AnyTeleop: A General Vision-Based Dexterous Robot Arm-Hand Teleoperation System

Yuzhe Qin, Wei Yang, Binghao Huang, Karl Van Wyk, Hao Su +3 more
7/10/2023
cs.ROcs.CVcs.LG

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Abstract

Vision-based teleoperation offers the possibility to endow robots with human-level intelligence to physically interact with the environment, while only requiring low-cost camera sensors. However, current vision-based teleoperation systems are designed and engineered towards a particular robot model and deploy environment, which scales poorly as the pool of the robot models expands and the variety of the operating environment increases. In this paper, we propose AnyTeleop, a unified and general teleoperation system to support multiple different arms, hands, realities, and camera configurations within a single system. Although being designed to provide great flexibility to the choice of simulators and real hardware, our system can still achieve great performance. For real-world experiments, AnyTeleop can outperform a previous system that was designed for a specific robot hardware with a higher success rate, using the same robot. For teleoperation in simulation, AnyTeleop leads to better imitation learning performance, compared with a previous system that is particularly designed for that simulator. Project page: https://yzqin.github.io/anyteleop/.

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Cite this paper

@article{qin2023anyteleop,
  title  = {AnyTeleop: A General Vision-Based Dexterous Robot Arm-Hand Teleoperation System},
  author = {Yuzhe Qin and Wei Yang and Binghao Huang and Karl Van Wyk and Hao Su and Xiaolong Wang and Yu-Wei Chao and Dieter Fox},
  year   = {2023},
  eprint = {2307.04577},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2307.04577v3}
}

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