Evolutionary generation of human-like bipedal locomotion

Abstract This paper shows how the computational model, which simulates the coordinated movements of human-like bipedal locomotion, can be evolutionarily generated without elaboration of manual coding. In the research of biomechanical engineering, robotics and neurophysiology, to clarify the mechanism of human bipedal walking is of their major interest. It can serve as a basis of developing several applications such as rehabilitation tools and humanoid robots. Nevertheless, because of complexity of human’s neuronal system that interacts with the body dynamics system to make walking movements, much is left unknown about the control mechanism of locomotion, and researchers were looking for the optimal model of the neuronal system by extensive efforts of trials and errors. In this paper, we applied genetic programming to induce the model of the nervous system automatically and showed its effectiveness by simulating a human bipedal gait with the obtained model. Our experimental results show some promising evidences for evolutionary generation of the human-like bipedal locomotion.