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arXiv · 2407.01512

Open-TeleVision: Teleoperation with Immersive Active Visual Feedback

Xuxin Cheng·Jialong Li·Shiqi Yang·Ge Yang·Xiaolong Wang
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Abstract

Teleoperation serves as a powerful method for collecting on-robot data essential for robot learning from demonstrations. The intuitiveness and ease of use of the teleoperation system are crucial for ensuring high-quality, diverse, and scalable data. To achieve this, we propose an immersive teleoperation system Open-TeleVision that allows operators to actively perceive the robot's surroundings in a stereoscopic manner. Additionally, the system mirrors the operator's arm and hand movements on the robot, creating an immersive experience as if the operator's mind is transmitted to a robot embodiment. We validate the effectiveness of our system by collecting data and training imitation learning policies on four long-horizon, precise tasks (Can Sorting, Can Insertion, Folding, and Unloading) for 2 different humanoid robots and deploy them in the real world. The system is open-sourced at: https://robot-tv.github.io/

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Xuxin Cheng, Jialong Li, Shiqi Yang, Ge Yang, Xiaolong Wang. 2024-07-01. Open-TeleVision: Teleoperation with Immersive Active Visual Feedback. https://arxiv.org/abs/2407.01512

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