license: mit
language:
- en
tags:
- robotics
- simulation
- hdf5
- labvla
pretty_name: LabEmbodied-Data Beta
LabEmbodied-Data Beta
LabEmbodied-Data Beta is a subset of LabEmbodied-Data, introduced in LabVLA. It provides successful laboratory robot demonstrations with multi-view video, language instructions, robot states, actions, and structured annotations.
Dataset layout
<robot>/<family>/<case>/ Episode files and task metadata
meta/ Dataset information and episode indexes
docs/ Data format reference
examples/ Optional LeRobot conversion example
Each episode is stored in an H5 file. Use meta/episodes.jsonl to locate episodes and their associated metadata. File paths in the index are relative to the dataset root.
Quick start
Read H5 files directly with h5py; see the data format reference for field definitions and Python usage. Camera videos are embedded in the H5 files.
Optional LeRobot export
The example exports states, actions, language, and RGB videos to LeRobot v3.0 using LeRobot 0.4.4. Run from the dataset root in a Python 3.10+ environment:
pip install -r examples/requirements.txt
python examples/convert_to_lerobot.py \
--source . --out ../labembodied-ur5e-lerobot \
--repo-id local/labembodied-ur5e --robot ur5e --max-episodes 2
Omit --max-episodes to export all episodes for the selected robot. Joint values and column order are preserved. Videos are decoded and re-encoded; other annotations remain in the H5 files. The output includes meta/source_episodes.jsonl to map LeRobot indices to the original episode IDs. Nothing is uploaded.
Citation
@article{ren2026labvla,
title = {LabVLA: Grounding Vision-Language-Action Models in Scientific Laboratories},
author = {Ren, Baochang and Liu, Xinjie and Chen, Xi and Liu, Yanshuo and
Li, Chenxi and Gao, Daqi and Su, Zeqin and Xing, Jintao and
Xue, Zirui and Li, Rui and Zhao, Xiangyu and Qiao, Shuofei and
Pan, Minting and Zuo, Wangmeng and Bai, Lei and Zhou, Dongzhan and
Zhang, Ningyu and Chen, Huajun},
journal = {arXiv preprint arXiv:2606.13578},
year = {2026}
}