Biologically inspired locomotion control of bipedal robot

Abstract

Due to recent growing popularity of humanoid robots in academia and industry, thebipedal locomotion control has become a fundamental issue of legged robotics. In thisthesis, we develop a simple control strategy based on biological inspiration to control thelocomotion of a bipedal robot. The control strategy utilizes a set of coupled neural oscillatorsto mimic the neural activities of the Central Pattern Generator (CPG) that is foundat the spinal cord of many vertebrate animals. The control strategy is tested on a ten Degreesof Freedom (DOF) model of bipedal robot. Simulation results suggest that due tothe coupling of the neural oscillators of CPG and the feedback from the environment, thealgorithm can generate stable and coordinated walking patterns of the bipedal robot onboth level and uneven ground.