| # Data Storage and Output |
|
|
| By default, proprio data will be recorded in the hdf5 file. To turn on image data recording, `robolab.constants.RECORD_IMAGE_DATA` needs to be set to True. |
|
|
| ## Single-Env vs Multi-Env Recording |
|
|
| RoboLab supports running multiple parallel environments per task. The recording system handles both cases: |
|
|
| **Single-env** (`--num_envs 1`, default): |
| - One episode per run, written to `run_{run_idx}.hdf5` as `demo_0` |
| - Videos: `{instruction}_{run_idx}.mp4` |
| - Subtask logs: `log_{run_idx}_env0.json` |
|
|
| **Multi-env** (`--num_envs N`): |
| - N parallel episodes per run, all written to `run_{run_idx}.hdf5` as `demo_0` through `demo_{N-1}` |
| - Each `demo_i` corresponds to `env_id=i` with independent trajectory data |
| - Videos: `{instruction}_{run_idx}_env{env_id}.mp4` (one per env) |
| - Subtask logs: `log_{run_idx}_env{env_id}.json` (one per env) |
| - Each env has its own subtask state machine, event tracker, and termination state |
| - Envs terminate independently — when an env succeeds, it freezes while others continue |
| - HDF5 recording uses auto-flush (every 500 steps) with concurrent per-env streaming — each env's buffer is flushed to its own demo without interfering with other envs |
| - Total episodes = `num_runs * num_envs` |
|
|
| > **Tip:** Prefer increasing `--num_envs` for more episodes. Only increase `--num-runs` (default 1) if you run out of GPU memory with the desired `num_envs`. For example, to run 24 episodes when only 12 fit in VRAM: `--num_envs 12 --num-runs 2`. |
| |
| The `episode_results.jsonl` tracks each env independently with a unique `episode` ID (`run_idx * num_envs + env_id`) and an `env_id` field. Each line is a self-contained JSON object (JSONL format) for safe append-only writes. |
|
|
| ## Output Directory Structure |
|
|
| ``` |
| output/ |
| └── <output_folder>/ |
| ├── episode_results.jsonl |
| ├── <ENV_NAME>/ |
| ├── run_0.hdf5 # Run 0 data (demo_0..demo_{N-1} for N envs) |
| ├── run_1.hdf5 # Run 1 data (if num_runs > 1) |
| ├── log_0_env0.json # Run 0, env 0 subtask log |
| ├── log_0_env1.json # Run 0, env 1 subtask log |
| ├── {instruction}_0_env0.mp4 # Run 0, env 0 observation video |
| ├── {instruction}_0_env0_viewport.mp4 |
| ├── {instruction}_0_env1.mp4 # Run 0, env 1 observation video |
| ├── {instruction}_0_env1_viewport.mp4 |
| └── env_cfg.json |
| ``` |
| For `ENV_NAME`, refer to [environment registration](environment_registration.md). |
|
|
| ## HDF5 Data Structure |
|
|
| Each `run_{i}.hdf5` file contains the following hierarchical structure (`h5glance run_0.hdf5`) |
| ``` |
| └data (2 attributes) |
| ├demo_0 (2 attributes) |
| │ ├actions [float32: 470 × 8] |
| │ ├initial_state |
| │ │ ├articulation |
| │ │ │ └robot |
| │ │ │ ├joint_position [float32: 1 × 13] |
| │ │ │ ├joint_velocity [float32: 1 × 13] |
| │ │ │ ├root_pose [float32: 1 × 7] |
| │ │ │ └root_velocity [float32: 1 × 6] |
| │ │ └rigid_object |
| │ │ ├banana |
| │ │ │ ├root_pose [float32: 1 × 7] |
| │ │ │ └root_velocity [float32: 1 × 6] |
| │ │ ├bowl |
| │ │ │ ├root_pose [float32: 1 × 7] |
| │ │ │ └root_velocity [float32: 1 × 6] |
| │ │ └rubiks_cube |
| │ │ ├root_pose [float32: 1 × 7] |
| │ │ └root_velocity [float32: 1 × 6] |
| │ ├obs |
| │ │ ├arm_joint_pos [float32: 470] |
| │ │ ├over_shoulder_left_camera [uint8: 470 × 720 × 1280 × 3] |
| │ │ ├gripper_pos [float32: 470] |
| │ │ └wrist_cam [uint8: 470 × 720 × 1280 × 3] |
| │ ├states |
| │ │ ├articulation |
| │ │ │ └robot |
| │ │ │ ├joint_position [float32: 470 × 13] |
| │ │ │ ├joint_velocity [float32: 470 × 13] |
| │ │ │ ├root_pose [float32: 470 × 7] |
| │ │ │ └root_velocity [float32: 470 × 6] |
| │ │ └rigid_object |
| │ │ ├banana |
| │ │ │ ├root_pose [float32: 470 × 7] |
| │ │ │ └root_velocity [float32: 470 × 6] |
| │ │ ├bowl |
| │ │ │ ├root_pose [float32: 470 × 7] |
| │ │ │ └root_velocity [float32: 470 × 6] |
| │ │ └rubiks_cube |
| │ │ ├root_pose [float32: 470 × 7] |
| │ │ └root_velocity [float32: 470 × 6] |
| │ ├subtask |
| │ │ ├completed [uint8: 470] |
| │ │ ├score [float32: 470] |
| │ │ └status [uint16: 470] |
| │ └bbox |
| │ ├bbox_mm |
| │ │ ├banana [int16: 470 × 8 × 3] # OBB corners in mm (relative to env origin) |
| │ │ ├bowl [int16: 470 × 8 × 3] |
| │ │ └rubiks_cube [int16: 470 × 8 × 3] |
| │ └centroid |
| │ ├banana [float16: 470 × 3] # centroid in meters (relative to env origin) |
| │ ├bowl [float16: 470 × 3] |
| │ └rubiks_cube [float16: 470 × 3] |
| ├demo_1 |
| .... |
| ``` |
|
|
| ## Data Structure Details |
|
|
| ### Episodes |
| - **`demo_i`**: Episode data for `env_id=i`. In single-env mode, only `demo_0` exists. In multi-env mode, `demo_0` through `demo_{N-1}` exist in each `run_{run_idx}.hdf5`. |
| |
| ### Data Components |
| - **`actions`**: Robot control commands (8-dimensional for joint positions) |
| - **`initial_state`**: Starting configuration of robot and objects |
| - **`obs`**: Observations including joint positions, camera images, and gripper state |
| - **`states`**: Full state trajectory of robot and objects over time |
| - **`subtask`**: Task progress tracking metrics |
| - **`bbox`**: Per-step oriented bounding box data for all rigid objects |
| - **`bbox_mm/{name}`**: OBB corners as `int16` in millimeters, shape `(T, 8, 3)`. Corner order: `[0-3]` bottom face (z-low), `[4-7]` top face (z-high). Positions are relative to env origin. Convert to meters: `corners_m = data[:] / 1000.0` |
| - **`centroid/{name}`**: Object centroid as `float16` in meters, shape `(T, 3)`. Relative to env origin. |
| |
| ### Object Tracking |
| The system tracks three main objects: |
| - **`banana`**: Position and velocity in 3D space |
| - **`bowl`**: Container object state |
| - **`rubiks_cube`**: Manipulation target object |
| |
| ## File Descriptions |
| |
| - **`run_{i}.hdf5`**: Per-run data file containing episode data for all envs in that run. Each `demo_j` within the file corresponds to `env_id=j`. Contains: |
| - Robot observations (joint states, end-effector poses, etc.) |
| - Actions taken by the policy |
| - Task-specific metrics and success/failure indicators |
| - Episode timestamps and metadata |
| |
| - **`env_cfg.json`**: Configuration file containing the environment setup, including: |
| - Task definition and parameters |
| - Robot configuration |
| - Observation and action space specifications |
| - Scene and lighting settings |
| |
| ## Episode Results |
| |
| #### `episode_results.jsonl` |
| The main results file, located at the top level of the output folder. Uses JSONL format (one JSON object per line) for safe append-only writes. Each line corresponds to one episode and contains task metadata, success/failure status, subtask scoring, trajectory metrics, and error events. |
| |
| > **Note:** Legacy folders may contain `episode_results.json` (JSON array format). All analysis tools read both formats transparently. |
| |
| ```jsonl |
| {"env_name": "RubiksCubeAndBananaTask", "task_name": "RubiksCubeAndBananaTask", "run_name": "RubiksCubeAndBananaTask_1", "episode": 1, "policy": "pi05", "instruction": "Put the cube and the banana in the bowl", "instruction_type": "default", "attributes": ["conjunction", "simple"], "success": true, "score": 1.0, "reason": "Completed subtask 'pick_and_place' 1/1", "episode_step": 232, "duration": 15.467, "dt": 0.06666666666666667, "metrics": {"ee_sparc": -3.971, "joint_sparc_mean": -6.190, "ee_isj": 213.389, "joint_isj": 5408.055, "ee_path_length": 1.126, "joint_rmse_mean": 0.022, "ee_speed_max": 0.195, "ee_speed_mean": 0.068}, "events": {"TARGET_OBJECT_DROPPED": 4}} |
| ``` |
| |
| **Fields:** |
| - `env_name`: Environment name (also the subfolder name on disk) |
| - `task_name`: Base task class name (multiple env_names can share the same task_name) |
| - `run_name`: Unique run identifier (`<ENV_NAME>_<RUN_IDX>`) |
| - `run`: Run index (which batch of parallel envs) |
| - `episode`: Global episode number (`run_idx * num_envs + env_id`) |
| - `env_id`: Which parallel environment within the run (0 to num_envs-1) |
| - `policy`: Policy backend used |
| - `instruction`: Language instruction for the task |
| - `instruction_type`: Instruction variant used (e.g., `default`, `vague`, `specific`) |
| - `attributes`: Task attribute tags (e.g., `simple`, `color`, `spatial`, `conjunction`) |
| - `success`: Whether the episode succeeded |
| - `score`: Subtask completion score (0.0 to 1.0), present when subtask tracking is enabled |
| - `reason`: Completion or failure reason, present when subtask tracking is enabled |
| - `episode_step`: Number of simulation steps in the episode |
| - `duration`: Episode duration in seconds |
| - `dt`: Simulation timestep (seconds per step) |
| - `metrics`: Trajectory quality metrics, computed automatically at the end of each episode from HDF5 data |
| - `ee_sparc`: End-effector SPARC smoothness (more negative = smoother) |
| - `joint_sparc_mean`: Mean SPARC across arm joints |
| - `ee_isj`: End-effector Integrated Squared Jerk |
| - `joint_isj`: Joint space Integrated Squared Jerk |
| - `ee_path_length`: End-effector path length in meters |
| - `joint_rmse_mean`: Mean joint tracking error (action vs actual) |
| - `ee_speed_max`: Maximum end-effector speed (m/s) |
| - `ee_speed_mean`: Mean end-effector speed (m/s) |
| - `timing`: Wall-clock timing breakdown per episode (always recorded) |
| - `policy_inference_s`: Total time spent in policy server queries |
| - `policy_inference_avg_ms`: Average policy query time per step |
| - `env_step_s`: Total time spent in `env.step()` (physics + observations + termination) |
| - `env_step_avg_ms`: Average env step time per step |
| - `video_write_s`: Total time spent encoding video frames |
| - `video_write_avg_ms`: Average video write time per step |
| - `wall_total_s`: Sum of all timed sections |
| - `it_per_sec`: Steps per second (`steps / wall_total_s`) |
| - `events`: Error event counts, extracted from episode log files at the end of each episode |
| - `WRONG_OBJECT_GRABBED`: Robot grabbed an unintended object |
| - `GRIPPER_HIT_TABLE`: Gripper made contact with table |
| - `GRIPPER_HIT_OBJECT`: Gripper collided with an object |
| - `GRIPPER_FULLY_CLOSED`: Gripper closed fully (empty grasp) |
| - `TARGET_OBJECT_DROPPED`: Target object was grabbed but dropped mid-transport |
| - `MULTIPLE_OBJECTS_GRABBED`: Multiple objects grabbed simultaneously |
| - `OBJECT_BUMPED`: Non-target object was nudged |
| - `OBJECT_MOVED`: Non-target object was significantly displaced |
| - `OBJECT_OUT_OF_SCENE`: Object fell off table or moved outside workspace |
| - `wrong_objects_grabbed`: List of wrong object names that were grabbed |
| |
| ## See Also |
| |
| - [Analysis and Results Parsing](analysis.md) — Scripts for summarizing, comparing, and auditing experiment results |
| |
