WFH-VR: Teleoperating a Robot Arm to set a Dining Table across the Globe via Virtual Reality

WFH-VR: Teleoperating a Robot Arm to set a Dining Table across the Globe via Virtual Reality

This paper presents an easy-to-deploy, virtual reality-based teleoperation system for controlling a robot arm. The proposed system is based on a consumer-grade virtual reality device (Oculus Quest 2) with a low-cost robot arm (a LoCoBot) to allow easy replication and set up. The proposed Work-from-H...

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Bibliographic Details
Published in:2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) pp. 4927 - 4934
Main Authors: Yim, Lai Sum, Vo, Quang TN, Huang, Ching-I, Wang, Chi-Ruei, McQueary, Wren, Wang, Hsueh-Cheng, Huang, Haikun, Yu, Lap-Fai
Format: Conference Proceeding
Language:English
Published: IEEE 23-10-2022
Subjects:
Manipulators
Pose estimation
Real-time systems
Robot vision systems
Streaming media
Three-dimensional displays
Virtual reality
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Summary:This paper presents an easy-to-deploy, virtual reality-based teleoperation system for controlling a robot arm. The proposed system is based on a consumer-grade virtual reality device (Oculus Quest 2) with a low-cost robot arm (a LoCoBot) to allow easy replication and set up. The proposed Work-from-Home Virtual Reality (WFH-VR) system allows the user to feel an intimate connection with the real remote robot arm. Virtual representations of the robot and objects to be manipulated in the real-world are presented in VR by streaming data pertaining to orientation and poses. The user studies suggest that 1) the proposed telerobotic system is effective under conditions both with and without network latency, whereas a method that simply streams video does not. This design enables the system implemented at an arbitrary distance from the actual work site. 2) The proposed system allows novices to perform manipulation tasks requiring higher dexterity than traditional keyboard controls can support, such as setting tableware. All results, hardware settings, and questionnaire feedback can be obtained at https://arg-nctu.github.io/projects/vr-robot-arm.html.
ISSN:2153-0866
DOI:10.1109/IROS47612.2022.9981729