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	Autonomous Evolution of High-Speed Quadruped Gaits Using Particle Swarm Optimization
	Rong, Chunxia ; Wang, Qining ; Huang, Yan ; Xie, Guangming ; Wang, Long
	2009
关键词	RUNNING GAITS
DOI	10.1007/978-3-642-02921-9_23
英文摘要	This paper presents a novel evolutionary computation approach to optimize fast forward gaits for a quadruped robot with three motor-driven joints on each limb. Our learning approach uses Particle Swarm Optimization to search for a set of parameters automatically aiming to develop the fastest. gait, that. an actual quadruped robot can possibly achieve, based on the concept of parameterized representation for quadruped gaits. In addition, we analyze the computational cost. of Particle Swarm Optimization taking the memory requirements and processing limitation into consideration. Real robot experiments show that the evolutionary approach is effective in developing quadruped gaits. Satisfactory results are obtained in less than an hour by the autonomous learning process, which starts with randomly generated parameters instead of any hand-tuned parameters.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000269207300023&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Computer Science, Artificial Intelligence; Robotics; EI; CPCI-S(ISTP); 1
语种	英语
内容类型	会议论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/316512]
专题	工学院
推荐引用方式 GB/T 7714	Rong, Chunxia,Wang, Qining,Huang, Yan,et al. Autonomous Evolution of High-Speed Quadruped Gaits Using Particle Swarm Optimization[C]. 见:.

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