🧪 DexBioLab

Benchmarking Dexterous Manipulation with Dynamic Experimental Phenomena in Realistic Laboratories

DexBioLab is a benchmark for dexterous robotic manipulation in realistic laboratory environments. It provides a simulation-based platform for laboratory task execution, scripted demonstration collection, LeRobot dataset generation, and learned policy evaluation.

Paper

This dataset accompanies the following paper:

• Paper: DexBioLab: Benchmarking Dexterous Manipulation with Dynamic Experimental Phenomena in Realistic Laboratories
• Hugging Face Paper Page: https://huggingface.co/papers/2610.13643

Dataset Overview

DexBioLab supports research on laboratory manipulation, including tool use, precise object interactions, instrument operation, and dynamic experimental phenomena.

The benchmark and simulation framework support:

• Simulation: Execute laboratory manipulation tasks in realistic simulated environments.
• Demonstration Collection: Generate scripted robot demonstrations.
• Dataset Generation: Render simulation trajectories into LeRobot-compatible datasets.
• Policy Evaluation: Evaluate learned manipulation policies and analyze task success rates.

This repository contains task-specific LeRobot datasets with robot observations, actions, multi-view RGB videos, and task metadata. For benchmark details and experimental results, please refer to the paper.

Project Resources

• Project Page: https://cumulusalpha.github.io/DexBioLabWebPage/
• GitHub Repository: https://github.com/CumulusAlpha/DexBioLab
• Hugging Face Dataset: https://huggingface.co/datasets/22364yiqun/DexBioLab

Usage

Download the dataset using huggingface_hub:

from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="22364yiqun/DexBioLab",
    repo_type="dataset",
    local_dir="./DexBioLab",
)

Each task directory contains an independent LeRobot dataset. To download a single task, add allow_patterns=["ABPP-Shadow-Tube-Insert/**"] to the call above.

For simulation setup, demonstration collection, dataset generation, and policy evaluation, see the official GitHub repository.

License

This dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Please provide appropriate attribution when using the dataset.

Citation

If you use DexBioLab in your research, please cite:

@article{wu2026dexbiolab,
  title = {{DexBioLab}: Benchmarking Dexterous Manipulation with Dynamic Experimental Phenomena in Realistic Laboratories},
  author = {Wu, Xuanye and Shi, Yue and Yang, Yongcan and Wang, Yiqun and Wan, Zhaoqi and Xia, Dayu and Shao, Yanming and Cao, Jiezhang and Li, Xiangfei and Mu, Yao and Zhai, Guangtao},
  journal = {arXiv preprint arXiv:2610.13643},
  year = {2026},
  url = {https://arxiv.org/abs/2610.13643}
}