OpenMOSS-Team/robodojo-lerobot-v3.0

RoboDojo LeRobot v3.0

This dataset packages RoboDojo robot-manipulation demonstrations in LeRobot v3.0 format for EasyWAM training. It contains synchronized high-view and dual-wrist RGB video, bimanual joint state, actions, and natural-language task metadata.

Dataset Summary

Episodes	Frames	Tasks	Recording rate
3,500	1,856,102	35	25 FPS

Structure

robodojo-lerobot-v3.0/
├── data/                  # frame-level Parquet files
├── meta/
│   ├── episodes/          # episode metadata
│   ├── info.json          # schema and dataset totals
│   ├── stats.json         # LeRobot feature statistics
│   └── tasks.parquet      # task index and language
├── videos/                # camera MP4 files
└── dataset_stats.json     # EasyWAM normalization statistics

Features

Feature	Type / shape	Description
observation.images.cam_high	RGB video, 480×640	High camera
observation.images.cam_left_wrist	RGB video, 480×640	Left wrist camera
observation.images.cam_right_wrist	RGB video, 480×640	Right wrist camera
observation.state	float32[14]	Left and right 7-DoF joint state
action	float32[14]	Left and right 7-DoF joint action
timestamp	float32	Frame timestamp
frame_index	int64	Frame index within the episode
episode_index	int64	Episode identifier
task_index	int64	Index into meta/tasks.parquet

Videos use AV1 with YUV 4:2:0 pixel format and contain no audio.

Download

hf download OpenMOSS-Team/robodojo-lerobot-v3.0 \
  --repo-type dataset \
  --local-dir data/robodojo-lerobot-v3.0

Use with EasyWAM

The EasyWAM pipeline resizes each camera to 240×320, composes the three views into a 384×320 observation, uses a 33-step action/state horizon with 9 decoded video timestamps, and applies global z-score normalization. A deterministic 1% episode split is used for validation.

python scripts/precompute_text_embeds.py task=robodojo_easywam_mot_wan22

NPROC_PER_NODE=8 bash scripts/train_zero1.sh \
  task=robodojo_easywam_mot_wan22

See the EasyWAM RoboDojo data guide for configuration details.

Project

• Project page: http://openmoss.ai/EasyWAM/
• Code: https://github.com/OpenMOSS/EasyWAM
• Upstream benchmark: https://github.com/RoboDojo-Benchmark/RoboDojo

License and Citation

This dataset is subject to the upstream RoboDojo terms. The upstream project identifies RoboDojo as available for non-commercial research, education, and evaluation; review the RoboDojo license and repository before use or redistribution.

@article{chen2026robodojo,
  title   = {RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies},
  author  = {Chen, Tianxing and Chen, Yue and Li, Zixuan and Tang, Junyuan and Su, Kailun and Wan, Weijie and Chen, Baijun and Lu, Haoran and Yan, Haowen and Su, Honghao and others},
  journal = {arXiv preprint arXiv:2607.04434},
  year    = {2026}
}