%0 Journal Article
%T Skill Learning for Human-Robot Interaction Using Wearable Device
%A Bin Fang
%A Xiang Wei
%A Fuchun Sun
%A Haiming Huang
%A Yuanlong Yu
%A Huaping Liu
%J 清华大学学报自然科学版（英文版）
%@ 1878-7606
%D 2019
%R 10.26599/TST.2018.9010096
%X 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
%K skill learning
%K interaction
%K teleoperation
%K dynamical movement primitive
%U http://tst.tsinghuajournals.com/EN/10.26599/TST.2018.9010096