Locomotion control of quadruped robots based on central pattern generators

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.