Locomotion control of quadruped robots based on central pattern generators

Abstract

This paper presents a biological inspired control strategy for a quadruped robot. A Central pattern generator (CPG) network and a knee-to-hip mapping function are presented to realize the rhythmic motion for the quadruped robot. Based on genetic algorithm (GA), basic animal-like gait patterns can be realized. Moreover, the animal's vestibular reflex mechanism is mimicked to realize the adaptive walking of the quadruped robot on slope terrain. Entrainment with the sensory feedback from robot-environment interaction, the robot can walk up and down a slope smoothly. The presented CPG-based control method is validated through simulations and experiments with AIBO. Under the control of the presented CPG network, AIBO can realize animal-like walking pattern. Couples with the body attitude feedback signals, it also can cope with slipping, falling down and walk on a slope successfully, which demonstrate the effectiveness of the proposed biological inspired control method.