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DOI: http://dx.doi.org/10.7551/978-0-262-31719-2-ch182
Pages 1182-1190
First published 2 September 2013

Crawling Posture Learning in Humanoid Robots using a Natural-Actor-Critic CPG Architecture

Cai Li, Robert Lowe, Tom Ziemke

Abstract

In this article, a four-cell CPG network, exploiting sensory feedback, is proposed in order to emulate infant crawling gaits when utilized on the NAO robot. Based on the crawling model, the positive episodic natural-actor-critic architecture is applied to learn a proper posture of crawling on a simulated NAO. By transferring the learned results to the physical NAO, the transferability from simulation to physical world is discussed. Finally, a discussion pertaining to locomotion learning based on dynamic system theory is given in the conclusion.