Static Gait Optimization Method for Quadruped Robot Based on Particle Swarm Optimization Algorithm

Focusing on static gait planning problem when the quadruped robot was adjusting laterally, a new method based on particle swarm optimization (PSO) was proposed to optimize the lateral adjustment parameter. The design variable was the body lateral adjustment parameter in motion. Stability, linearity and other motion performances were considered comprehensively in the objective function. Besides, the simulation experiments were carried out to verify the proposed optimization method in Matlab and Adams. Experimental results show the searching of global optimal parameters can be done quickly and efficiently by the proposed algorithm, such that the robot can achieve a good performance during static gait.