Abstract
This paper presents a learning approach to acquire holding-up manipulation by a humanoid robot. Information of force sensors attached at the surface of the arms are mapped to a lower-dimensional space and utilized to find a better configuration for the manipulation task. The proposed motion generation framework was verified by simulations with a humanoid robot. It was shown that the robot could judge failure of its manipulation using force sensor information, and succeed to modify its configuration so as to realize holding-up manipulation.
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More From: The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
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