QQ客服 官方微博 反馈留言

	Stable biped gait generation algorithm based on T-S fuzzy reinforcement learning method
	Hu Ling-Yun ; Sun Zeng-Qi
	2010-05-06 ; 2010-05-06
关键词	Theoretical or Mathematical Experimental/ fuzzy neural nets fuzzy set theory gait analysis learning (artificial intelligence) legged locomotion/ stable biped gait generation algorithm T-S fuzzy reinforcement learning method fuzzy network fuzzy rules zero moment point curve hip trajectory Luna biped robot/ C3390C Mobile robots C1230L Learning in AI C1230D Neural nets C1160 Combinatorial mathematics
中文摘要	A stable gait generation algorithm based on T-S type fuzzy learning net method is proposed in this paper. Reinforcement learning method is introduced into fuzzy network to learn the gain parameters. Few fuzzy rules are needed to formulate the nonlinear relation between the ZMP (zero moment point) curve and hip trajectory. The problem of multi-variables in continuous space is also simplified to search the independent action gains simultaneously. Simulation experiments on the Luna biped robot prove its feasibility.
语种	中文 ; 中文
出版者	Chinese Assoc. of Automation ; China
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/10393]
专题	清华大学
推荐引用方式 GB/T 7714	Hu Ling-Yun,Sun Zeng-Qi. Stable biped gait generation algorithm based on T-S fuzzy reinforcement learning method[J],2010, 2010.
APA	Hu Ling-Yun,&Sun Zeng-Qi.(2010).Stable biped gait generation algorithm based on T-S fuzzy reinforcement learning method..
MLA	Hu Ling-Yun,et al."Stable biped gait generation algorithm based on T-S fuzzy reinforcement learning method".(2010).

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。