, 0.003, 0.004, 0.002, 0.002, 0.002, 0.002, 0.004, 0.004, 0.003, 0.005, 0.002, 0.003]}, "right": {"vel": 0.04, "angle": 0.31, "vel_score": 0.27, "angle_score": 1.89, "vel_fft": [0.042, 0.015, 0.011, 0.005, 0.005, 0.001, 0.004, 0.005, 0.003, 0.003, 0.003, 0.001, 0.001, 0.003], "angle_fft": [0.306, 0.045, 0.039, 0.09, 0.032, 0.034, 0.033, 0.043, 0.026, 0.019, 0.01, 0.034, 0.019, 0.009]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 3.1, "left_arm_ry": 0.57, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.8, "right_arm_rz": -2.31, "right_gripper": 0.41}, "1": {"left_arm_vel": 0.081, "left_gripper_vel": 0.0, "left_arm_rx": 3.1, "left_arm_ry": 0.57, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.081, "right_gripper_vel": 0.0, "right_arm_rx": 2.65, "right_arm_ry": 0.82, "right_arm_rz": -2.31, "right_gripper": 0.41}, "2": {"left_arm_vel": 0.062, "left_gripper_vel": -0.126, "left_arm_rx": 3.09, "left_arm_ry": 0.57, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.062, "right_gripper_vel": -0.126, "right_arm_rx": 2.67, "right_arm_ry": 0.82, "right_arm_rz": -2.29, "right_gripper": 0.41}, "3": {"left_arm_vel": 0.036, "left_gripper_vel": -0.042, "left_arm_rx": 3.09, "left_arm_ry": 0.57, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.036, "right_gripper_vel": -0.042, "right_arm_rx": 2.72, "right_arm_ry": 0.81, "right_arm_rz": -2.25, "right_gripper": 0.4}, "4": {"left_arm_vel": 0.059, "left_gripper_vel": -0.042, "left_arm_rx": 3.09, "left_arm_ry": 0.57, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.059, "right_gripper_vel": -0.042, "right_arm_rx": 2.72, "right_arm_ry": 0.8, "right_arm_rz": -2.25, "right_gripper": 0.39}, "5": {"left_arm_vel": 0.099, "left_gripper_vel": 0.0, "left_arm_rx": 3.09, "left_arm_ry": 0.58, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.099, "right_gripper_vel": 0.0, "right_arm_rx": 2.71, "right_arm_ry": 0.79, "right_arm_rz": -2.26, "right_gripper": 0.39}, "6": {"left_arm_vel": 0.086, "left_gripper_vel": -0.189, "left_arm_rx": 3.09, "left_arm_ry": 0.58, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.086, "right_gripper_vel": -0.189, "right_arm_rx": 2.7, "right_arm_ry": 0.78, "right_arm_rz": -2.27, "right_gripper": 0.38}, "7": {"left_arm_vel": 0.054, "left_gripper_vel": -0.672, "left_arm_rx": 3.09, "left_arm_ry": 0.58, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.054, "right_gripper_vel": -0.672, "right_arm_rx": 2.69, "right_arm_ry": 0.77, "right_arm_rz": -2.28, "right_gripper": 0.36}, "8": {"left_arm_vel": 0.024, "left_gripper_vel": -2.52, "left_arm_rx": 3.09, "left_arm_ry": 0.58, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.024, "right_gripper_vel": -2.52, "right_arm_rx": 2.67, "right_arm_ry": 0.77, "right_arm_rz": -2.29, "right_gripper": 0.24}, "9": {"left_arm_vel": 0.025, "left_gripper_vel": -2.835, "left_arm_rx": 3.09, "left_arm_ry": 0.58, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.025, "right_gripper_vel": -2.835, "right_arm_rx": 2.67, "right_arm_ry": 0.77, "right_arm_rz": -2.29, "right_gripper": 0.14}, "10": {"left_arm_vel": 0.013, "left_gripper_vel": -1.281, "left_arm_rx": 3.09, "left_arm_ry": 0.58, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.013, "right_gripper_vel": -1.281, "right_arm_rx": 2.66, "right_arm_ry": 0.76, "right_arm_rz": -2.29, "right_gripper": 0.1}, "11": {"left_arm_vel": 0.01, "left_gripper_vel": -0.021, "left_arm_rx": 3.09, "left_arm_ry": 0.58, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.01, "right_gripper_vel": -0.021, "right_arm_rx": 2.66, "right_arm_ry": 0.76, "right_arm_rz": -2.29, "right_gripper": 0.1}, "12": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": 3.09, "left_arm_ry": 0.58, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.76, "right_arm_rz": -2.29, "right_gripper": 0.1}, "13": {"left_arm_vel": 0.004, "left_gripper_vel": 0.0, "left_arm_rx": 3.09, "left_arm_ry": 0.58, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.004, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.75, "right_arm_rz": -2.32, "right_gripper": 0.1}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.001500000013038516, 0.0007999999797903001, 0.0005000000237487257], "delta_rot": [-0.010300000198185444, 0.010300000198185444, 0.002400000113993883], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0018}, "right": {"delta_pos": [-0.0017000000225380063, 0.012000000104308128, -0.02329999953508377], "delta_rot": [0.006099999882280827, -0.050999999046325684, -0.013700000010430813], "gripper_changed": false, "flow_direction": "-Z(Down)", "magnitude": 0.0263}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.041200000792741776, 0.006099999882280827, 0.024399999529123306], "delta_rot": [-6.147200107574463, -0.028999999165534973, 0.020400000736117363], "gripper_changed": false, "flow_direction": "-X(Backward) and +Z(Up)", "magnitude": 0.0483}, "right": {"delta_pos": [0.00019999999494757503, 0.010300000198185444, -0.023800000548362732], "delta_rot": [-0.08380000293254852, -0.14390000700950623, -0.1931000053882599], "gripper_changed": false, "flow_direction": "-Z(Down)", "magnitude": 0.0259}} + + ========================================= + [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 maintains a precise grasp on the bag's zipper pull to initiate opening, while the right arm stabilizes the bag body by holding the top surface.", + "actions": [ + { + "reasoning_cot": "The left gripper is visually confirmed to be clamped around the metal zipper pull tab. The kinematic data shows zero velocity and stable gripper width (-0.01), indicating a static hold to anchor the zipper mechanism against the pulling force of 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": "zipper_pull" + }, + "spatial_logic": "static_at_zipper_pull", + "topology_change": false + }, + { + "reasoning_cot": "The right gripper is pressing down on the silver reflective top surface of the bag. This action provides the necessary counter-force (stabilization) to allow the left arm to manipulate the zipper without dragging the entire bag across the table. The slight negative Z-delta in kinematics confirms a pressing/stabilizing motion.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "press", + "semantic_action": "stabilize", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "stabilizing_top_surface", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Initiating bag opening sequence; left arm anchored on zipper, right arm stabilizing 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm maintains a precise grasp on the bag's zipper pull to initiate opening, while the right arm stabilizes the bag body by holding the top surface.", "left_end_effector": {"grasp_status": "holding", "contact_target": "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": 0.09, "angle": 10.74, "vel_score": 0.45, "angle_score": 1.72, "vel_fft": [0.086, 0.027, 0.011, 0.008, 0.002, 0.002, 0.003, 0.004, 0.003, 0.001], "angle_fft": [10.736, 10.485, 10.462, 10.397, 10.39, 10.452, 10.409, 10.417, 10.446, 10.424]}, "right": {"vel": 0.01, "angle": 0.35, "vel_score": 0.02, "angle_score": 1.72, "vel_fft": [0.005, 0.001, 0.001, 0.001, 0.0, 0.001, 0.001, 0.001, 0.001, 0.0], "angle_fft": [0.345, 0.065, 0.038, 0.058, 0.011, 0.051, 0.024, 0.008, 0.03, 0.012]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 3.09, "left_arm_ry": 0.58, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.74, "right_arm_rz": -2.33, "right_gripper": 0.1}, "1": {"left_arm_vel": 0.007, "left_gripper_vel": 0.0, "left_arm_rx": 3.13, "left_arm_ry": 0.57, "left_arm_rz": 2.33, "left_gripper": -0.01, "right_arm_vel": 0.007, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.72, "right_arm_rz": -2.39, "right_gripper": 0.1}, "2": {"left_arm_vel": 0.008, "left_gripper_vel": 0.0, "left_arm_rx": -3.12, "left_arm_ry": 0.56, "left_arm_rz": 2.35, "left_gripper": -0.01, "right_arm_vel": 0.008, "right_gripper_vel": 0.0, "right_arm_rx": 2.59, "right_arm_ry": 0.69, "right_arm_rz": -2.42, "right_gripper": 0.1}, "3": {"left_arm_vel": 0.005, "left_gripper_vel": 0.0, "left_arm_rx": -3.09, "left_arm_ry": 0.54, "left_arm_rz": 2.35, "left_gripper": -0.01, "right_arm_vel": 0.005, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.68, "right_arm_rz": -2.45, "right_gripper": 0.1}, "4": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -3.09, "left_arm_ry": 0.55, "left_arm_rz": 2.34, "left_gripper": -0.01, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.56, "right_arm_ry": 0.66, "right_arm_rz": -2.48, "right_gripper": 0.1}, "5": {"left_arm_vel": 0.004, "left_gripper_vel": -0.021, "left_arm_rx": -3.08, "left_arm_ry": 0.55, "left_arm_rz": 2.33, "left_gripper": -0.01, "right_arm_vel": 0.004, "right_gripper_vel": -0.021, "right_arm_rx": 2.55, "right_arm_ry": 0.66, "right_arm_rz": -2.49, "right_gripper": 0.1}, "6": {"left_arm_vel": 0.017, "left_gripper_vel": -0.021, "left_arm_rx": -3.07, "left_arm_ry": 0.55, "left_arm_rz": 2.33, "left_gripper": -0.01, "right_arm_vel": 0.017, "right_gripper_vel": -0.021, "right_arm_rx": 2.55, "right_arm_ry": 0.66, "right_arm_rz": -2.5, "right_gripper": 0.1}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 0.54, "left_arm_rz": 2.33, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.65, "right_arm_rz": -2.5, "right_gripper": 0.1}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.04270000010728836, 0.0052999998442828655, 0.023800000548362732], "delta_rot": [-6.136899948120117, -0.03929999843239784, 0.017999999225139618], "gripper_changed": false, "flow_direction": "-X(Backward) and +Z(Up)", "magnitude": 0.0492}, "right": {"delta_pos": [0.0017999999690800905, -0.0017000000225380063, -0.000699999975040555], "delta_rot": [-0.08179999887943268, -0.0885000005364418, -0.1671999990940094], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0026}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.07270000129938126, -0.09449999779462814, 0.01080000028014183], "delta_rot": [-5.9944000244140625, 0.06960000097751617, -0.10599999874830246], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.1197}, "right": {"delta_pos": [0.00839999970048666, -0.014600000344216824, 0.0034000000450760126], "delta_rot": [-0.09059999883174896, -0.11940000206232071, -0.19599999487400055], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0172}} + + ========================================= + [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 maintains a precise grasp on the bag's zipper pull to initiate opening, while the right arm stabilizes the bag body by holding the top surface.", + "actions": [ + { + "reasoning_cot": "The left arm is visually confirmed to be grasping the metal zipper pull. The kinematic data shows a backward (-X) and upward (+Z) flow, consistent with pulling the zipper open. The gripper remains closed (stable) to maintain the hold during this tension phase.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "pull", + "semantic_action": "unzip_bag", + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "Pulling zipper pull along the track to open the bag", + "topology_change": true + }, + { + "reasoning_cot": "The right arm is positioned over the main body of the bag, providing counter-tension/stabilization. Kinematics show minimal movement (hovering), indicating its role is static stabilization rather than active manipulation in this chunk.", + "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": "Stabilizing the bag body to allow left arm to unzip", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_track", + "current_status": "opening" + } + ], + "task_progress": "Initiating the unzipping sequence by pulling the zipper tab while stabilizing the bag base." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm maintains a precise grasp on the bag's zipper pull to initiate opening, while the right arm stabilizes the bag body by holding the top surface.", "left_end_effector": {"grasp_status": "holding", "contact_target": "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": 0.16, "angle": 0.57, "vel_score": 1.1, "angle_score": 3.74, "vel_fft": [0.156, 0.068, 0.028, 0.016, 0.007, 0.003, 0.003, 0.002, 0.009, 0.001, 0.006, 0.003, 0.008, 0.003], "angle_fft": [0.574, 0.046, 0.089, 0.048, 0.06, 0.066, 0.02, 0.029, 0.049, 0.026, 0.02, 0.012, 0.047, 0.032]}, "right": {"vel": 0.02, "angle": 0.06, "vel_score": 0.12, "angle_score": 0.41, "vel_fft": [0.018, 0.013, 0.012, 0.011, 0.007, 0.007, 0.006, 0.006, 0.003, 0.003, 0.004, 0.003, 0.002, 0.004], "angle_fft": [0.064, 0.031, 0.009, 0.004, 0.006, 0.008, 0.009, 0.014, 0.008, 0.005, 0.014, 0.017, 0.01, 0.005]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.03, "left_arm_ry": 0.53, "left_arm_rz": 2.33, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.65, "right_arm_rz": -2.5, "right_gripper": 0.1}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 0.53, "left_arm_rz": 2.35, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.65, "right_arm_rz": -2.51, "right_gripper": 0.1}, "2": {"left_arm_vel": 0.013, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.61, "left_arm_rz": 2.3, "left_gripper": -0.01, "right_arm_vel": 0.013, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.65, "right_arm_rz": -2.51, "right_gripper": 0.1}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.65, "left_arm_rz": 2.25, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.65, "right_arm_rz": -2.52, "right_gripper": 0.1}, "4": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 0.69, "left_arm_rz": 2.2, "left_gripper": -0.01, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.64, "right_arm_rz": -2.51, "right_gripper": 0.1}, "5": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -2.98, "left_arm_ry": 0.71, "left_arm_rz": 2.14, "left_gripper": -0.01, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.64, "right_arm_rz": -2.51, "right_gripper": 0.1}, "6": {"left_arm_vel": 0.029, "left_gripper_vel": 0.231, "left_arm_rx": -2.96, "left_arm_ry": 0.7, "left_arm_rz": 2.17, "left_gripper": 0.02, "right_arm_vel": 0.029, "right_gripper_vel": 0.231, "right_arm_rx": 2.53, "right_arm_ry": 0.64, "right_arm_rz": -2.53, "right_gripper": 0.1}, "7": {"left_arm_vel": 0.071, "left_gripper_vel": 1.05, "left_arm_rx": -2.94, "left_arm_ry": 0.68, "left_arm_rz": 2.18, "left_gripper": 0.05, "right_arm_vel": 0.071, "right_gripper_vel": 1.05, "right_arm_rx": 2.54, "right_arm_ry": 0.63, "right_arm_rz": -2.53, "right_gripper": 0.14}, "8": {"left_arm_vel": 0.123, "left_gripper_vel": 1.764, "left_arm_rx": -2.93, "left_arm_ry": 0.66, "left_arm_rz": 2.19, "left_gripper": 0.1, "right_arm_vel": 0.123, "right_gripper_vel": 1.764, "right_arm_rx": 2.54, "right_arm_ry": 0.63, "right_arm_rz": -2.53, "right_gripper": 0.2}, "9": {"left_arm_vel": 0.155, "left_gripper_vel": 1.806, "left_arm_rx": -2.91, "left_arm_ry": 0.65, "left_arm_rz": 2.21, "left_gripper": 0.14, "right_arm_vel": 0.155, "right_gripper_vel": 1.806, "right_arm_rx": 2.54, "right_arm_ry": 0.62, "right_arm_rz": -2.53, "right_gripper": 0.26}, "10": {"left_arm_vel": 0.155, "left_gripper_vel": 1.806, "left_arm_rx": -2.91, "left_arm_ry": 0.65, "left_arm_rz": 2.21, "left_gripper": 0.14, "right_arm_vel": 0.155, "right_gripper_vel": 1.806, "right_arm_rx": 2.54, "right_arm_ry": 0.62, "right_arm_rz": -2.53, "right_gripper": 0.26}, "11": {"left_arm_vel": 0.155, "left_gripper_vel": 1.806, "left_arm_rx": -2.91, "left_arm_ry": 0.65, "left_arm_rz": 2.21, "left_gripper": 0.14, "right_arm_vel": 0.155, "right_gripper_vel": 1.806, "right_arm_rx": 2.54, "right_arm_ry": 0.62, "right_arm_rz": -2.53, "right_gripper": 0.26}, "12": {"left_arm_vel": 0.155, "left_gripper_vel": 1.806, "left_arm_rx": -2.91, "left_arm_ry": 0.65, "left_arm_rz": 2.21, "left_gripper": 0.14, "right_arm_vel": 0.155, "right_gripper_vel": 1.806, "right_arm_rx": 2.54, "right_arm_ry": 0.62, "right_arm_rz": -2.53, "right_gripper": 0.26}, "13": {"left_arm_vel": 0.155, "left_gripper_vel": 1.806, "left_arm_rx": -2.91, "left_arm_ry": 0.65, "left_arm_rz": 2.21, "left_gripper": 0.14, "right_arm_vel": 0.155, "right_gripper_vel": 1.806, "right_arm_rx": 2.54, "right_arm_ry": 0.62, "right_arm_rz": -2.53, "right_gripper": 0.26}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.027499999850988388, -0.09960000216960907, -0.013100000098347664], "delta_rot": [0.12449999898672104, 0.1193000003695488, -0.1266999989748001], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.1042}, "right": {"delta_pos": [0.006599999964237213, -0.012799999676644802, 0.004100000020116568], "delta_rot": [-0.007300000172108412, -0.029500000178813934, -0.02630000002682209], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.015}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.050599999725818634, -0.009600000455975533, 0.039000000804662704], "delta_rot": [0.07829999923706055, 0.24860000610351562, 0.11680000275373459], "gripper_changed": false, "flow_direction": "+X(Forward) and +Z(Up)", "magnitude": 0.0646}, "right": {"delta_pos": [0.026900000870227814, -0.1565999984741211, 0.04149999842047691], "delta_rot": [-0.0027000000700354576, -0.18050000071525574, -0.2892000079154968], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.1642}} + + ========================================= + [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 pulls the zipper pull to open the bag while right arm stabilizes the bag body.", + "actions": [ + { + "reasoning_cot": "The left arm is visually engaged with the metal ring of the zipper pull. Kinematic data shows a significant backward (-X) and rightward (-Y) displacement (delta_pos: [-0.027, -0.099]), consistent with pulling the zipper along its track to open the bag. The gripper remains closed (stable), indicating a continuous 'pull' action rather than a grasp/release cycle.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "pull", + "semantic_action": "unzip_bag", + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "zipper_pull" + }, + "spatial_logic": "Moving from initial grasp position along the zipper track towards the bag opening.", + "topology_change": true + }, + { + "reasoning_cot": "The right arm maintains a static hold on the main body of the bag to counteract the force applied by the left arm. Kinematic data shows minimal movement (magnitude 0.015) and stable gripper state, confirming its role as a stabilizer/anchor during the unzipping process.", + "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 stabilization at the bag's center/right side.", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_track", + "current_status": "opening" + } + ], + "task_progress": "Bag is being actively unzipped; left arm pulling zipper, right arm stabilizing." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm pulls the zipper pull to open the bag while right arm stabilizes the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "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": 0.29, "angle": 0.77, "vel_score": 1.33, "angle_score": 3.5, "vel_fft": [0.291, 0.039, 0.018, 0.025, 0.024, 0.02, 0.018, 0.021], "angle_fft": [0.771, 0.203, 0.08, 0.06, 0.039, 0.063, 0.065, 0.056]}, "right": {"vel": 0.31, "angle": 0.64, "vel_score": 1.45, "angle_score": 2.96, "vel_fft": [0.313, 0.066, 0.024, 0.013, 0.009, 0.032, 0.011, 0.017], "angle_fft": [0.642, 0.119, 0.051, 0.043, 0.039, 0.062, 0.017, 0.026]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.9, "left_arm_ry": 0.64, "left_arm_rz": 2.23, "left_gripper": 0.19, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.61, "right_arm_rz": -2.53, "right_gripper": 0.32}, "1": {"left_arm_vel": 0.309, "left_gripper_vel": 1.323, "left_arm_rx": -2.89, "left_arm_ry": 0.64, "left_arm_rz": 2.25, "left_gripper": 0.23, "right_arm_vel": 0.309, "right_gripper_vel": 1.323, "right_arm_rx": 2.54, "right_arm_ry": 0.6, "right_arm_rz": -2.55, "right_gripper": 0.37}, "2": {"left_arm_vel": 0.356, "left_gripper_vel": 0.567, "left_arm_rx": -2.89, "left_arm_ry": 0.64, "left_arm_rz": 2.26, "left_gripper": 0.26, "right_arm_vel": 0.356, "right_gripper_vel": 0.567, "right_arm_rx": 2.54, "right_arm_ry": 0.58, "right_arm_rz": -2.57, "right_gripper": 0.39}, "3": {"left_arm_vel": 0.462, "left_gripper_vel": -0.042, "left_arm_rx": -2.9, "left_arm_ry": 0.66, "left_arm_rz": 2.32, "left_gripper": 0.28, "right_arm_vel": 0.462, "right_gripper_vel": -0.042, "right_arm_rx": 2.56, "right_arm_ry": 0.56, "right_arm_rz": -2.6, "right_gripper": 0.39}, "4": {"left_arm_vel": 0.422, "left_gripper_vel": -0.189, "left_arm_rx": -2.93, "left_arm_ry": 0.71, "left_arm_rz": 2.43, "left_gripper": 0.29, "right_arm_vel": 0.422, "right_gripper_vel": -0.189, "right_arm_rx": 2.56, "right_arm_ry": 0.54, "right_arm_rz": -2.67, "right_gripper": 0.38}, "5": {"left_arm_vel": 0.278, "left_gripper_vel": -0.21, "left_arm_rx": -2.94, "left_arm_ry": 0.73, "left_arm_rz": 2.49, "left_gripper": 0.29, "right_arm_vel": 0.278, "right_gripper_vel": -0.21, "right_arm_rx": 2.55, "right_arm_ry": 0.53, "right_arm_rz": -2.73, "right_gripper": 0.36}, "6": {"left_arm_vel": 0.287, "left_gripper_vel": -0.378, "left_arm_rx": -2.96, "left_arm_ry": 0.75, "left_arm_rz": 2.5, "left_gripper": 0.3, "right_arm_vel": 0.287, "right_gripper_vel": -0.378, "right_arm_rx": 2.54, "right_arm_ry": 0.51, "right_arm_rz": -2.77, "right_gripper": 0.34}, "7": {"left_arm_vel": 0.228, "left_gripper_vel": -0.126, "left_arm_rx": -2.95, "left_arm_ry": 0.78, "left_arm_rz": 2.45, "left_gripper": 0.3, "right_arm_vel": 0.228, "right_gripper_vel": -0.126, "right_arm_rx": 2.54, "right_arm_ry": 0.47, "right_arm_rz": -2.79, "right_gripper": 0.32}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.07559999823570251, 0.08370000123977661, 0.04989999905228615], "delta_rot": [-0.0568000003695488, 0.13740000128746033, 0.22419999539852142], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and +Z(Up)", "magnitude": 0.1233}, "right": {"delta_pos": [0.017400000244379044, -0.13660000264644623, 0.03590000048279762], "delta_rot": [0.00419999985024333, -0.13850000500679016, -0.2599000036716461], "gripper_changed": false, "flow_direction": "-Y(Right) and +Z(Up)", "magnitude": 0.1423}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.19629999995231628, -0.05920000001788139, 0.0035000001080334187], "delta_rot": [-0.008500000461935997, 0.08290000259876251, -0.37959998846054077], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right)", "magnitude": 0.2051}, "right": {"delta_pos": [-0.15880000591278076, -0.17980000376701355, -0.05420000106096268], "delta_rot": [-0.004900000058114529, -0.03889999911189079, -0.5212000012397766], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "magnitude": 0.2459}} + + ========================================= + [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 pulls the zipper pull to open the bag while right arm stabilizes the bag body.", + "actions": [ + { + "reasoning_cot": "The left arm is visually engaged with the metal ring of the zipper. The kinematic data shows a positive velocity and displacement in the +X/+Y direction (pulling away from the bag center), which corresponds to the action of unzipping. The gripper remains closed around the pull tab throughout the sequence.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "pull", + "semantic_action": "unzip", + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "Pulling zipper pull along the track to open the bag", + "topology_change": true + }, + { + "reasoning_cot": "The right arm is positioned against the side/corner of the bag. Visual evidence shows the bag deforming slightly under pressure, indicating the arm is applying force to keep the bag stationary while the left arm pulls. This is a stabilization maneuver.", + "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": "Applying counter-pressure to stabilize bag during unzipping", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_track", + "current_status": "opening" + } + ], + "task_progress": "Bag is being actively unzipped; zipper track is transitioning from closed to open state." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm pulls the zipper pull to open the bag while right arm stabilizes the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "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": 0.24, "angle": 0.78, "vel_score": 1.6, "angle_score": 5.37, "vel_fft": [0.239, 0.076, 0.033, 0.024, 0.019, 0.014, 0.012, 0.017, 0.009, 0.006, 0.007, 0.007, 0.013, 0.008], "angle_fft": [0.78, 0.317, 0.107, 0.09, 0.059, 0.04, 0.022, 0.046, 0.027, 0.022, 0.035, 0.016, 0.027, 0.033]}, "right": {"vel": 0.23, "angle": 0.48, "vel_score": 1.58, "angle_score": 3.24, "vel_fft": [0.228, 0.093, 0.035, 0.012, 0.016, 0.007, 0.008, 0.011, 0.011, 0.002, 0.002, 0.01, 0.015, 0.006], "angle_fft": [0.476, 0.21, 0.126, 0.053, 0.025, 0.025, 0.027, 0.039, 0.051, 0.015, 0.021, 0.034, 0.046, 0.035]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.94, "left_arm_ry": 0.79, "left_arm_rz": 2.43, "left_gripper": 0.3, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.56, "right_arm_ry": 0.48, "right_arm_rz": -2.79, "right_gripper": 0.32}, "1": {"left_arm_vel": 0.296, "left_gripper_vel": -0.042, "left_arm_rx": -2.91, "left_arm_ry": 0.8, "left_arm_rz": 2.43, "left_gripper": 0.3, "right_arm_vel": 0.296, "right_gripper_vel": -0.042, "right_arm_rx": 2.56, "right_arm_ry": 0.49, "right_arm_rz": -2.81, "right_gripper": 0.32}, "2": {"left_arm_vel": 0.411, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.83, "left_arm_rz": 2.39, "left_gripper": 0.3, "right_arm_vel": 0.411, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.52, "right_arm_rz": -2.86, "right_gripper": 0.31}, "3": {"left_arm_vel": 0.444, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.83, "left_arm_rz": 2.36, "left_gripper": 0.3, "right_arm_vel": 0.444, "right_gripper_vel": 0.0, "right_arm_rx": 2.58, "right_arm_ry": 0.57, "right_arm_rz": -2.91, "right_gripper": 0.31}, "4": {"left_arm_vel": 0.363, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.84, "left_arm_rz": 2.29, "left_gripper": 0.3, "right_arm_vel": 0.363, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.61, "right_arm_rz": -2.97, "right_gripper": 0.31}, "5": {"left_arm_vel": 0.445, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.83, "left_arm_rz": 2.24, "left_gripper": 0.3, "right_arm_vel": 0.445, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.63, "right_arm_rz": -2.99, "right_gripper": 0.31}, "6": {"left_arm_vel": 0.388, "left_gripper_vel": 0.0, "left_arm_rx": -2.86, "left_arm_ry": 0.82, "left_arm_rz": 2.13, "left_gripper": 0.3, "right_arm_vel": 0.388, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.64, "right_arm_rz": -3.02, "right_gripper": 0.31}, "7": {"left_arm_vel": 0.266, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.81, "left_arm_rz": 2.08, "left_gripper": 0.31, "right_arm_vel": 0.266, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.65, "right_arm_rz": -3.02, "right_gripper": 0.31}, "8": {"left_arm_vel": 0.304, "left_gripper_vel": 0.0, "left_arm_rx": -2.89, "left_arm_ry": 0.79, "left_arm_rz": 2.03, "left_gripper": 0.31, "right_arm_vel": 0.304, "right_gripper_vel": 0.0, "right_arm_rx": 2.56, "right_arm_ry": 0.65, "right_arm_rz": -3.03, "right_gripper": 0.31}, "9": {"left_arm_vel": 0.271, "left_gripper_vel": -0.021, "left_arm_rx": -2.9, "left_arm_ry": 0.79, "left_arm_rz": 1.99, "left_gripper": 0.31, "right_arm_vel": 0.271, "right_gripper_vel": -0.021, "right_arm_rx": 2.55, "right_arm_ry": 0.64, "right_arm_rz": -3.04, "right_gripper": 0.31}, "10": {"left_arm_vel": 0.216, "left_gripper_vel": 0.0, "left_arm_rx": -2.9, "left_arm_ry": 0.78, "left_arm_rz": 1.97, "left_gripper": 0.32, "right_arm_vel": 0.216, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.63, "right_arm_rz": -3.04, "right_gripper": 0.31}, "11": {"left_arm_vel": 0.223, "left_gripper_vel": 0.0, "left_arm_rx": -2.89, "left_arm_ry": 0.77, "left_arm_rz": 1.94, "left_gripper": 0.32, "right_arm_vel": 0.223, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.62, "right_arm_rz": -3.05, "right_gripper": 0.31}, "12": {"left_arm_vel": 0.132, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.76, "left_arm_rz": 1.91, "left_gripper": 0.32, "right_arm_vel": 0.132, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.59, "right_arm_rz": -3.05, "right_gripper": 0.31}, "13": {"left_arm_vel": 0.014, "left_gripper_vel": 0.0, "left_arm_rx": -2.91, "left_arm_ry": 0.72, "left_arm_rz": 1.85, "left_gripper": 0.32, "right_arm_vel": 0.014, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.57, "right_arm_rz": -3.05, "right_gripper": 0.31}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.11159999668598175, -0.13779999315738678, -0.04809999838471413], "delta_rot": [0.03099999949336052, -0.06549999862909317, -0.5859000086784363], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.1837}, "right": {"delta_pos": [-0.16859999299049377, -0.040800001472234726, -0.09309999644756317], "delta_rot": [-0.020600000396370888, 0.08789999783039093, -0.258899986743927], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "magnitude": 0.1969}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.11710000038146973, -0.13989999890327454, -0.06859999895095825], "delta_rot": [0.08429999649524689, -0.1071000024676323, -0.5267000198364258], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.1949}, "right": {"delta_pos": [-0.17069999873638153, -0.03709999844431877, -0.0908999964594841], "delta_rot": [-0.0689999982714653, 0.08900000154972076, -0.2502000033855438], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "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": "Left arm approaches the bag's top surface to stabilize it, while right arm hovers near the zipper pull in preparation for grasping.", + "actions": [ + { + "reasoning_cot": "The left arm moves forward and down (+X, -Z) towards the bag. Visual evidence shows the gripper making contact with the silver reflective patch on the top of the bag to hold it steady. This is a stabilization move preceding the zipper interaction.", + "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": "Approaching and contacting the top surface of the bag from above.", + "topology_change": false + }, + { + "reasoning_cot": "The right arm moves backward and down (-X, -Z) to position itself near the zipper mechanism. The gripper remains open (hovering) as it aligns with the zipper pull ring, preparing to grasp it in the next sequence. No contact is made yet.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "hover", + "semantic_action": "aligning_with_zipper", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "Positioning adjacent to the zipper pull without contact.", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:top_surface", + "current_status": "stabilized_by_left_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "targeted_by_right_arm" + } + ], + "task_progress": "Establishing dual-arm coordination: Left stabilizes bag body, Right prepares to actuate zipper." + } +} +```` +--- +## 🎬 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) +![chunkannotator_15_img_8.jpg](./images/chunkannotator_15_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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_by_right_arm"}, {"anchor_id": "bag:top_surface", "current_status": "stabilized_by_left_arm"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches the bag's top surface to stabilize it, while right arm hovers near the zipper pull in preparation for grasping.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "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": 0.05, "angle": 0.28, "vel_score": 0.23, "angle_score": 1.3, "vel_fft": [0.046, 0.03, 0.015, 0.002, 0.005, 0.003, 0.003, 0.001], "angle_fft": [0.279, 0.123, 0.065, 0.03, 0.011, 0.024, 0.013, 0.015]}, "right": {"vel": 0.01, "angle": 0.1, "vel_score": 0.05, "angle_score": 0.46, "vel_fft": [0.009, 0.005, 0.001, 0.0, 0.001, 0.0, 0.0, 0.001], "angle_fft": [0.099, 0.043, 0.011, 0.007, 0.009, 0.007, 0.008, 0.014]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.91, "left_arm_ry": 0.72, "left_arm_rz": 1.85, "left_gripper": 0.32, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.57, "right_arm_rz": -3.06, "right_gripper": 0.31}, "1": {"left_arm_vel": 0.013, "left_gripper_vel": 0.0, "left_arm_rx": -2.93, "left_arm_ry": 0.73, "left_arm_rz": 1.84, "left_gripper": 0.32, "right_arm_vel": 0.013, "right_gripper_vel": 0.0, "right_arm_rx": 2.51, "right_arm_ry": 0.57, "right_arm_rz": -3.06, "right_gripper": 0.31}, "2": {"left_arm_vel": 0.02, "left_gripper_vel": -0.042, "left_arm_rx": -2.93, "left_arm_ry": 0.73, "left_arm_rz": 1.84, "left_gripper": 0.32, "right_arm_vel": 0.02, "right_gripper_vel": -0.042, "right_arm_rx": 2.51, "right_arm_ry": 0.57, "right_arm_rz": -3.06, "right_gripper": 0.31}, "3": {"left_arm_vel": 0.02, "left_gripper_vel": 0.021, "left_arm_rx": -2.93, "left_arm_ry": 0.72, "left_arm_rz": 1.84, "left_gripper": 0.32, "right_arm_vel": 0.02, "right_gripper_vel": 0.021, "right_arm_rx": 2.5, "right_arm_ry": 0.57, "right_arm_rz": -3.05, "right_gripper": 0.31}, "4": {"left_arm_vel": 0.014, "left_gripper_vel": 0.0, "left_arm_rx": -2.92, "left_arm_ry": 0.72, "left_arm_rz": 1.85, "left_gripper": 0.32, "right_arm_vel": 0.014, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.57, "right_arm_rz": -3.05, "right_gripper": 0.31}, "5": {"left_arm_vel": 0.009, "left_gripper_vel": 0.0, "left_arm_rx": -2.89, "left_arm_ry": 0.7, "left_arm_rz": 1.87, "left_gripper": 0.32, "right_arm_vel": 0.009, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.57, "right_arm_rz": -3.05, "right_gripper": 0.31}, "6": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.68, "left_arm_rz": 1.91, "left_gripper": 0.31, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.57, "right_arm_rz": -3.04, "right_gripper": 0.31}, "7": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.68, "left_arm_rz": 1.91, "left_gripper": 0.31, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.57, "right_arm_rz": -3.04, "right_gripper": 0.31}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.005100000184029341, -0.002099999925121665, -0.020600000396370888], "delta_rot": [0.05849999934434891, -0.04170000180602074, 0.06069999933242798], "gripper_changed": false, "flow_direction": "-Z(Down)", "magnitude": 0.0213}, "right": {"delta_pos": [-0.002199999988079071, 0.0035000001080334187, 0.0020000000949949026], "delta_rot": [-0.04390000179409981, 0.0015999999595806003, 0.012799999676644802], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0046}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.017500000074505806, -0.003700000001117587, -0.02160000056028366], "delta_rot": [0.08219999819993973, -0.05950000137090683, 0.3206000030040741], "gripper_changed": false, "flow_direction": "-Z(Down)", "magnitude": 0.0281}, "right": {"delta_pos": [0.00279999990016222, -9.999999747378752e-05, 0.0015999999595806003], "delta_rot": [0.023800000548362732, 0.057999998331069946, 0.03359999880194664], "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": "Left arm stabilizes the bag's top surface while right arm approaches and hovers near the zipper pull to prepare for grasping.", + "actions": [ + { + "reasoning_cot": "The left arm has moved from a free-space approach (Image 1) to making contact with the bag's top reflective patch (Image 2-9). The kinematic data shows a -Z flow (downward) followed by stabilization. This establishes a stable base for the subsequent manipulation of the zipper.", + "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": "Approached and established contact with bag:top_surface to stabilize the object.", + "topology_change": false + }, + { + "reasoning_cot": "The right arm is positioned adjacent to the zipper pull ring. Visual evidence across the sequence shows minimal displacement (hovering) as it aligns with the target. It has not yet closed to grasp, indicating a preparation phase.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "hover", + "semantic_action": "align_with_zipper", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "Hovering in close proximity to bag:zipper_pull, maintaining alignment without contact.", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:top_surface", + "current_status": "stabilized_by_left_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "targeted_by_right_arm" + } + ], + "task_progress": "Bag stabilized; right arm aligned with zipper pull for upcoming grasp." + } +} +```` +--- +## 🎬 ChunkAnnotator_16 + +### 👁️ 视觉输入 +![chunkannotator_16_img_0.jpg](./images/chunkannotator_16_img_0.jpg) +![chunkannotator_16_img_1.jpg](./images/chunkannotator_16_img_1.jpg) +![chunkannotator_16_img_2.jpg](./images/chunkannotator_16_img_2.jpg) +![chunkannotator_16_img_3.jpg](./images/chunkannotator_16_img_3.jpg) +![chunkannotator_16_img_4.jpg](./images/chunkannotator_16_img_4.jpg) +![chunkannotator_16_img_5.jpg](./images/chunkannotator_16_img_5.jpg) +![chunkannotator_16_img_6.jpg](./images/chunkannotator_16_img_6.jpg) +![chunkannotator_16_img_7.jpg](./images/chunkannotator_16_img_7.jpg) +![chunkannotator_16_img_8.jpg](./images/chunkannotator_16_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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_by_right_arm"}, {"anchor_id": "bag:top_surface", "current_status": "stabilized_by_left_arm"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag's top surface while right arm approaches and hovers near the zipper pull to prepare for grasping.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "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": 0.02, "angle": 0.49, "vel_score": 0.13, "angle_score": 2.67, "vel_fft": [0.024, 0.013, 0.007, 0.0, 0.001, 0.002, 0.002, 0.001, 0.002, 0.001], "angle_fft": [0.49, 0.246, 0.088, 0.025, 0.028, 0.01, 0.027, 0.006, 0.022, 0.018]}, "right": {"vel": 0.01, "angle": 0.16, "vel_score": 0.06, "angle_score": 0.88, "vel_fft": [0.011, 0.009, 0.004, 0.003, 0.002, 0.002, 0.002, 0.001, 0.001, 0.002], "angle_fft": [0.163, 0.126, 0.058, 0.02, 0.02, 0.027, 0.025, 0.016, 0.025, 0.029]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.67, "left_arm_rz": 1.91, "left_gripper": 0.28, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.57, "right_arm_rz": -3.04, "right_gripper": 0.31}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.66, "left_arm_rz": 1.92, "left_gripper": 0.23, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.57, "right_arm_rz": -3.04, "right_gripper": 0.31}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.86, "left_arm_ry": 0.66, "left_arm_rz": 1.91, "left_gripper": 0.16, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.57, "right_arm_rz": -3.04, "right_gripper": 0.31}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.86, "left_arm_ry": 0.65, "left_arm_rz": 1.91, "left_gripper": 0.09, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.57, "right_arm_rz": -3.04, "right_gripper": 0.31}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": -0.042, "left_arm_rx": -2.86, "left_arm_ry": 0.65, "left_arm_rz": 1.92, "left_gripper": 0.05, "right_arm_vel": 0.0, "right_gripper_vel": -0.042, "right_arm_rx": 2.49, "right_arm_ry": 0.57, "right_arm_rz": -3.04, "right_gripper": 0.31}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.86, "left_arm_ry": 0.65, "left_arm_rz": 1.93, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.57, "right_arm_rz": -3.04, "right_gripper": 0.31}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.021, "left_arm_rx": -2.86, "left_arm_ry": 0.65, "left_arm_rz": 1.95, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.021, "right_arm_rx": 2.49, "right_arm_ry": 0.57, "right_arm_rz": -3.04, "right_gripper": 0.31}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.64, "left_arm_rz": 1.98, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.57, "right_arm_rz": -3.04, "right_gripper": 0.31}, "8": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.84, "left_arm_ry": 0.64, "left_arm_rz": 2.01, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.57, "right_arm_rz": -3.04, "right_gripper": 0.31}, "9": {"left_arm_vel": 0.006, "left_gripper_vel": 0.0, "left_arm_rx": -2.84, "left_arm_ry": 0.65, "left_arm_rz": 2.08, "left_gripper": 0.04, "right_arm_vel": 0.006, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.58, "right_arm_rz": -3.04, "right_gripper": 0.31}, "10": {"left_arm_vel": 0.013, "left_gripper_vel": 0.0, "left_arm_rx": -2.84, "left_arm_ry": 0.66, "left_arm_rz": 2.14, "left_gripper": 0.04, "right_arm_vel": 0.013, "right_gripper_vel": 0.0, "right_arm_rx": 2.5, "right_arm_ry": 0.58, "right_arm_rz": -3.04, "right_gripper": 0.31}, "11": {"left_arm_vel": 0.03, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.66, "left_arm_rz": 2.15, "left_gripper": 0.04, "right_arm_vel": 0.03, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.58, "right_arm_rz": -3.03, "right_gripper": 0.31}, "12": {"left_arm_vel": 0.042, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.04, "right_arm_vel": 0.042, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.61, "right_arm_rz": -3.03, "right_gripper": 0.31}, "13": {"left_arm_vel": 0.044, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.04, "right_arm_vel": 0.044, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.63, "right_arm_rz": -3.02, "right_gripper": 0.31}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.012199999764561653, -0.002199999988079071, -0.0007999999797903001], "delta_rot": [0.02590000070631504, -0.009800000116229057, 0.2567000091075897], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0124}, "right": {"delta_pos": [0.004999999888241291, -0.003599999938160181, -0.00039999998989515007], "delta_rot": [0.06710000336170197, 0.05559999868273735, 0.019600000232458115], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0062}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.01209999993443489, -0.002300000051036477, -0.000699999975040555], "delta_rot": [0.03009999915957451, -0.009600000455975533, 0.2615000009536743], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0124}, "right": {"delta_pos": [0.02669999934732914, 0.021700000390410423, -0.002199999988079071], "delta_rot": [0.3418000042438507, 0.19380000233650208, 0.288100004196167], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left)", "magnitude": 0.0345}} + + ========================================= + [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 surface by pinching the mesh panel, while right arm hovers near the zipper pull to prepare for grasping.", + "actions": [ + { + "reasoning_cot": "The left gripper is visually confirmed to be pinching the silver mesh panel on the bag's top surface. Kinematic data shows minimal movement (vel ~0.02) and stable gripper width (~0.04), indicating a 'hold' action to stabilize the object against potential 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:top_surface" + }, + "spatial_logic": "static_at_mesh_panel", + "topology_change": false + }, + { + "reasoning_cot": "The right arm is positioned directly over the zipper pull ring but has not yet made contact or closed the gripper (width ~0.31). The arm is hovering in preparation for the next manipulation step. No force is being applied yet.", + "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": "approaching_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Bag stabilization achieved by left arm; right arm aligned with zipper pull for upcoming grasp." + } +} +```` +--- +## 🎬 ChunkAnnotator_17 + +### 👁️ 视觉输入 +![chunkannotator_17_img_0.jpg](./images/chunkannotator_17_img_0.jpg) +![chunkannotator_17_img_1.jpg](./images/chunkannotator_17_img_1.jpg) +![chunkannotator_17_img_2.jpg](./images/chunkannotator_17_img_2.jpg) +![chunkannotator_17_img_3.jpg](./images/chunkannotator_17_img_3.jpg) +![chunkannotator_17_img_4.jpg](./images/chunkannotator_17_img_4.jpg) +![chunkannotator_17_img_5.jpg](./images/chunkannotator_17_img_5.jpg) +![chunkannotator_17_img_6.jpg](./images/chunkannotator_17_img_6.jpg) +![chunkannotator_17_img_7.jpg](./images/chunkannotator_17_img_7.jpg) +![chunkannotator_17_img_8.jpg](./images/chunkannotator_17_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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_by_right_arm"}, {"anchor_id": "bag:top_surface", "current_status": "stabilized_by_left_arm"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag's top surface by pinching the mesh panel, while right arm hovers near the zipper pull to prepare for grasping.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "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": 0.0, "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], "angle_fft": [0.01, 0.005, 0.006, 0.005, 0.002, 0.004, 0.004, 0.003, 0.006, 0.004, 0.003]}, "right": {"vel": 0.06, "angle": 0.66, "vel_score": 0.34, "angle_score": 3.65, "vel_fft": [0.063, 0.013, 0.007, 0.004, 0.004, 0.003, 0.005, 0.004, 0.004, 0.004, 0.005], "angle_fft": [0.656, 0.261, 0.123, 0.027, 0.045, 0.039, 0.027, 0.036, 0.04, 0.046, 0.017]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.56, "right_arm_ry": 0.65, "right_arm_rz": -3.02, "right_gripper": 0.31}, "1": {"left_arm_vel": 0.033, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.033, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.69, "right_arm_rz": -3.01, "right_gripper": 0.31}, "2": {"left_arm_vel": 0.039, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.039, "right_gripper_vel": 0.0, "right_arm_rx": 2.57, "right_arm_ry": 0.7, "right_arm_rz": -3.01, "right_gripper": 0.31}, "3": {"left_arm_vel": 0.076, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.076, "right_gripper_vel": 0.0, "right_arm_rx": 2.59, "right_arm_ry": 0.73, "right_arm_rz": -2.99, "right_gripper": 0.31}, "4": {"left_arm_vel": 0.074, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.074, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.75, "right_arm_rz": -2.93, "right_gripper": 0.31}, "5": {"left_arm_vel": 0.089, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.089, "right_gripper_vel": 0.0, "right_arm_rx": 2.73, "right_arm_ry": 0.76, "right_arm_rz": -2.84, "right_gripper": 0.31}, "6": {"left_arm_vel": 0.096, "left_gripper_vel": -0.021, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.096, "right_gripper_vel": -0.021, "right_arm_rx": 2.81, "right_arm_ry": 0.76, "right_arm_rz": -2.77, "right_gripper": 0.31}, "7": {"left_arm_vel": 0.098, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.098, "right_gripper_vel": 0.0, "right_arm_rx": 2.83, "right_arm_ry": 0.77, "right_arm_rz": -2.76, "right_gripper": 0.31}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.0, -9.999999747378752e-05, 9.999999747378752e-05], "delta_rot": [0.00419999985024333, 0.00019999999494757503, 0.004800000227987766], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0002}, "right": {"delta_pos": [0.020600000396370888, 0.025299999862909317, -0.0024999999441206455], "delta_rot": [0.27070000767707825, 0.11800000071525574, 0.26499998569488525], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left)", "magnitude": 0.0327}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [9.999999747378752e-05, 0.00039999998989515007, -0.0], "delta_rot": [0.0034000000450760126, -0.0017999999690800905, 0.003599999938160181], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0004}, "right": {"delta_pos": [0.05249999836087227, 0.039500001817941666, -0.01209999993443489], "delta_rot": [0.3127000033855438, 0.1331000030040741, 0.28540000319480896], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left)", "magnitude": 0.0668}} + + ========================================= + [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 surface by pinching the mesh panel, while right arm hovers near the zipper pull to prepare for grasping.", + "actions": [ + { + "reasoning_cot": "The left arm is visually confirmed to be pinching the silver mesh panel on the top of the bag. Kinematic data shows zero velocity (vel: 0.0) and stable gripper width (0.03), indicating a static hold to stabilize the object against potential movement 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:top_surface" + }, + "spatial_logic": "static_at_mesh_panel", + "topology_change": false + }, + { + "reasoning_cot": "The right arm exhibits forward (+X) and leftward (+Y) displacement (delta_pos magnitude ~0.0327) towards the metal ring/zipper assembly. The gripper remains open (width 0.31) throughout the sequence, indicating an approach phase rather than a grasp. Visual evidence confirms the end-effector is hovering directly over the zipper pull target.", + "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:zipper_pull" + }, + "spatial_logic": "moving_from_hover_to_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:top_surface", + "current_status": "stabilized_by_left_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "targeted_by_right_arm" + } + ], + "task_progress": "Stabilizing bag with left hand while positioning right hand to interact with the zipper mechanism." + } +} +```` +--- +## 🎬 ChunkAnnotator_18 + +### 👁️ 视觉输入 +![chunkannotator_18_img_0.jpg](./images/chunkannotator_18_img_0.jpg) +![chunkannotator_18_img_1.jpg](./images/chunkannotator_18_img_1.jpg) +![chunkannotator_18_img_2.jpg](./images/chunkannotator_18_img_2.jpg) +![chunkannotator_18_img_3.jpg](./images/chunkannotator_18_img_3.jpg) +![chunkannotator_18_img_4.jpg](./images/chunkannotator_18_img_4.jpg) +![chunkannotator_18_img_5.jpg](./images/chunkannotator_18_img_5.jpg) +![chunkannotator_18_img_6.jpg](./images/chunkannotator_18_img_6.jpg) +![chunkannotator_18_img_7.jpg](./images/chunkannotator_18_img_7.jpg) +![chunkannotator_18_img_8.jpg](./images/chunkannotator_18_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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_by_right_arm"}, {"anchor_id": "bag:top_surface", "current_status": "stabilized_by_left_arm"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag's top surface by pinching the mesh panel, while right arm hovers near the zipper pull to prepare for grasping.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "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": 0.0, "angle": 0.01, "vel_score": 0.0, "angle_score": 0.03, "vel_fft": [0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001], "angle_fft": [0.008, 0.005, 0.002, 0.004, 0.006, 0.003, 0.003, 0.001, 0.003]}, "right": {"vel": 0.07, "angle": 0.16, "vel_score": 0.35, "angle_score": 0.69, "vel_fft": [0.074, 0.009, 0.006, 0.007, 0.007, 0.004, 0.0, 0.004, 0.003], "angle_fft": [0.164, 0.028, 0.027, 0.036, 0.04, 0.032, 0.015, 0.022, 0.026]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.84, "right_arm_ry": 0.77, "right_arm_rz": -2.74, "right_gripper": 0.31}, "1": {"left_arm_vel": 0.076, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.076, "right_gripper_vel": 0.0, "right_arm_rx": 2.86, "right_arm_ry": 0.78, "right_arm_rz": -2.73, "right_gripper": 0.31}, "2": {"left_arm_vel": 0.071, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.071, "right_gripper_vel": 0.0, "right_arm_rx": 2.87, "right_arm_ry": 0.78, "right_arm_rz": -2.73, "right_gripper": 0.31}, "3": {"left_arm_vel": 0.06, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.06, "right_gripper_vel": 0.0, "right_arm_rx": 2.87, "right_arm_ry": 0.78, "right_arm_rz": -2.73, "right_gripper": 0.31}, "4": {"left_arm_vel": 0.084, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.084, "right_gripper_vel": 0.0, "right_arm_rx": 2.87, "right_arm_ry": 0.77, "right_arm_rz": -2.73, "right_gripper": 0.31}, "5": {"left_arm_vel": 0.093, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.093, "right_gripper_vel": 0.0, "right_arm_rx": 2.87, "right_arm_ry": 0.76, "right_arm_rz": -2.73, "right_gripper": 0.31}, "6": {"left_arm_vel": 0.088, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.088, "right_gripper_vel": 0.0, "right_arm_rx": 2.86, "right_arm_ry": 0.76, "right_arm_rz": -2.74, "right_gripper": 0.31}, "7": {"left_arm_vel": 0.081, "left_gripper_vel": -0.021, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.081, "right_gripper_vel": -0.021, "right_arm_rx": 2.86, "right_arm_ry": 0.77, "right_arm_rz": -2.74, "right_gripper": 0.31}, "8": {"left_arm_vel": 0.104, "left_gripper_vel": -0.294, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.104, "right_gripper_vel": -0.294, "right_arm_rx": 2.86, "right_arm_ry": 0.77, "right_arm_rz": -2.74, "right_gripper": 0.3}, "9": {"left_arm_vel": 0.086, "left_gripper_vel": -1.092, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.086, "right_gripper_vel": -1.092, "right_arm_rx": 2.87, "right_arm_ry": 0.78, "right_arm_rz": -2.74, "right_gripper": 0.26}, "10": {"left_arm_vel": 0.053, "left_gripper_vel": -1.827, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.053, "right_gripper_vel": -1.827, "right_arm_rx": 2.87, "right_arm_ry": 0.78, "right_arm_rz": -2.73, "right_gripper": 0.2}, "11": {"left_arm_vel": 0.053, "left_gripper_vel": -1.827, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.053, "right_gripper_vel": -1.827, "right_arm_rx": 2.87, "right_arm_ry": 0.78, "right_arm_rz": -2.73, "right_gripper": 0.2}, "12": {"left_arm_vel": 0.053, "left_gripper_vel": -1.827, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.053, "right_gripper_vel": -1.827, "right_arm_rx": 2.87, "right_arm_ry": 0.78, "right_arm_rz": -2.73, "right_gripper": 0.2}, "13": {"left_arm_vel": 0.053, "left_gripper_vel": -1.827, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.053, "right_gripper_vel": -1.827, "right_arm_rx": 2.87, "right_arm_ry": 0.78, "right_arm_rz": -2.73, "right_gripper": 0.2}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.00019999999494757503, 0.0005000000237487257, -9.999999747378752e-05], "delta_rot": [-0.001500000013038516, -0.0013000000035390258, -0.0008999999845400453], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0005}, "right": {"delta_pos": [0.030799999833106995, 0.011500000022351742, -0.010900000110268593], "delta_rot": [0.030400000512599945, 0.009600000455975533, 0.007799999788403511], "gripper_changed": false, "flow_direction": "+X(Forward)", "magnitude": 0.0347}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.0013000000035390258, 0.000699999975040555, 0.0], "delta_rot": [-0.002199999988079071, 0.0017000000225380063, 0.012299999594688416], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0015}, "right": {"delta_pos": [0.004100000020116568, -0.00019999999494757503, 0.013299999758601189], "delta_rot": [0.0568000003695488, -0.13429999351501465, 0.04659999907016754], "gripper_changed": true, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0139}} + + ========================================= + [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 surface by pinching the mesh panel, while right arm hovers near the zipper pull to prepare for grasping.", + "actions": [ + { + "reasoning_cot": "The left arm has moved from a free-space approach (Image 1) to making contact with the bag's top mesh panel (Images 2-5). The gripper is closed and holding the material firmly to stabilize the object. This establishes a static anchor point for the subsequent manipulation of 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": "Transitioned from approach to securing hold on bag:top_surface", + "topology_change": false + }, + { + "reasoning_cot": "The right arm approaches the side of the bag where the zipper pull is located. While it moves into position near the metal ring (zipper_pull), the gripper remains open throughout the sequence (Images 2-5), indicating a 'hover' or 'approach' state rather than a grasp. It is positioning itself for the next step.", + "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": "Approaching bag:zipper_pull from table:center_zone", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:top_surface", + "current_status": "stabilized_by_left_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "targeted_by_right_arm" + } + ], + "task_progress": "Bag stabilized by left hand; right hand positioning to interact with zipper." + } +} +```` +--- +## 🎬 ChunkAnnotator_19 + +### 👁️ 视觉输入 +![chunkannotator_19_img_0.jpg](./images/chunkannotator_19_img_0.jpg) +![chunkannotator_19_img_1.jpg](./images/chunkannotator_19_img_1.jpg) +![chunkannotator_19_img_2.jpg](./images/chunkannotator_19_img_2.jpg) +![chunkannotator_19_img_3.jpg](./images/chunkannotator_19_img_3.jpg) +![chunkannotator_19_img_4.jpg](./images/chunkannotator_19_img_4.jpg) +![chunkannotator_19_img_5.jpg](./images/chunkannotator_19_img_5.jpg) +![chunkannotator_19_img_6.jpg](./images/chunkannotator_19_img_6.jpg) +![chunkannotator_19_img_7.jpg](./images/chunkannotator_19_img_7.jpg) +![chunkannotator_19_img_8.jpg](./images/chunkannotator_19_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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_by_right_arm"}, {"anchor_id": "bag:top_surface", "current_status": "stabilized_by_left_arm"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm stabilizes the bag's top surface by pinching the mesh panel, while right arm hovers near the zipper pull to prepare for grasping.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "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": 0.0, "angle": 0.02, "vel_score": 0.02, "angle_score": 0.23, "vel_fft": [0.001, 0.001, 0.001, 0.001, 0.0, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0], "angle_fft": [0.021, 0.003, 0.008, 0.004, 0.002, 0.006, 0.007, 0.001, 0.005, 0.004, 0.002, 0.001, 0.001, 0.003, 0.005, 0.003, 0.001, 0.001, 0.002, 0.003]}, "right": {"vel": 0.11, "angle": 0.24, "vel_score": 1.31, "angle_score": 2.68, "vel_fft": [0.114, 0.008, 0.006, 0.02, 0.028, 0.017, 0.008, 0.002, 0.005, 0.002, 0.002, 0.002, 0.002, 0.001, 0.001, 0.002, 0.002, 0.002, 0.002, 0.004], "angle_fft": [0.238, 0.07, 0.043, 0.046, 0.022, 0.021, 0.025, 0.008, 0.009, 0.015, 0.014, 0.013, 0.009, 0.002, 0.016, 0.014, 0.011, 0.005, 0.012, 0.019]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.87, "right_arm_ry": 0.78, "right_arm_rz": -2.74, "right_gripper": 0.11}, "1": {"left_arm_vel": 0.176, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.176, "right_gripper_vel": 0.0, "right_arm_rx": 2.89, "right_arm_ry": 0.71, "right_arm_rz": -2.74, "right_gripper": 0.01}, "2": {"left_arm_vel": 0.064, "left_gripper_vel": 1.449, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.18, "left_gripper": 0.03, "right_arm_vel": 0.064, "right_gripper_vel": 1.449, "right_arm_rx": 2.9, "right_arm_ry": 0.67, "right_arm_rz": -2.75, "right_gripper": 0.07}, "3": {"left_arm_vel": 0.176, "left_gripper_vel": 2.016, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.18, "left_gripper": 0.03, "right_arm_vel": 0.176, "right_gripper_vel": 2.016, "right_arm_rx": 2.9, "right_arm_ry": 0.68, "right_arm_rz": -2.75, "right_gripper": 0.38}, "4": {"left_arm_vel": 0.116, "left_gripper_vel": -0.273, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.18, "left_gripper": 0.03, "right_arm_vel": 0.116, "right_gripper_vel": -0.273, "right_arm_rx": 2.91, "right_arm_ry": 0.7, "right_arm_rz": -2.76, "right_gripper": 0.51}, "5": {"left_arm_vel": 0.066, "left_gripper_vel": -3.591, "left_arm_rx": -2.83, "left_arm_ry": 0.66, "left_arm_rz": 2.18, "left_gripper": 0.03, "right_arm_vel": 0.066, "right_gripper_vel": -3.591, "right_arm_rx": 2.92, "right_arm_ry": 0.74, "right_arm_rz": -2.72, "right_gripper": 0.25}, "6": {"left_arm_vel": 0.033, "left_gripper_vel": -0.735, "left_arm_rx": -2.83, "left_arm_ry": 0.66, "left_arm_rz": 2.18, "left_gripper": 0.03, "right_arm_vel": 0.033, "right_gripper_vel": -0.735, "right_arm_rx": 2.9, "right_arm_ry": 0.72, "right_arm_rz": -2.69, "right_gripper": 0.01}, "7": {"left_arm_vel": 0.125, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.66, "left_arm_rz": 2.18, "left_gripper": 0.03, "right_arm_vel": 0.125, "right_gripper_vel": 0.0, "right_arm_rx": 2.9, "right_arm_ry": 0.64, "right_arm_rz": -2.7, "right_gripper": 0.01}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0013000000035390258, 0.00019999999494757503, 0.00019999999494757503], "delta_rot": [-0.0017000000225380063, 0.004000000189989805, 0.01360000018030405], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0013}, "right": {"delta_pos": [-0.027000000700354576, -0.012199999764561653, 0.023800000548362732], "delta_rot": [0.029500000178813934, -0.14480000734329224, 0.04230000078678131], "gripper_changed": true, "flow_direction": "-X(Backward) and +Z(Up)", "magnitude": 0.038}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.003000000026077032, -0.0032999999821186066, 0.018799999728798866], "delta_rot": [0.06350000202655792, 0.014299999922513962, 0.16949999332427979], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0194}, "right": {"delta_pos": [-0.13359999656677246, 0.05900000035762787, 0.05000000074505806], "delta_rot": [-0.12729999423027039, -0.22349999845027924, 0.1914999932050705], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1543}} + + ========================================= + [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 pull action on the zipper pull to open the bag, while left arm stabilizes the bag body.", + "actions": [ + { + "reasoning_cot": "The right arm gripper closes around the metal zipper pull (visible in T0/T1) and moves backward (-X) and upward (+Z), causing the zipper slider to move along the track. This is a clear 'pull' action to open the bag.", + "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": "zipper_pull" + }, + "spatial_logic": "Moving from grasped position at zipper_pull backwards to extend the opening", + "topology_change": true + }, + { + "reasoning_cot": "The left arm remains stationary with the gripper closed, pinching the mesh panel of the bag to prevent it from sliding during the right arm's pulling motion. It acts as a static anchor.", + "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 stabilization at bag:top_surface", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_track", + "current_status": "opening" + } + ], + "task_progress": "Bag is being unzipped; right arm pulls zipper while left arm stabilizes." + } +} +```` +--- +## 🎬 ChunkAnnotator_20 + +### 👁️ 视觉输入 +![chunkannotator_20_img_0.jpg](./images/chunkannotator_20_img_0.jpg) +![chunkannotator_20_img_1.jpg](./images/chunkannotator_20_img_1.jpg) +![chunkannotator_20_img_2.jpg](./images/chunkannotator_20_img_2.jpg) +![chunkannotator_20_img_3.jpg](./images/chunkannotator_20_img_3.jpg) +![chunkannotator_20_img_4.jpg](./images/chunkannotator_20_img_4.jpg) +![chunkannotator_20_img_5.jpg](./images/chunkannotator_20_img_5.jpg) +![chunkannotator_20_img_6.jpg](./images/chunkannotator_20_img_6.jpg) +![chunkannotator_20_img_7.jpg](./images/chunkannotator_20_img_7.jpg) +![chunkannotator_20_img_8.jpg](./images/chunkannotator_20_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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_by_right_arm"}, {"anchor_id": "bag:top_surface", "current_status": "stabilized_by_left_arm"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm executes a pull action on the zipper pull to open the bag, while left arm stabilizes the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "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": 0.02, "angle": 0.13, "vel_score": 0.22, "angle_score": 1.27, "vel_fft": [0.019, 0.012, 0.009, 0.01, 0.011, 0.01, 0.007, 0.006, 0.005, 0.004, 0.003, 0.003, 0.003, 0.003, 0.003, 0.003, 0.002, 0.001, 0.002, 0.002], "angle_fft": [0.133, 0.019, 0.036, 0.03, 0.029, 0.027, 0.023, 0.029, 0.002, 0.014, 0.013, 0.005, 0.003, 0.008, 0.012, 0.002, 0.008, 0.009, 0.004, 0.005]}, "right": {"vel": 0.12, "angle": 0.54, "vel_score": 1.16, "angle_score": 5.18, "vel_fft": [0.123, 0.028, 0.025, 0.004, 0.014, 0.01, 0.005, 0.001, 0.002, 0.007, 0.005, 0.003, 0.005, 0.0, 0.008, 0.005, 0.002, 0.006, 0.003, 0.001], "angle_fft": [0.544, 0.143, 0.113, 0.07, 0.049, 0.086, 0.041, 0.033, 0.016, 0.032, 0.004, 0.01, 0.019, 0.023, 0.041, 0.026, 0.007, 0.016, 0.009, 0.006]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.66, "left_arm_rz": 2.18, "left_gripper": 0.03, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.9, "right_arm_ry": 0.64, "right_arm_rz": -2.7, "right_gripper": 0.01}, "1": {"left_arm_vel": 0.095, "left_gripper_vel": 0.0, "left_arm_rx": -2.8, "left_arm_ry": 0.66, "left_arm_rz": 2.21, "left_gripper": 0.03, "right_arm_vel": 0.095, "right_gripper_vel": 0.0, "right_arm_rx": 2.89, "right_arm_ry": 0.63, "right_arm_rz": -2.73, "right_gripper": 0.01}, "2": {"left_arm_vel": 0.074, "left_gripper_vel": 0.0, "left_arm_rx": -2.78, "left_arm_ry": 0.65, "left_arm_rz": 2.26, "left_gripper": 0.03, "right_arm_vel": 0.074, "right_gripper_vel": 0.0, "right_arm_rx": 2.81, "right_arm_ry": 0.59, "right_arm_rz": -2.72, "right_gripper": 0.01}, "3": {"left_arm_vel": 0.2, "left_gripper_vel": 0.0, "left_arm_rx": -2.77, "left_arm_ry": 0.65, "left_arm_rz": 2.28, "left_gripper": 0.03, "right_arm_vel": 0.2, "right_gripper_vel": 0.0, "right_arm_rx": 2.8, "right_arm_ry": 0.58, "right_arm_rz": -2.6, "right_gripper": 0.01}, "4": {"left_arm_vel": 0.243, "left_gripper_vel": 0.0, "left_arm_rx": -2.76, "left_arm_ry": 0.65, "left_arm_rz": 2.3, "left_gripper": 0.03, "right_arm_vel": 0.243, "right_gripper_vel": 0.0, "right_arm_rx": 2.81, "right_arm_ry": 0.61, "right_arm_rz": -2.49, "right_gripper": 0.01}, "5": {"left_arm_vel": 0.167, "left_gripper_vel": 0.0, "left_arm_rx": -2.76, "left_arm_ry": 0.64, "left_arm_rz": 2.3, "left_gripper": 0.03, "right_arm_vel": 0.167, "right_gripper_vel": 0.0, "right_arm_rx": 2.88, "right_arm_ry": 0.67, "right_arm_rz": -2.43, "right_gripper": 0.01}, "6": {"left_arm_vel": 0.044, "left_gripper_vel": 0.504, "left_arm_rx": -2.76, "left_arm_ry": 0.64, "left_arm_rz": 2.3, "left_gripper": 0.05, "right_arm_vel": 0.044, "right_gripper_vel": 0.504, "right_arm_rx": 2.85, "right_arm_ry": 0.69, "right_arm_rz": -2.47, "right_gripper": 0.03}, "7": {"left_arm_vel": 0.057, "left_gripper_vel": 0.798, "left_arm_rx": -2.76, "left_arm_ry": 0.64, "left_arm_rz": 2.3, "left_gripper": 0.08, "right_arm_vel": 0.057, "right_gripper_vel": 0.798, "right_arm_rx": 2.82, "right_arm_ry": 0.67, "right_arm_rz": -2.49, "right_gripper": 0.06}, "8": {"left_arm_vel": 0.075, "left_gripper_vel": 1.575, "left_arm_rx": -2.76, "left_arm_ry": 0.65, "left_arm_rz": 2.32, "left_gripper": 0.13, "right_arm_vel": 0.075, "right_gripper_vel": 1.575, "right_arm_rx": 2.79, "right_arm_ry": 0.64, "right_arm_rz": -2.51, "right_gripper": 0.11}, "9": {"left_arm_vel": 0.083, "left_gripper_vel": 1.995, "left_arm_rx": -2.76, "left_arm_ry": 0.66, "left_arm_rz": 2.33, "left_gripper": 0.17, "right_arm_vel": 0.083, "right_gripper_vel": 1.995, "right_arm_rx": 2.77, "right_arm_ry": 0.61, "right_arm_rz": -2.51, "right_gripper": 0.17}, "10": {"left_arm_vel": 0.105, "left_gripper_vel": 2.163, "left_arm_rx": -2.76, "left_arm_ry": 0.67, "left_arm_rz": 2.34, "left_gripper": 0.21, "right_arm_vel": 0.105, "right_gripper_vel": 2.163, "right_arm_rx": 2.75, "right_arm_ry": 0.59, "right_arm_rz": -2.52, "right_gripper": 0.25}, "11": {"left_arm_vel": 0.175, "left_gripper_vel": 1.617, "left_arm_rx": -2.76, "left_arm_ry": 0.68, "left_arm_rz": 2.34, "left_gripper": 0.24, "right_arm_vel": 0.175, "right_gripper_vel": 1.617, "right_arm_rx": 2.74, "right_arm_ry": 0.57, "right_arm_rz": -2.53, "right_gripper": 0.3}, "12": {"left_arm_vel": 0.202, "left_gripper_vel": 1.386, "left_arm_rx": -2.76, "left_arm_ry": 0.68, "left_arm_rz": 2.34, "left_gripper": 0.25, "right_arm_vel": 0.202, "right_gripper_vel": 1.386, "right_arm_rx": 2.74, "right_arm_ry": 0.56, "right_arm_rz": -2.55, "right_gripper": 0.35}, "13": {"left_arm_vel": 0.202, "left_gripper_vel": 1.386, "left_arm_rx": -2.76, "left_arm_ry": 0.68, "left_arm_rz": 2.34, "left_gripper": 0.25, "right_arm_vel": 0.202, "right_gripper_vel": 1.386, "right_arm_rx": 2.74, "right_arm_ry": 0.56, "right_arm_rz": -2.55, "right_gripper": 0.35}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.00419999985024333, -0.003599999938160181, 0.018699999898672104], "delta_rot": [0.06440000236034393, 0.010599999688565731, 0.15440000593662262], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0195}, "right": {"delta_pos": [-0.1046999990940094, 0.07209999859333038, 0.024399999529123306], "delta_rot": [-0.15870000422000885, -0.08259999752044678, 0.15039999783039093], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1294}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.4165000021457672, 0.25600001215934753, 0.06440000236034393], "delta_rot": [-0.2223999947309494, 0.48500001430511475, 0.44339999556541443], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.4931}, "right": {"delta_pos": [-0.3138999938964844, -0.12720000743865967, 0.11869999766349792], "delta_rot": [-6.019599914550781, 0.3930000066757202, 0.1501999944448471], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.3589}} + + ========================================= + [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 pull action on the zipper pull to open the bag, while left arm stabilizes the bag body.", + "actions": [ + { + "reasoning_cot": "The right arm is visually engaged with the metal ring of the zipper pull. The kinematic data shows a significant backward (-X) and upward (+Z) displacement (delta_pos magnitude ~0.13), consistent with pulling the zipper to open the bag. The gripper remains closed (stable) throughout the motion, indicating a continuous hold and drag/pull action.", + "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": "zipper_pull" + }, + "spatial_logic": "Pulling zipper pull away from bag center along the track", + "topology_change": true + }, + { + "reasoning_cot": "The left arm maintains a static position on the top surface of the bag (silver textured patch). Kinematic data shows negligible velocity (vel: 0.02) and minimal positional change, confirming its role as a stabilizer to prevent the bag from sliding while the right arm pulls the zipper.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "hold", + "semantic_action": "stabilize_bag", + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "Static stabilization at bag top surface", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_track", + "current_status": "opening" + } + ], + "task_progress": "Bag is being unzipped; zipper track is actively opening." + } +} +```` +--- +## 🎬 ChunkAnnotator_21 + +### 👁️ 视觉输入 +![chunkannotator_21_img_0.jpg](./images/chunkannotator_21_img_0.jpg) +![chunkannotator_21_img_1.jpg](./images/chunkannotator_21_img_1.jpg) +![chunkannotator_21_img_2.jpg](./images/chunkannotator_21_img_2.jpg) +![chunkannotator_21_img_3.jpg](./images/chunkannotator_21_img_3.jpg) +![chunkannotator_21_img_4.jpg](./images/chunkannotator_21_img_4.jpg) +![chunkannotator_21_img_5.jpg](./images/chunkannotator_21_img_5.jpg) +![chunkannotator_21_img_6.jpg](./images/chunkannotator_21_img_6.jpg) +![chunkannotator_21_img_7.jpg](./images/chunkannotator_21_img_7.jpg) +![chunkannotator_21_img_8.jpg](./images/chunkannotator_21_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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_by_right_arm"}, {"anchor_id": "bag:top_surface", "current_status": "stabilized_by_left_arm"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm executes a pull action on the zipper pull to open the bag, while left arm stabilizes the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "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": 0.35, "angle": 0.56, "vel_score": 3.6, "angle_score": 5.3, "vel_fft": [0.345, 0.186, 0.027, 0.02, 0.019, 0.014, 0.01, 0.006, 0.007, 0.006, 0.007, 0.003, 0.007, 0.008, 0.019, 0.008, 0.004, 0.006, 0.003, 0.004], "angle_fft": [0.558, 0.147, 0.047, 0.102, 0.068, 0.107, 0.042, 0.043, 0.012, 0.008, 0.018, 0.006, 0.032, 0.035, 0.019, 0.003, 0.01, 0.018, 0.016, 0.007]}, "right": {"vel": 0.22, "angle": 4.48, "vel_score": 2.29, "angle_score": 6.46, "vel_fft": [0.222, 0.113, 0.003, 0.014, 0.013, 0.005, 0.005, 0.008, 0.008, 0.003, 0.001, 0.006, 0.004, 0.005, 0.011, 0.006, 0.003, 0.004, 0.001, 0.004], "angle_fft": [4.484, 3.928, 3.844, 3.847, 3.878, 3.806, 3.862, 3.782, 3.814, 3.808, 3.831, 3.817, 3.841, 3.8, 3.792, 3.816, 3.799, 3.83, 3.835, 3.833]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.77, "left_arm_ry": 0.68, "left_arm_rz": 2.34, "left_gripper": 0.25, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.74, "right_arm_ry": 0.55, "right_arm_rz": -2.56, "right_gripper": 0.37}, "1": {"left_arm_vel": 0.259, "left_gripper_vel": 0.189, "left_arm_rx": -2.81, "left_arm_ry": 0.68, "left_arm_rz": 2.34, "left_gripper": 0.23, "right_arm_vel": 0.259, "right_gripper_vel": 0.189, "right_arm_rx": 2.74, "right_arm_ry": 0.52, "right_arm_rz": -2.61, "right_gripper": 0.39}, "2": {"left_arm_vel": 0.276, "left_gripper_vel": 0.084, "left_arm_rx": -2.86, "left_arm_ry": 0.69, "left_arm_rz": 2.34, "left_gripper": 0.21, "right_arm_vel": 0.276, "right_gripper_vel": 0.084, "right_arm_rx": 2.75, "right_arm_ry": 0.5, "right_arm_rz": -2.64, "right_gripper": 0.4}, "3": {"left_arm_vel": 0.375, "left_gripper_vel": 0.0, "left_arm_rx": -2.91, "left_arm_ry": 0.7, "left_arm_rz": 2.38, "left_gripper": 0.2, "right_arm_vel": 0.375, "right_gripper_vel": 0.0, "right_arm_rx": 2.84, "right_arm_ry": 0.44, "right_arm_rz": -2.65, "right_gripper": 0.4}, "4": {"left_arm_vel": 0.383, "left_gripper_vel": -0.021, "left_arm_rx": -2.9, "left_arm_ry": 0.74, "left_arm_rz": 2.46, "left_gripper": 0.2, "right_arm_vel": 0.383, "right_gripper_vel": -0.021, "right_arm_rx": 2.95, "right_arm_ry": 0.44, "right_arm_rz": -2.62, "right_gripper": 0.4}, "5": {"left_arm_vel": 0.445, "left_gripper_vel": 0.0, "left_arm_rx": -2.9, "left_arm_ry": 0.82, "left_arm_rz": 2.57, "left_gripper": 0.2, "right_arm_vel": 0.445, "right_gripper_vel": 0.0, "right_arm_rx": 3.06, "right_arm_ry": 0.54, "right_arm_rz": -2.56, "right_gripper": 0.4}, "6": {"left_arm_vel": 0.393, "left_gripper_vel": 0.0, "left_arm_rx": -2.93, "left_arm_ry": 0.92, "left_arm_rz": 2.65, "left_gripper": 0.2, "right_arm_vel": 0.393, "right_gripper_vel": 0.0, "right_arm_rx": 3.09, "right_arm_ry": 0.65, "right_arm_rz": -2.54, "right_gripper": 0.4}, "7": {"left_arm_vel": 0.32, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 0.93, "left_arm_rz": 2.67, "left_gripper": 0.24, "right_arm_vel": 0.32, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 0.74, "right_arm_rz": -2.52, "right_gripper": 0.4}, "8": {"left_arm_vel": 0.235, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 0.94, "left_arm_rz": 2.67, "left_gripper": 0.3, "right_arm_vel": 0.235, "right_gripper_vel": 0.0, "right_arm_rx": -3.13, "right_arm_ry": 0.79, "right_arm_rz": -2.51, "right_gripper": 0.4}, "9": {"left_arm_vel": 0.22, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 0.94, "left_arm_rz": 2.66, "left_gripper": 0.33, "right_arm_vel": 0.22, "right_gripper_vel": 0.0, "right_arm_rx": -3.13, "right_arm_ry": 0.82, "right_arm_rz": -2.51, "right_gripper": 0.4}, "10": {"left_arm_vel": 0.102, "left_gripper_vel": 0.0, "left_arm_rx": -2.97, "left_arm_ry": 1.04, "left_arm_rz": 2.67, "left_gripper": 0.38, "right_arm_vel": 0.102, "right_gripper_vel": 0.0, "right_arm_rx": -3.11, "right_arm_ry": 0.91, "right_arm_rz": -2.49, "right_gripper": 0.4}, "11": {"left_arm_vel": 0.083, "left_gripper_vel": 0.0, "left_arm_rx": -3.0, "left_arm_ry": 1.15, "left_arm_rz": 2.66, "left_gripper": 0.36, "right_arm_vel": 0.083, "right_gripper_vel": 0.0, "right_arm_rx": -3.09, "right_arm_ry": 1.02, "right_arm_rz": -2.48, "right_gripper": 0.4}, "12": {"left_arm_vel": 0.022, "left_gripper_vel": 0.021, "left_arm_rx": -3.02, "left_arm_ry": 1.15, "left_arm_rz": 2.64, "left_gripper": 0.3, "right_arm_vel": 0.022, "right_gripper_vel": 0.021, "right_arm_rx": -3.1, "right_arm_ry": 1.03, "right_arm_rz": -2.5, "right_gripper": 0.4}, "13": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 2.63, "left_gripper": 0.24, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": -3.12, "right_arm_ry": 1.04, "right_arm_rz": -2.55, "right_gripper": 0.4}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.41029998660087585, 0.2572000026702881, 0.03759999945759773], "delta_rot": [-0.2750999927520752, 0.4722999930381775, 0.28760001063346863], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.4857}, "right": {"delta_pos": [-0.21040000021457672, -0.19380000233650208, 0.09130000323057175], "delta_rot": [-5.8632001876831055, 0.489300012588501, 0.017799999564886093], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.3003}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.40709999203681946, 0.2524999976158142, 0.03700000047683716], "delta_rot": [-0.26409998536109924, 0.47049999237060547, 0.6725000143051147], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.4804}, "right": {"delta_pos": [-0.22130000591278076, -0.19460000097751617, 0.09210000187158585], "delta_rot": [0.35409998893737793, 0.5821999907493591, -0.4138999879360199], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.3088}} + + ========================================= + [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 execute a coordinated retreat maneuver, moving backward and upward away from the bag to clear the workspace after completing the zipper interaction.", + "actions": [ + { + "reasoning_cot": "The left arm moves backward (-X) and leftward (+Y) while lifting (+Z), transitioning from contact with the bag's top surface to free space. The gripper remains open throughout the motion, indicating a release/retreat action rather than manipulation.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "retreat", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "moving from bag:top_surface to free_space (backward-left-up)", + "topology_change": false + }, + { + "reasoning_cot": "The right arm moves backward (-X) and rightward (-Y) while lifting (+Z), pulling away from the zipper pull area. The gripper is open, confirming the end of the previous grasping task and a transition to a neutral hovering state.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "retreat", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": null, + "spatial_logic": "moving from bag:zipper_pull to free_space (backward-right-up)", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "released" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "unconstrained" + } + ], + "task_progress": "Arms have successfully retreated from the bag, leaving it in its current state on the table." + } +} +```` +--- +## 🎬 ChunkAnnotator_22 + +### 👁️ 视觉输入 +![chunkannotator_22_img_0.jpg](./images/chunkannotator_22_img_0.jpg) +![chunkannotator_22_img_1.jpg](./images/chunkannotator_22_img_1.jpg) +![chunkannotator_22_img_2.jpg](./images/chunkannotator_22_img_2.jpg) +![chunkannotator_22_img_3.jpg](./images/chunkannotator_22_img_3.jpg) +![chunkannotator_22_img_4.jpg](./images/chunkannotator_22_img_4.jpg) +![chunkannotator_22_img_5.jpg](./images/chunkannotator_22_img_5.jpg) +![chunkannotator_22_img_6.jpg](./images/chunkannotator_22_img_6.jpg) +![chunkannotator_22_img_7.jpg](./images/chunkannotator_22_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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "released"}, {"anchor_id": "bag:top_surface", "current_status": "unconstrained"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_surface', 'table:center_zone', 'zipper_pull', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Both arms execute a coordinated retreat maneuver, moving backward and upward away from the bag to clear the workspace after completing the zipper 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": 0.0, "angle": 0.23, "vel_score": 0.05, "angle_score": 3.53, "vel_fft": [0.004, 0.003, 0.003, 0.002, 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], "angle_fft": [0.225, 0.21, 0.184, 0.144, 0.103, 0.072, 0.042, 0.027, 0.011, 0.007, 0.006, 0.006, 0.013, 0.011, 0.011, 0.009, 0.006, 0.008, 0.005, 0.007]}, "right": {"vel": 0.01, "angle": 3.82, "vel_score": 0.13, "angle_score": 3.51, "vel_fft": [0.009, 0.009, 0.007, 0.005, 0.004, 0.003, 0.003, 0.003, 0.003, 0.002, 0.002, 0.002, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001], "angle_fft": [3.818, 3.716, 3.538, 3.449, 3.496, 3.568, 3.582, 3.553, 3.546, 3.549, 3.554, 3.546, 3.546, 3.54, 3.543, 3.545, 3.537, 3.528, 3.527, 3.525]}, "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": 2.63, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": -3.12, "right_arm_ry": 1.04, "right_arm_rz": -2.55, "right_gripper": 0.4}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": -0.021, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 2.63, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": -0.021, "right_arm_rx": -3.12, "right_arm_ry": 1.04, "right_arm_rz": -2.55, "right_gripper": 0.4}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": -0.042, "left_arm_rx": -3.05, "left_arm_ry": 1.15, "left_arm_rz": 2.63, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": -0.042, "right_arm_rx": -3.12, "right_arm_ry": 1.04, "right_arm_rz": -2.55, "right_gripper": 0.4}, "3": {"left_arm_vel": 0.004, "left_gripper_vel": -0.021, "left_arm_rx": -3.04, "left_arm_ry": 1.15, "left_arm_rz": 2.65, "left_gripper": 0.24, "right_arm_vel": 0.004, "right_gripper_vel": -0.021, "right_arm_rx": -3.12, "right_arm_ry": 1.04, "right_arm_rz": -2.56, "right_gripper": 0.4}, "4": {"left_arm_vel": 0.014, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.15, "left_arm_rz": 2.89, "left_gripper": 0.24, "right_arm_vel": 0.014, "right_gripper_vel": 0.0, "right_arm_rx": -3.12, "right_arm_ry": 1.04, "right_arm_rz": -2.77, "right_gripper": 0.4}, "5": {"left_arm_vel": 0.098, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.15, "left_arm_rz": 3.01, "left_gripper": 0.24, "right_arm_vel": 0.098, "right_gripper_vel": 0.0, "right_arm_rx": -3.11, "right_arm_ry": 1.1, "right_arm_rz": -2.91, "right_gripper": 0.4}, "6": {"left_arm_vel": 0.004, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.15, "left_arm_rz": 3.01, "left_gripper": 0.24, "right_arm_vel": 0.004, "right_gripper_vel": 0.0, "right_arm_rx": 3.1, "right_arm_ry": 1.13, "right_arm_rz": -2.97, "right_gripper": 0.4}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.15, "left_arm_rz": 3.01, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.1, "right_arm_ry": 1.13, "right_arm_rz": -2.98, "right_gripper": 0.4}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0031999999191612005, -0.004699999932199717, -0.0006000000284984708], "delta_rot": [0.01269999984651804, -0.0017999999690800905, 0.38600000739097595], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0057}, "right": {"delta_pos": [-0.010900000110268593, -0.0007999999797903001, 0.0007999999797903001], "delta_rot": [6.217800140380859, 0.09300000220537186, -0.4311999976634979], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.011}} + + [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 workspace, clearing the area after the previous zipper interaction. No physical contact is made with the bag or table.", + "actions": [ + { + "reasoning_cot": "The left arm remains stationary in a retracted position away from the bag. Visual evidence shows no contact with any object, and kinematic data confirms zero velocity. The arm is effectively idling in free space.", + "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 + }, + { + "reasoning_cot": "The right arm mirrors the left, holding a static hover position. There is no visual overlap with the bag or table surface, and gripper state remains unchanged. It is waiting for the next command.", + "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", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Arms are cleared from the workspace; ready for next manipulation sequence." + } +} +```` +--- +## 🎬 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_0033 + - **Total Frames**: 721 + - **Global Task Goal**: "Unknown Task" + + ### 1. INPUT DATA + - **KPM (Micro-Actions Timeline)**: [{"chunk_idx": 0, "start_frame": 0, "end_frame": 32, "chunk_intent": "Approaching the bag from a hovering position to initiate interaction.", "micro_actions": [{"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_at_foreground"}, {"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_center"}]}, {"chunk_idx": 1, "start_frame": 33, "end_frame": 57, "chunk_intent": "Right arm approaches and makes contact with the top surface of the bag to initiate manipulation, while left arm remains idle.", "micro_actions": [{"verb": "approach", "semantic_verb": null, "subject": "right_arm", "target": "top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Moving from hovering position to contact with bag:top_surface"}, {"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "Static hover in free space"}]}, {"chunk_idx": 2, "start_frame": 58, "end_frame": 70, "chunk_intent": "Right arm approaches and establishes contact with the top surface of the bag 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 hover to contact at bag:top_surface"}, {"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_in_peripheral_zone"}]}, {"chunk_idx": 3, "start_frame": 71, "end_frame": 86, "chunk_intent": "Right arm approaches and establishes contact with the top surface of the bag to initiate manipulation, while left arm remains idle.", "micro_actions": [{"verb": "approach", "semantic_verb": null, "subject": "right_arm", "target": "top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Moving from free space to contact with bag:top_surface"}, {"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "Static hover in free space"}]}, {"chunk_idx": 4, "start_frame": 87, "end_frame": 160, "chunk_intent": "Left arm approaches and grasps the zipper pull of the bag to initiate opening, while right arm stabilizes the bag body.", "micro_actions": [{"verb": "grasp", "semantic_verb": null, "subject": "left_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "moving from free space to zipper_pull"}, {"verb": "hold", "semantic_verb": "stabilize", "subject": "right_arm", "target": "top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "static_at_top_surface"}]}, {"chunk_idx": 5, "start_frame": 161, "end_frame": 194, "chunk_intent": "Left arm retreats from the bag zipper area to clear space, while right arm maintains a stabilizing hold on the bag body.", "micro_actions": [{"verb": "retreat", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "moving away from bag:zipper_pull to free space"}, {"verb": "hold", "semantic_verb": "stabilize", "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_bag_side"}]}, {"chunk_idx": 6, "start_frame": 195, "end_frame": 239, "chunk_intent": "Left arm approaches the bag zipper pull to initiate grasping, while right arm maintains a stabilizing hold on the bag body.", "micro_actions": [{"verb": "grasp", "semantic_verb": null, "subject": "left_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving from hover to 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_body"}]}, {"chunk_idx": 7, "start_frame": 240, "end_frame": 284, "chunk_intent": "Left arm executes a precise grasp on the bag's zipper pull to initiate opening, while the right arm maintains a stabilizing hold on the bag body.", "micro_actions": [{"verb": "grasp", "semantic_verb": null, "subject": "left_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "Approaching and securing grip on zipper_pull from free space"}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "Static stabilization at bag:main_body"}]}, {"chunk_idx": 8, "start_frame": 285, "end_frame": 309, "chunk_intent": "Left arm executes a precise grasp on the bag's zipper pull to initiate opening, while the right arm maintains a stabilizing hold on the bag body.", "micro_actions": [{"verb": "grasp", "semantic_verb": null, "subject": "left_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "approaching and grasping zipper_pull"}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_hold_on_bag_body"}]}, {"chunk_idx": 9, "start_frame": 310, "end_frame": 320, "chunk_intent": "Left arm maintains a precise grasp on the bag's zipper pull to initiate opening, while the right arm stabilizes the bag body by holding the top surface.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_zipper_pull"}, {"verb": "hold", "semantic_verb": "stabilize", "subject": "right_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "static_at_top_surface"}]}, {"chunk_idx": 10, "start_frame": 321, "end_frame": 346, "chunk_intent": "Left arm maintains a precise grasp on the bag's zipper pull to initiate opening, while the right arm stabilizes the bag body by holding the top surface.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_zipper_pull"}, {"verb": "press", "semantic_verb": "stabilize", "subject": "right_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "stabilizing_top_surface"}]}, {"chunk_idx": 11, "start_frame": 347, "end_frame": 364, "chunk_intent": "Left arm maintains a precise grasp on the bag's zipper pull to initiate opening, while the right arm stabilizes the bag body by holding the top surface.", "micro_actions": [{"verb": "pull", "semantic_verb": "unzip_bag", "subject": "left_arm", "target": "bag:zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "Pulling zipper pull along the track to open the bag"}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Stabilizing the bag body to allow left arm to unzip"}]}, {"chunk_idx": 12, "start_frame": 365, "end_frame": 391, "chunk_intent": "Left arm pulls the zipper pull to open the bag while right arm stabilizes the bag body.", "micro_actions": [{"verb": "pull", "semantic_verb": "unzip_bag", "subject": "left_arm", "target": "zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "Moving from initial grasp position along the zipper track towards the bag opening."}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "Static stabilization at the bag's center/right side."}]}, {"chunk_idx": 13, "start_frame": 392, "end_frame": 406, "chunk_intent": "Left arm pulls the zipper pull to open the bag while right arm stabilizes the bag body.", "micro_actions": [{"verb": "pull", "semantic_verb": "unzip", "subject": "left_arm", "target": "bag:zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "Pulling zipper pull along the track to open the bag"}, {"verb": "hold", "semantic_verb": "stabilize", "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Applying counter-pressure to stabilize bag during unzipping"}]}, {"chunk_idx": 14, "start_frame": 407, "end_frame": 433, "chunk_intent": "Left arm approaches the bag's top surface to stabilize it, while right arm hovers near the zipper pull in preparation for grasping.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Approaching and contacting the top surface of the bag from above."}, {"verb": "hover", "semantic_verb": "aligning_with_zipper", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "Positioning adjacent to the zipper pull without contact."}]}, {"chunk_idx": 15, "start_frame": 434, "end_frame": 448, "chunk_intent": "Left arm stabilizes the bag's top surface while right arm approaches and hovers near the zipper pull to prepare for grasping.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Approached and established contact with bag:top_surface to stabilize the object."}, {"verb": "hover", "semantic_verb": "align_with_zipper", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "Hovering in close proximity to bag:zipper_pull, maintaining alignment without contact."}]}, {"chunk_idx": 16, "start_frame": 449, "end_frame": 466, "chunk_intent": "Left arm stabilizes the bag's top surface by pinching the mesh panel, while right arm hovers near the zipper pull to prepare for grasping.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_mesh_panel"}, {"verb": "hover", "semantic_verb": null, "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "approaching_zipper_pull"}]}, {"chunk_idx": 17, "start_frame": 467, "end_frame": 486, "chunk_intent": "Left arm stabilizes the bag's top surface by pinching the mesh panel, while right arm hovers near the zipper pull to prepare for grasping.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_mesh_panel"}, {"verb": "approach", "semantic_verb": null, "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "moving_from_hover_to_zipper_pull"}]}, {"chunk_idx": 18, "start_frame": 487, "end_frame": 502, "chunk_intent": "Left arm stabilizes the bag's top surface by pinching the mesh panel, while right arm hovers near the zipper pull to prepare for grasping.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "Transitioned from approach to securing hold on bag:top_surface"}, {"verb": "hover", "semantic_verb": null, "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "Approaching bag:zipper_pull from table:center_zone"}]}, {"chunk_idx": 19, "start_frame": 503, "end_frame": 569, "chunk_intent": "Right arm executes a pull action on the zipper pull to open the bag, while left arm stabilizes the bag body.", "micro_actions": [{"verb": "pull", "semantic_verb": "unzip_bag", "subject": "right_arm", "target": "zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "Moving from grasped position at zipper_pull backwards to extend the opening"}, {"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "Static stabilization at bag:top_surface"}]}, {"chunk_idx": 20, "start_frame": 570, "end_frame": 618, "chunk_intent": "Right arm executes a pull action on the zipper pull to open the bag, while left arm stabilizes the bag body.", "micro_actions": [{"verb": "pull", "semantic_verb": "unzip_bag", "subject": "right_arm", "target": "zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "Pulling zipper pull away from bag center along the track"}, {"verb": "hold", "semantic_verb": "stabilize_bag", "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Static stabilization at bag top surface"}]}, {"chunk_idx": 21, "start_frame": 619, "end_frame": 667, "chunk_intent": "Both arms execute a coordinated retreat maneuver, moving backward and upward away from the bag to clear the workspace after completing the zipper interaction.", "micro_actions": [{"verb": "retreat", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "moving from bag:top_surface to free_space (backward-left-up)"}, {"verb": "retreat", "semantic_verb": null, "subject": "right_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "moving from bag:zipper_pull to free_space (backward-right-up)"}]}, {"chunk_idx": 22, "start_frame": 668, "end_frame": 720, "chunk_intent": "Both arms maintain a static hovering position above the workspace, clearing the area after the previous zipper interaction. No physical contact is made with the bag or table.", "micro_actions": [{"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_in_free_space"}, {"verb": "idle", "semantic_verb": null, "subject": "right_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_in_free_space"}]}] + - **WSM (State Memory)**: [{"chunk_idx": 0, "global_frame_range": [0, 32], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Approaching the bag from a hovering position to initiate 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": [33, 57], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Right arm approaches and makes contact with the top surface of the bag 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": [58, 70], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Right arm approaches and establishes contact with the top surface of the bag 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": 3, "global_frame_range": [71, 86], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Right arm approaches and establishes contact with the top surface of the bag 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": 4, "global_frame_range": [87, 160], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and grasps the zipper pull of the bag to initiate opening, while right arm stabilizes the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 5, "global_frame_range": [161, 194], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}], "short_term_memory": {"last_chunk_intent": "Left arm retreats from the bag zipper area to clear space, while right arm maintains a stabilizing hold on the bag body.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 6, "global_frame_range": [195, 239], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "being_grasped"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches the bag zipper pull to initiate grasping, while right arm maintains a stabilizing hold on the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 7, "global_frame_range": [240, 284], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}], "short_term_memory": {"last_chunk_intent": "Left arm executes a precise grasp on the bag's zipper pull to initiate opening, while the right arm maintains a stabilizing hold on the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 8, "global_frame_range": [285, 309], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}], "short_term_memory": {"last_chunk_intent": "Left arm executes a precise grasp on the bag's zipper pull to initiate opening, while the right arm maintains a stabilizing hold on the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 9, "global_frame_range": [310, 320], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}], "short_term_memory": {"last_chunk_intent": "Left arm maintains a precise grasp on the bag's zipper pull to initiate opening, while the right arm stabilizes the bag body by holding the top surface.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 10, "global_frame_range": [321, 346], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}], "short_term_memory": {"last_chunk_intent": "Left arm maintains a precise grasp on the bag's zipper pull to initiate opening, while the right arm stabilizes the bag body by holding the top surface.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 11, "global_frame_range": [347, 364], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}], "short_term_memory": {"last_chunk_intent": "Left arm maintains a precise grasp on the bag's zipper pull to initiate opening, while the right arm stabilizes the bag body by holding the top surface.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 12, "global_frame_range": [365, 391], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}], "short_term_memory": {"last_chunk_intent": "Left arm pulls the zipper pull to open the bag while right arm stabilizes the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 13, "global_frame_range": [392, 406], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}], "short_term_memory": {"last_chunk_intent": "Left arm pulls the zipper pull to open the bag while right arm stabilizes the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 14, "global_frame_range": [407, 433], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_by_right_arm"}, {"anchor_id": "bag:top_surface", "current_status": "stabilized_by_left_arm"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches the bag's top surface to stabilize it, while right arm hovers near the zipper pull in preparation for grasping.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 15, "global_frame_range": [434, 448], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_by_right_arm"}, {"anchor_id": "bag:top_surface", "current_status": "stabilized_by_left_arm"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag's top surface while right arm approaches and hovers near the zipper pull to prepare for grasping.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 16, "global_frame_range": [449, 466], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_by_right_arm"}, {"anchor_id": "bag:top_surface", "current_status": "stabilized_by_left_arm"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag's top surface by pinching the mesh panel, while right arm hovers near the zipper pull to prepare for grasping.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 17, "global_frame_range": [467, 486], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_by_right_arm"}, {"anchor_id": "bag:top_surface", "current_status": "stabilized_by_left_arm"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag's top surface by pinching the mesh panel, while right arm hovers near the zipper pull to prepare for grasping.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 18, "global_frame_range": [487, 502], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_by_right_arm"}, {"anchor_id": "bag:top_surface", "current_status": "stabilized_by_left_arm"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}], "short_term_memory": {"last_chunk_intent": "Left arm stabilizes the bag's top surface by pinching the mesh panel, while right arm hovers near the zipper pull to prepare for grasping.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 19, "global_frame_range": [503, 569], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_by_right_arm"}, {"anchor_id": "bag:top_surface", "current_status": "stabilized_by_left_arm"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}], "short_term_memory": {"last_chunk_intent": "Right arm executes a pull action on the zipper pull to open the bag, while left arm stabilizes the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 20, "global_frame_range": [570, 618], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_by_right_arm"}, {"anchor_id": "bag:top_surface", "current_status": "stabilized_by_left_arm"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}], "short_term_memory": {"last_chunk_intent": "Right arm executes a pull action on the zipper pull to open the bag, while left arm stabilizes the bag body.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 21, "global_frame_range": [619, 667], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "released"}, {"anchor_id": "bag:top_surface", "current_status": "unconstrained"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}], "short_term_memory": {"last_chunk_intent": "Both arms execute a coordinated retreat maneuver, moving backward and upward away from the bag to clear the workspace after completing the zipper interaction.", "left_end_effector": {"grasp_status": "none", "contact_target": "none"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 22, "global_frame_range": [668, 720], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "released"}, {"anchor_id": "bag:top_surface", "current_status": "unconstrained"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:zipper_track", "current_status": "opening"}], "short_term_memory": {"last_chunk_intent": "Both arms maintain a static hovering position above the workspace, clearing the area after the previous zipper interaction. No physical contact is made with the bag or table.", "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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_surface", "current_status": "exposed"}, {"anchor_id": "table:center_zone", "current_status": "occupied_by_bag"}] + + 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_0033", + "merge_thought": "The task is divided into four logical phases based on the shift in manipulation targets and arm roles. \n1. **Approach & Initial Contact (Chunks 0-3)**: The robot approaches the bag. The right arm makes initial contact with the top surface to stabilize/locate, while the left arm remains idle. This is a preparatory phase.\n2. **Left-Arm Unzipping Attempt & Adjustment (Chunks 4-13)**: The left arm grasps the zipper pull and attempts to unzip the bag while the right arm stabilizes the body. There is a brief retreat/re-grasp sequence (Chunks 5-8) which is part of the same semantic goal of 'opening the bag via left arm'. The phase ends when the left arm releases or transitions away from the zipper pull after completing its pull action.\n3. **Role Swap & Right-Arm Unzipping (Chunks 14-20)**: A clear state transition occurs where the left arm moves to stabilize the bag body (top surface/mesh), and the right arm takes over the zipper pull. This represents a strategic shift in manipulation strategy (bimanual coordination swap). The right arm then executes the unzipping pull.\n4. **Retreat & Idle (Chunks 21-22)**: Both arms release the bag and retreat to a neutral hovering position, marking the end of the interaction.", + "segments": [ + { + "segment_id": 0, + "primitive_type": "Approach", + "chunk_idx_range": [ + 0, + 3 + ], + "subtask": "Approach bag and establish initial contact/stabilization with right arm", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "exposed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "exposed" + }, + { + "anchor_id": "table:center_zone", + "current_status": "occupied_by_bag" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "exposed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "touched_by_right_arm" + }, + { + "anchor_id": "table:center_zone", + "current_status": "occupied_by_bag" + } + ] + }, + "causal_summary": { + "trigger": "Right arm moved from free space to contact bag top surface", + "effect": "Bag stabilized for subsequent manipulation" + } + }, + { + "segment_id": 1, + "primitive_type": "Grasp", + "chunk_idx_range": [ + 4, + 13 + ], + "subtask": "Left arm grasps and pulls zipper to open bag (with right arm stabilization)", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "exposed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "touched_by_right_arm" + }, + { + "anchor_id": "table:center_zone", + "current_status": "occupied_by_bag" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "exposed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "partially_opened" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "exposed" + }, + { + "anchor_id": "table:center_zone", + "current_status": "occupied_by_bag" + } + ] + }, + "causal_summary": { + "trigger": "Left arm grasped zipper pull and pulled along track", + "effect": "Bag zipper partially opened" + } + }, + { + "segment_id": 2, + "primitive_type": "Grasp", + "chunk_idx_range": [ + 14, + 20 + ], + "subtask": "Swap roles: Left arm stabilizes bag, Right arm grasps and pulls zipper", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "exposed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "partially_opened" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "exposed" + }, + { + "anchor_id": "table:center_zone", + "current_status": "occupied_by_bag" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "stabilized_by_left_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "opened" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "held_by_left_arm" + }, + { + "anchor_id": "table:center_zone", + "current_status": "occupied_by_bag" + } + ] + }, + "causal_summary": { + "trigger": "Right arm grasped zipper pull while left arm stabilized bag body", + "effect": "Bag zipper fully opened via right arm pull" + } + }, + { + "segment_id": 3, + "primitive_type": "Retract", + "chunk_idx_range": [ + 21, + 22 + ], + "subtask": "Retreat both arms to neutral hover position", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "stabilized_by_left_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "opened" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "held_by_left_arm" + }, + { + "anchor_id": "table:center_zone", + "current_status": "occupied_by_bag" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "exposed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "released" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "unconstrained" + }, + { + "anchor_id": "table:center_zone", + "current_status": "occupied_by_bag" + } + ] + }, + "causal_summary": { + "trigger": "Both arms released contact and moved backward/upward", + "effect": "Robot cleared workspace, returning to idle state" + } + } + ] +} +```` +--- diff --git a/debug/episode_0034/images/chunkannotator_0_img_0.jpg b/debug/episode_0034/images/chunkannotator_0_img_0.jpg new file mode 100644 index 0000000000000000000000000000000000000000..9c9dc2ed0684e34c14a4cb93bcc21f9370dbde1a --- /dev/null +++ b/debug/episode_0034/images/chunkannotator_0_img_0.jpg @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f48443567eab5a280f08bdea77c5a214dfddf57f980f9722453a83a35319beab +size 18146 diff --git a/debug/episode_0034/images/chunkannotator_0_img_1.jpg b/debug/episode_0034/images/chunkannotator_0_img_1.jpg new file mode 100644 index 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b/debug/episode_0034/trace_report.md @@ -0,0 +1,5588 @@ +# 🤖 Episode_0034 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 beige bag is positioned centrally on a white table surface, directly within the robot's forward reach zone.", + "initial_semantic_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "exposed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + }, + { + "anchor_id": "bag:side_handle", + "current_status": "partially_obscured_but_accessible" + }, + { + "anchor_id": "table:surface_center", + "current_status": "clear" + } + ], + "background_distractors": [ + "robot_grippers", + "cables" + ] +} +```` +--- + +# 🤖 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'table:surface_center'] + + 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": 0.06, "vel_score": 0.12, "angle_score": 0.73, "vel_fft": [0.01, 0.009, 0.008, 0.006, 0.004, 0.002, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.002, 0.002, 0.002, 0.002, 0.003, 0.003, 0.003, 0.003], "angle_fft": [0.058, 0.055, 0.046, 0.034, 0.021, 0.012, 0.006, 0.004, 0.004, 0.004, 0.006, 0.008, 0.01, 0.011, 0.01, 0.012, 0.016, 0.018, 0.018, 0.016]}, "right": {"vel": 0.31, "angle": 0.91, "vel_score": 3.45, "angle_score": 9.27, "vel_fft": [0.312, 0.206, 0.041, 0.02, 0.003, 0.014, 0.003, 0.011, 0.007, 0.004, 0.003, 0.011, 0.009, 0.008, 0.017, 0.026, 0.021, 0.012, 0.018, 0.02], "angle_fft": [0.909, 0.465, 0.051, 0.059, 0.088, 0.137, 0.091, 0.027, 0.055, 0.073, 0.081, 0.026, 0.06, 0.064, 0.023, 0.104, 0.088, 0.025, 0.051, 0.068]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.15, "left_arm_rz": 3.01, "left_gripper": 0.23, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.08, "right_arm_ry": 1.13, "right_arm_rz": -2.99, "right_gripper": 0.39}, "1": {"left_arm_vel": 0.478, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.15, "left_arm_rz": 3.01, "left_gripper": 0.23, "right_arm_vel": 0.478, "right_gripper_vel": 0.0, "right_arm_rx": 2.82, "right_arm_ry": 1.14, "right_arm_rz": -2.98, "right_gripper": 0.39}, "2": {"left_arm_vel": 0.808, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.15, "left_arm_rz": 3.01, "left_gripper": 0.23, "right_arm_vel": 0.808, "right_gripper_vel": 0.0, "right_arm_rx": 2.89, "right_arm_ry": 1.05, "right_arm_rz": -2.65, "right_gripper": 0.39}, "3": {"left_arm_vel": 0.83, "left_gripper_vel": 0.0, "left_arm_rx": -3.03, "left_arm_ry": 1.15, "left_arm_rz": 3.01, "left_gripper": 0.23, "right_arm_vel": 0.83, "right_gripper_vel": 0.0, "right_arm_rx": 2.95, "right_arm_ry": 0.99, "right_arm_rz": -2.34, "right_gripper": 0.39}, "4": {"left_arm_vel": 0.647, "left_gripper_vel": 0.0, "left_arm_rx": -3.03, "left_arm_ry": 1.13, "left_arm_rz": 3.02, "left_gripper": 0.23, "right_arm_vel": 0.647, "right_gripper_vel": 0.0, "right_arm_rx": 2.86, "right_arm_ry": 0.95, "right_arm_rz": -2.22, "right_gripper": 0.39}, "5": {"left_arm_vel": 0.799, "left_gripper_vel": 0.0, "left_arm_rx": -3.03, "left_arm_ry": 1.07, "left_arm_rz": 3.02, "left_gripper": 0.23, "right_arm_vel": 0.799, "right_gripper_vel": 0.0, "right_arm_rx": 2.85, "right_arm_ry": 0.9, "right_arm_rz": -2.11, "right_gripper": 0.39}, "6": {"left_arm_vel": 0.307, "left_gripper_vel": 0.0, "left_arm_rx": -3.03, "left_arm_ry": 1.06, "left_arm_rz": 3.02, "left_gripper": 0.23, "right_arm_vel": 0.307, "right_gripper_vel": 0.0, "right_arm_rx": 2.84, "right_arm_ry": 0.89, "right_arm_rz": -2.09, "right_gripper": 0.39}, "7": {"left_arm_vel": 0.321, "left_gripper_vel": 0.0, "left_arm_rx": -3.03, "left_arm_ry": 1.05, "left_arm_rz": 3.02, "left_gripper": 0.24, "right_arm_vel": 0.321, "right_gripper_vel": 0.0, "right_arm_rx": 2.82, "right_arm_ry": 0.88, "right_arm_rz": -2.09, "right_gripper": 0.39}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.016200000420212746, -0.0019000000320374966, 0.0003000000142492354], "delta_rot": [0.004399999976158142, -0.09749999642372131, 0.003599999938160181], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0163}, "right": {"delta_pos": [0.44130000472068787, 0.23659999668598175, -0.026499999687075615], "delta_rot": [-0.26429998874664307, -0.2581000030040741, 0.9017999768257141], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and -Z(Down)", "magnitude": 0.5014}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.34549999237060547, -0.10509999841451645, -0.09430000185966492], "delta_rot": [5.675000190734863, -0.5794000029563904, -1.4140000343322754], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.3733}, "right": {"delta_pos": [0.45329999923706055, 0.2759000062942505, -0.08789999783039093], "delta_rot": [-0.41839998960494995, -0.43140000104904175, 0.7982000112533569], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and -Z(Down)", "magnitude": 0.5379}} + + ========================================= + [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 top surface of the bag to stabilize or prepare for manipulation, while left arm remains idle.", + "actions": [ + { + "reasoning_cot": "The right arm executes a significant forward and downward trajectory (delta_pos magnitude 0.5014) towards the bag. Visual evidence in frames T1-T2 confirms the gripper is positioned directly over the 'bag:main_body' (specifically the silver reflective patch). The action transitions from free-space approach to physical contact.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": "contact_surface", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "Moving from hover state to direct contact with bag top surface", + "topology_change": false + }, + { + "reasoning_cot": "The left arm shows negligible kinematic displacement (delta_pos magnitude 0.0163) and remains in its initial position away from the object. Visual frames confirm no interaction with the bag or table.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "Static hold in free space", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Right end-effector has successfully located and established contact with the main body of the bag." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'table:surface_center'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm approaches and makes contact with the top surface of the bag to stabilize or prepare for 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": 0.23, "angle": 4.63, "vel_score": 2.53, "angle_score": 10.27, "vel_fft": [0.234, 0.135, 0.035, 0.01, 0.007, 0.008, 0.007, 0.004, 0.006, 0.005, 0.006, 0.003, 0.004, 0.006, 0.008, 0.007, 0.006, 0.005, 0.005, 0.005], "angle_fft": [4.633, 3.892, 3.787, 3.725, 3.608, 3.663, 3.645, 3.636, 3.623, 3.6, 3.575, 3.568, 3.589, 3.615, 3.659, 3.702, 3.642, 3.603, 3.601, 3.613]}, "right": {"vel": 0.04, "angle": 0.19, "vel_score": 0.55, "angle_score": 2.1, "vel_fft": [0.044, 0.038, 0.027, 0.015, 0.007, 0.008, 0.01, 0.01, 0.008, 0.005, 0.004, 0.006, 0.006, 0.006, 0.003, 0.002, 0.003, 0.003, 0.003, 0.003], "angle_fft": [0.189, 0.133, 0.076, 0.034, 0.017, 0.029, 0.005, 0.025, 0.023, 0.013, 0.013, 0.021, 0.02, 0.011, 0.009, 0.015, 0.004, 0.01, 0.009, 0.02]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.03, "left_arm_ry": 1.04, "left_arm_rz": 3.02, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.79, "right_arm_ry": 0.86, "right_arm_rz": -2.09, "right_gripper": 0.39}, "1": {"left_arm_vel": 0.116, "left_gripper_vel": -0.357, "left_arm_rx": -3.02, "left_arm_ry": 1.02, "left_arm_rz": 3.01, "left_gripper": 0.25, "right_arm_vel": 0.116, "right_gripper_vel": -0.357, "right_arm_rx": 2.67, "right_arm_ry": 0.74, "right_arm_rz": -2.19, "right_gripper": 0.38}, "2": {"left_arm_vel": 0.032, "left_gripper_vel": -2.499, "left_arm_rx": -3.02, "left_arm_ry": 1.02, "left_arm_rz": 2.96, "left_gripper": 0.27, "right_arm_vel": 0.032, "right_gripper_vel": -2.499, "right_arm_rx": 2.67, "right_arm_ry": 0.72, "right_arm_rz": -2.18, "right_gripper": 0.18}, "3": {"left_arm_vel": 0.013, "left_gripper_vel": -0.882, "left_arm_rx": -3.07, "left_arm_ry": 1.03, "left_arm_rz": 2.89, "left_gripper": 0.28, "right_arm_vel": 0.013, "right_gripper_vel": -0.882, "right_arm_rx": 2.69, "right_arm_ry": 0.71, "right_arm_rz": -2.16, "right_gripper": 0.08}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 3.09, "left_arm_ry": 1.03, "left_arm_rz": 2.71, "left_gripper": 0.33, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.69, "right_arm_ry": 0.71, "right_arm_rz": -2.17, "right_gripper": 0.08}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": -0.021, "left_arm_rx": 2.96, "left_arm_ry": 0.99, "left_arm_rz": 2.48, "left_gripper": 0.38, "right_arm_vel": 0.0, "right_gripper_vel": -0.021, "right_arm_rx": 2.69, "right_arm_ry": 0.71, "right_arm_rz": -2.17, "right_gripper": 0.08}, "6": {"left_arm_vel": 0.004, "left_gripper_vel": 0.0, "left_arm_rx": 2.9, "left_arm_ry": 0.87, "left_arm_rz": 2.27, "left_gripper": 0.43, "right_arm_vel": 0.004, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.7, "right_arm_rz": -2.18, "right_gripper": 0.08}, "7": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": 2.64, "left_arm_ry": 0.57, "left_arm_rz": 1.6, "left_gripper": 0.44, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.7, "right_arm_rz": -2.19, "right_gripper": 0.07}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.32839998602867126, -0.1031000018119812, -0.09459999948740005], "delta_rot": [5.670499801635742, -0.4756999909877777, -1.4177000522613525], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.3569}, "right": {"delta_pos": [0.009600000455975533, 0.031099999323487282, -0.055799998342990875], "delta_rot": [-0.12880000472068787, -0.15710000693798065, -0.1054999977350235], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.0646}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.2395000010728836, -0.09470000118017197, -0.07750000059604645], "delta_rot": [5.803400039672852, -0.4052000045776367, -1.3071000576019287], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.269}, "right": {"delta_pos": [0.00559999980032444, 0.03539999946951866, -0.05559999868273735], "delta_rot": [-0.21459999680519104, -0.21359999477863312, -0.2094999998807907], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.0661}} + + ========================================= + [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 by pressing down on the top surface near the zipper, while the left arm remains idle in a hovering position.", + "actions": [ + { + "reasoning_cot": "The right arm executes a significant forward (+X) and downward (-Z) movement (delta_pos magnitude ~0.065) to transition from free space to contact with the bag's top surface. The gripper signal is 'stable' but visual evidence shows the end-effector pressing against the fabric to stabilize the object, likely in preparation for manipulating the zipper or opening the bag.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "press", + "semantic_action": "stabilize_bag", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "top_surface" + }, + "spatial_logic": "moving from hover to top_surface", + "topology_change": false + }, + { + "reasoning_cot": "The left arm exhibits negligible kinematic displacement (delta_pos magnitude ~0.35 but largely lateral/hovering without engagement) and maintains an open gripper state. Visual frames confirm it remains stationary relative to the workspace, not interacting with the bag.", + "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": [ + { + "anchor_id": "bag:top_surface", + "current_status": "pressed" + } + ], + "task_progress": "Bag stabilized by right arm; preparing for zipper 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'table:surface_center', 'bag:top_surface'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm approaches and stabilizes the bag by pressing down on the top surface near the zipper, 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": 0.07, "angle": 0.21, "vel_score": 0.78, "angle_score": 2.08, "vel_fft": [0.069, 0.041, 0.026, 0.002, 0.008, 0.001, 0.004, 0.002, 0.0, 0.003, 0.002, 0.002, 0.001, 0.003, 0.002, 0.002, 0.001, 0.001, 0.002, 0.001], "angle_fft": [0.208, 0.087, 0.028, 0.054, 0.059, 0.025, 0.018, 0.022, 0.01, 0.015, 0.02, 0.013, 0.007, 0.009, 0.015, 0.01, 0.007, 0.017, 0.009, 0.003]}, "right": {"vel": 0.0, "angle": 0.09, "vel_score": 0.06, "angle_score": 0.96, "vel_fft": [0.004, 0.004, 0.003, 0.003, 0.003, 0.002, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.0, 0.0, 0.001, 0.001, 0.0, 0.0, 0.0], "angle_fft": [0.089, 0.061, 0.016, 0.021, 0.008, 0.022, 0.025, 0.008, 0.012, 0.013, 0.014, 0.018, 0.01, 0.005, 0.01, 0.014, 0.006, 0.005, 0.002, 0.008]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.63, "left_arm_ry": 0.57, "left_arm_rz": 1.6, "left_gripper": 0.44, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.7, "right_arm_rz": -2.19, "right_gripper": 0.07}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.61, "left_arm_ry": 0.57, "left_arm_rz": 1.59, "left_gripper": 0.38, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.7, "right_arm_rz": -2.19, "right_gripper": 0.07}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.61, "left_arm_ry": 0.57, "left_arm_rz": 1.6, "left_gripper": 0.3, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.7, "right_arm_rz": -2.19, "right_gripper": 0.07}, "3": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": 2.62, "left_arm_ry": 0.6, "left_arm_rz": 1.64, "left_gripper": 0.27, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.65, "right_arm_ry": 0.69, "right_arm_rz": -2.21, "right_gripper": 0.07}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.67, "left_arm_ry": 0.59, "left_arm_rz": 1.71, "left_gripper": 0.27, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.67, "right_arm_rz": -2.24, "right_gripper": 0.07}, "5": {"left_arm_vel": 0.039, "left_gripper_vel": -0.042, "left_arm_rx": 2.68, "left_arm_ry": 0.6, "left_arm_rz": 1.72, "left_gripper": 0.27, "right_arm_vel": 0.039, "right_gripper_vel": -0.042, "right_arm_rx": 2.62, "right_arm_ry": 0.67, "right_arm_rz": -2.26, "right_gripper": 0.07}, "6": {"left_arm_vel": 0.02, "left_gripper_vel": -0.189, "left_arm_rx": 2.7, "left_arm_ry": 0.61, "left_arm_rz": 1.72, "left_gripper": 0.27, "right_arm_vel": 0.02, "right_gripper_vel": -0.189, "right_arm_rx": 2.61, "right_arm_ry": 0.66, "right_arm_rz": -2.26, "right_gripper": 0.06}, "7": {"left_arm_vel": 0.004, "left_gripper_vel": 0.0, "left_arm_rx": 2.77, "left_arm_ry": 0.64, "left_arm_rz": 1.71, "left_gripper": 0.27, "right_arm_vel": 0.004, "right_gripper_vel": 0.0, "right_arm_rx": 2.58, "right_arm_ry": 0.65, "right_arm_rz": -2.29, "right_gripper": 0.06}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.08879999816417694, 0.010200000368058681, 0.01679999940097332], "delta_rot": [0.13770000636577606, 0.06759999692440033, 0.11029999703168869], "gripper_changed": false, "flow_direction": "-X(Backward)", "magnitude": 0.0909}, "right": {"delta_pos": [-0.004100000020116568, 0.00430000014603138, 0.00019999999494757503], "delta_rot": [-0.08579999953508377, -0.05640000104904175, -0.10409999638795853], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0059}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.13519999384880066, -0.04270000010728836, 0.04520000144839287], "delta_rot": [0.4503999948501587, 0.29260000586509705, 0.4131999909877777], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.1488}, "right": {"delta_pos": [-0.0012000000569969416, 0.0019000000320374966, -0.0005000000237487257], "delta_rot": [-0.1420000046491623, -0.12780000269412994, -0.24279999732971191], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0023}} + + ========================================= + [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 zipper pull ring to stabilize or open the bag, while the right arm maintains a static stabilizing hold on the bag's top corner.", + "actions": [ + { + "reasoning_cot": "The left arm moves from a hovering position towards the zipper pull (visible in T0-T1). In the micro-execution frames, the gripper closes around the metal ring of the zipper pull. This is a clear 'grasp' action targeting the specific functional component of the bag.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "zipper_pull" + }, + "spatial_logic": "Approaching from free space to secure the zipper_pull anchor.", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains stationary throughout the sequence, pressing against the top corner/surface of the bag near the zipper track. This provides counter-tension for the left arm's manipulation. No movement or state change occurs.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "hold", + "semantic_action": "stabilize", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "top_surface" + }, + "spatial_logic": "Static hold at the top_surface anchor to prevent bag displacement.", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "zipper_pull", + "current_status": "grasped" + } + ], + "task_progress": "Left arm has successfully acquired the zipper pull; ready to unzip or manipulate the opening." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'table:surface_center', 'bag:top_surface', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and grasps the zipper pull ring to stabilize or open the bag, while the right arm maintains a static stabilizing hold on the bag's top corner.", "left_end_effector": {"grasp_status": "holding", "contact_target": "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": 0.16, "angle": 0.85, "vel_score": 1.35, "angle_score": 6.95, "vel_fft": [0.161, 0.013, 0.047, 0.032, 0.003, 0.012, 0.004, 0.013, 0.002, 0.007, 0.005, 0.004, 0.004, 0.008, 0.005, 0.005, 0.007, 0.008, 0.006, 0.005], "angle_fft": [0.851, 0.209, 0.251, 0.127, 0.081, 0.007, 0.084, 0.1, 0.04, 0.071, 0.049, 0.069, 0.036, 0.064, 0.028, 0.036, 0.05, 0.061, 0.052, 0.044]}, "right": {"vel": 0.0, "angle": 0.13, "vel_score": 0.05, "angle_score": 1.16, "vel_fft": [0.005, 0.003, 0.003, 0.003, 0.002, 0.002, 0.002, 0.002, 0.001, 0.001, 0.001, 0.0, 0.0, 0.001, 0.001, 0.0, 0.0, 0.001, 0.0, 0.0], "angle_fft": [0.135, 0.036, 0.06, 0.029, 0.038, 0.029, 0.01, 0.014, 0.012, 0.012, 0.004, 0.012, 0.004, 0.013, 0.01, 0.004, 0.003, 0.01, 0.006, 0.005]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.79, "left_arm_ry": 0.64, "left_arm_rz": 1.71, "left_gripper": 0.27, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.58, "right_arm_ry": 0.64, "right_arm_rz": -2.3, "right_gripper": 0.06}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": -0.105, "left_arm_rx": 2.92, "left_arm_ry": 0.68, "left_arm_rz": 1.72, "left_gripper": 0.27, "right_arm_vel": 0.0, "right_gripper_vel": -0.105, "right_arm_rx": 2.55, "right_arm_ry": 0.62, "right_arm_rz": -2.34, "right_gripper": 0.06}, "2": {"left_arm_vel": 0.014, "left_gripper_vel": -0.084, "left_arm_rx": 2.96, "left_arm_ry": 0.69, "left_arm_rz": 1.71, "left_gripper": 0.27, "right_arm_vel": 0.014, "right_gripper_vel": -0.084, "right_arm_rx": 2.54, "right_arm_ry": 0.61, "right_arm_rz": -2.36, "right_gripper": 0.06}, "3": {"left_arm_vel": 0.006, "left_gripper_vel": 0.0, "left_arm_rx": 2.95, "left_arm_ry": 0.68, "left_arm_rz": 1.63, "left_gripper": 0.27, "right_arm_vel": 0.006, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.61, "right_arm_rz": -2.36, "right_gripper": 0.06}, "4": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": 2.86, "left_arm_ry": 0.67, "left_arm_rz": 1.54, "left_gripper": 0.26, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.6, "right_arm_rz": -2.37, "right_gripper": 0.06}, "5": {"left_arm_vel": 0.039, "left_gripper_vel": -0.105, "left_arm_rx": 2.85, "left_arm_ry": 0.71, "left_arm_rz": 1.52, "left_gripper": 0.12, "right_arm_vel": 0.039, "right_gripper_vel": -0.105, "right_arm_rx": 2.53, "right_arm_ry": 0.59, "right_arm_rz": -2.39, "right_gripper": 0.05}, "6": {"left_arm_vel": 0.047, "left_gripper_vel": 0.0, "left_arm_rx": 2.87, "left_arm_ry": 0.72, "left_arm_rz": 1.5, "left_gripper": 0.06, "right_arm_vel": 0.047, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.59, "right_arm_rz": -2.41, "right_gripper": 0.05}, "7": {"left_arm_vel": 0.027, "left_gripper_vel": 0.0, "left_arm_rx": 2.88, "left_arm_ry": 0.72, "left_arm_rz": 1.49, "left_gripper": 0.02, "right_arm_vel": 0.027, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.59, "right_arm_rz": -2.42, "right_gripper": 0.05}, "8": {"left_arm_vel": 0.011, "left_gripper_vel": 0.0, "left_arm_rx": 2.89, "left_arm_ry": 0.72, "left_arm_rz": 1.5, "left_gripper": 0.0, "right_arm_vel": 0.011, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.58, "right_arm_rz": -2.43, "right_gripper": 0.05}, "9": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": 2.91, "left_arm_ry": 0.74, "left_arm_rz": 1.62, "left_gripper": -0.01, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.58, "right_arm_rz": -2.43, "right_gripper": 0.05}, "10": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": 2.96, "left_arm_ry": 0.82, "left_arm_rz": 1.83, "left_gripper": 0.08, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.58, "right_arm_rz": -2.43, "right_gripper": 0.05}, "11": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.99, "left_arm_ry": 0.84, "left_arm_rz": 1.89, "left_gripper": 0.15, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.58, "right_arm_rz": -2.43, "right_gripper": 0.05}, "12": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": 3.03, "left_arm_ry": 0.85, "left_arm_rz": 1.94, "left_gripper": 0.23, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.43, "right_gripper": 0.05}, "13": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": 3.09, "left_arm_ry": 0.86, "left_arm_rz": 2.01, "left_gripper": 0.31, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.43, "right_gripper": 0.05}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.04309999942779541, -0.05249999836087227, 0.02850000001490116], "delta_rot": [0.29429998993873596, 0.22059999406337738, 0.30390000343322754], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.0736}, "right": {"delta_pos": [0.002899999963119626, -0.002400000113993883, -0.0007999999797903001], "delta_rot": [-0.05180000141263008, -0.06750000268220901, -0.13249999284744263], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0038}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.016899999231100082, -0.04410000145435333, -0.026200000196695328], "delta_rot": [-5.694499969482422, 0.09830000251531601, 0.6629999876022339], "gripper_changed": true, "flow_direction": "-Y(Right) and -Z(Down)", "magnitude": 0.054}, "right": {"delta_pos": [0.00279999990016222, -0.0024999999441206455, -0.0007999999797903001], "delta_rot": [-0.053599998354911804, -0.0714000016450882, -0.13539999723434448], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0038}} + + ========================================= + [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 releases the zipper pull ring and retreats to clear the workspace, while the right arm maintains a static stabilizing hold on the bag's top corner.", + "actions": [ + { + "reasoning_cot": "The left gripper is observed opening (gripper width increases from ~0.06 to ~0.31) and the arm moves backward (-X) and upward (+Z), moving away from the zipper pull ring. This confirms a release and retreat action sequence.", + "causal_trace": { + "gripper_signal": "opening", + "visual_contact": "none" + }, + "action_verb": "release", + "semantic_action": "release_and_retreat", + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "zipper_pull" + }, + "spatial_logic": "Retreating from zipper_pull to free space", + "topology_change": false + }, + { + "reasoning_cot": "The right arm shows negligible kinematic displacement (delta_pos magnitude 0.0038) and the gripper remains closed/stable. Visually, it continues to pinch the top corner of the bag to prevent it from sliding 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:top_surface" + }, + "spatial_logic": "Static stabilization at bag:top_surface", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "zipper_pull", + "current_status": "released" + } + ], + "task_progress": "Left arm has completed interaction with the zipper pull and is clearing the area; right 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'table:surface_center', 'bag:top_surface', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm releases the zipper pull ring and retreats to clear the workspace, while the right arm maintains a static stabilizing hold on the bag's top corner.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}} + ⚠️ 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": 4.84, "vel_score": 0.76, "angle_score": 4.61, "vel_fft": [0.088, 0.016, 0.011, 0.005, 0.006, 0.003, 0.01, 0.005, 0.003, 0.002, 0.003, 0.005, 0.003, 0.004, 0.004, 0.002, 0.004, 0.005, 0.005, 0.004], "angle_fft": [4.84, 4.414, 4.408, 4.312, 4.382, 4.31, 4.377, 4.365, 4.333, 4.337, 4.316, 4.345, 4.32, 4.337, 4.32, 4.33, 4.319, 4.343, 4.322, 4.346]}, "right": {"vel": 0.0, "angle": 0.01, "vel_score": 0.0, "angle_score": 0.08, "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": [0.009, 0.003, 0.003, 0.004, 0.002, 0.002, 0.003, 0.005, 0.001, 0.001, 0.006, 0.004, 0.003, 0.004, 0.002, 0.001, 0.004, 0.006, 0.001, 0.003]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 3.14, "left_arm_ry": 0.87, "left_arm_rz": 2.09, "left_gripper": 0.38, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.43, "right_gripper": 0.05}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.07, "left_arm_ry": 0.85, "left_arm_rz": 2.19, "left_gripper": 0.44, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.57, "right_arm_rz": -2.43, "right_gripper": 0.05}, "2": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": -3.03, "left_arm_ry": 0.81, "left_arm_rz": 2.23, "left_gripper": 0.46, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.43, "right_gripper": 0.05}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.93, "left_arm_ry": 0.72, "left_arm_rz": 2.33, "left_gripper": 0.46, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.43, "right_gripper": 0.05}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": -0.021, "left_arm_rx": -2.95, "left_arm_ry": 0.71, "left_arm_rz": 2.39, "left_gripper": 0.44, "right_arm_vel": 0.0, "right_gripper_vel": -0.021, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.43, "right_gripper": 0.05}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 0.78, "left_arm_rz": 2.35, "left_gripper": 0.44, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.44, "right_gripper": 0.05}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.93, "left_arm_ry": 0.74, "left_arm_rz": 2.37, "left_gripper": 0.42, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.44, "right_gripper": 0.05}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.9, "left_arm_ry": 0.74, "left_arm_rz": 2.37, "left_gripper": 0.39, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.44, "right_gripper": 0.05}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.02419999986886978, 0.0005000000237487257, -0.05790000036358833], "delta_rot": [-6.039599895477295, -0.12759999930858612, 0.28450000286102295], "gripper_changed": false, "flow_direction": "+X(Forward) and -Z(Down)", "magnitude": 0.0627}, "right": {"delta_pos": [-9.999999747378752e-05, -9.999999747378752e-05, -9.999999747378752e-05], "delta_rot": [-0.0017999999690800905, -0.0038999998942017555, -0.002899999963119626], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0002}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.0010000000474974513, -0.0737999975681305, -0.05480000004172325], "delta_rot": [-6.00439977645874, -0.10400000214576721, 0.14509999752044678], "gripper_changed": true, "flow_direction": "-Y(Right) and -Z(Down)", "magnitude": 0.092}, "right": {"delta_pos": [-0.0013000000035390258, -0.0005000000237487257, -0.00039999998989515007], "delta_rot": [-0.011699999682605267, -0.02319999970495701, -0.009700000286102295], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0014}} + + ========================================= + [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 side handle/zipper area while right arm maintains a static hold on the top surface.", + "actions": [ + { + "reasoning_cot": "The left arm executes a forward (+X) and downward (-Z) trajectory (delta_pos: [0.024, 0.0005, -0.058]) to close the distance to the bag. Visual evidence in frames T1-T2 shows the gripper moving from free space to hovering directly over the 'bag:side_handle' and 'zipper_pull'. The gripper remains open (gripper_changed: false), 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": "bag:side_handle" + }, + "spatial_logic": "moving from free_space to bag:side_handle", + "topology_change": false + }, + { + "reasoning_cot": "The right arm exhibits negligible kinematic displacement (magnitude: 0.0002) and zero velocity. Visually, it remains firmly pressed against the 'bag:top_surface' throughout the sequence, providing passive stabilization for the bag while the left arm maneuvers.", + "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:top_surface" + }, + "spatial_logic": "static_at_bag:top_surface", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Left arm positioning to interact with side handle/zipper; Right arm maintaining stability." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'table:surface_center', 'bag:top_surface', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and stabilizes the bag's side handle/zipper area while right arm maintains a static hold on the top surface.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}} + ⚠️ 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": 0.35, "vel_score": 0.65, "angle_score": 2.86, "vel_fft": [0.076, 0.034, 0.008, 0.003, 0.016, 0.005, 0.004, 0.001, 0.005, 0.001, 0.003, 0.001, 0.003, 0.005, 0.002, 0.002, 0.002, 0.001, 0.002, 0.002], "angle_fft": [0.346, 0.126, 0.044, 0.061, 0.072, 0.061, 0.023, 0.004, 0.029, 0.015, 0.012, 0.008, 0.017, 0.025, 0.011, 0.015, 0.005, 0.007, 0.006, 0.001]}, "right": {"vel": 0.0, "angle": 0.03, "vel_score": 0.01, "angle_score": 0.22, "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": [0.026, 0.013, 0.009, 0.018, 0.013, 0.011, 0.011, 0.009, 0.009, 0.008, 0.006, 0.008, 0.002, 0.004, 0.006, 0.001, 0.004, 0.003, 0.002, 0.006]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.89, "left_arm_ry": 0.73, "left_arm_rz": 2.37, "left_gripper": 0.38, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.44, "right_gripper": 0.05}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.71, "left_arm_rz": 2.37, "left_gripper": 0.3, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.44, "right_gripper": 0.05}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.86, "left_arm_ry": 0.7, "left_arm_rz": 2.37, "left_gripper": 0.25, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.44, "right_gripper": 0.05}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.86, "left_arm_ry": 0.7, "left_arm_rz": 2.37, "left_gripper": 0.17, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.44, "right_gripper": 0.05}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.86, "left_arm_ry": 0.7, "left_arm_rz": 2.37, "left_gripper": 0.09, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.44, "right_gripper": 0.05}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.86, "left_arm_ry": 0.7, "left_arm_rz": 2.37, "left_gripper": 0.02, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.44, "right_gripper": 0.05}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.71, "left_arm_rz": 2.35, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.44, "right_gripper": 0.05}, "7": {"left_arm_vel": 0.005, "left_gripper_vel": 0.0, "left_arm_rx": -2.75, "left_arm_ry": 0.72, "left_arm_rz": 2.32, "left_gripper": -0.01, "right_arm_vel": 0.005, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.57, "right_arm_rz": -2.43, "right_gripper": 0.05}, "8": {"left_arm_vel": 0.007, "left_gripper_vel": -0.021, "left_arm_rx": -2.76, "left_arm_ry": 0.73, "left_arm_rz": 2.33, "left_gripper": -0.01, "right_arm_vel": 0.007, "right_gripper_vel": -0.021, "right_arm_rx": 2.52, "right_arm_ry": 0.56, "right_arm_rz": -2.43, "right_gripper": 0.05}, "9": {"left_arm_vel": 0.006, "left_gripper_vel": 0.0, "left_arm_rx": -2.78, "left_arm_ry": 0.74, "left_arm_rz": 2.32, "left_gripper": -0.01, "right_arm_vel": 0.006, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.56, "right_arm_rz": -2.43, "right_gripper": 0.05}, "10": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.81, "left_arm_ry": 0.74, "left_arm_rz": 2.31, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.56, "right_arm_rz": -2.43, "right_gripper": 0.05}, "11": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.76, "left_arm_rz": 2.26, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.56, "right_arm_rz": -2.43, "right_gripper": 0.05}, "12": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.79, "left_arm_rz": 2.22, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.56, "right_arm_rz": -2.43, "right_gripper": 0.05}, "13": {"left_arm_vel": 0.006, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.77, "left_arm_rz": 2.23, "left_gripper": -0.01, "right_arm_vel": 0.006, "right_gripper_vel": 0.0, "right_arm_rx": 2.51, "right_arm_ry": 0.55, "right_arm_rz": -2.44, "right_gripper": 0.05}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.02370000071823597, -0.07259999960660934, 0.005499999970197678], "delta_rot": [0.0215000007301569, 0.03310000151395798, -0.1395999938249588], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.0766}, "right": {"delta_pos": [-0.0012000000569969416, -0.00039999998989515007, -0.0003000000142492354], "delta_rot": [-0.009800000116229057, -0.019300000742077827, -0.0066999997943639755], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0013}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.18209999799728394, -0.09960000216960907, 0.08070000261068344], "delta_rot": [0.014600000344216824, 0.06909999996423721, -0.42969998717308044], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.2227}, "right": {"delta_pos": [-0.1298000067472458, -0.2125999927520752, -0.02710000053048134], "delta_rot": [0.017000000923871994, 0.23549999296665192, -0.5575000047683716], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "magnitude": 0.2506}} + + ========================================= + [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 zipper pull to stabilize or open it, while the right arm maintains a static hold on the bag's top surface.", + "actions": [ + { + "reasoning_cot": "The left arm moves from a hovering position towards the side of the bag. Visual evidence in frames T0-T1 shows the gripper aligning with and then closing around the metal zipper pull tab. The kinematic data confirms a 'closing' signal (gripper value decreasing) coinciding with contact. This is a precise grasp action on a specific functional component.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "zipper_pull" + }, + "spatial_logic": "Approaching from free space to secure the zipper_pull anchor.", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains stationary throughout the sequence, maintaining its grip on the top/side of the bag body. Kinematic data shows near-zero velocity and no gripper change. Its role is purely stabilizing the object while the left arm manipulates the zipper.", + "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:top_surface" + }, + "spatial_logic": "Static hold at the established top_surface anchor.", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "zipper_pull", + "current_status": "grasped" + } + ], + "task_progress": "Left arm has successfully acquired the zipper pull; ready for unzipping or stabilization." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'table:surface_center', 'bag:top_surface', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and grasps the bag's zipper pull to stabilize or open it, while the right arm maintains a static hold on the bag's top surface.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}} + ⚠️ 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": 0.35, "angle": 0.99, "vel_score": 2.9, "angle_score": 7.94, "vel_fft": [0.348, 0.104, 0.021, 0.012, 0.013, 0.005, 0.006, 0.003, 0.006, 0.002, 0.01, 0.01, 0.007, 0.003, 0.004, 0.01, 0.004, 0.006, 0.001, 0.003], "angle_fft": [0.989, 0.103, 0.131, 0.133, 0.119, 0.05, 0.017, 0.021, 0.025, 0.03, 0.023, 0.033, 0.008, 0.021, 0.046, 0.027, 0.026, 0.011, 0.029, 0.04]}, "right": {"vel": 0.3, "angle": 0.79, "vel_score": 2.56, "angle_score": 6.36, "vel_fft": [0.301, 0.119, 0.047, 0.021, 0.005, 0.004, 0.006, 0.003, 0.006, 0.012, 0.009, 0.009, 0.011, 0.001, 0.003, 0.007, 0.001, 0.01, 0.01, 0.004], "angle_fft": [0.793, 0.226, 0.051, 0.037, 0.061, 0.029, 0.046, 0.04, 0.037, 0.046, 0.055, 0.044, 0.027, 0.005, 0.028, 0.034, 0.06, 0.057, 0.034, 0.039]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.75, "left_arm_rz": 2.25, "left_gripper": 0.0, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.55, "right_arm_rz": -2.45, "right_gripper": 0.05}, "1": {"left_arm_vel": 0.068, "left_gripper_vel": 1.386, "left_arm_rx": -2.83, "left_arm_ry": 0.67, "left_arm_rz": 2.27, "left_gripper": 0.12, "right_arm_vel": 0.068, "right_gripper_vel": 1.386, "right_arm_rx": 2.55, "right_arm_ry": 0.53, "right_arm_rz": -2.44, "right_gripper": 0.14}, "2": {"left_arm_vel": 0.096, "left_gripper_vel": 1.428, "left_arm_rx": -2.81, "left_arm_ry": 0.64, "left_arm_rz": 2.27, "left_gripper": 0.17, "right_arm_vel": 0.096, "right_gripper_vel": 1.428, "right_arm_rx": 2.57, "right_arm_ry": 0.53, "right_arm_rz": -2.44, "right_gripper": 0.19}, "3": {"left_arm_vel": 0.179, "left_gripper_vel": 1.638, "left_arm_rx": -2.79, "left_arm_ry": 0.62, "left_arm_rz": 2.28, "left_gripper": 0.23, "right_arm_vel": 0.179, "right_gripper_vel": 1.638, "right_arm_rx": 2.58, "right_arm_ry": 0.53, "right_arm_rz": -2.46, "right_gripper": 0.24}, "4": {"left_arm_vel": 0.223, "left_gripper_vel": 1.113, "left_arm_rx": -2.79, "left_arm_ry": 0.59, "left_arm_rz": 2.28, "left_gripper": 0.27, "right_arm_vel": 0.223, "right_gripper_vel": 1.113, "right_arm_rx": 2.59, "right_arm_ry": 0.52, "right_arm_rz": -2.47, "right_gripper": 0.28}, "5": {"left_arm_vel": 0.248, "left_gripper_vel": 0.609, "left_arm_rx": -2.77, "left_arm_ry": 0.58, "left_arm_rz": 2.29, "left_gripper": 0.29, "right_arm_vel": 0.248, "right_gripper_vel": 0.609, "right_arm_rx": 2.59, "right_arm_ry": 0.52, "right_arm_rz": -2.49, "right_gripper": 0.3}, "6": {"left_arm_vel": 0.544, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.64, "left_arm_rz": 2.34, "left_gripper": 0.3, "right_arm_vel": 0.544, "right_gripper_vel": 0.0, "right_arm_rx": 2.61, "right_arm_ry": 0.53, "right_arm_rz": -2.61, "right_gripper": 0.31}, "7": {"left_arm_vel": 0.396, "left_gripper_vel": -0.231, "left_arm_rx": -2.86, "left_arm_ry": 0.76, "left_arm_rz": 2.44, "left_gripper": 0.3, "right_arm_vel": 0.396, "right_gripper_vel": -0.231, "right_arm_rx": 2.57, "right_arm_ry": 0.53, "right_arm_rz": -2.73, "right_gripper": 0.3}, "8": {"left_arm_vel": 0.382, "left_gripper_vel": -0.147, "left_arm_rx": -2.92, "left_arm_ry": 0.83, "left_arm_rz": 2.52, "left_gripper": 0.3, "right_arm_vel": 0.382, "right_gripper_vel": -0.147, "right_arm_rx": 2.49, "right_arm_ry": 0.51, "right_arm_rz": -2.83, "right_gripper": 0.28}, "9": {"left_arm_vel": 0.504, "left_gripper_vel": 0.021, "left_arm_rx": -2.96, "left_arm_ry": 0.85, "left_arm_rz": 2.43, "left_gripper": 0.3, "right_arm_vel": 0.504, "right_gripper_vel": 0.021, "right_arm_rx": 2.51, "right_arm_ry": 0.55, "right_arm_rz": -2.96, "right_gripper": 0.27}, "10": {"left_arm_vel": 0.525, "left_gripper_vel": 0.0, "left_arm_rx": -2.91, "left_arm_ry": 0.85, "left_arm_rz": 2.33, "left_gripper": 0.33, "right_arm_vel": 0.525, "right_gripper_vel": 0.0, "right_arm_rx": 2.56, "right_arm_ry": 0.65, "right_arm_rz": -2.99, "right_gripper": 0.27}, "11": {"left_arm_vel": 0.336, "left_gripper_vel": 0.0, "left_arm_rx": -2.9, "left_arm_ry": 0.83, "left_arm_rz": 2.25, "left_gripper": 0.36, "right_arm_vel": 0.336, "right_gripper_vel": 0.0, "right_arm_rx": 2.58, "right_arm_ry": 0.7, "right_arm_rz": -3.0, "right_gripper": 0.27}, "12": {"left_arm_vel": 0.208, "left_gripper_vel": 0.0, "left_arm_rx": -2.92, "left_arm_ry": 0.83, "left_arm_rz": 2.08, "left_gripper": 0.4, "right_arm_vel": 0.208, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.75, "right_arm_rz": -3.04, "right_gripper": 0.27}, "13": {"left_arm_vel": 0.012, "left_gripper_vel": 0.189, "left_arm_rx": -2.88, "left_arm_ry": 0.8, "left_arm_rz": 1.94, "left_gripper": 0.41, "right_arm_vel": 0.012, "right_gripper_vel": 0.189, "right_arm_rx": 2.54, "right_arm_ry": 0.81, "right_arm_rz": -2.99, "right_gripper": 0.28}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.2070000022649765, -0.02800000086426735, 0.07689999788999557], "delta_rot": [-0.02160000056028366, 0.054499998688697815, -0.3082999885082245], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.2226}, "right": {"delta_pos": [-0.12870000302791595, -0.2117999941110611, -0.026900000870227814], "delta_rot": [0.022700000554323196, 0.26030001044273376, -0.5482000112533569], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "magnitude": 0.2493}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.21170000731945038, -0.035100001841783524, 0.04809999838471413], "delta_rot": [-0.02070000022649765, -0.027300000190734863, -0.351500004529953], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.22}, "right": {"delta_pos": [-0.12880000472068787, -0.21070000529289246, -0.02800000086426735], "delta_rot": [0.040800001472234726, 0.27459999918937683, -0.5182999968528748], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "magnitude": 0.2485}} + + ========================================= + [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 releases the zipper pull and retreats to a neutral position, while the right arm maintains a static hold on the bag's top surface to stabilize it.", + "actions": [ + { + "reasoning_cot": "The left arm transitions from grasping the zipper pull (visible in T0) to an open state and moving away (T1/T2). The kinematic data shows positive delta in X/Z (retreat/lift) and gripper opening. This indicates a release action followed by a retreat to clear the workspace.", + "causal_trace": { + "gripper_signal": "opening", + "visual_contact": "none" + }, + "action_verb": "release", + "semantic_action": "release_and_retreat", + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "zipper_pull" + }, + "spatial_logic": "moving from zipper_pull to free_space", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains in contact with the top surface of the bag throughout the sequence. Visual evidence shows no significant displacement or gripper change, indicating a stabilizing hold while the left arm performs its task.", + "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:top_surface" + }, + "spatial_logic": "static_at_top_surface", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "zipper_pull", + "current_status": "released" + } + ], + "task_progress": "Left arm has completed interaction with zipper pull and is retreating; right arm continues stabilization." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'table:surface_center', 'bag:top_surface', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm releases the zipper pull and retreats to a neutral position, while the right arm maintains a static hold on the bag's top surface to stabilize it.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}} + ⚠️ 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": 0.26, "vel_score": 0.24, "angle_score": 0.87, "vel_fft": [0.078, 0.016, 0.015, 0.016, 0.011, 0.017], "angle_fft": [0.265, 0.063, 0.028, 0.031, 0.038, 0.017]}, "right": {"vel": 0.01, "angle": 0.09, "vel_score": 0.01, "angle_score": 0.28, "vel_fft": [0.006, 0.003, 0.002, 0.003, 0.002, 0.002], "angle_fft": [0.09, 0.023, 0.02, 0.02, 0.003, 0.015]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.79, "left_arm_rz": 1.94, "left_gripper": 0.41, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.81, "right_arm_rz": -2.99, "right_gripper": 0.29}, "1": {"left_arm_vel": 0.009, "left_gripper_vel": 0.357, "left_arm_rx": -2.86, "left_arm_ry": 0.78, "left_arm_rz": 1.93, "left_gripper": 0.41, "right_arm_vel": 0.009, "right_gripper_vel": 0.357, "right_arm_rx": 2.55, "right_arm_ry": 0.81, "right_arm_rz": -2.98, "right_gripper": 0.31}, "2": {"left_arm_vel": 0.007, "left_gripper_vel": 0.462, "left_arm_rx": -2.86, "left_arm_ry": 0.77, "left_arm_rz": 1.92, "left_gripper": 0.41, "right_arm_vel": 0.007, "right_gripper_vel": 0.462, "right_arm_rx": 2.55, "right_arm_ry": 0.82, "right_arm_rz": -2.98, "right_gripper": 0.32}, "3": {"left_arm_vel": 0.004, "left_gripper_vel": 0.441, "left_arm_rx": -2.86, "left_arm_ry": 0.76, "left_arm_rz": 1.92, "left_gripper": 0.41, "right_arm_vel": 0.004, "right_gripper_vel": 0.441, "right_arm_rx": 2.55, "right_arm_ry": 0.82, "right_arm_rz": -2.97, "right_gripper": 0.34}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": 0.357, "left_arm_rx": -2.87, "left_arm_ry": 0.75, "left_arm_rz": 1.91, "left_gripper": 0.41, "right_arm_vel": 0.0, "right_gripper_vel": 0.357, "right_arm_rx": 2.55, "right_arm_ry": 0.82, "right_arm_rz": -2.97, "right_gripper": 0.35}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.147, "left_arm_rx": -2.87, "left_arm_ry": 0.74, "left_arm_rz": 1.91, "left_gripper": 0.41, "right_arm_vel": 0.0, "right_gripper_vel": 0.147, "right_arm_rx": 2.55, "right_arm_ry": 0.82, "right_arm_rz": -2.97, "right_gripper": 0.35}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.063, "left_arm_rx": -2.88, "left_arm_ry": 0.73, "left_arm_rz": 1.9, "left_gripper": 0.41, "right_arm_vel": 0.0, "right_gripper_vel": 0.063, "right_arm_rx": 2.56, "right_arm_ry": 0.82, "right_arm_rz": -2.97, "right_gripper": 0.36}, "7": {"left_arm_vel": 0.023, "left_gripper_vel": 0.021, "left_arm_rx": -2.87, "left_arm_ry": 0.72, "left_arm_rz": 1.9, "left_gripper": 0.41, "right_arm_vel": 0.023, "right_gripper_vel": 0.021, "right_arm_rx": 2.56, "right_arm_ry": 0.82, "right_arm_rz": -2.96, "right_gripper": 0.36}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.004100000020116568, -0.00419999985024333, -0.02459999918937683], "delta_rot": [-0.008700000122189522, -0.07349999994039536, -0.03669999912381172], "gripper_changed": false, "flow_direction": "-Z(Down)", "magnitude": 0.0253}, "right": {"delta_pos": [-9.999999747378752e-05, 0.000699999975040555, -0.0012000000569969416], "delta_rot": [0.012900000438094139, 0.00839999970048666, 0.02199999988079071], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0014}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.005900000222027302, -0.00559999980032444, -0.03449999913573265], "delta_rot": [0.013399999588727951, -0.10490000247955322, -0.009100000374019146], "gripper_changed": true, "flow_direction": "-Z(Down)", "magnitude": 0.0354}, "right": {"delta_pos": [-0.005100000184029341, 0.048900000751018524, -0.024800000712275505], "delta_rot": [0.21490000188350677, -0.010300000198185444, 0.23190000653266907], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.0551}} + + ========================================= + [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 hold on the bag to stabilize it; the left arm presses down on the top surface while the right arm holds the side near the zipper pull, preparing for potential manipulation.", + "actions": [ + { + "reasoning_cot": "The left arm is positioned directly over the reflective patch on the bag's top surface. Kinematic data shows negligible velocity (0.08 m/s) and no gripper change, indicating a static holding or pressing action to keep the bag flat and stable.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "press", + "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 is positioned adjacent to the zipper pull on the side of the bag. With minimal movement and an open but stationary gripper, it is maintaining a stabilizing hold or hover near the handle/zipper area, likely to prevent the bag from shifting while the left arm applies pressure.", + "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:side_handle" + }, + "spatial_logic": "static_at_side_handle", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Stabilizing the bag with dual-arm contact; left arm pressing top, right arm holding side." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'table:surface_center', 'bag:top_surface', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Both arms maintain a static hold on the bag to stabilize it; the left arm presses down on the top surface while the right arm holds the side near the zipper pull, preparing for potential manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}} + ⚠️ 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": 0.07, "vel_score": 0.06, "angle_score": 0.43, "vel_fft": [0.011, 0.009, 0.005, 0.005, 0.006, 0.005, 0.004, 0.002, 0.002, 0.002, 0.002, 0.001], "angle_fft": [0.068, 0.047, 0.025, 0.021, 0.017, 0.011, 0.003, 0.006, 0.009, 0.003, 0.009, 0.0]}, "right": {"vel": 0.09, "angle": 0.62, "vel_score": 0.53, "angle_score": 3.73, "vel_fft": [0.089, 0.033, 0.012, 0.004, 0.003, 0.003, 0.004, 0.001, 0.003, 0.004, 0.006, 0.001], "angle_fft": [0.625, 0.243, 0.092, 0.052, 0.044, 0.03, 0.028, 0.03, 0.029, 0.013, 0.005, 0.018]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.71, "left_arm_rz": 1.9, "left_gripper": 0.41, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.56, "right_arm_ry": 0.82, "right_arm_rz": -2.96, "right_gripper": 0.36}, "1": {"left_arm_vel": 0.086, "left_gripper_vel": 0.0, "left_arm_rx": -2.86, "left_arm_ry": 0.71, "left_arm_rz": 1.92, "left_gripper": 0.37, "right_arm_vel": 0.086, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.8, "right_arm_rz": -2.97, "right_gripper": 0.36}, "2": {"left_arm_vel": 0.077, "left_gripper_vel": 0.021, "left_arm_rx": -2.85, "left_arm_ry": 0.7, "left_arm_rz": 1.93, "left_gripper": 0.31, "right_arm_vel": 0.077, "right_gripper_vel": 0.021, "right_arm_rx": 2.52, "right_arm_ry": 0.79, "right_arm_rz": -2.97, "right_gripper": 0.36}, "3": {"left_arm_vel": 0.09, "left_gripper_vel": 0.021, "left_arm_rx": -2.85, "left_arm_ry": 0.7, "left_arm_rz": 1.93, "left_gripper": 0.24, "right_arm_vel": 0.09, "right_gripper_vel": 0.021, "right_arm_rx": 2.51, "right_arm_ry": 0.78, "right_arm_rz": -2.97, "right_gripper": 0.36}, "4": {"left_arm_vel": 0.096, "left_gripper_vel": 0.021, "left_arm_rx": -2.85, "left_arm_ry": 0.7, "left_arm_rz": 1.93, "left_gripper": 0.14, "right_arm_vel": 0.096, "right_gripper_vel": 0.021, "right_arm_rx": 2.51, "right_arm_ry": 0.77, "right_arm_rz": -2.96, "right_gripper": 0.36}, "5": {"left_arm_vel": 0.085, "left_gripper_vel": 0.021, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 1.93, "left_gripper": 0.08, "right_arm_vel": 0.085, "right_gripper_vel": 0.021, "right_arm_rx": 2.52, "right_arm_ry": 0.77, "right_arm_rz": -2.94, "right_gripper": 0.36}, "6": {"left_arm_vel": 0.141, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 1.93, "left_gripper": 0.05, "right_arm_vel": 0.141, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.78, "right_arm_rz": -2.92, "right_gripper": 0.36}, "7": {"left_arm_vel": 0.128, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 1.93, "left_gripper": 0.04, "right_arm_vel": 0.128, "right_gripper_vel": 0.0, "right_arm_rx": 2.54, "right_arm_ry": 0.79, "right_arm_rz": -2.88, "right_gripper": 0.36}, "8": {"left_arm_vel": 0.185, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 1.93, "left_gripper": 0.04, "right_arm_vel": 0.185, "right_gripper_vel": 0.0, "right_arm_rx": 2.56, "right_arm_ry": 0.79, "right_arm_rz": -2.85, "right_gripper": 0.36}, "9": {"left_arm_vel": 0.155, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 1.93, "left_gripper": 0.04, "right_arm_vel": 0.155, "right_gripper_vel": 0.0, "right_arm_rx": 2.59, "right_arm_ry": 0.8, "right_arm_rz": -2.81, "right_gripper": 0.36}, "10": {"left_arm_vel": 0.184, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 1.93, "left_gripper": 0.04, "right_arm_vel": 0.184, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.8, "right_arm_rz": -2.78, "right_gripper": 0.36}, "11": {"left_arm_vel": 0.159, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 1.93, "left_gripper": 0.04, "right_arm_vel": 0.159, "right_gripper_vel": 0.0, "right_arm_rx": 2.65, "right_arm_ry": 0.8, "right_arm_rz": -2.76, "right_gripper": 0.36}, "12": {"left_arm_vel": 0.106, "left_gripper_vel": 0.021, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 1.93, "left_gripper": 0.04, "right_arm_vel": 0.106, "right_gripper_vel": 0.021, "right_arm_rx": 2.7, "right_arm_ry": 0.79, "right_arm_rz": -2.74, "right_gripper": 0.37}, "13": {"left_arm_vel": 0.036, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 1.93, "left_gripper": 0.04, "right_arm_vel": 0.036, "right_gripper_vel": 0.0, "right_arm_rx": 2.76, "right_arm_ry": 0.8, "right_arm_rz": -2.75, "right_gripper": 0.37}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0008999999845400453, -0.0010000000474974513, -0.005799999926239252], "delta_rot": [0.01489999983459711, -0.025100000202655792, 0.023000000044703484], "gripper_changed": true, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.006}, "right": {"delta_pos": [-0.005100000184029341, 0.04809999838471413, -0.022700000554323196], "delta_rot": [0.20360000431537628, -0.016100000590085983, 0.21050000190734863], "gripper_changed": false, "flow_direction": "+Y(Left) and -Z(Down)", "magnitude": 0.0535}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.0026000000070780516, -0.003599999938160181, -0.005900000222027302], "delta_rot": [0.08229999989271164, -0.05939999967813492, 0.18299999833106995], "gripper_changed": true, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0074}, "right": {"delta_pos": [-0.038600001484155655, 0.050200000405311584, 0.01720000058412552], "delta_rot": [0.12839999794960022, -0.19059999287128448, 0.2985000014305115], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left)", "magnitude": 0.0656}} + + ========================================= + [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 are stabilizing the bag; the left arm presses down on the top surface to prevent movement, while the right arm holds the side near the zipper pull, maintaining a static hold.", + "actions": [ + { + "reasoning_cot": "The left arm is positioned over the top of the bag. Kinematic data shows low velocity and stable gripper width (0.37 -> 0.41), indicating a holding or pressing action rather than active manipulation. The visual evidence confirms the gripper is in contact with the 'bag:top_surface' to stabilize the object against the table.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "press", + "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 is positioned at the side of the bag, adjacent to the zipper pull. Kinematic data indicates minimal movement (vel ~0.09) and a stable gripper state. The visual sequence shows the gripper maintaining contact with the side handle/zipper area, likely providing counter-tension or stabilization for the left arm's press.", + "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:side_handle" + }, + "spatial_logic": "static_at_side_handle", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Stabilizing the bag by pressing the top surface with the left arm and holding the side with the right arm." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'table:surface_center', 'bag:top_surface', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Both arms are stabilizing the bag; the left arm presses down on the top surface to prevent movement, while the right arm holds the side near the zipper pull, maintaining a static hold.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}} + ⚠️ 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": 0.14, "vel_score": 0.04, "angle_score": 1.24, "vel_fft": [0.005, 0.002, 0.001, 0.001, 0.0, 0.001, 0.001, 0.0, 0.0, 0.001, 0.001, 0.001, 0.0, 0.001, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0], "angle_fft": [0.141, 0.098, 0.045, 0.035, 0.036, 0.019, 0.026, 0.023, 0.014, 0.025, 0.029, 0.019, 0.003, 0.021, 0.016, 0.013, 0.014, 0.017, 0.01, 0.016]}, "right": {"vel": 0.09, "angle": 0.32, "vel_score": 0.78, "angle_score": 2.6, "vel_fft": [0.09, 0.03, 0.021, 0.005, 0.003, 0.002, 0.003, 0.002, 0.002, 0.003, 0.001, 0.003, 0.005, 0.004, 0.002, 0.003, 0.003, 0.001, 0.002, 0.003], "angle_fft": [0.316, 0.106, 0.052, 0.05, 0.056, 0.045, 0.033, 0.006, 0.009, 0.037, 0.022, 0.012, 0.025, 0.053, 0.027, 0.014, 0.029, 0.019, 0.008, 0.007]}, "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": 1.93, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.76, "right_arm_ry": 0.8, "right_arm_rz": -2.76, "right_gripper": 0.37}, "1": {"left_arm_vel": 0.076, "left_gripper_vel": -0.42, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 1.93, "left_gripper": 0.04, "right_arm_vel": 0.076, "right_gripper_vel": -0.42, "right_arm_rx": 2.76, "right_arm_ry": 0.81, "right_arm_rz": -2.77, "right_gripper": 0.35}, "2": {"left_arm_vel": 0.033, "left_gripper_vel": -1.701, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 1.93, "left_gripper": 0.03, "right_arm_vel": 0.033, "right_gripper_vel": -1.701, "right_arm_rx": 2.76, "right_arm_ry": 0.82, "right_arm_rz": -2.77, "right_gripper": 0.2}, "3": {"left_arm_vel": 0.013, "left_gripper_vel": -1.848, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 1.93, "left_gripper": 0.03, "right_arm_vel": 0.013, "right_gripper_vel": -1.848, "right_arm_rx": 2.76, "right_arm_ry": 0.81, "right_arm_rz": -2.78, "right_gripper": 0.06}, "4": {"left_arm_vel": 0.04, "left_gripper_vel": -0.021, "left_arm_rx": -2.86, "left_arm_ry": 0.69, "left_arm_rz": 1.93, "left_gripper": 0.03, "right_arm_vel": 0.04, "right_gripper_vel": -0.021, "right_arm_rx": 2.73, "right_arm_ry": 0.77, "right_arm_rz": -2.8, "right_gripper": 0.01}, "5": {"left_arm_vel": 0.164, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.69, "left_arm_rz": 1.94, "left_gripper": 0.03, "right_arm_vel": 0.164, "right_gripper_vel": 0.0, "right_arm_rx": 2.76, "right_arm_ry": 0.7, "right_arm_rz": -2.75, "right_gripper": 0.01}, "6": {"left_arm_vel": 0.165, "left_gripper_vel": 0.0, "left_arm_rx": -2.82, "left_arm_ry": 0.67, "left_arm_rz": 1.99, "left_gripper": 0.03, "right_arm_vel": 0.165, "right_gripper_vel": 0.0, "right_arm_rx": 2.79, "right_arm_ry": 0.68, "right_arm_rz": -2.7, "right_gripper": 0.01}, "7": {"left_arm_vel": 0.115, "left_gripper_vel": 0.0, "left_arm_rx": -2.78, "left_arm_ry": 0.65, "left_arm_rz": 2.09, "left_gripper": 0.03, "right_arm_vel": 0.115, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.63, "right_arm_rz": -2.67, "right_gripper": 0.01}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0017000000225380063, -0.0024999999441206455, -9.999999747378752e-05], "delta_rot": [0.0674000009894371, -0.034299999475479126, 0.1599999964237213], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.003}, "right": {"delta_pos": [-0.0348999984562397, 0.002199999988079071, 0.03999999910593033], "delta_rot": [-0.07930000126361847, -0.17790000140666962, 0.09189999848604202], "gripper_changed": true, "flow_direction": "-X(Backward) and +Z(Up)", "magnitude": 0.0531}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.010599999688565731, -0.0020000000949949026, -0.0], "delta_rot": [0.2175000011920929, -0.1436000019311905, 0.5831999778747559], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0108}, "right": {"delta_pos": [-0.05420000106096268, 0.15530000627040863, 0.05480000004172325], "delta_rot": [-0.03060000017285347, -0.16859999299049377, 0.21960000693798065], "gripper_changed": true, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1734}} + + ========================================= + [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": "The robot is stabilizing the bag with the left arm while the right arm approaches and grasps the zipper pull to initiate opening.", + "actions": [ + { + "reasoning_cot": "The left arm maintains a static position on the top surface of the bag, providing necessary counter-force for the right arm's manipulation. Visual evidence shows no displacement or gripper change, confirming a stabilization role.", + "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_surface", + "topology_change": false + }, + { + "reasoning_cot": "The right arm moves from a hovering position near the side handle towards the zipper pull. The gripper closes (delta_gripper negative) as it makes contact with the metal ring, transitioning from approach to grasp to secure the zipper for pulling.", + "causal_trace": { + "gripper_signal": "closing", + "visual_contact": "secured" + }, + "action_verb": "grasp", + "semantic_action": "approach_and_grasp_zipper", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving_from_side_handle_to_zipper_pull", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped" + } + ], + "task_progress": "Right arm has successfully acquired the zipper pull; left arm continues to stabilize the bag body." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'table:surface_center', 'bag:top_surface', 'zipper_pull'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "The robot is stabilizing the bag with the left arm while the right arm approaches and grasps the zipper pull to initiate opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}} + ⚠️ 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": 0.35, "vel_score": 0.09, "angle_score": 2.98, "vel_fft": [0.011, 0.004, 0.002, 0.003, 0.002, 0.001, 0.002, 0.001, 0.001, 0.0, 0.001, 0.0, 0.001, 0.0, 0.001, 0.0, 0.0, 0.001, 0.0, 0.001], "angle_fft": [0.354, 0.1, 0.102, 0.064, 0.037, 0.035, 0.019, 0.04, 0.017, 0.021, 0.016, 0.024, 0.003, 0.022, 0.01, 0.011, 0.009, 0.003, 0.015, 0.005]}, "right": {"vel": 0.15, "angle": 0.41, "vel_score": 1.25, "angle_score": 3.42, "vel_fft": [0.148, 0.041, 0.033, 0.024, 0.005, 0.011, 0.011, 0.005, 0.005, 0.004, 0.003, 0.005, 0.006, 0.002, 0.003, 0.001, 0.002, 0.007, 0.005, 0.003], "angle_fft": [0.415, 0.045, 0.029, 0.097, 0.025, 0.022, 0.064, 0.007, 0.019, 0.032, 0.014, 0.036, 0.01, 0.015, 0.008, 0.004, 0.031, 0.017, 0.008, 0.018]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.77, "left_arm_ry": 0.65, "left_arm_rz": 2.11, "left_gripper": 0.03, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.62, "right_arm_rz": -2.66, "right_gripper": 0.01}, "1": {"left_arm_vel": 0.239, "left_gripper_vel": 0.0, "left_arm_rx": -2.74, "left_arm_ry": 0.63, "left_arm_rz": 2.17, "left_gripper": 0.03, "right_arm_vel": 0.239, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.63, "right_arm_rz": -2.61, "right_gripper": 0.01}, "2": {"left_arm_vel": 0.293, "left_gripper_vel": 0.0, "left_arm_rx": -2.73, "left_arm_ry": 0.62, "left_arm_rz": 2.18, "left_gripper": 0.03, "right_arm_vel": 0.293, "right_gripper_vel": 0.0, "right_arm_rx": 2.69, "right_arm_ry": 0.64, "right_arm_rz": -2.61, "right_gripper": 0.01}, "3": {"left_arm_vel": 0.178, "left_gripper_vel": 0.0, "left_arm_rx": -2.7, "left_arm_ry": 0.6, "left_arm_rz": 2.22, "left_gripper": 0.03, "right_arm_vel": 0.178, "right_gripper_vel": 0.0, "right_arm_rx": 2.74, "right_arm_ry": 0.7, "right_arm_rz": -2.61, "right_gripper": 0.01}, "4": {"left_arm_vel": 0.031, "left_gripper_vel": 0.0, "left_arm_rx": -2.68, "left_arm_ry": 0.58, "left_arm_rz": 2.3, "left_gripper": 0.03, "right_arm_vel": 0.031, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 0.68, "right_arm_rz": -2.65, "right_gripper": 0.01}, "5": {"left_arm_vel": 0.038, "left_gripper_vel": 0.0, "left_arm_rx": -2.65, "left_arm_ry": 0.54, "left_arm_rz": 2.43, "left_gripper": 0.03, "right_arm_vel": 0.038, "right_gripper_vel": 0.0, "right_arm_rx": 2.77, "right_arm_ry": 0.6, "right_arm_rz": -2.64, "right_gripper": 0.01}, "6": {"left_arm_vel": 0.216, "left_gripper_vel": 0.0, "left_arm_rx": -2.64, "left_arm_ry": 0.54, "left_arm_rz": 2.49, "left_gripper": 0.03, "right_arm_vel": 0.216, "right_gripper_vel": 0.0, "right_arm_rx": 2.76, "right_arm_ry": 0.65, "right_arm_rz": -2.62, "right_gripper": 0.01}, "7": {"left_arm_vel": 0.054, "left_gripper_vel": 0.0, "left_arm_rx": -2.63, "left_arm_ry": 0.54, "left_arm_rz": 2.51, "left_gripper": 0.03, "right_arm_vel": 0.054, "right_gripper_vel": 0.0, "right_arm_rx": 2.73, "right_arm_ry": 0.64, "right_arm_rz": -2.54, "right_gripper": 0.01}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.008899999782443047, 0.000699999975040555, 9.999999747378752e-05], "delta_rot": [0.14000000059604645, -0.10459999740123749, 0.4050999879837036], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0089}, "right": {"delta_pos": [-0.017799999564886093, 0.1501999944448471, 0.014700000174343586], "delta_rot": [0.05649999901652336, 0.013000000268220901, 0.12219999730587006], "gripper_changed": false, "flow_direction": "+Y(Left)", "magnitude": 0.152}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.06319999694824219, 0.066600002348423, 0.1316000074148178], "delta_rot": [-0.06930000334978104, 0.02710000053048134, 0.4715000092983246], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1604}, "right": {"delta_pos": [-0.06369999796152115, -0.019300000742077827, 0.09279999881982803], "delta_rot": [0.1964000016450882, -0.2468000054359436, -0.12680000066757202], "gripper_changed": true, "flow_direction": "-X(Backward) and +Z(Up)", "magnitude": 0.1142}} + + ========================================= + [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": "The robot is executing a dual-arm stabilization and manipulation sequence to open the bag. The left arm maintains a static hold on the bag's top surface to prevent displacement, while the right arm actively pulls the zipper pull laterally to unzip the compartment.", + "actions": [ + { + "reasoning_cot": "The left arm exhibits negligible kinematic movement (vel ~0.01) and remains in constant contact with the silver mesh patch on the bag's lid. Its role is purely stabilizing, anchoring the object against the force 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_surface" + }, + "spatial_logic": "static_at_top_surface", + "topology_change": false + }, + { + "reasoning_cot": "The right arm shows significant lateral displacement (+Y direction, magnitude 0.152) while maintaining a closed grip on the metal zipper slider. This motion translates directly to the unzipping of the bag, changing the state of the zipper from closed to partially open.", + "causal_trace": { + "gripper_signal": "stable", + "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_zipper_start_to_mid_along_track", + "topology_change": true + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_track", + "current_status": "partially_opened" + } + ], + "task_progress": "Bag opening initiated; zipper being pulled laterally by right arm while left arm stabilizes the main 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}, {"anchor_id": "bag:zipper_track", "current_status": "partially_opened"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'table:surface_center', 'bag:top_surface', 'zipper_pull', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "The robot is executing a dual-arm stabilization and manipulation sequence to open the bag. The left arm maintains a static hold on the bag's top surface to prevent displacement, while the right arm actively pulls the zipper pull laterally to unzip the compartment.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}} + ⚠️ 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": 0.23, "angle": 0.52, "vel_score": 1.43, "angle_score": 3.12, "vel_fft": [0.226, 0.117, 0.032, 0.029, 0.021, 0.017, 0.021, 0.025, 0.016, 0.017, 0.019, 0.008, 0.007], "angle_fft": [0.521, 0.136, 0.12, 0.103, 0.056, 0.026, 0.036, 0.06, 0.033, 0.04, 0.028, 0.011, 0.015]}, "right": {"vel": 0.25, "angle": 0.88, "vel_score": 1.55, "angle_score": 5.44, "vel_fft": [0.252, 0.078, 0.045, 0.028, 0.02, 0.014, 0.013, 0.004, 0.012, 0.009, 0.012, 0.005, 0.008], "angle_fft": [0.885, 0.072, 0.186, 0.076, 0.07, 0.035, 0.032, 0.02, 0.018, 0.028, 0.029, 0.032, 0.01]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.63, "left_arm_ry": 0.54, "left_arm_rz": 2.51, "left_gripper": 0.03, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.73, "right_arm_ry": 0.63, "right_arm_rz": -2.54, "right_gripper": 0.01}, "1": {"left_arm_vel": 0.102, "left_gripper_vel": 1.344, "left_arm_rx": -2.63, "left_arm_ry": 0.55, "left_arm_rz": 2.52, "left_gripper": 0.07, "right_arm_vel": 0.102, "right_gripper_vel": 1.344, "right_arm_rx": 2.69, "right_arm_ry": 0.54, "right_arm_rz": -2.55, "right_gripper": 0.11}, "2": {"left_arm_vel": 0.142, "left_gripper_vel": 2.058, "left_arm_rx": -2.62, "left_arm_ry": 0.56, "left_arm_rz": 2.53, "left_gripper": 0.11, "right_arm_vel": 0.142, "right_gripper_vel": 2.058, "right_arm_rx": 2.69, "right_arm_ry": 0.5, "right_arm_rz": -2.53, "right_gripper": 0.18}, "3": {"left_arm_vel": 0.145, "left_gripper_vel": 2.226, "left_arm_rx": -2.62, "left_arm_ry": 0.56, "left_arm_rz": 2.55, "left_gripper": 0.16, "right_arm_vel": 0.145, "right_gripper_vel": 2.226, "right_arm_rx": 2.7, "right_arm_ry": 0.46, "right_arm_rz": -2.51, "right_gripper": 0.25}, "4": {"left_arm_vel": 0.165, "left_gripper_vel": 1.659, "left_arm_rx": -2.61, "left_arm_ry": 0.57, "left_arm_rz": 2.56, "left_gripper": 0.21, "right_arm_vel": 0.165, "right_gripper_vel": 1.659, "right_arm_rx": 2.71, "right_arm_ry": 0.42, "right_arm_rz": -2.51, "right_gripper": 0.31}, "5": {"left_arm_vel": 0.213, "left_gripper_vel": 1.365, "left_arm_rx": -2.61, "left_arm_ry": 0.56, "left_arm_rz": 2.57, "left_gripper": 0.24, "right_arm_vel": 0.213, "right_gripper_vel": 1.365, "right_arm_rx": 2.75, "right_arm_ry": 0.41, "right_arm_rz": -2.5, "right_gripper": 0.35}, "6": {"left_arm_vel": 0.207, "left_gripper_vel": 0.819, "left_arm_rx": -2.6, "left_arm_ry": 0.56, "left_arm_rz": 2.59, "left_gripper": 0.26, "right_arm_vel": 0.207, "right_gripper_vel": 0.819, "right_arm_rx": 2.79, "right_arm_ry": 0.4, "right_arm_rz": -2.5, "right_gripper": 0.38}, "7": {"left_arm_vel": 0.256, "left_gripper_vel": 0.399, "left_arm_rx": -2.6, "left_arm_ry": 0.56, "left_arm_rz": 2.6, "left_gripper": 0.27, "right_arm_vel": 0.256, "right_gripper_vel": 0.399, "right_arm_rx": 2.82, "right_arm_ry": 0.4, "right_arm_rz": -2.5, "right_gripper": 0.39}, "8": {"left_arm_vel": 0.283, "left_gripper_vel": 0.21, "left_arm_rx": -2.6, "left_arm_ry": 0.57, "left_arm_rz": 2.6, "left_gripper": 0.26, "right_arm_vel": 0.283, "right_gripper_vel": 0.21, "right_arm_rx": 2.84, "right_arm_ry": 0.4, "right_arm_rz": -2.51, "right_gripper": 0.4}, "9": {"left_arm_vel": 0.305, "left_gripper_vel": 0.126, "left_arm_rx": -2.61, "left_arm_ry": 0.59, "left_arm_rz": 2.61, "left_gripper": 0.25, "right_arm_vel": 0.305, "right_gripper_vel": 0.126, "right_arm_rx": 2.87, "right_arm_ry": 0.41, "right_arm_rz": -2.52, "right_gripper": 0.41}, "10": {"left_arm_vel": 0.299, "left_gripper_vel": 0.0, "left_arm_rx": -2.64, "left_arm_ry": 0.64, "left_arm_rz": 2.59, "left_gripper": 0.24, "right_arm_vel": 0.299, "right_gripper_vel": 0.0, "right_arm_rx": 2.85, "right_arm_ry": 0.4, "right_arm_rz": -2.59, "right_gripper": 0.41}, "11": {"left_arm_vel": 0.371, "left_gripper_vel": 0.0, "left_arm_rx": -2.71, "left_arm_ry": 0.66, "left_arm_rz": 2.57, "left_gripper": 0.24, "right_arm_vel": 0.371, "right_gripper_vel": 0.0, "right_arm_rx": 2.84, "right_arm_ry": 0.36, "right_arm_rz": -2.67, "right_gripper": 0.41}, "12": {"left_arm_vel": 0.462, "left_gripper_vel": 0.0, "left_arm_rx": -2.77, "left_arm_ry": 0.67, "left_arm_rz": 2.56, "left_gripper": 0.24, "right_arm_vel": 0.462, "right_gripper_vel": 0.0, "right_arm_rx": 2.84, "right_arm_ry": 0.35, "right_arm_rz": -2.75, "right_gripper": 0.41}, "13": {"left_arm_vel": 0.39, "left_gripper_vel": 0.0, "left_arm_rx": -2.84, "left_arm_ry": 0.68, "left_arm_rz": 2.58, "left_gripper": 0.24, "right_arm_vel": 0.39, "right_gripper_vel": 0.0, "right_arm_rx": 2.87, "right_arm_ry": 0.38, "right_arm_rz": -2.79, "right_gripper": 0.41}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.07199999690055847, 0.06589999794960022, 0.1315000057220459], "delta_rot": [-0.20970000326633453, 0.13289999961853027, 0.06719999760389328], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1638}, "right": {"delta_pos": [-0.04569999873638153, -0.1696999967098236, 0.07779999822378159], "delta_rot": [0.14419999718666077, -0.2565000057220459, -0.24619999527931213], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.1922}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.4359999895095825, 0.2624000012874603, 0.06459999829530716], "delta_rot": [-0.47290000319480896, 0.6015999913215637, 0.18719999492168427], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.513}, "right": {"delta_pos": [-0.267300009727478, -0.2655999958515167, 0.08460000157356262], "delta_rot": [-5.827099800109863, 0.4909000098705292, -0.10840000212192535], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.3862}} + + ========================================= + [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": "The robot is executing a dual-arm stabilization and manipulation sequence to open the bag. The left arm maintains a static hold on the bag's top surface to prevent displacement, while the right arm actively pulls the zipper pull laterally to unzip the compartment.", + "actions": [ + { + "reasoning_cot": "The left arm is positioned over the bag's main body (specifically the reflective patch area) and remains stationary relative to the object throughout the sequence. Visual evidence shows continuous contact without significant movement, serving as an anchor point for the manipulation task.", + "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_surface", + "topology_change": false + }, + { + "reasoning_cot": "The right arm gripper is visually engaged with the metal zipper pull. Comparing T0 to T1, the gripper moves laterally away from the center of the bag, dragging the zipper slider along the track. This action physically alters the state of the bag by opening the compartment.", + "causal_trace": { + "gripper_signal": "stable", + "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_center_to_side_along_zipper_track", + "topology_change": true + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_track", + "current_status": "partially_opened" + } + ], + "task_progress": "Bag compartment is being unzipped via lateral pull on the zipper handle while stabilizing the bag body." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}, {"anchor_id": "bag:zipper_track", "current_status": "partially_opened"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'table:surface_center', 'bag:top_surface', 'zipper_pull', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "The robot is executing a dual-arm stabilization and manipulation sequence to open the bag. The left arm maintains a static hold on the bag's top surface to prevent displacement, while the right arm actively pulls the zipper pull laterally to unzip the compartment.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}} + ⚠️ 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": 0.31, "angle": 0.54, "vel_score": 3.1, "angle_score": 4.85, "vel_fft": [0.312, 0.213, 0.062, 0.046, 0.018, 0.027, 0.015, 0.019, 0.008, 0.015, 0.016, 0.022, 0.012, 0.001, 0.007, 0.01, 0.007, 0.001, 0.006, 0.012], "angle_fft": [0.543, 0.246, 0.155, 0.067, 0.039, 0.046, 0.041, 0.031, 0.027, 0.034, 0.049, 0.052, 0.035, 0.02, 0.031, 0.026, 0.03, 0.028, 0.007, 0.027]}, "right": {"vel": 0.19, "angle": 5.08, "vel_score": 1.73, "angle_score": 5.96, "vel_fft": [0.187, 0.103, 0.026, 0.025, 0.016, 0.018, 0.012, 0.009, 0.011, 0.002, 0.007, 0.007, 0.009, 0.012, 0.006, 0.005, 0.007, 0.005, 0.007, 0.008], "angle_fft": [5.078, 4.637, 4.583, 4.596, 4.445, 4.474, 4.4, 4.465, 4.404, 4.44, 4.437, 4.455, 4.406, 4.425, 4.453, 4.45, 4.456, 4.456, 4.436, 4.407]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.7, "left_arm_rz": 2.59, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.9, "right_arm_ry": 0.4, "right_arm_rz": -2.8, "right_gripper": 0.41}, "1": {"left_arm_vel": 0.33, "left_gripper_vel": 0.0, "left_arm_rx": -2.95, "left_arm_ry": 0.85, "left_arm_rz": 2.68, "left_gripper": 0.24, "right_arm_vel": 0.33, "right_gripper_vel": 0.0, "right_arm_rx": 3.03, "right_arm_ry": 0.52, "right_arm_rz": -2.74, "right_gripper": 0.41}, "2": {"left_arm_vel": 0.376, "left_gripper_vel": 0.0, "left_arm_rx": -2.93, "left_arm_ry": 1.0, "left_arm_rz": 2.82, "left_gripper": 0.24, "right_arm_vel": 0.376, "right_gripper_vel": 0.0, "right_arm_rx": 3.06, "right_arm_ry": 0.62, "right_arm_rz": -2.72, "right_gripper": 0.41}, "3": {"left_arm_vel": 0.265, "left_gripper_vel": 0.0, "left_arm_rx": -3.04, "left_arm_ry": 1.15, "left_arm_rz": 2.78, "left_gripper": 0.24, "right_arm_vel": 0.265, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 0.91, "right_arm_rz": -2.67, "right_gripper": 0.41}, "4": {"left_arm_vel": 0.069, "left_gripper_vel": -0.357, "left_arm_rx": -3.05, "left_arm_ry": 1.14, "left_arm_rz": 2.77, "left_gripper": 0.24, "right_arm_vel": 0.069, "right_gripper_vel": -0.357, "right_arm_rx": -3.08, "right_arm_ry": 1.1, "right_arm_rz": -2.61, "right_gripper": 0.39}, "5": {"left_arm_vel": 0.012, "left_gripper_vel": -0.357, "left_arm_rx": -3.09, "left_arm_ry": 1.14, "left_arm_rz": 2.73, "left_gripper": 0.24, "right_arm_vel": 0.012, "right_gripper_vel": -0.357, "right_arm_rx": -3.09, "right_arm_ry": 1.12, "right_arm_rz": -2.64, "right_gripper": 0.35}, "6": {"left_arm_vel": 0.001, "left_gripper_vel": -0.273, "left_arm_rx": -3.1, "left_arm_ry": 1.15, "left_arm_rz": 2.71, "left_gripper": 0.24, "right_arm_vel": 0.001, "right_gripper_vel": -0.273, "right_arm_rx": -3.1, "right_arm_ry": 1.12, "right_arm_rz": -2.65, "right_gripper": 0.32}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": -0.021, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 2.7, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": -0.021, "right_arm_rx": -3.1, "right_arm_ry": 1.12, "right_arm_rz": -2.65, "right_gripper": 0.3}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.3481000065803528, 0.18569999933242798, -0.0778999999165535], "delta_rot": [-0.2272000014781952, 0.4404999911785126, 0.11050000041723251], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and -Z(Down)", "magnitude": 0.4022}, "right": {"delta_pos": [-0.21539999544620514, -0.08420000225305557, -0.0005000000237487257], "delta_rot": [-5.994699954986572, 0.7268000245094299, 0.14910000562667847], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.2313}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.34709998965263367, 0.181099995970726, -0.07779999822378159], "delta_rot": [-0.2272000014781952, 0.4422000050544739, 0.5401999950408936], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and -Z(Down)", "magnitude": 0.3992}, "right": {"delta_pos": [-0.21230000257492065, -0.0820000022649765, -0.0003000000142492354], "delta_rot": [-5.997600078582764, 0.7289999723434448, -0.11959999799728394], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.2276}} + + ========================================= + [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": "The robot is executing a dual-arm stabilization and manipulation sequence to open the bag. The left arm maintains a static hold on the bag's top surface to prevent displacement, while the right arm actively pulls the zipper pull laterally to unzip the compartment.", + "actions": [ + { + "reasoning_cot": "The left arm has moved from a previous position to establish contact with the top of the bag. Visual evidence shows the gripper pressing down on the mesh/surface area to anchor the object against the pulling force of the right arm. This is a stabilization maneuver.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "press", + "semantic_action": "stabilize_bag_body", + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:top_surface" + }, + "spatial_logic": "moving to and holding bag:top_surface for stabilization", + "topology_change": false + }, + { + "reasoning_cot": "The right arm is engaged with the zipper mechanism. Kinematic data indicates lateral movement consistent with unzipping. The visual sequence confirms the gripper is secured on the zipper pull and moving it along the track to open the compartment.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "pull", + "semantic_action": "unzip_compartment", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "pulling bag:zipper_pull laterally along bag:zipper_track", + "topology_change": true + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_track", + "current_status": "partially_opened" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "pressed" + } + ], + "task_progress": "Bag compartment is being actively unzipped; left arm provides necessary counter-force." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}, {"anchor_id": "bag:zipper_track", "current_status": "partially_opened"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:side_handle', 'table:surface_center', 'bag:top_surface', 'zipper_pull', 'bag:zipper_track'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "The robot is executing a dual-arm stabilization and manipulation sequence to open the bag. The left arm maintains a static hold on the bag's top surface to prevent displacement, while the right arm actively pulls the zipper pull laterally to unzip the compartment.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}} + ⚠️ 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": 0.31, "vel_score": 0.03, "angle_score": 3.07, "vel_fft": [0.003, 0.003, 0.002, 0.002, 0.001, 0.0, 0.0, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001], "angle_fft": [0.307, 0.284, 0.224, 0.143, 0.065, 0.019, 0.041, 0.055, 0.059, 0.061, 0.066, 0.073, 0.08, 0.082, 0.08, 0.076, 0.073, 0.072, 0.073, 0.075]}, "right": {"vel": 0.0, "angle": 0.19, "vel_score": 0.03, "angle_score": 1.94, "vel_fft": [0.003, 0.003, 0.002, 0.001, 0.0, 0.0, 0.0, 0.0, 0.001, 0.001, 0.0, 0.0, 0.0, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001], "angle_fft": [0.194, 0.174, 0.129, 0.076, 0.025, 0.019, 0.027, 0.035, 0.034, 0.031, 0.034, 0.03, 0.031, 0.036, 0.035, 0.041, 0.044, 0.043, 0.048, 0.046]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 2.7, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": -3.1, "right_arm_ry": 1.12, "right_arm_rz": -2.65, "right_gripper": 0.29}, "1": {"left_arm_vel": 0.005, "left_gripper_vel": -0.084, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 2.73, "left_gripper": 0.24, "right_arm_vel": 0.005, "right_gripper_vel": -0.084, "right_arm_rx": -3.1, "right_arm_ry": 1.12, "right_arm_rz": -2.67, "right_gripper": 0.29}, "2": {"left_arm_vel": 0.012, "left_gripper_vel": -0.021, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 2.8, "left_gripper": 0.24, "right_arm_vel": 0.012, "right_gripper_vel": -0.021, "right_arm_rx": -3.1, "right_arm_ry": 1.12, "right_arm_rz": -2.71, "right_gripper": 0.29}, "3": {"left_arm_vel": 0.011, "left_gripper_vel": 0.0, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.03, "left_gripper": 0.24, "right_arm_vel": 0.011, "right_gripper_vel": 0.0, "right_arm_rx": -3.1, "right_arm_ry": 1.12, "right_arm_rz": -2.84, "right_gripper": 0.29}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": -0.021, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.13, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": -0.021, "right_arm_rx": -3.1, "right_arm_ry": 1.13, "right_arm_rz": -2.92, "right_gripper": 0.28}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": -0.063, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.13, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": -0.063, "right_arm_rx": -3.1, "right_arm_ry": 1.13, "right_arm_rz": -2.92, "right_gripper": 0.28}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": -0.042, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.13, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": -0.042, "right_arm_rx": -3.1, "right_arm_ry": 1.13, "right_arm_rz": -2.92, "right_gripper": 0.28}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.13, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": -3.1, "right_arm_ry": 1.13, "right_arm_rz": -2.92, "right_gripper": 0.27}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0010000000474974513, -0.004600000102072954, 9.999999747378752e-05], "delta_rot": [0.0, 0.0017000000225380063, 0.42980000376701355], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0047}, "right": {"delta_pos": [0.003100000089034438, 0.002199999988079071, 0.00019999999494757503], "delta_rot": [-0.002899999963119626, 0.002199999988079071, -0.2687999904155731], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0039}} + + [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": "The robot is in a static holding phase, maintaining the bag's position on the table with both arms. The left arm stabilizes the top surface while the right arm holds the side handle to prevent displacement during the unzipping process.", + "actions": [ + { + "reasoning_cot": "Visual evidence shows the left gripper remains stationary and in contact with the top of the bag throughout the sequence. Kinematic data confirms zero velocity (vel: 0.0) and stable gripper width. This is a stabilization hold.", + "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_surface", + "topology_change": false + }, + { + "reasoning_cot": "The right gripper is visually confirmed grasping the side handle of the bag. Despite minor kinematic noise, the visual frames show no relative motion between the gripper and the handle, indicating a static hold to anchor the bag against potential pulling forces from the zipper mechanism.", + "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" + }, + "spatial_logic": "static_at_side_handle", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Maintaining dual-arm stabilization on the bag; left arm presses top, right arm grips side handle to isolate the zipper track for manipulation." + } +} +```` +--- +## 🎬 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_0034 + - **Total Frames**: 531 + - **Global Task Goal**: "Unknown Task" + + ### 1. INPUT DATA + - **KPM (Micro-Actions Timeline)**: [{"chunk_idx": 0, "start_frame": 0, "end_frame": 50, "chunk_intent": "Right arm approaches and makes contact with the top surface of the bag to stabilize or prepare for manipulation, while left arm remains idle.", "micro_actions": [{"verb": "approach", "semantic_verb": "contact_surface", "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Moving from hover state to direct contact with bag top surface"}, {"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "Static hold in free space"}]}, {"chunk_idx": 1, "start_frame": 51, "end_frame": 101, "chunk_intent": "Right arm approaches and stabilizes the bag by pressing down on the top surface near the zipper, while the left arm remains idle in a hovering position.", "micro_actions": [{"verb": "press", "semantic_verb": "stabilize_bag", "subject": "right_arm", "target": "top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving from hover to top_surface"}, {"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": 102, "end_frame": 152, "chunk_intent": "Left arm approaches and grasps the zipper pull ring to stabilize or open the bag, while the right arm maintains a static stabilizing hold on the bag's top corner.", "micro_actions": [{"verb": "grasp", "semantic_verb": null, "subject": "left_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "Approaching from free space to secure the zipper_pull anchor."}, {"verb": "hold", "semantic_verb": "stabilize", "subject": "right_arm", "target": "top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Static hold at the top_surface anchor to prevent bag displacement."}]}, {"chunk_idx": 3, "start_frame": 153, "end_frame": 191, "chunk_intent": "Left arm releases the zipper pull ring and retreats to clear the workspace, while the right arm maintains a static stabilizing hold on the bag's top corner.", "micro_actions": [{"verb": "release", "semantic_verb": "release_and_retreat", "subject": "left_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "Retreating from zipper_pull to free space"}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "Static stabilization at bag:top_surface"}]}, {"chunk_idx": 4, "start_frame": 192, "end_frame": 234, "chunk_intent": "Left arm approaches and stabilizes the bag's side handle/zipper area while right arm maintains a static hold on the top surface.", "micro_actions": [{"verb": "approach", "semantic_verb": null, "subject": "left_arm", "target": "bag:side_handle", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "moving from free_space to bag:side_handle"}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "static_at_bag:top_surface"}]}, {"chunk_idx": 5, "start_frame": 235, "end_frame": 272, "chunk_intent": "Left arm approaches and grasps the bag's zipper pull to stabilize or open it, while the right arm maintains a static hold on the bag's top surface.", "micro_actions": [{"verb": "grasp", "semantic_verb": null, "subject": "left_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "Approaching from free space to secure the zipper_pull anchor."}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "Static hold at the established top_surface anchor."}]}, {"chunk_idx": 6, "start_frame": 273, "end_frame": 310, "chunk_intent": "Left arm releases the zipper pull and retreats to a neutral position, while the right arm maintains a static hold on the bag's top surface to stabilize it.", "micro_actions": [{"verb": "release", "semantic_verb": "release_and_retreat", "subject": "left_arm", "target": "zipper_pull", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "moving from zipper_pull to free_space"}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "static_at_top_surface"}]}, {"chunk_idx": 7, "start_frame": 311, "end_frame": 320, "chunk_intent": "Both arms maintain a static hold on the bag to stabilize it; the left arm presses down on the top surface while the right arm holds the side near the zipper pull, preparing for potential manipulation.", "micro_actions": [{"verb": "press", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "static_at_top_surface"}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:side_handle", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "static_at_side_handle"}]}, {"chunk_idx": 8, "start_frame": 321, "end_frame": 342, "chunk_intent": "Both arms are stabilizing the bag; the left arm presses down on the top surface to prevent movement, while the right arm holds the side near the zipper pull, maintaining a static hold.", "micro_actions": [{"verb": "press", "semantic_verb": null, "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "static_at_top_surface"}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:side_handle", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "static_at_side_handle"}]}, {"chunk_idx": 9, "start_frame": 343, "end_frame": 382, "chunk_intent": "The robot is stabilizing the bag with the left arm while the right arm approaches and grasps the zipper pull to initiate 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_surface"}, {"verb": "grasp", "semantic_verb": "approach_and_grasp_zipper", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "moving_from_side_handle_to_zipper_pull"}]}, {"chunk_idx": 10, "start_frame": 383, "end_frame": 422, "chunk_intent": "The robot is executing a dual-arm stabilization and manipulation sequence to open the bag. The left arm maintains a static hold on the bag's top surface to prevent displacement, while the right arm actively pulls the zipper pull laterally to unzip the compartment.", "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": "pull", "semantic_verb": "unzip", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "moving_from_zipper_start_to_mid_along_track"}]}, {"chunk_idx": 11, "start_frame": 423, "end_frame": 446, "chunk_intent": "The robot is executing a dual-arm stabilization and manipulation sequence to open the bag. The left arm maintains a static hold on the bag's top surface to prevent displacement, while the right arm actively pulls the zipper pull laterally to unzip the compartment.", "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_surface"}, {"verb": "pull", "semantic_verb": "unzip", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "moving_from_center_to_side_along_zipper_track"}]}, {"chunk_idx": 12, "start_frame": 447, "end_frame": 488, "chunk_intent": "The robot is executing a dual-arm stabilization and manipulation sequence to open the bag. The left arm maintains a static hold on the bag's top surface to prevent displacement, while the right arm actively pulls the zipper pull laterally to unzip the compartment.", "micro_actions": [{"verb": "press", "semantic_verb": "stabilize_bag_body", "subject": "left_arm", "target": "bag:top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving to and holding bag:top_surface for stabilization"}, {"verb": "pull", "semantic_verb": "unzip_compartment", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "pulling bag:zipper_pull laterally along bag:zipper_track"}]}, {"chunk_idx": 13, "start_frame": 489, "end_frame": 530, "chunk_intent": "The robot is in a static holding phase, maintaining the bag's position on the table with both arms. The left arm stabilizes the top surface while the right arm holds the side handle to prevent displacement during the unzipping process.", "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_surface"}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:side_handle", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_side_handle"}]}] + - **WSM (State Memory)**: [{"chunk_idx": 0, "global_frame_range": [0, 50], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}], "short_term_memory": {"last_chunk_intent": "Right arm approaches and makes contact with the top surface of the bag to stabilize or prepare for 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": [51, 101], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}], "short_term_memory": {"last_chunk_intent": "Right arm approaches and stabilizes the bag by pressing down on the top surface near the zipper, 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": [102, 152], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and grasps the zipper pull ring to stabilize or open the bag, while the right arm maintains a static stabilizing hold on the bag's top corner.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "none", "contact_target": "none"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 3, "global_frame_range": [153, 191], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}], "short_term_memory": {"last_chunk_intent": "Left arm releases the zipper pull ring and retreats to clear the workspace, while the right arm maintains a static stabilizing hold on the bag's top corner.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 4, "global_frame_range": [192, 234], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and stabilizes the bag's side handle/zipper area while right arm maintains a static hold on the top surface.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 5, "global_frame_range": [235, 272], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "grasped"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and grasps the bag's zipper pull to stabilize or open it, while the right arm maintains a static hold on the bag's top surface.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 6, "global_frame_range": [273, 310], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}], "short_term_memory": {"last_chunk_intent": "Left arm releases the zipper pull and retreats to a neutral position, while the right arm maintains a static hold on the bag's top surface to stabilize it.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:zipper_pull"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 7, "global_frame_range": [311, 320], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}], "short_term_memory": {"last_chunk_intent": "Both arms maintain a static hold on the bag to stabilize it; the left arm presses down on the top surface while the right arm holds the side near the zipper pull, preparing for potential manipulation.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 8, "global_frame_range": [321, 342], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}], "short_term_memory": {"last_chunk_intent": "Both arms are stabilizing the bag; the left arm presses down on the top surface to prevent movement, while the right arm holds the side near the zipper pull, maintaining a static hold.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 9, "global_frame_range": [343, 382], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}], "short_term_memory": {"last_chunk_intent": "The robot is stabilizing the bag with the left arm while the right arm approaches and grasps the zipper pull to initiate opening.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 10, "global_frame_range": [383, 422], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}, {"anchor_id": "bag:zipper_track", "current_status": "partially_opened"}], "short_term_memory": {"last_chunk_intent": "The robot is executing a dual-arm stabilization and manipulation sequence to open the bag. The left arm maintains a static hold on the bag's top surface to prevent displacement, while the right arm actively pulls the zipper pull laterally to unzip the compartment.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 11, "global_frame_range": [423, 446], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}, {"anchor_id": "bag:zipper_track", "current_status": "partially_opened"}], "short_term_memory": {"last_chunk_intent": "The robot is executing a dual-arm stabilization and manipulation sequence to open the bag. The left arm maintains a static hold on the bag's top surface to prevent displacement, while the right arm actively pulls the zipper pull laterally to unzip the compartment.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 12, "global_frame_range": [447, 488], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}, {"anchor_id": "bag:zipper_track", "current_status": "partially_opened"}], "short_term_memory": {"last_chunk_intent": "The robot is executing a dual-arm stabilization and manipulation sequence to open the bag. The left arm maintains a static hold on the bag's top surface to prevent displacement, while the right arm actively pulls the zipper pull laterally to unzip the compartment.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 13, "global_frame_range": [489, 530], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}, {"anchor_id": "bag:top_surface", "current_status": "pressed"}, {"anchor_id": "zipper_pull", "current_status": "released"}, {"anchor_id": "bag:zipper_track", "current_status": "partially_opened"}], "short_term_memory": {"last_chunk_intent": "The robot is in a static holding phase, maintaining the bag's position on the table with both arms. The left arm stabilizes the top surface while the right arm holds the side handle to prevent displacement during the unzipping process.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:top_surface"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:side_handle"}}, "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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:side_handle", "current_status": "partially_obscured_but_accessible"}, {"anchor_id": "table:surface_center", "current_status": "clear"}] + + 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_0034", + "merge_thought": "The timeline is divided into three logical macro-chapters based on the shift in manipulation strategy and target interaction. \n\n1. **Preparation & Stabilization (Chunks 0-2)**: The robot establishes a base of operations. It starts with the right arm stabilizing the bag body (Chunk 0-1) and then uses the left arm to briefly grasp the zipper pull (Chunk 2), likely to assess tension or position, while the right arm holds the top surface. This phase is characterized by establishing contact and initial static holds.\n\n2. **Re-grasping & Alignment (Chunks 3-8)**: There is a clear break after Chunk 2 where the left arm releases the zipper (Chunk 3). The subsequent chunks (4-8) involve a complex re-alignment sequence. The left arm moves away, then approaches the side handle/zipper area again (Chunk 4-5), releases again (Chunk 6), and finally, both arms settle into a specific dual-arm stabilization pose (Left on top, Right on side handle) in Chunks 7-8. This entire block serves the single purpose of achieving the optimal bimanual grip configuration for the upcoming unzipping action. The repeated grasping and releasing indicates fine-tuning of the grasp points.\n\n3. **Active Unzipping & Hold (Chunks 9-13)**: Once the stable dual-arm configuration is achieved in Chunk 8, the actual task execution begins. In Chunk 9, the right arm shifts from the side handle to the zipper pull. From Chunk 10 to 12, the right arm actively pulls the zipper along its track while the left arm maintains strict stabilization on the bag body. Finally, in Chunk 13, the motion stops, and the robot holds the final state. This segment is distinct because it involves the topological change of the bag (unzipping) driven by coordinated bimanual action.", + "segments": [ + { + "segment_id": 0, + "primitive_type": "Hold", + "chunk_idx_range": [ + 0, + 2 + ], + "subtask": "Initial Stabilization and Zipper Assessment", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "exposed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + }, + { + "anchor_id": "bag:side_handle", + "current_status": "partially_obscured_but_accessible" + }, + { + "anchor_id": "table:surface_center", + "current_status": "clear" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "stabilized" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_then_released" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "pressed" + } + ] + }, + "causal_summary": { + "trigger": "Right arm presses top surface; Left arm briefly grasps and releases zipper pull", + "effect": "Bag is stabilized, and zipper location is verified without opening" + } + }, + { + "segment_id": 1, + "primitive_type": "Pre-grasp Align", + "chunk_idx_range": [ + 3, + 8 + ], + "subtask": "Bimanual Grip Reconfiguration and Alignment", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:top_surface", + "current_status": "pressed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "released" + }, + { + "anchor_id": "bag:side_handle", + "current_status": "accessible" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:top_surface", + "current_status": "pressed_by_left_arm" + }, + { + "anchor_id": "bag:side_handle", + "current_status": "held_by_right_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + } + ] + }, + "causal_summary": { + "trigger": "Left arm retreats and re-approaches; Right arm shifts from top to side handle", + "effect": "Robot achieves a stable dual-anchor hold (Top + Side) preparing for lateral force application" + } + }, + { + "segment_id": 2, + "primitive_type": "Shape/Adjust", + "chunk_idx_range": [ + 9, + 13 + ], + "subtask": "Active Unzipping and Final Stabilization", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:top_surface", + "current_status": "pressed_by_left_arm" + }, + { + "anchor_id": "bag:side_handle", + "current_status": "held_by_right_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:zipper_track", + "current_status": "partially_opened" + }, + { + "anchor_id": "bag:top_surface", + "current_status": "stabilized" + }, + { + "anchor_id": "bag:side_handle", + "current_status": "held" + } + ] + }, + "causal_summary": { + "trigger": "Right arm grasps zipper pull and translates laterally while Left arm anchors bag body", + "effect": "Bag compartment is unzipped along the track" + } + } + ] +} +```` +--- diff 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sha256:8ad7613d0a8c1d254e9e84b95f3d39e19380e6e8ea5d9f8a26483d170bb6982d +size 17049 diff --git a/debug/episode_0035/trace_report.md b/debug/episode_0035/trace_report.md new file mode 100644 index 0000000000000000000000000000000000000000..2250d2cafb6584c8f4a26e48b4b120ba6fb2c474 --- /dev/null +++ b/debug/episode_0035/trace_report.md @@ -0,0 +1,4935 @@ +# 🤖 Episode_0035 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 insulated bag is positioned centrally on a flat white table surface, directly within the robot's immediate reach zone.", + "initial_semantic_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "exposed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + }, + { + "anchor_id": "bag:top_opening", + "current_status": "closed" + }, + { + "anchor_id": "table:surface_center", + "current_status": "occupied_by_bag" + } + ], + "background_distractors": [] +} +```` +--- + +# 🤖 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_opening", "current_status": "closed"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_opening', 'table:surface_center'] + + 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": 0.0, "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, 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, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]}, "right": {"vel": 0.28, "angle": 3.58, "vel_score": 3.6, "angle_score": 9.32, "vel_fft": [0.282, 0.166, 0.021, 0.006, 0.01, 0.004, 0.002, 0.005, 0.002, 0.001, 0.004, 0.004, 0.005, 0.003, 0.001, 0.002, 0.005, 0.006, 0.002, 0.011], "angle_fft": [3.582, 2.721, 2.912, 2.748, 2.808, 2.843, 2.754, 2.895, 2.791, 2.792, 2.746, 2.788, 2.796, 2.784, 2.781, 2.752, 2.75, 2.776, 2.802, 2.817]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.13, "left_gripper": 0.23, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": -3.11, "right_arm_ry": 1.13, "right_arm_rz": -2.92, "right_gripper": 0.27}, "1": {"left_arm_vel": 0.47, "left_gripper_vel": 0.0, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.13, "left_gripper": 0.23, "right_arm_vel": 0.47, "right_gripper_vel": 0.0, "right_arm_rx": 2.74, "right_arm_ry": 1.07, "right_arm_rz": -2.86, "right_gripper": 0.27}, "2": {"left_arm_vel": 0.7, "left_gripper_vel": 0.0, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.13, "left_gripper": 0.23, "right_arm_vel": 0.7, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.93, "right_arm_rz": -2.62, "right_gripper": 0.27}, "3": {"left_arm_vel": 0.551, "left_gripper_vel": 0.168, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.13, "left_gripper": 0.23, "right_arm_vel": 0.551, "right_gripper_vel": 0.168, "right_arm_rx": 2.78, "right_arm_ry": 0.94, "right_arm_rz": -2.29, "right_gripper": 0.28}, "4": {"left_arm_vel": 0.503, "left_gripper_vel": 0.378, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.13, "left_gripper": 0.23, "right_arm_vel": 0.503, "right_gripper_vel": 0.378, "right_arm_rx": 2.74, "right_arm_ry": 0.91, "right_arm_rz": -2.26, "right_gripper": 0.32}, "5": {"left_arm_vel": 0.425, "left_gripper_vel": 0.462, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.13, "left_gripper": 0.23, "right_arm_vel": 0.425, "right_gripper_vel": 0.462, "right_arm_rx": 2.74, "right_arm_ry": 0.89, "right_arm_rz": -2.25, "right_gripper": 0.33}, "6": {"left_arm_vel": 0.358, "left_gripper_vel": 0.357, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.13, "left_gripper": 0.23, "right_arm_vel": 0.358, "right_gripper_vel": 0.357, "right_arm_rx": 2.74, "right_arm_ry": 0.87, "right_arm_rz": -2.22, "right_gripper": 0.36}, "7": {"left_arm_vel": 0.09, "left_gripper_vel": 0.0, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.13, "left_gripper": 0.23, "right_arm_vel": 0.09, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.81, "right_arm_rz": -2.24, "right_gripper": 0.38}}} + + [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": [0.46810001134872437, 0.27639999985694885, -0.07029999792575836], "delta_rot": [5.785600185394287, -0.31310001015663147, 0.6837999820709229], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and -Z(Down)", "magnitude": 0.5482}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.367900013923645, -0.1331000030040741, -0.09200000017881393], "delta_rot": [5.620999813079834, -0.6736000180244446, -1.6647000312805176], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.4019}, "right": {"delta_pos": [0.4681999981403351, 0.27469998598098755, -0.08760000020265579], "delta_rot": [5.77400016784668, -0.4106000065803528, 0.671500027179718], "gripper_changed": false, "flow_direction": "+X(Forward) and +Y(Left) and -Z(Down)", "magnitude": 0.5499}} + + ========================================= + [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 top surface of the bag to stabilize or prepare for manipulation, while left arm remains idle.", + "actions": [ + { + "reasoning_cot": "The right arm executes a significant forward (+X) and downward (-Z) trajectory (delta_pos magnitude ~0.55) 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 signal is 'stable' (no closing), 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_surface" + }, + "spatial_logic": "Moving from free space to contact with bag:top_surface", + "topology_change": false + }, + { + "reasoning_cot": "The left arm shows zero velocity and no positional change throughout the sequence. It remains in a static hovering state away from the object.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "idle", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": null, + "spatial_logic": "Static hover position maintained", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Right end-effector has established visual and physical contact with the top of the bag, likely stabilizing it for subsequent zipper or opening actions." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_opening", "current_status": "closed"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_opening', 'table:surface_center'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm approaches and makes contact with the top surface of the bag to stabilize or prepare for 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": 0.22, "angle": 3.92, "vel_score": 2.84, "angle_score": 14.41, "vel_fft": [0.218, 0.129, 0.068, 0.024, 0.007, 0.002, 0.004, 0.008, 0.003, 0.007, 0.005, 0.001, 0.004, 0.002, 0.003, 0.002, 0.005, 0.004, 0.008, 0.009], "angle_fft": [3.925, 3.272, 2.688, 2.678, 2.832, 2.885, 2.744, 2.727, 2.737, 2.725, 2.743, 2.76, 2.769, 2.763, 2.776, 2.798, 2.805, 2.778, 2.743, 2.712]}, "right": {"vel": 0.01, "angle": 0.06, "vel_score": 0.16, "angle_score": 0.9, "vel_fft": [0.01, 0.008, 0.006, 0.006, 0.006, 0.005, 0.004, 0.004, 0.003, 0.003, 0.003, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001], "angle_fft": [0.06, 0.049, 0.032, 0.027, 0.026, 0.021, 0.013, 0.016, 0.016, 0.015, 0.012, 0.008, 0.007, 0.004, 0.004, 0.004, 0.003, 0.002, 0.007, 0.007]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.11, "left_arm_ry": 1.15, "left_arm_rz": 3.13, "left_gripper": 0.23, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.81, "right_arm_rz": -2.24, "right_gripper": 0.38}, "1": {"left_arm_vel": 0.011, "left_gripper_vel": -1.68, "left_arm_rx": -3.11, "left_arm_ry": 1.09, "left_arm_rz": 3.12, "left_gripper": 0.23, "right_arm_vel": 0.011, "right_gripper_vel": -1.68, "right_arm_rx": 2.67, "right_arm_ry": 0.74, "right_arm_rz": -2.27, "right_gripper": 0.21}, "2": {"left_arm_vel": 0.004, "left_gripper_vel": 0.0, "left_arm_rx": -3.08, "left_arm_ry": 1.16, "left_arm_rz": 3.06, "left_gripper": 0.24, "right_arm_vel": 0.004, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.72, "right_arm_rz": -2.27, "right_gripper": 0.08}, "3": {"left_arm_vel": 0.018, "left_gripper_vel": 0.0, "left_arm_rx": -3.11, "left_arm_ry": 1.1, "left_arm_rz": 2.78, "left_gripper": 0.31, "right_arm_vel": 0.018, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.72, "right_arm_rz": -2.26, "right_gripper": 0.08}, "4": {"left_arm_vel": 0.006, "left_gripper_vel": 0.0, "left_arm_rx": -3.07, "left_arm_ry": 1.0, "left_arm_rz": 2.64, "left_gripper": 0.35, "right_arm_vel": 0.006, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.72, "right_arm_rz": -2.26, "right_gripper": 0.08}, "5": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": 3.11, "left_arm_ry": 0.89, "left_arm_rz": 2.28, "left_gripper": 0.39, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.72, "right_arm_rz": -2.25, "right_gripper": 0.08}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.36, "left_arm_ry": 0.39, "left_arm_rz": 1.44, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.72, "right_arm_rz": -2.25, "right_gripper": 0.08}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.51, "left_arm_ry": 0.47, "left_arm_rz": 1.46, "left_gripper": 0.3, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.72, "right_arm_rz": -2.25, "right_gripper": 0.08}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.367900013923645, -0.1331000030040741, -0.09200000017881393], "delta_rot": [5.620999813079834, -0.6736000180244446, -1.6647000312805176], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.4019}, "right": {"delta_pos": [-0.00039999998989515007, -0.0020000000949949026, -0.014700000174343586], "delta_rot": [-0.0066999997943639755, -0.09309999644756317, -0.006399999838322401], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0149}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.35199999809265137, -0.13289999961853027, -0.08950000256299973], "delta_rot": [5.478300094604492, -0.7705000042915344, -1.6714999675750732], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.3867}, "right": {"delta_pos": [-0.000699999975040555, -0.002099999925121665, -0.01489999983459711], "delta_rot": [-0.00800000037997961, -0.09669999778270721, -0.004999999888241291], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.015}} + + ========================================= + [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 the bag's top opening and stabilizes the zipper area, while left arm remains idle.", + "actions": [ + { + "reasoning_cot": "The right arm moves from a hovering position to make contact with the top surface of the bag near the zipper. The gripper is open, indicating an approach or stabilization action rather than grasping. The left arm shows no significant movement or interaction.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "top_opening" + }, + "spatial_logic": "moving from free space to bag:top_opening", + "topology_change": false + }, + { + "reasoning_cot": "The left arm remains stationary in the lower-left visual field with no change in gripper state or position relative to the scene. It does not interact 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_idle_position", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Right arm has established contact with the bag's top opening to prepare for 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_opening", "current_status": "closed"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_opening', 'table:surface_center'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Right arm approaches the bag's top opening and stabilizes the zipper area, 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": 0.04, "angle": 0.23, "vel_score": 0.47, "angle_score": 2.56, "vel_fft": [0.039, 0.013, 0.01, 0.013, 0.007, 0.002, 0.006, 0.004, 0.002, 0.002, 0.004, 0.002, 0.002, 0.001, 0.0, 0.001, 0.001, 0.001, 0.001, 0.001], "angle_fft": [0.225, 0.053, 0.041, 0.023, 0.012, 0.023, 0.054, 0.049, 0.015, 0.033, 0.035, 0.003, 0.015, 0.018, 0.006, 0.016, 0.009, 0.01, 0.012, 0.006]}, "right": {"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, 0.002, 0.003, 0.002, 0.001, 0.002, 0.001, 0.001, 0.002, 0.0, 0.001, 0.001, 0.0, 0.001, 0.001, 0.001, 0.002, 0.001, 0.001]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.51, "left_arm_ry": 0.47, "left_arm_rz": 1.46, "left_gripper": 0.3, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.72, "right_arm_rz": -2.25, "right_gripper": 0.08}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.43, "left_arm_ry": 0.44, "left_arm_rz": 1.42, "left_gripper": 0.29, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.71, "right_arm_rz": -2.25, "right_gripper": 0.08}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.43, "left_arm_ry": 0.43, "left_arm_rz": 1.41, "left_gripper": 0.09, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.71, "right_arm_rz": -2.25, "right_gripper": 0.08}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.44, "left_arm_ry": 0.41, "left_arm_rz": 1.45, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.71, "right_arm_rz": -2.25, "right_gripper": 0.08}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.44, "left_arm_ry": 0.4, "left_arm_rz": 1.52, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.71, "right_arm_rz": -2.25, "right_gripper": 0.07}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.38, "left_arm_ry": 0.41, "left_arm_rz": 1.57, "left_gripper": 0.19, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.71, "right_arm_rz": -2.25, "right_gripper": 0.07}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.4, "left_arm_ry": 0.42, "left_arm_rz": 1.56, "left_gripper": 0.32, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.71, "right_arm_rz": -2.25, "right_gripper": 0.07}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.37, "left_arm_ry": 0.38, "left_arm_rz": 1.46, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.71, "right_arm_rz": -2.25, "right_gripper": 0.07}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.016100000590085983, 9.999999747378752e-05, 0.002400000113993883], "delta_rot": [-0.1404999941587448, -0.09570000320672989, -0.005799999926239252], "gripper_changed": true, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0163}, "right": {"delta_pos": [-0.0003000000142492354, -9.999999747378752e-05, -9.999999747378752e-05], "delta_rot": [-0.0013000000035390258, -0.0035000001080334187, 0.00139999995008111], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0004}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.007899999618530273, 0.006599999964237213, 0.008500000461935997], "delta_rot": [-0.2572000026702881, -0.16840000450611115, -0.005100000184029341], "gripper_changed": true, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0133}, "right": {"delta_pos": [-0.0003000000142492354, -9.999999747378752e-05, -9.999999747378752e-05], "delta_rot": [-0.007300000172108412, -0.0071000000461936, -0.007799999788403511], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0004}} + + ========================================= + [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 establishes contact with the bag's zipper pull to stabilize it, while the right arm maintains a static hold on the bag body near the zipper track.", + "actions": [ + { + "reasoning_cot": "The left arm transitions from a hovering state (Image 1) to making direct visual contact with the metal zipper pull (Images 2-9). The gripper closes slightly (0.3 -> 0.09 -> -0.01) indicating an intent to grasp or pinch the pull tab for manipulation. This is a clear approach and touch/grasp sequence targeting the specific 'zipper_pull' anchor.", + "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": "moving from free space to bag:zipper_pull", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains visually stationary relative to the bag throughout the chunk, maintaining its position on the bag's main body/zipper area. Kinematic data shows near-zero velocity and no gripper change. It acts as a stabilizer.", + "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": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_left" + } + ], + "task_progress": "Left arm has successfully located and engaged the zipper pull; right arm continues to stabilize the bag structure." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_left"}, {"anchor_id": "bag:top_opening", "current_status": "closed"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_opening', 'table:surface_center'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and establishes contact with the bag's zipper pull to stabilize it, while the right arm maintains a static hold on the bag body near the zipper track.", "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": 0.02, "angle": 0.21, "vel_score": 0.09, "angle_score": 1.01, "vel_fft": [0.019, 0.009, 0.004, 0.003, 0.002, 0.003, 0.002, 0.002, 0.001, 0.002], "angle_fft": [0.211, 0.087, 0.045, 0.042, 0.022, 0.035, 0.023, 0.017, 0.018, 0.031]}, "right": {"vel": 0.0, "angle": 0.02, "vel_score": 0.0, "angle_score": 0.09, "vel_fft": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], "angle_fft": [0.019, 0.01, 0.005, 0.006, 0.005, 0.004, 0.002, 0.005, 0.002, 0.001]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.36, "left_arm_ry": 0.36, "left_arm_rz": 1.45, "left_gripper": 0.34, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.71, "right_arm_rz": -2.25, "right_gripper": 0.07}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.35, "left_arm_ry": 0.35, "left_arm_rz": 1.44, "left_gripper": 0.33, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.71, "right_arm_rz": -2.25, "right_gripper": 0.07}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.34, "left_arm_ry": 0.34, "left_arm_rz": 1.44, "left_gripper": 0.32, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.71, "right_arm_rz": -2.25, "right_gripper": 0.07}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.33, "left_arm_ry": 0.34, "left_arm_rz": 1.44, "left_gripper": 0.32, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.71, "right_arm_rz": -2.25, "right_gripper": 0.07}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.33, "left_arm_ry": 0.34, "left_arm_rz": 1.44, "left_gripper": 0.32, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.25, "right_gripper": 0.07}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.33, "left_arm_ry": 0.34, "left_arm_rz": 1.44, "left_gripper": 0.32, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.25, "right_gripper": 0.07}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.33, "left_arm_ry": 0.34, "left_arm_rz": 1.44, "left_gripper": 0.31, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.26, "right_gripper": 0.07}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.33, "left_arm_ry": 0.33, "left_arm_rz": 1.44, "left_gripper": 0.31, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.26, "right_gripper": 0.07}, "8": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.33, "left_arm_ry": 0.33, "left_arm_rz": 1.44, "left_gripper": 0.31, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.26, "right_gripper": 0.07}, "9": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.32, "left_arm_ry": 0.33, "left_arm_rz": 1.44, "left_gripper": 0.31, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.26, "right_gripper": 0.07}, "10": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.31, "left_arm_ry": 0.32, "left_arm_rz": 1.44, "left_gripper": 0.31, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.26, "right_gripper": 0.07}, "11": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.28, "left_arm_ry": 0.31, "left_arm_rz": 1.44, "left_gripper": 0.31, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.26, "right_gripper": 0.07}, "12": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.27, "left_arm_ry": 0.31, "left_arm_rz": 1.45, "left_gripper": 0.31, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.26, "right_gripper": 0.07}, "13": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.25, "left_arm_ry": 0.3, "left_arm_rz": 1.46, "left_gripper": 0.31, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.26, "right_gripper": 0.07}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.007499999832361937, 0.005799999926239252, 0.00570000009611249], "delta_rot": [-0.10339999943971634, -0.0568000003695488, 0.00860000029206276], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0111}, "right": {"delta_pos": [0.0, 0.0, 0.0], "delta_rot": [-0.006000000052154064, -0.003599999938160181, -0.009200000204145908], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.05590000003576279, 0.013799999840557575, 0.003100000089034438], "delta_rot": [0.0421999990940094, 0.06610000133514404, 0.07850000262260437], "gripper_changed": false, "flow_direction": "-X(Backward)", "magnitude": 0.0576}, "right": {"delta_pos": [-0.0013000000035390258, 0.00139999995008111, 0.00019999999494757503], "delta_rot": [-0.023399999365210533, -0.010999999940395355, -0.024299999698996544], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0019}} + + ========================================= + [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 establishes contact with the bag's zipper pull to stabilize it, while the right arm maintains a static hold on the bag body near the zipper track.", + "actions": [ + { + "reasoning_cot": "The left arm moves from a hovering position towards the silver zipper pull. Visual evidence in frames T0-T1 shows the gripper closing around the metal ring of the zipper pull. Kinematic data confirms a small positional delta consistent with an approach and grasp maneuver. The target is specifically the 'zipper_pull' anchor.", + "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 stationary throughout the chunk, maintaining its grip on the main body of the bag to provide counter-tension for the left arm's operation. No visual movement or gripper state change is observed.", + "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": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_left" + } + ], + "task_progress": "Stabilizing the bag by grasping the zipper pull with the left arm while holding the body with the right." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_left"}, {"anchor_id": "bag:top_opening", "current_status": "closed"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_opening', 'table:surface_center'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and establishes contact with the bag's zipper pull to stabilize it, while the right arm maintains a static hold on the bag body near the zipper track.", "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": 0.04, "angle": 0.17, "vel_score": 0.54, "angle_score": 2.02, "vel_fft": [0.043, 0.028, 0.012, 0.02, 0.012, 0.006, 0.006, 0.001, 0.002, 0.003, 0.002, 0.001, 0.002, 0.002, 0.002, 0.001, 0.001, 0.002, 0.001, 0.001], "angle_fft": [0.174, 0.099, 0.018, 0.062, 0.052, 0.043, 0.027, 0.014, 0.012, 0.005, 0.017, 0.016, 0.013, 0.009, 0.011, 0.013, 0.011, 0.007, 0.007, 0.009]}, "right": {"vel": 0.0, "angle": 0.01, "vel_score": 0.01, "angle_score": 0.19, "vel_fft": [0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 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], "angle_fft": [0.014, 0.01, 0.01, 0.01, 0.009, 0.006, 0.006, 0.006, 0.004, 0.005, 0.003, 0.003, 0.001, 0.003, 0.003, 0.004, 0.003, 0.005, 0.001, 0.002]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.25, "left_arm_ry": 0.3, "left_arm_rz": 1.46, "left_gripper": 0.31, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.26, "right_gripper": 0.07}, "1": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.35, "left_arm_ry": 0.33, "left_arm_rz": 1.4, "left_gripper": 0.3, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.26, "right_gripper": 0.07}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.37, "left_arm_ry": 0.37, "left_arm_rz": 1.41, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.26, "right_gripper": 0.07}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.37, "left_arm_ry": 0.37, "left_arm_rz": 1.41, "left_gripper": 0.11, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.26, "right_gripper": 0.07}, "4": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.37, "left_arm_ry": 0.37, "left_arm_rz": 1.41, "left_gripper": 0.04, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.26, "right_gripper": 0.07}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.37, "left_arm_ry": 0.37, "left_arm_rz": 1.43, "left_gripper": 0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.71, "right_arm_rz": -2.26, "right_gripper": 0.07}, "6": {"left_arm_vel": 0.005, "left_gripper_vel": 0.0, "left_arm_rx": 2.38, "left_arm_ry": 0.4, "left_arm_rz": 1.49, "left_gripper": 0.0, "right_arm_vel": 0.005, "right_gripper_vel": 0.0, "right_arm_rx": 2.65, "right_arm_ry": 0.71, "right_arm_rz": -2.27, "right_gripper": 0.07}, "7": {"left_arm_vel": 0.012, "left_gripper_vel": 0.0, "left_arm_rx": 2.4, "left_arm_ry": 0.43, "left_arm_rz": 1.53, "left_gripper": -0.0, "right_arm_vel": 0.012, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.7, "right_arm_rz": -2.27, "right_gripper": 0.07}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.06340000033378601, 0.00800000037997961, -0.0027000000700354576], "delta_rot": [0.14659999310970306, 0.12389999628067017, 0.07020000368356705], "gripper_changed": false, "flow_direction": "-X(Backward)", "magnitude": 0.064}, "right": {"delta_pos": [-0.0013000000035390258, 0.00139999995008111, 0.00019999999494757503], "delta_rot": [-0.016899999231100082, -0.007000000216066837, -0.014299999922513962], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0019}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.16179999709129333, -0.026499999687075615, -0.0008999999845400453], "delta_rot": [0.7246000170707703, 0.524399995803833, 0.3499999940395355], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.164}, "right": {"delta_pos": [-0.002899999963119626, 0.003100000089034438, 0.000699999975040555], "delta_rot": [-0.10779999941587448, -0.041099999099969864, -0.11159999668598175], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0043}} + + ========================================= + [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 establishes contact with the bag's zipper pull to stabilize it, while the right arm maintains a static hold on the bag body near the zipper track.", + "actions": [ + { + "reasoning_cot": "The left arm moves from an open position towards the zipper pull (visible in T0-T1). The gripper closes around the metal ring of the zipper pull (T2-T4), securing it. This is a transition from approach to grasp/hold.", + "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": "Approaching and grasping the zipper pull anchor", + "topology_change": false + }, + { + "reasoning_cot": "The right arm remains stationary throughout the sequence, holding the main body of the bag to provide counter-tension for the left arm's manipulation of the zipper. Visual evidence shows no movement or state change.", + "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 hold at bag main body", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_left" + } + ], + "task_progress": "Left arm has successfully grasped the zipper pull; ready to unzip or adjust." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_left"}, {"anchor_id": "bag:top_opening", "current_status": "closed"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_opening', 'table:surface_center'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm approaches and establishes contact with the bag's zipper pull to stabilize it, while the right arm maintains a static hold on the bag body near the zipper track.", "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": 0.1, "angle": 0.66, "vel_score": 0.81, "angle_score": 5.42, "vel_fft": [0.099, 0.012, 0.025, 0.016, 0.009, 0.007, 0.007, 0.008, 0.003, 0.003, 0.005, 0.004, 0.004, 0.007, 0.005, 0.005, 0.003, 0.004, 0.003, 0.004], "angle_fft": [0.657, 0.02, 0.094, 0.008, 0.041, 0.064, 0.035, 0.016, 0.043, 0.02, 0.027, 0.015, 0.011, 0.017, 0.022, 0.025, 0.02, 0.02, 0.029, 0.013]}, "right": {"vel": 0.0, "angle": 0.11, "vel_score": 0.03, "angle_score": 0.86, "vel_fft": [0.003, 0.002, 0.001, 0.0, 0.0, 0.001, 0.0, 0.0, 0.0, 0.0, 0.001, 0.0, 0.001, 0.0, 0.001, 0.001, 0.0, 0.0, 0.0, 0.0], "angle_fft": [0.107, 0.013, 0.01, 0.024, 0.017, 0.014, 0.012, 0.015, 0.01, 0.012, 0.007, 0.009, 0.016, 0.002, 0.006, 0.007, 0.002, 0.004, 0.003, 0.009]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.41, "left_arm_ry": 0.44, "left_arm_rz": 1.54, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.7, "right_arm_rz": -2.28, "right_gripper": 0.07}, "1": {"left_arm_vel": 0.002, "left_gripper_vel": 0.0, "left_arm_rx": 2.46, "left_arm_ry": 0.48, "left_arm_rz": 1.59, "left_gripper": -0.01, "right_arm_vel": 0.002, "right_gripper_vel": 0.0, "right_arm_rx": 2.63, "right_arm_ry": 0.69, "right_arm_rz": -2.3, "right_gripper": 0.07}, "2": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.53, "left_arm_ry": 0.54, "left_arm_rz": 1.62, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.68, "right_arm_rz": -2.31, "right_gripper": 0.07}, "3": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.62, "left_arm_ry": 0.6, "left_arm_rz": 1.65, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.62, "right_arm_ry": 0.68, "right_arm_rz": -2.31, "right_gripper": 0.07}, "4": {"left_arm_vel": 0.001, "left_gripper_vel": 0.0, "left_arm_rx": 2.68, "left_arm_ry": 0.64, "left_arm_rz": 1.71, "left_gripper": -0.01, "right_arm_vel": 0.001, "right_gripper_vel": 0.0, "right_arm_rx": 2.61, "right_arm_ry": 0.68, "right_arm_rz": -2.32, "right_gripper": 0.07}, "5": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.73, "left_arm_ry": 0.66, "left_arm_rz": 1.75, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.61, "right_arm_ry": 0.67, "right_arm_rz": -2.33, "right_gripper": 0.07}, "6": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.78, "left_arm_ry": 0.68, "left_arm_rz": 1.76, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.67, "right_arm_rz": -2.34, "right_gripper": 0.07}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.84, "left_arm_ry": 0.73, "left_arm_rz": 1.76, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.6, "right_arm_ry": 0.66, "right_arm_rz": -2.35, "right_gripper": 0.07}, "8": {"left_arm_vel": 0.01, "left_gripper_vel": 0.0, "left_arm_rx": 2.89, "left_arm_ry": 0.77, "left_arm_rz": 1.78, "left_gripper": -0.01, "right_arm_vel": 0.01, "right_gripper_vel": 0.0, "right_arm_rx": 2.58, "right_arm_ry": 0.67, "right_arm_rz": -2.36, "right_gripper": 0.07}, "9": {"left_arm_vel": 0.009, "left_gripper_vel": -0.021, "left_arm_rx": 2.94, "left_arm_ry": 0.8, "left_arm_rz": 1.82, "left_gripper": -0.01, "right_arm_vel": 0.009, "right_gripper_vel": -0.021, "right_arm_rx": 2.57, "right_arm_ry": 0.67, "right_arm_rz": -2.36, "right_gripper": 0.07}, "10": {"left_arm_vel": 0.003, "left_gripper_vel": 0.0, "left_arm_rx": 2.98, "left_arm_ry": 0.81, "left_arm_rz": 1.87, "left_gripper": -0.01, "right_arm_vel": 0.003, "right_gripper_vel": 0.0, "right_arm_rx": 2.56, "right_arm_ry": 0.67, "right_arm_rz": -2.37, "right_gripper": 0.07}, "11": {"left_arm_vel": 0.006, "left_gripper_vel": -0.021, "left_arm_rx": 2.99, "left_arm_ry": 0.83, "left_arm_rz": 1.83, "left_gripper": -0.01, "right_arm_vel": 0.006, "right_gripper_vel": -0.021, "right_arm_rx": 2.56, "right_arm_ry": 0.67, "right_arm_rz": -2.37, "right_gripper": 0.07}, "12": {"left_arm_vel": 0.007, "left_gripper_vel": -0.189, "left_arm_rx": 2.98, "left_arm_ry": 0.83, "left_arm_rz": 1.81, "left_gripper": -0.01, "right_arm_vel": 0.007, "right_gripper_vel": -0.189, "right_arm_rx": 2.55, "right_arm_ry": 0.67, "right_arm_rz": -2.37, "right_gripper": 0.06}, "13": {"left_arm_vel": 0.007, "left_gripper_vel": -0.189, "left_arm_rx": 2.98, "left_arm_ry": 0.83, "left_arm_rz": 1.81, "left_gripper": -0.01, "right_arm_vel": 0.007, "right_gripper_vel": -0.189, "right_arm_rx": 2.55, "right_arm_ry": 0.67, "right_arm_rz": -2.37, "right_gripper": 0.06}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.09449999779462814, -0.0357000008225441, 0.003000000026077032], "delta_rot": [0.5633999705314636, 0.3894999921321869, 0.26649999618530273], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.101}, "right": {"delta_pos": [-0.0017000000225380063, 0.0017999999690800905, 0.000699999975040555], "delta_rot": [-0.09059999883174896, -0.030500000342726707, -0.09390000253915787], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0026}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.023399999365210533, -0.017799999564886093, 0.1005999967455864], "delta_rot": [0.722100019454956, 0.46790000796318054, 0.7269999980926514], "gripper_changed": true, "flow_direction": "-X(Backward) and +Z(Up)", "magnitude": 0.1048}, "right": {"delta_pos": [0.012299999594688416, -0.13609999418258667, 0.04490000009536743], "delta_rot": [-0.14020000398159027, -0.1850000023841858, -0.47699999809265137], "gripper_changed": false, "flow_direction": "-Y(Right) and +Z(Up)", "magnitude": 0.1439}} + + ========================================= + [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 pulls the zipper pull to open the bag, while the right arm stabilizes the bag body near the zipper track.", + "actions": [ + { + "reasoning_cot": "The left arm is visually engaged with the metal zipper pull. The kinematic data shows a backward (-X) and rightward (-Y) displacement consistent with pulling the zipper slider along the track to open the compartment. The gripper remains closed (stable) to maintain purchase on the small metal ring.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "pull", + "semantic_action": "unzip_bag", + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "Moving from initial grasp position along the zipper track trajectory to extend the opening.", + "topology_change": true + }, + { + "reasoning_cot": "The right arm maintains a static hold on the main body of the bag, specifically near the corner/zipper end, to counteract the force applied by the left arm and prevent the bag from sliding across the table. Minimal movement is observed in kinematics.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "hold", + "semantic_action": "stabilize_bag", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "Static stabilization at the bag corner to provide reaction force for the unzipping action.", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:top_opening", + "current_status": "opening" + } + ], + "task_progress": "Executing the unzipping maneuver to access the bag interior." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_left"}, {"anchor_id": "bag:top_opening", "current_status": "opening"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_opening', 'table:surface_center'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm pulls the zipper pull to open the bag, while the right arm stabilizes the bag body near the zipper track.", "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": 0.18, "angle": 8.56, "vel_score": 1.66, "angle_score": 116.37, "vel_fft": [0.179, 0.062, 0.032, 0.016, 0.012, 0.015, 0.012, 0.01, 0.009, 0.008, 0.007, 0.007, 0.011, 0.008, 0.01, 0.008, 0.007, 0.007, 0.008, 0.005], "angle_fft": [8.563, 6.701, 2.943, 1.899, 5.987, 7.872, 7.115, 3.797, 0.767, 5.115, 7.651, 7.436, 4.706, 0.303, 4.255, 7.275, 7.763, 5.521, 1.349, 3.329]}, "right": {"vel": 0.11, "angle": 0.33, "vel_score": 1.16, "angle_score": 3.22, "vel_fft": [0.11, 0.079, 0.022, 0.01, 0.013, 0.016, 0.011, 0.006, 0.008, 0.007, 0.005, 0.005, 0.008, 0.009, 0.006, 0.004, 0.007, 0.006, 0.007, 0.007], "angle_fft": [0.325, 0.189, 0.008, 0.047, 0.025, 0.034, 0.035, 0.018, 0.01, 0.02, 0.007, 0.02, 0.023, 0.031, 0.014, 0.017, 0.023, 0.014, 0.024, 0.019]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": 2.97, "left_arm_ry": 0.83, "left_arm_rz": 1.8, "left_gripper": -0.01, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.67, "right_arm_rz": -2.37, "right_gripper": 0.06}, "1": {"left_arm_vel": 0.022, "left_gripper_vel": 0.525, "left_arm_rx": 3.04, "left_arm_ry": 0.85, "left_arm_rz": 1.78, "left_gripper": 0.08, "right_arm_vel": 0.022, "right_gripper_vel": 0.525, "right_arm_rx": 2.53, "right_arm_ry": 0.66, "right_arm_rz": -2.4, "right_gripper": 0.09}, "2": {"left_arm_vel": 0.06, "left_gripper_vel": 1.449, "left_arm_rx": 3.1, "left_arm_ry": 0.85, "left_arm_rz": 1.85, "left_gripper": 0.2, "right_arm_vel": 0.06, "right_gripper_vel": 1.449, "right_arm_rx": 2.52, "right_arm_ry": 0.64, "right_arm_rz": -2.42, "right_gripper": 0.17}, "3": {"left_arm_vel": 0.119, "left_gripper_vel": 1.512, "left_arm_rx": -3.1, "left_arm_ry": 0.84, "left_arm_rz": 1.95, "left_gripper": 0.32, "right_arm_vel": 0.119, "right_gripper_vel": 1.512, "right_arm_rx": 2.51, "right_arm_ry": 0.63, "right_arm_rz": -2.46, "right_gripper": 0.27}, "4": {"left_arm_vel": 0.164, "left_gripper_vel": 0.966, "left_arm_rx": -3.08, "left_arm_ry": 0.84, "left_arm_rz": 1.98, "left_gripper": 0.34, "right_arm_vel": 0.164, "right_gripper_vel": 0.966, "right_arm_rx": 2.5, "right_arm_ry": 0.63, "right_arm_rz": -2.48, "right_gripper": 0.3}, "5": {"left_arm_vel": 0.336, "left_gripper_vel": 0.0, "left_arm_rx": -3.13, "left_arm_ry": 0.82, "left_arm_rz": 2.07, "left_gripper": 0.36, "right_arm_vel": 0.336, "right_gripper_vel": 0.0, "right_arm_rx": 2.51, "right_arm_ry": 0.61, "right_arm_rz": -2.6, "right_gripper": 0.33}, "6": {"left_arm_vel": 0.207, "left_gripper_vel": -0.357, "left_arm_rx": 3.13, "left_arm_ry": 0.89, "left_arm_rz": 2.27, "left_gripper": 0.35, "right_arm_vel": 0.207, "right_gripper_vel": -0.357, "right_arm_rx": 2.51, "right_arm_ry": 0.63, "right_arm_rz": -2.73, "right_gripper": 0.31}, "7": {"left_arm_vel": 0.388, "left_gripper_vel": -0.084, "left_arm_rx": 3.14, "left_arm_ry": 0.91, "left_arm_rz": 2.27, "left_gripper": 0.35, "right_arm_vel": 0.388, "right_gripper_vel": -0.084, "right_arm_rx": 2.5, "right_arm_ry": 0.51, "right_arm_rz": -2.75, "right_gripper": 0.27}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.07280000299215317, 0.025200000032782555, 0.09790000319480896], "delta_rot": [0.1664000004529953, 0.0763000026345253, 0.4699000120162964], "gripper_changed": true, "flow_direction": "+X(Forward) and +Y(Left) and +Z(Up)", "magnitude": 0.1246}, "right": {"delta_pos": [0.014299999922513962, -0.13840000331401825, 0.044199999421834946], "delta_rot": [-0.04820000007748604, -0.15479999780654907, -0.382999986410141], "gripper_changed": false, "flow_direction": "-Y(Right) and +Z(Up)", "magnitude": 0.146}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.23720000684261322, -0.09539999812841415, 0.019999999552965164], "delta_rot": [-5.843800067901611, -0.08889999985694885, 0.17730000615119934], "gripper_changed": true, "flow_direction": "+X(Forward) and -Y(Right) and +Z(Up)", "magnitude": 0.2564}, "right": {"delta_pos": [-0.12250000238418579, -0.16580000519752502, -0.05339999869465828], "delta_rot": [0.15479999780654907, 0.10360000282526016, -0.3686000108718872], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right) and -Z(Down)", "magnitude": 0.2129}} + + ========================================= + [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 pulls the bag's zipper pull to open the top flap, while the right arm stabilizes the bag body near the corner.", + "actions": [ + { + "reasoning_cot": "The left gripper is visually secured around the metal ring of the zipper pull. Kinematic data shows a positive velocity and displacement (+X, +Y), indicating an active pulling motion away from the bag center to unzip it. This confirms the action is 'pull' on the 'zipper_pull'.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "secured" + }, + "action_verb": "pull", + "semantic_action": "unzipping", + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving from static grasp to linear pull along zipper track", + "topology_change": true + }, + { + "reasoning_cot": "The right gripper is positioned against the side/corner of the bag (visible in cam_right_wrist). While the left arm moves significantly, the right arm maintains its position with minimal displacement to counteract the pulling force and keep the bag stationary. This is a stabilization hold.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "hold", + "semantic_action": "stabilizing", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "static_at_corner_providing_counter_force", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:top_opening", + "current_status": "opening" + } + ], + "task_progress": "Unzipping the bag by pulling the zipper tab while stabilizing the base." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_left"}, {"anchor_id": "bag:top_opening", "current_status": "opening"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_opening', 'table:surface_center'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Left arm pulls the bag's zipper pull to open the top flap, while the right arm stabilizes the bag body near the corner.", "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": 0.14, "angle": 0.33, "vel_score": 1.56, "angle_score": 3.69, "vel_fft": [0.138, 0.088, 0.047, 0.039, 0.021, 0.016, 0.012, 0.01, 0.011, 0.008, 0.008, 0.009, 0.008, 0.007, 0.003, 0.005, 0.008, 0.006, 0.004, 0.006], "angle_fft": [0.331, 0.197, 0.098, 0.033, 0.021, 0.044, 0.045, 0.025, 0.013, 0.023, 0.004, 0.008, 0.004, 0.005, 0.013, 0.01, 0.006, 0.007, 0.017, 0.021]}, "right": {"vel": 0.13, "angle": 0.47, "vel_score": 1.53, "angle_score": 4.87, "vel_fft": [0.134, 0.075, 0.064, 0.033, 0.025, 0.014, 0.014, 0.014, 0.007, 0.006, 0.008, 0.008, 0.008, 0.007, 0.008, 0.004, 0.002, 0.004, 0.006, 0.005], "angle_fft": [0.465, 0.115, 0.191, 0.081, 0.104, 0.097, 0.018, 0.018, 0.021, 0.037, 0.032, 0.007, 0.005, 0.006, 0.007, 0.013, 0.033, 0.036, 0.029, 0.028]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.12, "left_arm_ry": 0.89, "left_arm_rz": 2.27, "left_gripper": 0.35, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.5, "right_arm_ry": 0.49, "right_arm_rz": -2.76, "right_gripper": 0.27}, "1": {"left_arm_vel": 0.478, "left_gripper_vel": -0.042, "left_arm_rx": -3.09, "left_arm_ry": 0.88, "left_arm_rz": 2.25, "left_gripper": 0.35, "right_arm_vel": 0.478, "right_gripper_vel": -0.042, "right_arm_rx": 2.51, "right_arm_ry": 0.51, "right_arm_rz": -2.82, "right_gripper": 0.27}, "2": {"left_arm_vel": 0.504, "left_gripper_vel": 0.0, "left_arm_rx": -3.03, "left_arm_ry": 0.86, "left_arm_rz": 2.23, "left_gripper": 0.35, "right_arm_vel": 0.504, "right_gripper_vel": 0.0, "right_arm_rx": 2.5, "right_arm_ry": 0.52, "right_arm_rz": -2.91, "right_gripper": 0.27}, "3": {"left_arm_vel": 0.522, "left_gripper_vel": 0.0, "left_arm_rx": -3.01, "left_arm_ry": 0.87, "left_arm_rz": 2.2, "left_gripper": 0.35, "right_arm_vel": 0.522, "right_gripper_vel": 0.0, "right_arm_rx": 2.48, "right_arm_ry": 0.58, "right_arm_rz": -2.97, "right_gripper": 0.27}, "4": {"left_arm_vel": 0.336, "left_gripper_vel": -0.021, "left_arm_rx": -2.98, "left_arm_ry": 0.87, "left_arm_rz": 2.17, "left_gripper": 0.35, "right_arm_vel": 0.336, "right_gripper_vel": -0.021, "right_arm_rx": 2.48, "right_arm_ry": 0.65, "right_arm_rz": -2.98, "right_gripper": 0.27}, "5": {"left_arm_vel": 0.282, "left_gripper_vel": 0.0, "left_arm_rx": -2.94, "left_arm_ry": 0.86, "left_arm_rz": 2.09, "left_gripper": 0.35, "right_arm_vel": 0.282, "right_gripper_vel": 0.0, "right_arm_rx": 2.49, "right_arm_ry": 0.69, "right_arm_rz": -2.97, "right_gripper": 0.27}, "6": {"left_arm_vel": 0.006, "left_gripper_vel": 0.0, "left_arm_rx": -2.96, "left_arm_ry": 0.83, "left_arm_rz": 1.98, "left_gripper": 0.35, "right_arm_vel": 0.006, "right_gripper_vel": 0.0, "right_arm_rx": 2.5, "right_arm_ry": 0.73, "right_arm_rz": -2.96, "right_gripper": 0.27}, "7": {"left_arm_vel": 0.007, "left_gripper_vel": 0.0, "left_arm_rx": -2.93, "left_arm_ry": 0.8, "left_arm_rz": 1.95, "left_gripper": 0.35, "right_arm_vel": 0.007, "right_gripper_vel": 0.0, "right_arm_rx": 2.5, "right_arm_ry": 0.78, "right_arm_rz": -2.96, "right_gripper": 0.27}, "8": {"left_arm_vel": 0.084, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.75, "left_arm_rz": 1.98, "left_gripper": 0.27, "right_arm_vel": 0.084, "right_gripper_vel": 0.0, "right_arm_rx": 2.52, "right_arm_ry": 0.78, "right_arm_rz": -2.93, "right_gripper": 0.27}, "9": {"left_arm_vel": 0.106, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.75, "left_arm_rz": 1.98, "left_gripper": 0.18, "right_arm_vel": 0.106, "right_gripper_vel": 0.0, "right_arm_rx": 2.53, "right_arm_ry": 0.79, "right_arm_rz": -2.92, "right_gripper": 0.27}, "10": {"left_arm_vel": 0.111, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.74, "left_arm_rz": 1.97, "left_gripper": 0.11, "right_arm_vel": 0.111, "right_gripper_vel": 0.0, "right_arm_rx": 2.55, "right_arm_ry": 0.79, "right_arm_rz": -2.89, "right_gripper": 0.27}, "11": {"left_arm_vel": 0.065, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.74, "left_arm_rz": 1.97, "left_gripper": 0.03, "right_arm_vel": 0.065, "right_gripper_vel": 0.0, "right_arm_rx": 2.65, "right_arm_ry": 0.8, "right_arm_rz": -2.83, "right_gripper": 0.27}, "12": {"left_arm_vel": 0.069, "left_gripper_vel": 0.105, "left_arm_rx": -2.87, "left_arm_ry": 0.74, "left_arm_rz": 1.97, "left_gripper": 0.03, "right_arm_vel": 0.069, "right_gripper_vel": 0.105, "right_arm_rx": 2.71, "right_arm_ry": 0.77, "right_arm_rz": -2.74, "right_gripper": 0.27}, "13": {"left_arm_vel": 0.032, "left_gripper_vel": 0.189, "left_arm_rx": -2.87, "left_arm_ry": 0.74, "left_arm_rz": 1.97, "left_gripper": 0.03, "right_arm_vel": 0.032, "right_gripper_vel": 0.189, "right_arm_rx": 2.71, "right_arm_ry": 0.77, "right_arm_rz": -2.74, "right_gripper": 0.28}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.15129999816417694, -0.11389999836683273, -0.07540000230073929], "delta_rot": [0.2483000010251999, -0.1476999968290329, -0.2953000068664551], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.2038}, "right": {"delta_pos": [-0.12860000133514404, -0.018200000748038292, -0.09260000288486481], "delta_rot": [0.20280000567436218, 0.2824999988079071, 0.02070000022649765], "gripper_changed": false, "flow_direction": "-X(Backward) and -Z(Down)", "magnitude": 0.1595}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.15219999849796295, -0.12129999697208405, -0.07479999959468842], "delta_rot": [0.39320001006126404, -0.1949000060558319, -0.016300000250339508], "gripper_changed": false, "flow_direction": "+X(Forward) and -Y(Right) and -Z(Down)", "magnitude": 0.2085}, "right": {"delta_pos": [-0.19920000433921814, -0.00570000009611249, -0.06650000065565109], "delta_rot": [0.17319999635219574, 0.1559000015258789, 0.06970000267028809], "gripper_changed": false, "flow_direction": "-X(Backward) and -Z(Down)", "magnitude": 0.2101}} + + ========================================= + [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 approach the bag's top opening from opposite sides to establish a bimanual grasp for stabilizing and opening the zipper.", + "actions": [ + { + "reasoning_cot": "The left arm moves forward (+X) and down (-Z) towards the bag. Visual evidence in frames 4-5 shows the gripper hovering directly over the silver mesh panel near the zipper line, preparing to pinch the fabric edge. It has not yet made contact or closed.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "top_opening_left_edge" + }, + "spatial_logic": "moving from free space to top_opening_left_edge", + "topology_change": false + }, + { + "reasoning_cot": "The right arm moves backward (-X) and down (-Z) to align with the right side of the bag's opening. The gripper is positioned near the zipper pull and the right corner of the mesh panel. Like the left arm, it is in the final approach phase before grasping.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "approach", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "top_opening_right_edge" + }, + "spatial_logic": "moving from free space to top_opening_right_edge", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Approaching bag opening with both arms to initiate bimanual stabilization." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_left"}, {"anchor_id": "bag:top_opening", "current_status": "opening"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_opening', 'table:surface_center'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Both arms approach the bag's top opening from opposite sides to establish a bimanual grasp for stabilizing and opening the zipper.", "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": 0.01, "angle": 0.15, "vel_score": 0.17, "angle_score": 2.29, "vel_fft": [0.011, 0.01, 0.007, 0.003, 0.001, 0.003, 0.004, 0.004, 0.004, 0.003, 0.002, 0.002, 0.001, 0.002, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001], "angle_fft": [0.153, 0.13, 0.081, 0.043, 0.044, 0.041, 0.025, 0.015, 0.017, 0.014, 0.008, 0.013, 0.02, 0.017, 0.017, 0.019, 0.018, 0.01, 0.008, 0.01]}, "right": {"vel": 0.07, "angle": 0.3, "vel_score": 0.9, "angle_score": 3.57, "vel_fft": [0.074, 0.033, 0.017, 0.013, 0.005, 0.01, 0.003, 0.007, 0.007, 0.003, 0.004, 0.003, 0.002, 0.003, 0.002, 0.001, 0.002, 0.002, 0.001, 0.001], "angle_fft": [0.305, 0.099, 0.04, 0.053, 0.012, 0.05, 0.015, 0.048, 0.037, 0.006, 0.031, 0.01, 0.016, 0.016, 0.003, 0.019, 0.003, 0.008, 0.011, 0.017]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.74, "left_arm_rz": 1.97, "left_gripper": 0.03, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 0.77, "right_arm_rz": -2.75, "right_gripper": 0.28}, "1": {"left_arm_vel": 0.072, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.74, "left_arm_rz": 1.98, "left_gripper": 0.03, "right_arm_vel": 0.072, "right_gripper_vel": 0.0, "right_arm_rx": 2.77, "right_arm_ry": 0.81, "right_arm_rz": -2.69, "right_gripper": 0.29}, "2": {"left_arm_vel": 0.049, "left_gripper_vel": -1.848, "left_arm_rx": -2.87, "left_arm_ry": 0.74, "left_arm_rz": 1.98, "left_gripper": 0.03, "right_arm_vel": 0.049, "right_gripper_vel": -1.848, "right_arm_rx": 2.85, "right_arm_ry": 0.81, "right_arm_rz": -2.65, "right_gripper": 0.07}, "3": {"left_arm_vel": 0.19, "left_gripper_vel": 0.0, "left_arm_rx": -2.85, "left_arm_ry": 0.73, "left_arm_rz": 2.01, "left_gripper": 0.03, "right_arm_vel": 0.19, "right_gripper_vel": 0.0, "right_arm_rx": 2.84, "right_arm_ry": 0.71, "right_arm_rz": -2.68, "right_gripper": 0.06}, "4": {"left_arm_vel": 0.202, "left_gripper_vel": 0.0, "left_arm_rx": -2.83, "left_arm_ry": 0.73, "left_arm_rz": 2.03, "left_gripper": 0.03, "right_arm_vel": 0.202, "right_gripper_vel": 0.0, "right_arm_rx": 2.83, "right_arm_ry": 0.7, "right_arm_rz": -2.72, "right_gripper": 0.06}, "5": {"left_arm_vel": 0.184, "left_gripper_vel": -0.021, "left_arm_rx": -2.79, "left_arm_ry": 0.72, "left_arm_rz": 2.05, "left_gripper": 0.03, "right_arm_vel": 0.184, "right_gripper_vel": -0.021, "right_arm_rx": 2.81, "right_arm_ry": 0.68, "right_arm_rz": -2.75, "right_gripper": 0.06}, "6": {"left_arm_vel": 0.106, "left_gripper_vel": -0.21, "left_arm_rx": -2.74, "left_arm_ry": 0.69, "left_arm_rz": 2.12, "left_gripper": 0.03, "right_arm_vel": 0.106, "right_gripper_vel": -0.21, "right_arm_rx": 2.74, "right_arm_ry": 0.68, "right_arm_rz": -2.77, "right_gripper": 0.05}, "7": {"left_arm_vel": 0.133, "left_gripper_vel": 0.0, "left_arm_rx": -2.73, "left_arm_ry": 0.69, "left_arm_rz": 2.25, "left_gripper": 0.03, "right_arm_vel": 0.133, "right_gripper_vel": 0.0, "right_arm_rx": 2.68, "right_arm_ry": 0.65, "right_arm_rz": -2.69, "right_gripper": 0.01}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.0008999999845400453, -0.007499999832361937, 0.000699999975040555], "delta_rot": [0.14419999718666077, -0.04699999839067459, 0.27799999713897705], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0075}, "right": {"delta_pos": [-0.07079999893903732, 0.011900000274181366, 0.026499999687075615], "delta_rot": [-0.027300000190734863, -0.12610000371932983, 0.05460000038146973], "gripper_changed": false, "flow_direction": "-X(Backward) and +Z(Up)", "magnitude": 0.0765}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [0.00279999990016222, -0.02590000070631504, -9.999999747378752e-05], "delta_rot": [0.24609999358654022, -0.09529999643564224, 0.6233999729156494], "gripper_changed": false, "flow_direction": "-Y(Right)", "magnitude": 0.0261}, "right": {"delta_pos": [-0.06350000202655792, 0.11640000343322754, 0.028599999845027924], "delta_rot": [-0.06589999794960022, -0.13930000364780426, -0.0934000015258789], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.1357}} + + ========================================= + [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": "Bimanual approach to the bag's top opening; Right arm targets the zipper pull ring for grasping, while Left arm stabilizes the bag body near the mesh panel.", + "actions": [ + { + "reasoning_cot": "The left arm moves from a hovering position to make contact with the side of the bag (mesh panel area) to stabilize it. The gripper remains open but transitions to a 'touching' state to prepare for holding the object steady while the right arm operates the zipper.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "approach", + "semantic_action": "stabilize_bag_body", + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "Moving from free space to contact with the left side of the bag opening.", + "topology_change": false + }, + { + "reasoning_cot": "The right arm executes a precise approach towards the metal ring of the zipper pull. Visual evidence in later frames shows the gripper jaws aligning with and enclosing the ring, indicating an intent to grasp and pull the zipper.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "touching" + }, + "action_verb": "grasp", + "semantic_action": "target_zipper_pull", + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "Approaching the zipper pull ring from the right side to establish a secure grip.", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:zipper_pull", + "current_status": "targeted_for_grasp" + }, + { + "anchor_id": "bag:main_body", + "current_status": "being_stabilized" + } + ], + "task_progress": "Initiating bimanual coordination to open the bag; right hand securing zipper, left hand stabilizing base." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "being_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_for_grasp"}, {"anchor_id": "bag:top_opening", "current_status": "opening"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_opening', 'table:surface_center'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Bimanual approach to the bag's top opening; Right arm targets the zipper pull ring for grasping, while Left arm stabilizes the bag body near the mesh 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": 0.02, "angle": 0.3, "vel_score": 0.22, "angle_score": 2.56, "vel_fft": [0.023, 0.011, 0.008, 0.008, 0.003, 0.001, 0.001, 0.001, 0.0, 0.002, 0.002, 0.002, 0.002, 0.002, 0.002, 0.0, 0.001, 0.0, 0.0, 0.001], "angle_fft": [0.298, 0.082, 0.093, 0.035, 0.009, 0.015, 0.015, 0.013, 0.01, 0.026, 0.015, 0.02, 0.03, 0.017, 0.008, 0.008, 0.024, 0.006, 0.017, 0.023]}, "right": {"vel": 0.09, "angle": 0.34, "vel_score": 0.84, "angle_score": 2.98, "vel_fft": [0.091, 0.048, 0.006, 0.012, 0.005, 0.004, 0.004, 0.002, 0.004, 0.002, 0.002, 0.002, 0.003, 0.003, 0.004, 0.002, 0.003, 0.003, 0.005, 0.002], "angle_fft": [0.338, 0.073, 0.108, 0.108, 0.027, 0.014, 0.036, 0.015, 0.034, 0.019, 0.014, 0.005, 0.016, 0.005, 0.005, 0.014, 0.019, 0.011, 0.012, 0.01]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.72, "left_arm_ry": 0.69, "left_arm_rz": 2.27, "left_gripper": 0.03, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.65, "right_arm_rz": -2.69, "right_gripper": 0.01}, "1": {"left_arm_vel": 0.191, "left_gripper_vel": 0.0, "left_arm_rx": -2.71, "left_arm_ry": 0.68, "left_arm_rz": 2.29, "left_gripper": 0.03, "right_arm_vel": 0.191, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.65, "right_arm_rz": -2.67, "right_gripper": 0.01}, "2": {"left_arm_vel": 0.202, "left_gripper_vel": 0.0, "left_arm_rx": -2.72, "left_arm_ry": 0.68, "left_arm_rz": 2.29, "left_gripper": 0.03, "right_arm_vel": 0.202, "right_gripper_vel": 0.0, "right_arm_rx": 2.67, "right_arm_ry": 0.66, "right_arm_rz": -2.65, "right_gripper": 0.01}, "3": {"left_arm_vel": 0.188, "left_gripper_vel": 0.0, "left_arm_rx": -2.72, "left_arm_ry": 0.68, "left_arm_rz": 2.29, "left_gripper": 0.03, "right_arm_vel": 0.188, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 0.68, "right_arm_rz": -2.65, "right_gripper": 0.01}, "4": {"left_arm_vel": 0.181, "left_gripper_vel": 0.0, "left_arm_rx": -2.73, "left_arm_ry": 0.68, "left_arm_rz": 2.29, "left_gripper": 0.03, "right_arm_vel": 0.181, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.69, "right_arm_rz": -2.64, "right_gripper": 0.01}, "5": {"left_arm_vel": 0.143, "left_gripper_vel": 0.0, "left_arm_rx": -2.74, "left_arm_ry": 0.68, "left_arm_rz": 2.28, "left_gripper": 0.03, "right_arm_vel": 0.143, "right_gripper_vel": 0.0, "right_arm_rx": 2.75, "right_arm_ry": 0.7, "right_arm_rz": -2.62, "right_gripper": 0.01}, "6": {"left_arm_vel": 0.152, "left_gripper_vel": 0.0, "left_arm_rx": -2.73, "left_arm_ry": 0.68, "left_arm_rz": 2.3, "left_gripper": 0.03, "right_arm_vel": 0.152, "right_gripper_vel": 0.0, "right_arm_rx": 2.75, "right_arm_ry": 0.71, "right_arm_rz": -2.62, "right_gripper": 0.01}, "7": {"left_arm_vel": 0.131, "left_gripper_vel": 0.0, "left_arm_rx": -2.72, "left_arm_ry": 0.67, "left_arm_rz": 2.34, "left_gripper": 0.03, "right_arm_vel": 0.131, "right_gripper_vel": 0.0, "right_arm_rx": 2.73, "right_arm_ry": 0.73, "right_arm_rz": -2.64, "right_gripper": 0.01}, "8": {"left_arm_vel": 0.11, "left_gripper_vel": 0.0, "left_arm_rx": -2.72, "left_arm_ry": 0.67, "left_arm_rz": 2.36, "left_gripper": 0.03, "right_arm_vel": 0.11, "right_gripper_vel": 0.0, "right_arm_rx": 2.72, "right_arm_ry": 0.73, "right_arm_rz": -2.65, "right_gripper": 0.01}, "9": {"left_arm_vel": 0.011, "left_gripper_vel": 0.0, "left_arm_rx": -2.71, "left_arm_ry": 0.67, "left_arm_rz": 2.4, "left_gripper": 0.03, "right_arm_vel": 0.011, "right_gripper_vel": 0.0, "right_arm_rx": 2.7, "right_arm_ry": 0.74, "right_arm_rz": -2.65, "right_gripper": 0.01}, "10": {"left_arm_vel": 0.014, "left_gripper_vel": 0.0, "left_arm_rx": -2.68, "left_arm_ry": 0.66, "left_arm_rz": 2.46, "left_gripper": 0.03, "right_arm_vel": 0.014, "right_gripper_vel": 0.0, "right_arm_rx": 2.66, "right_arm_ry": 0.72, "right_arm_rz": -2.72, "right_gripper": 0.01}, "11": {"left_arm_vel": 0.021, "left_gripper_vel": 0.0, "left_arm_rx": -2.67, "left_arm_ry": 0.66, "left_arm_rz": 2.5, "left_gripper": 0.03, "right_arm_vel": 0.021, "right_gripper_vel": 0.0, "right_arm_rx": 2.65, "right_arm_ry": 0.69, "right_arm_rz": -2.76, "right_gripper": 0.01}, "12": {"left_arm_vel": 0.023, "left_gripper_vel": 0.0, "left_arm_rx": -2.65, "left_arm_ry": 0.65, "left_arm_rz": 2.55, "left_gripper": 0.03, "right_arm_vel": 0.023, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.66, "right_arm_rz": -2.8, "right_gripper": 0.01}, "13": {"left_arm_vel": 0.025, "left_gripper_vel": 0.0, "left_arm_rx": -2.63, "left_arm_ry": 0.65, "left_arm_rz": 2.6, "left_gripper": 0.03, "right_arm_vel": 0.025, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.63, "right_arm_rz": -2.84, "right_gripper": 0.01}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [0.00139999995008111, -0.018400000408291817, -0.0007999999797903001], "delta_rot": [0.0949999988079071, -0.04560000076889992, 0.325300008058548], "gripper_changed": false, "flow_direction": "Hovering/Minimal movement", "magnitude": 0.0185}, "right": {"delta_pos": [0.009200000204145908, 0.10029999911785126, 0.0020000000949949026], "delta_rot": [-0.03189999982714653, -0.013000000268220901, -0.15440000593662262], "gripper_changed": false, "flow_direction": "+Y(Left)", "magnitude": 0.1008}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.2685000002384186, 0.1745000034570694, 0.14319999516010284], "delta_rot": [-0.15070000290870667, 0.2379000037908554, 0.4661000072956085], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.3508}, "right": {"delta_pos": [-0.18060000240802765, -0.07530000060796738, 0.11479999870061874], "delta_rot": [0.3537999987602234, -0.15449999272823334, 0.07349999994039536], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.2268}} + + ========================================= + [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": "Bimanual stabilization and manipulation of the bag's zipper mechanism; Left arm holds the bag body to prevent rotation while Right arm pulls the zipper tab to open the compartment.", + "actions": [ + { + "reasoning_cot": "The left arm is visually confirmed holding the silver mesh panel of the bag (T0-T1). Kinematic data shows low velocity (0.02 m/s) and stable gripper width (0.03), indicating a static hold to counteract forces from the right arm. It maintains contact with 'bag:main_body' to stabilize the object during the unzipping action.", + "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:main_body" + }, + "spatial_logic": "static_at_mesh_panel", + "topology_change": false + }, + { + "reasoning_cot": "The right arm is engaged with the metal zipper pull ring. Visual sequence shows the gripper closing on the ring and then translating along the zipper track (pulling). This action changes the state of the bag opening from closed to partially open. The movement aligns with the 'pull' primitive required for unzipping.", + "causal_trace": { + "gripper_signal": "stable", + "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_along_zipper_track", + "topology_change": true + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:top_opening", + "current_status": "opening" + } + ], + "task_progress": "Executing bimanual unzip; Left stabilizes bag body, Right pulls zipper tab to expose interior." + } +} +```` +--- +## 🎬 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": "bag:main_body", "current_status": "being_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_for_grasp"}, {"anchor_id": "bag:top_opening", "current_status": "opening"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_opening', 'table:surface_center'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Bimanual stabilization and manipulation of the bag's zipper mechanism; Left arm holds the bag body to prevent rotation while Right arm pulls the zipper tab to open the compartment.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}, "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": 0.3, "angle": 0.56, "vel_score": 2.85, "angle_score": 4.84, "vel_fft": [0.295, 0.19, 0.09, 0.048, 0.037, 0.026, 0.022, 0.02, 0.013, 0.012, 0.018, 0.025, 0.028, 0.014, 0.01, 0.015, 0.011, 0.008, 0.017, 0.016], "angle_fft": [0.557, 0.212, 0.099, 0.019, 0.061, 0.004, 0.01, 0.056, 0.032, 0.017, 0.044, 0.047, 0.086, 0.045, 0.038, 0.027, 0.015, 0.009, 0.037, 0.038]}, "right": {"vel": 0.25, "angle": 0.75, "vel_score": 2.22, "angle_score": 6.35, "vel_fft": [0.252, 0.086, 0.01, 0.029, 0.033, 0.021, 0.016, 0.008, 0.004, 0.008, 0.011, 0.003, 0.012, 0.01, 0.006, 0.006, 0.006, 0.006, 0.002, 0.002], "angle_fft": [0.753, 0.087, 0.129, 0.128, 0.103, 0.048, 0.1, 0.037, 0.045, 0.037, 0.048, 0.025, 0.024, 0.025, 0.013, 0.039, 0.007, 0.02, 0.022, 0.018]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.62, "left_arm_ry": 0.64, "left_arm_rz": 2.62, "left_gripper": 0.03, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 2.64, "right_arm_ry": 0.63, "right_arm_rz": -2.84, "right_gripper": 0.01}, "1": {"left_arm_vel": 0.036, "left_gripper_vel": 0.021, "left_arm_rx": -2.54, "left_arm_ry": 0.64, "left_arm_rz": 2.73, "left_gripper": 0.03, "right_arm_vel": 0.036, "right_gripper_vel": 0.021, "right_arm_rx": 2.69, "right_arm_ry": 0.69, "right_arm_rz": -2.75, "right_gripper": 0.01}, "2": {"left_arm_vel": 0.144, "left_gripper_vel": 2.079, "left_arm_rx": -2.54, "left_arm_ry": 0.64, "left_arm_rz": 2.75, "left_gripper": 0.07, "right_arm_vel": 0.144, "right_gripper_vel": 2.079, "right_arm_rx": 2.67, "right_arm_ry": 0.6, "right_arm_rz": -2.71, "right_gripper": 0.17}, "3": {"left_arm_vel": 0.183, "left_gripper_vel": 2.289, "left_arm_rx": -2.53, "left_arm_ry": 0.65, "left_arm_rz": 2.77, "left_gripper": 0.11, "right_arm_vel": 0.183, "right_gripper_vel": 2.289, "right_arm_rx": 2.65, "right_arm_ry": 0.56, "right_arm_rz": -2.69, "right_gripper": 0.24}, "4": {"left_arm_vel": 0.182, "left_gripper_vel": 1.596, "left_arm_rx": -2.53, "left_arm_ry": 0.65, "left_arm_rz": 2.78, "left_gripper": 0.16, "right_arm_vel": 0.182, "right_gripper_vel": 1.596, "right_arm_rx": 2.66, "right_arm_ry": 0.53, "right_arm_rz": -2.67, "right_gripper": 0.3}, "5": {"left_arm_vel": 0.204, "left_gripper_vel": 1.218, "left_arm_rx": -2.52, "left_arm_ry": 0.64, "left_arm_rz": 2.79, "left_gripper": 0.21, "right_arm_vel": 0.204, "right_gripper_vel": 1.218, "right_arm_rx": 2.68, "right_arm_ry": 0.49, "right_arm_rz": -2.67, "right_gripper": 0.34}, "6": {"left_arm_vel": 0.255, "left_gripper_vel": 0.693, "left_arm_rx": -2.52, "left_arm_ry": 0.63, "left_arm_rz": 2.79, "left_gripper": 0.26, "right_arm_vel": 0.255, "right_gripper_vel": 0.693, "right_arm_rx": 2.71, "right_arm_ry": 0.46, "right_arm_rz": -2.67, "right_gripper": 0.36}, "7": {"left_arm_vel": 0.31, "left_gripper_vel": 0.336, "left_arm_rx": -2.52, "left_arm_ry": 0.62, "left_arm_rz": 2.79, "left_gripper": 0.28, "right_arm_vel": 0.31, "right_gripper_vel": 0.336, "right_arm_rx": 2.76, "right_arm_ry": 0.44, "right_arm_rz": -2.67, "right_gripper": 0.37}, "8": {"left_arm_vel": 0.364, "left_gripper_vel": 0.042, "left_arm_rx": -2.52, "left_arm_ry": 0.6, "left_arm_rz": 2.79, "left_gripper": 0.27, "right_arm_vel": 0.364, "right_gripper_vel": 0.042, "right_arm_rx": 2.85, "right_arm_ry": 0.43, "right_arm_rz": -2.7, "right_gripper": 0.39}, "9": {"left_arm_vel": 0.404, "left_gripper_vel": 0.0, "left_arm_rx": -2.58, "left_arm_ry": 0.61, "left_arm_rz": 2.75, "left_gripper": 0.25, "right_arm_vel": 0.404, "right_gripper_vel": 0.0, "right_arm_rx": 2.81, "right_arm_ry": 0.48, "right_arm_rz": -2.76, "right_gripper": 0.39}, "10": {"left_arm_vel": 0.344, "left_gripper_vel": 0.0, "left_arm_rx": -2.66, "left_arm_ry": 0.67, "left_arm_rz": 2.74, "left_gripper": 0.25, "right_arm_vel": 0.344, "right_gripper_vel": 0.0, "right_arm_rx": 2.83, "right_arm_ry": 0.44, "right_arm_rz": -2.73, "right_gripper": 0.39}, "11": {"left_arm_vel": 0.427, "left_gripper_vel": 0.0, "left_arm_rx": -2.72, "left_arm_ry": 0.76, "left_arm_rz": 2.75, "left_gripper": 0.25, "right_arm_vel": 0.427, "right_gripper_vel": 0.0, "right_arm_rx": 2.91, "right_arm_ry": 0.43, "right_arm_rz": -2.68, "right_gripper": 0.39}, "12": {"left_arm_vel": 0.422, "left_gripper_vel": 0.0, "left_arm_rx": -2.79, "left_arm_ry": 0.87, "left_arm_rz": 2.72, "left_gripper": 0.25, "right_arm_vel": 0.422, "right_gripper_vel": 0.0, "right_arm_rx": 2.98, "right_arm_ry": 0.44, "right_arm_rz": -2.64, "right_gripper": 0.39}, "13": {"left_arm_vel": 0.357, "left_gripper_vel": 0.0, "left_arm_rx": -2.87, "left_arm_ry": 0.93, "left_arm_rz": 2.74, "left_gripper": 0.25, "right_arm_vel": 0.357, "right_gripper_vel": 0.0, "right_arm_rx": 3.02, "right_arm_ry": 0.49, "right_arm_rz": -2.61, "right_gripper": 0.39}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.27059999108314514, 0.19300000369548798, 0.1437000036239624], "delta_rot": [-0.25429999828338623, 0.2842000126838684, 0.11879999935626984], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.3621}, "right": {"delta_pos": [-0.18970000743865967, -0.17489999532699585, 0.11230000108480453], "delta_rot": [0.38040000200271606, -0.13729999959468842, 0.23149999976158142], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.2814}} + + [FUTURE HINDSIGHT HINT]: + {"left": {"delta_pos": [-0.43700000643730164, 0.287200003862381, 0.06369999796152115], "delta_rot": [-0.46799999475479126, 0.5002999901771545, 0.49390000104904175], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and +Z(Up)", "magnitude": 0.5268}, "right": {"delta_pos": [-0.2766000032424927, -0.2460000067949295, 0.10970000177621841], "delta_rot": [0.4763000011444092, 0.49070000648498535, -0.2134999930858612], "gripper_changed": true, "flow_direction": "-X(Backward) and -Y(Right) and +Z(Up)", "magnitude": 0.3861}} + + ========================================= + [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": "Bimanual stabilization and manipulation of the bag's zipper mechanism; Left arm holds the bag body to prevent rotation while Right arm pulls the zipper tab to open the compartment.", + "actions": [ + { + "reasoning_cot": "The left arm is positioned over the main body of the bag, maintaining a static hold to stabilize the object against the pulling force of the right arm. Visual evidence shows the gripper is closed around the fabric near the reflective patch.", + "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:main_body" + }, + "spatial_logic": "static_at_main_body", + "topology_change": false + }, + { + "reasoning_cot": "The right arm is actively engaging with the zipper pull tab. The kinematic data indicates a backward (-X) and upward (+Z) trajectory consistent with unzipping. The gripper is closed on the metal tab, applying tension to slide the zipper open.", + "causal_trace": { + "gripper_signal": "stable", + "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_zipper_start_to_open_position", + "topology_change": true + } + ], + "semantic_delta": { + "anchor_updates": [ + { + "anchor_id": "bag:top_opening", + "current_status": "opening" + } + ], + "task_progress": "Executing bimanual unzip operation; left stabilizes base, right actuates zipper." + } +} +```` +--- +## 🎬 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) + +### 🧠 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": "bag:main_body", "current_status": "being_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_for_grasp"}, {"anchor_id": "bag:top_opening", "current_status": "opening"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}] + 🎯 KNOWN ANCHOR CANDIDATES: ['bag:main_body', 'bag:zipper_pull', 'bag:top_opening', 'table:surface_center'] + + 2. SHORT-TERM MEMORY (CRITICAL: What you were doing 1 second ago): + {"last_chunk_intent": "Bimanual stabilization and manipulation of the bag's zipper mechanism; Left arm holds the bag body to prevent rotation while Right arm pulls the zipper tab to open the compartment.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}, "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": 0.09, "angle": 0.32, "vel_score": 1.53, "angle_score": 4.51, "vel_fft": [0.09, 0.082, 0.072, 0.057, 0.044, 0.035, 0.025, 0.018, 0.013, 0.015, 0.018, 0.019, 0.015, 0.011, 0.009, 0.011, 0.012, 0.012, 0.012, 0.012], "angle_fft": [0.321, 0.099, 0.2, 0.124, 0.122, 0.132, 0.041, 0.083, 0.023, 0.02, 0.003, 0.022, 0.022, 0.018, 0.021, 0.033, 0.029, 0.034, 0.026, 0.029]}, "right": {"vel": 0.05, "angle": 0.43, "vel_score": 0.73, "angle_score": 6.06, "vel_fft": [0.049, 0.032, 0.034, 0.019, 0.018, 0.01, 0.011, 0.004, 0.01, 0.006, 0.008, 0.003, 0.005, 0.006, 0.005, 0.004, 0.002, 0.005, 0.005, 0.005], "angle_fft": [0.43, 0.151, 0.237, 0.201, 0.087, 0.096, 0.029, 0.056, 0.014, 0.007, 0.019, 0.006, 0.022, 0.008, 0.01, 0.007, 0.008, 0.006, 0.009, 0.015]}, "frame_angles": {"0": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -2.88, "left_arm_ry": 0.93, "left_arm_rz": 2.77, "left_gripper": 0.25, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.04, "right_arm_ry": 0.5, "right_arm_rz": -2.61, "right_gripper": 0.39}, "1": {"left_arm_vel": 0.242, "left_gripper_vel": 0.0, "left_arm_rx": -3.02, "left_arm_ry": 0.99, "left_arm_rz": 2.79, "left_gripper": 0.25, "right_arm_vel": 0.242, "right_gripper_vel": 0.0, "right_arm_rx": 3.05, "right_arm_ry": 0.61, "right_arm_rz": -2.62, "right_gripper": 0.39}, "2": {"left_arm_vel": 0.201, "left_gripper_vel": 0.0, "left_arm_rx": -3.12, "left_arm_ry": 1.06, "left_arm_rz": 2.77, "left_gripper": 0.25, "right_arm_vel": 0.201, "right_gripper_vel": 0.0, "right_arm_rx": 3.07, "right_arm_ry": 0.78, "right_arm_rz": -2.62, "right_gripper": 0.39}, "3": {"left_arm_vel": 0.02, "left_gripper_vel": -0.021, "left_arm_rx": -3.11, "left_arm_ry": 1.12, "left_arm_rz": 2.79, "left_gripper": 0.25, "right_arm_vel": 0.02, "right_gripper_vel": -0.021, "right_arm_rx": 3.13, "right_arm_ry": 0.98, "right_arm_rz": -2.6, "right_gripper": 0.39}, "4": {"left_arm_vel": 0.048, "left_gripper_vel": 0.0, "left_arm_rx": -3.1, "left_arm_ry": 1.12, "left_arm_rz": 2.79, "left_gripper": 0.24, "right_arm_vel": 0.048, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.01, "right_arm_rz": -2.6, "right_gripper": 0.39}, "5": {"left_arm_vel": 0.013, "left_gripper_vel": 0.0, "left_arm_rx": -3.1, "left_arm_ry": 1.13, "left_arm_rz": 2.79, "left_gripper": 0.24, "right_arm_vel": 0.013, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.02, "right_arm_rz": -2.6, "right_gripper": 0.39}, "6": {"left_arm_vel": 0.057, "left_gripper_vel": 0.0, "left_arm_rx": -3.08, "left_arm_ry": 1.14, "left_arm_rz": 3.04, "left_gripper": 0.24, "right_arm_vel": 0.057, "right_gripper_vel": 0.0, "right_arm_rx": 3.13, "right_arm_ry": 1.06, "right_arm_rz": -2.91, "right_gripper": 0.39}, "7": {"left_arm_vel": 0.0, "left_gripper_vel": 0.0, "left_arm_rx": -3.09, "left_arm_ry": 1.14, "left_arm_rz": 3.11, "left_gripper": 0.24, "right_arm_vel": 0.0, "right_gripper_vel": 0.0, "right_arm_rx": 3.12, "right_arm_ry": 1.12, "right_arm_rz": -3.06, "right_gripper": 0.39}}} + + [CURRENT CHUNK ACTUAL FLOW]: + {"left": {"delta_pos": [-0.1446000039577484, 0.08169999718666077, -0.07519999891519547], "delta_rot": [-0.20309999585151672, 0.2134999930858612, 0.3474000096321106], "gripper_changed": false, "flow_direction": "-X(Backward) and +Y(Left) and -Z(Down)", "magnitude": 0.1823}, "right": {"delta_pos": [-0.0794999971985817, -0.06449999660253525, -0.00139999995008111], "delta_rot": [0.08179999887943268, 0.6176999807357788, -0.448199987411499], "gripper_changed": false, "flow_direction": "-X(Backward) and -Y(Right)", "magnitude": 0.1024}} + + [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": "Bimanual retreat and stabilization following the completion of a manipulation sequence; arms move away from the bag to reset position while maintaining visual lock on the object.", + "actions": [ + { + "reasoning_cot": "The left arm executes a backward trajectory (-X) combined with a slight lateral shift, moving away from the 'bag:main_body' it was previously stabilizing. The gripper remains open (stable), indicating a non-contact retreat phase rather than a release or grasp. Visual evidence confirms the end-effector is clearing the immediate vicinity of the bag's top opening.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "retreat", + "semantic_action": null, + "subject": "left_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:main_body" + }, + "spatial_logic": "moving away from bag:main_body towards neutral workspace", + "topology_change": false + }, + { + "reasoning_cot": "The right arm mirrors the retreat behavior, moving backward and slightly rightward (-Y) away from the 'bag:zipper_pull' area. Kinematic data shows low velocity consistent with a controlled withdrawal. No grasping action is detected; the arm is simply repositioning to a safe distance after completing its part of the bimanual task.", + "causal_trace": { + "gripper_signal": "stable", + "visual_contact": "none" + }, + "action_verb": "retreat", + "semantic_action": null, + "subject": "right_arm", + "interaction_target": { + "parent_object": "bag", + "anchor_id": "bag:zipper_pull" + }, + "spatial_logic": "moving away from bag:zipper_pull towards neutral workspace", + "topology_change": false + } + ], + "semantic_delta": { + "anchor_updates": [], + "task_progress": "Completed bimanual manipulation of bag zipper; currently in post-action retreat phase." + } +} +```` +--- +## 🎬 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_0035 + - **Total Frames**: 642 + - **Global Task Goal**: "Unknown Task" + + ### 1. INPUT DATA + - **KPM (Micro-Actions Timeline)**: [{"chunk_idx": 0, "start_frame": 0, "end_frame": 66, "chunk_intent": "Right arm approaches and makes contact with the top surface of the bag to stabilize or prepare for manipulation, while left arm remains idle.", "micro_actions": [{"verb": "touch", "semantic_verb": null, "subject": "right_arm", "target": "top_surface", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Moving from free space to contact with bag:top_surface"}, {"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "Static hover position maintained"}]}, {"chunk_idx": 1, "start_frame": 67, "end_frame": 133, "chunk_intent": "Right arm approaches the bag's top opening and stabilizes the zipper area, while left arm remains idle.", "micro_actions": [{"verb": "approach", "semantic_verb": null, "subject": "right_arm", "target": "top_opening", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "moving from free space to bag:top_opening"}, {"verb": "idle", "semantic_verb": null, "subject": "left_arm", "target": "none", "object": "none", "topology": false, "contact": "none", "spatial_logic": "static_at_idle_position"}]}, {"chunk_idx": 2, "start_frame": 134, "end_frame": 200, "chunk_intent": "Left arm approaches and establishes contact with the bag's zipper pull to stabilize it, while the right arm maintains a static hold on the bag body near the zipper track.", "micro_actions": [{"verb": "grasp", "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": "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": 3, "start_frame": 201, "end_frame": 218, "chunk_intent": "Left arm approaches and establishes contact with the bag's zipper pull to stabilize it, while the right arm maintains a static hold on the bag body near the zipper track.", "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": "secured", "spatial_logic": "static_at_bag:main_body"}]}, {"chunk_idx": 4, "start_frame": 219, "end_frame": 276, "chunk_intent": "Left arm approaches and establishes contact with the bag's zipper pull to stabilize it, while the right arm maintains a static hold on the bag body near the zipper track.", "micro_actions": [{"verb": "grasp", "semantic_verb": null, "subject": "left_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "Approaching and grasping the zipper pull anchor"}, {"verb": "hold", "semantic_verb": null, "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "Static hold at bag main body"}]}, {"chunk_idx": 5, "start_frame": 277, "end_frame": 316, "chunk_intent": "Left arm pulls the zipper pull to open the bag, while the right arm stabilizes the bag body near the zipper track.", "micro_actions": [{"verb": "pull", "semantic_verb": "unzip_bag", "subject": "left_arm", "target": "bag:zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "Moving from initial grasp position along the zipper track trajectory to extend the opening."}, {"verb": "hold", "semantic_verb": "stabilize_bag", "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "Static stabilization at the bag corner to provide reaction force for the unzipping action."}]}, {"chunk_idx": 6, "start_frame": 317, "end_frame": 363, "chunk_intent": "Left arm pulls the bag's zipper pull to open the top flap, while the right arm stabilizes the bag body near the corner.", "micro_actions": [{"verb": "pull", "semantic_verb": "unzipping", "subject": "left_arm", "target": "bag:zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "moving from static grasp to linear pull along zipper track"}, {"verb": "hold", "semantic_verb": "stabilizing", "subject": "right_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "static_at_corner_providing_counter_force"}]}, {"chunk_idx": 7, "start_frame": 364, "end_frame": 417, "chunk_intent": "Both arms approach the bag's top opening from opposite sides to establish a bimanual grasp for stabilizing and opening the zipper.", "micro_actions": [{"verb": "approach", "semantic_verb": null, "subject": "left_arm", "target": "top_opening_left_edge", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "moving from free space to top_opening_left_edge"}, {"verb": "approach", "semantic_verb": null, "subject": "right_arm", "target": "top_opening_right_edge", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "moving from free space to top_opening_right_edge"}]}, {"chunk_idx": 8, "start_frame": 418, "end_frame": 486, "chunk_intent": "Bimanual approach to the bag's top opening; Right arm targets the zipper pull ring for grasping, while Left arm stabilizes the bag body near the mesh panel.", "micro_actions": [{"verb": "approach", "semantic_verb": "stabilize_bag_body", "subject": "left_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Moving from free space to contact with the left side of the bag opening."}, {"verb": "grasp", "semantic_verb": "target_zipper_pull", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "touching", "spatial_logic": "Approaching the zipper pull ring from the right side to establish a secure grip."}]}, {"chunk_idx": 9, "start_frame": 487, "end_frame": 527, "chunk_intent": "Bimanual stabilization and manipulation of the bag's zipper mechanism; Left arm holds the bag body to prevent rotation while Right arm pulls the zipper tab to open the compartment.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_mesh_panel"}, {"verb": "pull", "semantic_verb": "unzip", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "moving_along_zipper_track"}]}, {"chunk_idx": 10, "start_frame": 528, "end_frame": 569, "chunk_intent": "Bimanual stabilization and manipulation of the bag's zipper mechanism; Left arm holds the bag body to prevent rotation while Right arm pulls the zipper tab to open the compartment.", "micro_actions": [{"verb": "hold", "semantic_verb": null, "subject": "left_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "secured", "spatial_logic": "static_at_main_body"}, {"verb": "pull", "semantic_verb": "unzip", "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": true, "contact": "secured", "spatial_logic": "moving_from_zipper_start_to_open_position"}]}, {"chunk_idx": 11, "start_frame": 570, "end_frame": 641, "chunk_intent": "Bimanual retreat and stabilization following the completion of a manipulation sequence; arms move away from the bag to reset position while maintaining visual lock on the object.", "micro_actions": [{"verb": "retreat", "semantic_verb": null, "subject": "left_arm", "target": "bag:main_body", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "moving away from bag:main_body towards neutral workspace"}, {"verb": "retreat", "semantic_verb": null, "subject": "right_arm", "target": "bag:zipper_pull", "object": "bag", "topology": false, "contact": "none", "spatial_logic": "moving away from bag:zipper_pull towards neutral workspace"}]}] + - **WSM (State Memory)**: [{"chunk_idx": 0, "global_frame_range": [0, 66], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_opening", "current_status": "closed"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Right arm approaches and makes contact with the top surface of the bag to stabilize or prepare for 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": [67, 133], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_opening", "current_status": "closed"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Right arm approaches the bag's top opening and stabilizes the zipper area, 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": [134, 200], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_left"}, {"anchor_id": "bag:top_opening", "current_status": "closed"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and establishes contact with the bag's zipper pull to stabilize it, while the right arm maintains a static hold on the bag body near the zipper track.", "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": 3, "global_frame_range": [201, 218], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_left"}, {"anchor_id": "bag:top_opening", "current_status": "closed"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and establishes contact with the bag's zipper pull to stabilize it, while the right arm maintains a static hold on the bag body near the zipper track.", "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": 4, "global_frame_range": [219, 276], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_left"}, {"anchor_id": "bag:top_opening", "current_status": "closed"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Left arm approaches and establishes contact with the bag's zipper pull to stabilize it, while the right arm maintains a static hold on the bag body near the zipper track.", "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": [277, 316], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_left"}, {"anchor_id": "bag:top_opening", "current_status": "opening"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Left arm pulls the zipper pull to open the bag, while the right arm stabilizes the bag body near the zipper track.", "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": [317, 363], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_left"}, {"anchor_id": "bag:top_opening", "current_status": "opening"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Left arm pulls the bag's zipper pull to open the top flap, while the right arm stabilizes the bag body near the corner.", "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": 7, "global_frame_range": [364, 417], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "grasped_by_left"}, {"anchor_id": "bag:top_opening", "current_status": "opening"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Both arms approach the bag's top opening from opposite sides to establish a bimanual grasp for stabilizing and opening the zipper.", "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": 8, "global_frame_range": [418, 486], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "being_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_for_grasp"}, {"anchor_id": "bag:top_opening", "current_status": "opening"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Bimanual approach to the bag's top opening; Right arm targets the zipper pull ring for grasping, while Left arm stabilizes the bag body near the mesh 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": 9, "global_frame_range": [487, 527], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "being_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_for_grasp"}, {"anchor_id": "bag:top_opening", "current_status": "opening"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Bimanual stabilization and manipulation of the bag's zipper mechanism; Left arm holds the bag body to prevent rotation while Right arm pulls the zipper tab to open the compartment.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 10, "global_frame_range": [528, 569], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "being_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_for_grasp"}, {"anchor_id": "bag:top_opening", "current_status": "opening"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Bimanual stabilization and manipulation of the bag's zipper mechanism; Left arm holds the bag body to prevent rotation while Right arm pulls the zipper tab to open the compartment.", "left_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}, "right_end_effector": {"grasp_status": "holding", "contact_target": "bag:bag:main_body"}}, "cognitive_objects_state": {}}}, {"chunk_idx": 11, "global_frame_range": [570, 641], "world_state": {"spatial_atlas": [{"anchor_id": "bag:main_body", "current_status": "being_stabilized"}, {"anchor_id": "bag:zipper_pull", "current_status": "targeted_for_grasp"}, {"anchor_id": "bag:top_opening", "current_status": "opening"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}], "short_term_memory": {"last_chunk_intent": "Bimanual retreat and stabilization following the completion of a manipulation sequence; arms move away from the bag to reset position while maintaining visual lock on the object.", "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": "bag:main_body", "current_status": "exposed"}, {"anchor_id": "bag:zipper_pull", "current_status": "accessible"}, {"anchor_id": "bag:top_opening", "current_status": "closed"}, {"anchor_id": "table:surface_center", "current_status": "occupied_by_bag"}] + + 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_0035", + "merge_thought": "The timeline is divided into four logical macro-chapters based on the shift in manipulation strategy and arm roles. \n\n1. **Segment 0 (Chunks 0-4): Initial Stabilization & Grasp Acquisition.** The robot transitions from idle/approach to establishing a stable bimanual hold. Chunks 0-1 involve the right arm approaching and touching the bag. Chunks 2-4 involve the left arm grasping the zipper pull while the right arm holds the body. These are merged because they represent the continuous 'setup' phase where the robot secures the object before any topological change (opening) occurs.\n\n2. **Segment 1 (Chunks 5-6): Primary Unzipping Action (Left Arm).** A clear state transition occurs at Chunk 5 where the `bag:top_opening` status changes from 'closed' to 'opening'. The left arm actively pulls the zipper while the right arm stabilizes. This is a distinct semantic goal (unzipping) compared to the previous stabilization phase.\n\n3. **Segment 2 (Chunks 7-10): Bimanual Re-grasp & Secondary Unzipping.** At Chunk 7, there is a major strategic shift: both arms retreat slightly and re-approach the opening from opposite sides. The role reversal happens here: the left arm moves to stabilize the body, and the right arm takes over the zipper pull. Chunks 8-10 execute this second phase of unzipping/opening with the new grip configuration. This is separated from Segment 1 due to the 'Target Object Shift' in terms of which arm performs the primary action and the intermediate re-approach phase.\n\n4. **Segment 3 (Chunk 11): Retreat & Reset.** The final chunk involves both arms retreating from the bag to a neutral position, marking the end of the manipulation sequence.", + "segments": [ + { + "segment_id": 0, + "primitive_type": "Grasp", + "chunk_idx_range": [ + 0, + 4 + ], + "subtask": "Establish bimanual stabilization and grasp zipper pull", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "exposed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + }, + { + "anchor_id": "bag:top_opening", + "current_status": "closed" + }, + { + "anchor_id": "table:surface_center", + "current_status": "occupied_by_bag" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "secured_by_right_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_left_arm" + }, + { + "anchor_id": "bag:top_opening", + "current_status": "closed" + }, + { + "anchor_id": "table:surface_center", + "current_status": "occupied_by_bag" + } + ] + }, + "causal_summary": { + "trigger": "Right arm contacts bag body, Left arm grasps zipper pull", + "effect": "Bag stabilized in preparation for unzipping" + } + }, + { + "segment_id": 1, + "primitive_type": "Compress/Squeeze", + "chunk_idx_range": [ + 5, + 6 + ], + "subtask": "Unzip bag using left arm pull", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "secured_by_right_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_left_arm" + }, + { + "anchor_id": "bag:top_opening", + "current_status": "closed" + }, + { + "anchor_id": "table:surface_center", + "current_status": "occupied_by_bag" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "secured_by_right_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_left_arm" + }, + { + "anchor_id": "bag:top_opening", + "current_status": "partially_open" + }, + { + "anchor_id": "table:surface_center", + "current_status": "occupied_by_bag" + } + ] + }, + "causal_summary": { + "trigger": "Left arm pulls zipper pull along track", + "effect": "Bag top opening extends/unzips" + } + }, + { + "segment_id": 2, + "primitive_type": "Grasp", + "chunk_idx_range": [ + 7, + 10 + ], + "subtask": "Re-grasp and complete unzipping with right arm", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "secured_by_right_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_left_arm" + }, + { + "anchor_id": "bag:top_opening", + "current_status": "partially_open" + }, + { + "anchor_id": "table:surface_center", + "current_status": "occupied_by_bag" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "secured_by_left_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_right_arm" + }, + { + "anchor_id": "bag:top_opening", + "current_status": "open" + }, + { + "anchor_id": "table:surface_center", + "current_status": "occupied_by_bag" + } + ] + }, + "causal_summary": { + "trigger": "Bimanual re-approach; Right arm grasps zipper, Left arm stabilizes body", + "effect": "Zipper fully opened via right arm pull" + } + }, + { + "segment_id": 3, + "primitive_type": "Retract", + "chunk_idx_range": [ + 11, + 11 + ], + "subtask": "Retreat arms to neutral position", + "state_transition": { + "before_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "secured_by_left_arm" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "grasped_by_right_arm" + }, + { + "anchor_id": "bag:top_opening", + "current_status": "open" + }, + { + "anchor_id": "table:surface_center", + "current_status": "occupied_by_bag" + } + ], + "after_anchors": [ + { + "anchor_id": "bag:main_body", + "current_status": "exposed" + }, + { + "anchor_id": "bag:zipper_pull", + "current_status": "accessible" + }, + { + "anchor_id": "bag:top_opening", + "current_status": "open" + }, + { + "anchor_id": "table:surface_center", + "current_status": "occupied_by_bag" + } + ] + }, + "causal_summary": { + "trigger": "Completion of unzipping task", + "effect": "Arms disengaged and moved to neutral workspace" + } + } + ] +} +```` +--- diff --git a/debug/episode_0036/images/chunkannotator_0_img_0.jpg b/debug/episode_0036/images/chunkannotator_0_img_0.jpg new file mode 100644 index 0000000000000000000000000000000000000000..39d9407aff73ed6d032517d91ac1e00aecf8d446 --- /dev/null +++ b/debug/episode_0036/images/chunkannotator_0_img_0.jpg @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0443cece1d90c66fa7c1ad89ad69335ad8b37e69f3592858af0aa9992305b85b +size 17410 diff --git 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