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A task learning mechanism for the telerobots

Luo, Jing; Yang, Chenguang; Li, Qiang; Wang, Min

Authors

Jing Luo

Qiang Li

Min Wang



Abstract

Telerobotic systems have attracted growing attention because of their superiority in the dangerous or unknown interaction tasks. It is very challengeable to exploit such systems to
implement complex tasks in an autonomous way. In this paper, we propose a task learning framework to represent the manipulation skill demonstrated by a remotely controlled robot.
Gaussian mixture model is utilized to encode and parametrize the smooth task trajectory according to the observations from the demonstrations. After encoding the demonstrated trajectory, a new task trajectory is generated based on the variability information of the learned model. Experimental results have demonstrated the feasibility of the proposed method.

Journal Article Type Article
Journal International Journal of Humanoid Robotics
Print ISSN 0219-8436
Publisher World Scientific Publishing
Peer Reviewed Peer Reviewed
Pages 1950009
Institution Citation Luo, J., Yang, C., Li, Q., & Wang, M. (in press). A task learning mechanism for the telerobots. International Journal of Humanoid Robotics, 1950009. https://doi.org/10.1142/S0219843619500099
DOI https://doi.org/10.1142/S0219843619500099
Publisher URL http://doi.org/10.1142/S0219843619500099

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