关键词: 四足机器人, Hopf模型, 中枢模式发生器（CPG）, 粒子群算法（PSO）, 自适应权重

Abstract: In order to solve the stability problem of the quadruped robot when its center of mass deviates from the geometric center of the torso, this paper proposes an optimization method based on an improved particle swarm algorithm. Firstly, it uses an oscillator based on the Hopf model to build a central pattern generator（central pattern generator, CPG） network topology, through the trajectory planning of the foot to determine the relevant parameters of the CPG model, and optimize the coupling coefficient matrix between the CPG units to enable it to output the correct gait signal. Then it uses the adaptive weight adjustment particle swarm. The algorithm quickly finds the optimal parameter combination of the output model through continuous iteration, and solves the stability problem caused by the shift of the center of gravity. Finally, using Webots and MATLAB to conduct simulation experiments on the proposed optimization method, the simulation results prove that the method can quickly and effectively improve the motion stability of the quadruped robot under the condition of shifting the center of gravity.

Key words: quadruped robot, Hopf model, central pattern generator（CPG）, particle swarm optimization（PSO）, adaptive weight