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On-line learning of a feedback controller for quasi-passive-dynamic walking by a stochastic policy gradient method

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4 Author(s)
K. Hitomi ; Nara Inst. of Sci. & Technol., Japan ; T. Shibata ; Y. Nakamura ; S. Ishii

A class of biped locomotion called passive dynamic walking (PDW) has been recognized to be efficient in energy consumption and a key to understand human walking. Although PDW is sensitive to the initial condition and disturbances, some studies of quasi-PDW, which introduces supplementary actuators, are reported to overcome the sensitivity. In this article, for realization of the quasi-PDW, an on-line learning scheme of a feedback controller based on a policy gradient reinforcement learning method is proposed. Computer simulations show that the parameter in a quasi-PDW controller is automatically tuned by our method utilizing the passivity of the robot dynamics. The obtained controller is robust against variations in the slope gradient to some extent.

Published in:

2005 IEEE/RSJ International Conference on Intelligent Robots and Systems

Date of Conference:

2-6 Aug. 2005