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Learning Sensory Feedback to CPG with Policy Gradient for Biped Locomotion

10 years 3 months ago
Learning Sensory Feedback to CPG with Policy Gradient for Biped Locomotion
— This paper proposes a learning framework for a CPG-based biped locomotion controller using a policy gradient method. Our goal in this study is to develop an efficient learning algorithm by reducing the dimensionality of the state space used for learning. We demonstrate that an appropriate feedback controller in the CPG-based controller can be acquired using the proposed method within a few thousand trials by numerical simulations. Furthermore, we implement the learned controller on the physical biped robot to experimentally show that the learned controller successfully works in the real environment.
Takamitsu Matsubara, Jun Morimoto, Jun Nakanishi,
Added 25 Jun 2010
Updated 25 Jun 2010
Type Conference
Year 2005
Where ICRA
Authors Takamitsu Matsubara, Jun Morimoto, Jun Nakanishi, Masa-aki Sato, Kenji Doya
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