| --- |
| license: mit |
| task_categories: |
| - robotics |
| - reinforcement-learning |
| tags: |
| - LeRobot-v3 |
| - piper-robot |
| - teleoperation |
| - manipulation |
| - imitation-learning |
| size_categories: |
| - 1K<n<10K |
| language: |
| - en |
| pretty_name: PiPER Robot Teaching Episodes |
| --- |
| |
| # PiPER Robot Teaching Episodes Dataset |
|
|
| **13 teleoperation demonstrations** for robot manipulation using a 7-DOF PiPER arm. Fully compatible with LeRobot v3 format. |
|
|
| ## Quick Info |
|
|
| - **Episodes**: 13 | **Tasks**: 12 | **Size**: ~6.2 GB | **FPS**: 30 |
| - **Robot**: PiPER 7-DOF arm | **Cameras**: Table (800×720) + Wrist | **Version**: v0.3 |
| - **Format**: HDF5 + PNG images | **Compatible**: LeRobot v3, ACT, Diffusion Policy, SmolVLA |
|
|
| ## Tasks |
|
|
| `cleaningcloth` `fillamentroll` `gamecontroller` `hexwrench` `pencil` `scissors` `scissors_hidden` `screwdriver` `smallkey` `smallpaper` `smallwoodenstick` `thinmetaldisk` |
|
|
| ## Dataset Structure |
|
|
| ``` |
| {episode_name}_{timestamp}.hdf5 # Robot state, actions, compressed images |
| {episode_name}_{timestamp}.json # Episode metadata (frames, fps, stats) |
| {episode_name}_images/ |
| ├── observation.images.table_cam/ # 800×720 PNG frames |
| └── observation.images.wrist_cam/ # PNG frames (vertically flipped) |
| meta_data/ |
| ├── info.json # Dataset config, encoding, shapes |
| ├── tasks.jsonl # Task definitions |
| └── episodes.jsonl # Episode-task mapping |
| info.json # Root metadata (LeRobot v3) |
| ``` |
|
|
| ### HDF5 Structure |
|
|
| - `observations/state`: 7-DOF joint angles (degrees) |
| - `observations/images/table_cam`: Compressed JPEG images |
| - `observations/images/wrist_cam`: Compressed JPEG images |
| - `actions`: 7-DOF commands |
| - `timestamps`: Frame timestamps |
|
|
| ### Metadata (JSON) |
|
|
| Each episode JSON contains: `episode_name`, `n_frames`, `duration_seconds`, `fps`, `state_dim`, `cameras`, `state_stats` (mean/std/min/max), `recording_date` |
|
|
| ## Usage |
|
|
| ### LeRobot Library (Recommended) |
|
|
| ```python |
| from lerobot.common.datasets.lerobot_dataset import LeRobotDataset |
| |
| dataset = LeRobotDataset("charithmunasinghe/piper_picking_tests", version="v0.3") |
| |
| for batch in dataset: |
| state = batch['observation']['observation.state'] |
| action = batch['action'] |
| table_img = batch['observation']['observation.images.table_cam'] |
| wrist_img = batch['observation']['observation.images.wrist_cam'] |
| ``` |
|
|
| ### Visualize |
|
|
| ```python |
| from lerobot.scripts.visualize_dataset import visualize_dataset |
| |
| visualize_dataset( |
| repo_id="charithmunasinghe/piper_picking_tests", |
| episode_index=0, |
| version="v0.3" |
| ) |
| ``` |
|
|
| ### Direct HDF5 Access |
|
|
| ```python |
| import h5py |
| from PIL import Image |
| from pathlib import Path |
| |
| with h5py.File("screwdriver_20251104_203022.hdf5", 'r') as f: |
| states = f['observations/state'][:] |
| actions = f['actions'][:] |
| |
| img = Image.open("screwdriver_images/observation.images.table_cam/frame_000000.png") |
| ``` |
|
|
| ## Dataset Info |
|
|
| - **Collection**: Human teleoperation in lab environment |
| - **Preprocessing**: Table camera cropped (+300,0 offset), wrist camera flipped vertically |
| - **Split**: Single train split (13 episodes) |
| - **License**: MIT |
|
|
| ## Citation |
|
|
| ```bibtex |
| @dataset{piper_teaching_episodes_2025, |
| title={PiPER Robot Teaching Episodes Dataset}, |
| author={Munasinghe, Charith and Toffetti, Giovanni}, |
| year={2025}, |
| publisher={Hugging Face}, |
| howpublished={\url{https://huggingface.co/datasets/charithmunasinghe/piper_picking_tests}} |
| } |
| ``` |
|
|
| **Contact**: charithmunasinghe (Hugging Face) |
|
|
