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Adaptive walking control of quadruped robots based on central pattern generator (CPG) and reflex

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Abstract

This paper presents a central pattern generator (CPG) and vestibular reflex combined control strategy for a quadruped robot. An oscillator network and a knee-to-hip mapping function are presented to realize the rhythmic motion for the quadruped robot. A two-phase parameter tuning method is designed to adjust the parameters of oscillator network. First, based on the numerical simulation, the influences of the parameters on the output signals are analyzed, then the genetic algorithm (GA) is used to evolve the phase relationships of the oscillators to realize the basic animal-like walking pattern. Moreover, the animal’s vestibular reflex mechanism is mimicked to realize the adaptive walking of the quadruped robot on a slope terrain. Coupled with the sensory feedback information, the robot can walk up and down the slope smoothly. The presented bio-inspired control method is validated through simulations and experiments with AIBO. Under the control of the presented CPG and vestibular reflex combined control method, AIBO can cope with slipping, falling down and walk on a slope successfully, which demonstrates the effectiveness of the proposed walking control method.

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Authors and Affiliations

  1. Department of Electronics and Information Engineering, and Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai, 201804, China

    Chengju Liu, Qijun Chen & Guoxing Wang

Authors
  1. Chengju Liu
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  2. Qijun Chen
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  3. Guoxing Wang
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Corresponding author

Correspondence to Qijun Chen.

Additional information

This work was supported by the National Natural Science Foundation of China (No. 61203344), the International Technology Cooperation Project (No. 2010DFA12210), the China Postdoctoral Science Foundation (No. 2011M500627), the Shanghai Science and Technology Committee Talent Program (No. 11XD1404800), and the ‘Dawn Tracking’ Program of Shanghai Education Commission, China (No. 10GG11).

Chengju LIU is a postdoctoral fellow at the School of Electronics and Information Engineering, Tongji University, Shanghai, China. She received her Ph.D. degree from Tongji University in 2011. She received her M.S. degree from Qingdao University of Science and Technology, China, in 2007. Her research interests include control of robotics and bioinspired control.

Qijun CHEN is a professor at the School of Electronics and Information Engineering, Tongji University, Shanghai, China. He received his B.S. degree in Automatic Control from Huazhong University of Science and Technology, Wuhan China, in 1987, M.S. degree in Control Engineering from Xi’an Jiaotong University, Xi’an, China, in 1990, and Ph.D. degree in Control Theory and Control Engineering from Tongji University, Shanghai, China, in 1999, respectively. His current research interests include robust and process control, network based control systems, and biological induced locomotion control methods for robots.

Guoxing WANG is a M.S. candidate at the School of Electronics and Information Engineering, Tongji University, Shanghai, China. He received his B.S. degree from the School of Electronics and Information Engineering, Tongji University, Shanghai, China, in 2005.

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Liu, C., Chen, Q. & Wang, G. Adaptive walking control of quadruped robots based on central pattern generator (CPG) and reflex. J. Control Theory Appl. 11, 386–392 (2013). https://doi.org/10.1007/s11768-013-1171-6

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  • DOI: https://doi.org/10.1007/s11768-013-1171-6

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