| --- |
| license: cc-by-4.0 |
| task_categories: |
| - robotics |
| tags: |
| - robotics |
| - imitation-learning |
| - bimanual-manipulation |
| - aloha-agilex |
| - lerobot |
| pretty_name: RoboPro |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # RoboPro |
|
|
| **RoboPro** is an 80-task bimanual manipulation dataset collected on a dual-arm **Aloha-Agilex** platform. It contains 15,999 expert teleoperation episodes (3.73 M frames at 50 Hz) recorded from three RGB cameras and synchronised 14-DoF joint commands. Each task includes a **clean** variant and ten **cluttered** variants (`d6`…`d15`) with progressively added distractor objects. |
|
|
| The dataset is released in [LeRobot v2.1](https://github.com/huggingface/lerobot) format. |
|
|
| ## At a glance |
|
|
| | | | |
| |---|---| |
| | Robot | Aloha-Agilex (dual-arm, 14-DoF) | |
| | Episodes | 15,999 | |
| | Frames | 3,728,445 | |
| | FPS | 50 Hz | |
| | Cameras | 3 × RGB 480×640 H.264 (cam_high, cam_left_wrist, cam_right_wrist) | |
| | Tasks | 80 base × {clean, d6…d15} variants, 1,622 unique language prompts | |
| | Format | LeRobot v2.1 (Parquet + MP4) | |
| | License | CC-BY-4.0 | |
| |
| ## Layout |
| |
| ``` |
| lerobot/roboreal_all_80tasks/ |
| ├── meta/ |
| │ ├── info.json # schema, fps, episode count |
| │ ├── tasks.jsonl # 1,622 task language descriptions |
| │ ├── episodes.jsonl # per-episode metadata |
| │ └── episodes_stats.jsonl |
| ├── data/ |
| │ └── chunk-{000..015}/ |
| │ └── episode_{000000..015998}.parquet # 50 Hz proprioception |
| └── videos/ |
| └── chunk-{000..015}/ |
| └── observation.images.{cam_high,cam_left_wrist,cam_right_wrist}/ |
| └── episode_{000000..015998}.mp4 # H.264 yuv420p, GOP=2 |
| ``` |
| |
| Each Parquet row contains: |
| - `observation.state` — `float32[14]` joint state |
| - `action` — `float32[14]` target joint command |
| - `timestamp`, `frame_index`, `episode_index`, `index`, `task_index` |
|
|
| The 14-DoF channel order for both `observation.state` and `action` is: |
| ``` |
| left_waist, left_shoulder, left_elbow, left_forearm_roll, |
| left_wrist_angle, left_wrist_rotate, left_gripper, |
| right_waist, right_shoulder, right_elbow, right_forearm_roll, |
| right_wrist_angle, right_wrist_rotate, right_gripper |
| ``` |
|
|
| ## Loading |
|
|
| ```python |
| from lerobot.common.datasets.lerobot_dataset import LeRobotDataset |
| |
| ds = LeRobotDataset( |
| repo_id="RoboPRO/RoboPRO_data", |
| root="lerobot/roboreal_all_80tasks", # subfolder within the repo |
| ) |
| ``` |
|
|
| Or stream individual files: |
|
|
| ```python |
| from huggingface_hub import hf_hub_download |
| import pyarrow.parquet as pq |
| |
| p = hf_hub_download( |
| "RoboPRO/RoboPRO_data", |
| "lerobot/roboreal_all_80tasks/data/chunk-000/episode_000000.parquet", |
| repo_type="dataset", |
| ) |
| table = pq.read_table(p) |
| ``` |
|
|
| ## Citation |
|
|
| RoboPRO was introduced in the RSS 2026 Data-Centric Robotics Workshop paper *Data and Evaluation Protocols for Robust Robotic Manipulation*. Please cite: |
|
|
| ```bibtex |
| @inproceedings{li2026robopro, |
| title = {Data and Evaluation Protocols for Robust Robotic Manipulation}, |
| author = {Li, Zhiyuan and Eret, Charles and Zhao, Xuan and Wu, Yangzheng and Rasouli, Amir}, |
| booktitle = {Data-Centric Robotics Workshop at Robotics: Science and Systems (RSS)}, |
| year = {2026}, |
| url = {https://robopro-bench.github.io/RoboPRO/} |
| } |
| ``` |
|
|
| ## Limitations & ethical considerations |
|
|
| - All demonstrations were recorded on a single Aloha-Agilex unit in a fixed laboratory environment; lighting, camera intrinsics, and table geometry do not vary across episodes. |
| - Tasks are short-horizon (<10 s) tabletop manipulation — no long-horizon, navigation, or contact-rich (insertion, peg-in-hole) tasks. |
| - Demonstrations reflect the kinematic preferences of a small operator pool; they are not guaranteed to be task-optimal. |
| - No human faces, voices, biometric or other personal information is captured. Scenes consist of inanimate objects on a laboratory table. |
|
|
