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Summary: A Simple Reinforcement Learning Algorithm For
Biped Walking
Jun Morimoto, Gordon Cheng,
Department of Humanoid Robotics and
Computational Neuroscience
ATR Computational Neuroscience Labs
xmorimo@atr.co.jp, gordon@atr.co.jp
http://www.cns.atr.co.jp/hrcn
Christopher G. Atkeson, and Garth Zeglin
The Robotics Institute
Carnegie Mellon University
cga@cs.cmu.edu, garthz@ri.cmu.edu
http://www.ri.cmu.edu
Abstract-- We propose a model-based reinforcement learning
algorithm for biped walking in which the robot learns to
appropriately place the swing leg. This decision is based on
a learned model of the Poincare map of the periodic walking
pattern. The model maps from a state at the middle of a step
and foot placement to a state at next middle of a step. We
also modify the desired walking cycle frequency based on online
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