Stable Gait Optimization for Small-Sized Humanoid Robot Using CFO

Abstract

This paper proposes a new way to optimize the gait design for human robots that allows stable stepping with preset foot-lifting magnitude. The novel Central Force Optimization (CFO) algorithm is used to optimize the gait parameters to help humanoid robot walk steadily. The efficiency of the proposed method is compared with the GA-Genetic Algorithm, PSO-Particle Swarm Optimization and improved differential evolution algorithm (MDE-Modified Differential Evolution). The simulated and experimental results applied on the small-sized humanoid robot show that the newly proposed algorithm offers an efficient and stable gait for humanoid robots with accurate foot-lifting magnitude.