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Document type:
Konferenzbeitrag 
Contribution type:
Textbeitrag / Aufsatz 
Author(s):
Jun Morimoto, Gordon Cheng, Christopher G Atkeson, Garth Zeglin 
Title:
A simple reinforcement learning algorithm for biped walking 
Pages contribution:
3030-3035 
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 measurements. We present simulation results, and are currently implementing this approach...    »
 
Editor:
IEEE 
Book / Congress title:
IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA'04. 2004 
Volume:
Organization:
IEEE 
Year:
2004 
Year / month:
2004-04 
Reviewed:
ja 
Language:
en