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