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Abstract:
It is an effective way for the robots to learn operation skills from the humans. In this paper, we realize a skill learning system based on a teleportation system for transferring the human experience to the robot. Firstly, the robotic teleoperation system with a wearable device is developed by controlling the motor speed directly. This system greatly reduces the time delay by comparing with the way that controlling with point position. Then, a rotation invariant dynamical movement primitive method is presented for learning the operation skills. Finally, the effectiveness of the proposed human experience learning system is evaluated by experiments on a Baxter robot. The human-robot interaction experiment shows the validity of the presented robotic skill learning system.
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Source :
2017 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (IEEE ROBIO 2017)
Year: 2017
Page: 756-761
Language: English
Cited Count:
WoS CC Cited Count: 3
SCOPUS Cited Count:
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 0
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