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Open Access

Skill Learning for Human-Robot Interaction Using Wearable Device

Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China.
College of Information Engineering, Shenzhen University, Shenzhen 518060, China.
Fuzhou University, Fuzhou 350108, China.
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Abstract

With the accelerated aging of the global population and escalating labor costs, more service robots are needed to help people perform complex tasks. As such, human-robot interaction is a particularly important research topic. To effectively transfer human behavior skills to a robot, in this study, we conveyed skill-learning functions via our proposed wearable device. The robotic teleoperation system utilizes interactive demonstration via the wearable device by directly controlling the speed of the motors. We present a rotation-invariant dynamical-movement-primitive method for learning interaction skills. We also conducted robotic teleoperation demonstrations and designed imitation learning experiments. The experimental human-robot interaction results confirm the effectiveness of the proposed method.

Keywords

skill learninginteractionteleoperationdynamical movement primitive

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Tsinghua Science and Technology
Volume 24 Issue 6,
December 2019
Pages 654-662
DOI: 10.26599/TST.2018.9010096
Cite this article:
Fang B, Wei X, Sun F, et al. Skill Learning for Human-Robot Interaction Using Wearable Device. Tsinghua Science and Technology, 2019, 24(6): 654-662. https://doi.org/10.26599/TST.2018.9010096

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Received: 09 February 2018
Revised: 13 April 2018
Accepted: 27 April 2018
Published: 05 December 2019
© The author(s) 2019
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