NDLI: A mixed-kernel-based SVR controller for biped robots

Content Provider	IEEE Xplore Digital Library
Author	Wang Li-Yang Liu Zhi Zhao Zhi-Guang Zhang Yun
Copyright Year	2011
Description	Author affiliation: Department of Electronic Engineering, Shunde Polytechnic, Foshan Guangdong 528300, China (Wang Li-Yang) \|\| Faculty of Automation, Guangdong University of Technology, Guangzhou 510006, China (Liu Zhi; Zhao Zhi-Guang; Zhang Yun)
Abstract	Aiming at the stable walking control problem in the dynamic environments for biped robots, this paper puts forward a method of gait control based on support vector machine(SVM), which provides a solution for the learning control issue based on small sample sizes. Using ankle trajectory and hip trajectory as inputs, and the corresponding trunk trajectory, which guarantees the ZMP criterion as outputs, the SVM is trained based on small sample sizes to learn the dynamic kinematics relationships between the legs and the trunk of the biped robots. The trained SVM is incorporated into the control system of the robots. Robustness of the gait control is enhanced, which is propitious to realize the stable biped walking. Simulation results demonstrate the superiority of the proposed methods.
Starting Page	3925
Ending Page	3930
File Size	158919
Page Count	6
File Format	PDF
ISBN	9781457706776
ISSN	21612927
e-ISBN	9789881725592
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Assoc of Automati
Subject Keyword	Legged locomotion Support vector machines Small sample sizes Gait Polynomials Biped robots Trajectory Learning control Kernel Hip SVR
Content Type	Text
Resource Type	Article

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