OPEN TEACH: A Versatile Teleoperation System for Robotic Manipulation

Aadhithya Iyer, Zhuoran Peng, Yinlong Dai, Irmak Guzey, Siddhant Haldar, Soumith Chintala, Lerrel Pinto

Keywords: Low Cost Teleoperation, Imitation Learning, Robot Manipulation

TL;DR: Low Cost Versatile Teleoperation for Robot Manipulation

Abstract: Open-sourced, user-friendly tools form the bedrock of scientific advancement across disciplines. The widespread adoption of data-driven learning has led to remarkable progress in multi-fingered dexterity, bimanual manipulation, and applications ranging from logistics to home robotics. However, existing data collection platforms are often proprietary, costly, or tailored to specific robotic morphologies. We present Open Teach, a new teleoperation system leveraging VR headsets to immerse users in mixed reality for intuitive robot control. Built on the affordable Meta Quest 3, which costs $500, Open Teach enables real-time control of various robots, including multi-fingered hands, bimanual arms, and mobile manipulators, through an easy-to-use app. Using natural hand gestures and movements, users can manipulate robots at up to 90Hz with smooth visual feedback and interface widgets offering closeup environment views.

Previous Publication: Yes

Submission Number: 20