Bimanual Dexterity for Complex Tasks

Abstract

To train generalist robot policies, machine learning methods often require a substantial amount of expert human teleoperation data. An ideal robot for humans collecting data is one that closely mimics them: bimanual arms and dexterous hands. However, creating such a bimanual teleoperation system with over 50 DoF is a significant challenge. To address this, we introduce Bidex, an extremely dexterous, low-cost, low-latency and portable bimanual dexterous teleoperation system which relies on motion capture gloves and teacher arms. We compare Bidex to a Vision Pro teleoperation system and a SteamVR system and find Bidex to produce better quality data for more complex tasks at a faster rate. Additionally, we show Bidex operating a mobile bimanual robot for in the wild tasks. Please refer to https://bidex-teleop.github.io for video results and instructions to recreate Bidex. The robot hands (5k USD) and teleoperation system (7k USD) is readily reproducible and can be used on many robot arms including two xArms ($16k USD).

Cite

Text

Shaw et al. "Bimanual Dexterity for Complex Tasks." Proceedings of The 8th Conference on Robot Learning, 2024.

Markdown

[Shaw et al. "Bimanual Dexterity for Complex Tasks." Proceedings of The 8th Conference on Robot Learning, 2024.](https://mlanthology.org/corl/2024/shaw2024corl-bimanual/)

BibTeX

@inproceedings{shaw2024corl-bimanual,
  title     = {{Bimanual Dexterity for Complex Tasks}},
  author    = {Shaw, Kenneth and Li, Yulong and Yang, Jiahui and Srirama, Mohan Kumar and Liu, Ray and Xiong, Haoyu and Mendonca, Russell and Pathak, Deepak},
  booktitle = {Proceedings of The 8th Conference on Robot Learning},
  year      = {2024},
  pages     = {5166-5183},
  volume    = {270},
  url       = {https://mlanthology.org/corl/2024/shaw2024corl-bimanual/}
}