Novel Stable Walking for Humanoid Robot Using Particle Swarm Optimization Algorithm

摘要

This paper describes a novel walking gait generation algorithm based on inverse kinematics for a biped robot. The proposed algorithm uses the PSO (Particle Swarm Optimization) algorithm in order to find optimized values for the five walking algorithm parameters. The proposed experiment approach is tested on a small-sized humanoid robot in the DCSELAB, VNU-HCM. Simulation and experimental results reveal that using the PSO algorithm with an efficient fitness function can significantly reduce learning time. Moreover, a considerable fast walking speed is achieved.