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--- |
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license: apache-2.0 |
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task_categories: |
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- robotics |
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tags: |
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- LeRobot |
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configs: |
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- config_name: default |
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data_files: data/*/*.parquet |
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--- |
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This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). |
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## Dataset Description |
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This dataset contains the first set of teleoperated demonstrations collected during a two-day hackathon using the LeRobot library and SO-101 robot arms in a leader–follower setup. |
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Each episode shows the follower arm picking one colored cube and placing it onto the matching colored cross inside a 2×2 grid. |
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Two synchronized RGB cameras were used: |
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- **Top camera**: overhead, provides a full 2D view of the workspace (arm, cube, grid). |
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- **Front/low camera**: slightly above ground level, facing the arm and grid to capture z-axis cues and arm self-pose. |
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The background was masked with cardboard panels, but ambient lighting varied throughout the day; this variation is preserved and is useful for robustness studies. |
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Intended for vision-based imitation learning, multi-view fusion, and tabletop manipulation research. |
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### Use Cases |
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- **Imitation Learning**: Behavior cloning from teleop demonstrations. |
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- **Multiview Perception**: Fusing top + front perspectives for depth inference without explicit depth sensors. |
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- **Robustness to Lighting**: Evaluating policy sensitivity to illumination drift. |
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- **State–Action Alignment**: Leveraging synchronized proprioception and images. |
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- **Policy Bootstrapping for curricula**: pretrain on single-cube before multi-cube tasks. |
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## Data Collection |
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### Teleoperation & Hardware |
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- **Leader–Follower teleop**: human drives a leader arm; follower SO-101 replicates to produce demonstrations. |
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- **Workspace**: Tabletop with 2×2 grid; only one cell has a colored cross. One cube is placed in its matching cross per episode. |
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- **Cameras**: |
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- **Front**: static overhead. |
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- **Left**: static frontal view emphasizing depth. |
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- **Environment**: Cardboard background; illumination changes across time are present in the data. |
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### Episode Protocol |
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1- Move to pre-grasp and visually localize the target cube. |
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2- Approach and grasp the cube. |
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3- Transport and align over the colored cross. |
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4- Place, release, and return to neutral. |
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## Known Limitations |
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Lighting drift: Varying brightness/temperature across episodes; apply color constancy, normalization, or photometric augmentation. |
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Occlusions: Hand/gripper and cube may occlude from the front camera during close approaches. |
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No depth sensor: Only RGB; consider multi-view fusion or learned depth cues. |
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Action semantics: Confirm whether actions are delta-pose or joint velocities in each metadata.json. |
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Early-phase variability: Being the first batch, some episodes may include exploratory motions, hesitations, or failed initial grasps that later recover—useful for learning robustness but consider filtering for clean BC. |
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## Additional Information |
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- **Homepage:** [deel-ai](https://www.irt-saintexupery.com/deel/) |
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- **License:** apache-2.0 |
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## Dataset Structure |
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[meta/info.json](meta/info.json): |
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```json |
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{ |
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"codebase_version": "v3.0", |
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"robot_type": "so101_follower", |
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"total_episodes": 206, |
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"total_frames": 84098, |
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"total_tasks": 1, |
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"chunks_size": 1000, |
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"data_files_size_in_mb": 100, |
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"video_files_size_in_mb": 500, |
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"fps": 30, |
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"splits": { |
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"train": "0:206" |
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}, |
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"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet", |
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"video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4", |
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"features": { |
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"action": { |
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"dtype": "float32", |
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"names": [ |
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"shoulder_pan.pos", |
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"shoulder_lift.pos", |
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"elbow_flex.pos", |
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"wrist_flex.pos", |
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"wrist_roll.pos", |
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"gripper.pos" |
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], |
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"shape": [ |
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6 |
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] |
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}, |
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"observation.state": { |
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"dtype": "float32", |
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"names": [ |
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"shoulder_pan.pos", |
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"shoulder_lift.pos", |
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"elbow_flex.pos", |
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"wrist_flex.pos", |
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"wrist_roll.pos", |
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"gripper.pos" |
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], |
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"shape": [ |
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6 |
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] |
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}, |
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"observation.images.left": { |
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"dtype": "video", |
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"shape": [ |
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480, |
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640, |
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3 |
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], |
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"names": [ |
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"height", |
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"width", |
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"channels" |
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], |
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"info": { |
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"video.height": 480, |
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"video.width": 640, |
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"video.codec": "av1", |
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"video.pix_fmt": "yuv420p", |
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"video.is_depth_map": false, |
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"video.fps": 30, |
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"video.channels": 3, |
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"has_audio": false |
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} |
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}, |
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"observation.images.front": { |
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"dtype": "video", |
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"shape": [ |
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480, |
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640, |
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3 |
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], |
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"names": [ |
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"height", |
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"width", |
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"channels" |
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], |
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"info": { |
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"video.height": 480, |
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"video.width": 640, |
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"video.codec": "av1", |
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"video.pix_fmt": "yuv420p", |
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"video.is_depth_map": false, |
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"video.fps": 30, |
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"video.channels": 3, |
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"has_audio": false |
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} |
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}, |
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"timestamp": { |
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"dtype": "float32", |
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"shape": [ |
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1 |
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], |
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"names": null |
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}, |
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"frame_index": { |
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"dtype": "int64", |
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"shape": [ |
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1 |
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], |
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"names": null |
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}, |
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"episode_index": { |
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"dtype": "int64", |
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"shape": [ |
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1 |
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], |
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"names": null |
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}, |
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"index": { |
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"dtype": "int64", |
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"shape": [ |
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1 |
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], |
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"names": null |
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}, |
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"task_index": { |
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"dtype": "int64", |
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"shape": [ |
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1 |
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], |
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"names": null |
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|
} |
|
|
} |
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} |
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``` |
