1. Bunny-VisionPro: Real-Time Bimanual Dexterous Teleoperation for Imitation Learning
- Author
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Ding, Runyu, Qin, Yuzhe, Zhu, Jiyue, Jia, Chengzhe, Yang, Shiqi, Yang, Ruihan, Qi, Xiaojuan, and Wang, Xiaolong
- Subjects
Computer Science - Robotics ,Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning - Abstract
Teleoperation is a crucial tool for collecting human demonstrations, but controlling robots with bimanual dexterous hands remains a challenge. Existing teleoperation systems struggle to handle the complexity of coordinating two hands for intricate manipulations. We introduce Bunny-VisionPro, a real-time bimanual dexterous teleoperation system that leverages a VR headset. Unlike previous vision-based teleoperation systems, we design novel low-cost devices to provide haptic feedback to the operator, enhancing immersion. Our system prioritizes safety by incorporating collision and singularity avoidance while maintaining real-time performance through innovative designs. Bunny-VisionPro outperforms prior systems on a standard task suite, achieving higher success rates and reduced task completion times. Moreover, the high-quality teleoperation demonstrations improve downstream imitation learning performance, leading to better generalizability. Notably, Bunny-VisionPro enables imitation learning with challenging multi-stage, long-horizon dexterous manipulation tasks, which have rarely been addressed in previous work. Our system's ability to handle bimanual manipulations while prioritizing safety and real-time performance makes it a powerful tool for advancing dexterous manipulation and imitation learning., Comment: project page: https://dingry.github.io/projects/bunny_visionpro.html
- Published
- 2024