基于粒子群算法的四足机器人静步态优化方法

针对四足机器人机身因实现平衡稳定而进行横向调整的静步态稳定性规划问题，提出了一种新的基于粒子群算法的四足机器人机身横向调整参数优化方法.算法以运动过程中机身的横向调整参数为设计变量，其目标函数综合考虑了四足机器人躯体稳定性、行走直线性等运动性能，并利用Matlab与Adams软件对所提出的优化方法进行了一系列仿真实验验证.仿真实验结果表明:所提优化方法可以快速有效地寻求全局最优参数，使四足机器人能够实现具有良好运动性能的静步态. 

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.