基于改进粒子群算法的移动机器人全局路径规划

Global Path Planning for Mobile Robot Based on Improved Particle Swarm Optimization

在标准粒子群算法的基础上加入混沌初始化、变异以及杂交操作。改进算法在保持标准粒子群算法结构简单、收敛速度快等特点的同时增加了种群的多样性,扩大了粒子搜索空间,有效克服了算法的早熟收敛问题,获得了从起点到终点的最优路径,证明了该方法的有效性和实用性。

In this article,chaos initialization,mutation and cross operation were added to the standard particle swarm optimization.While maintaining the simple structure and fast convergence of the standard particle swarm optimization,the improved algorithms increase the diversity of group,enlarge the search space,avoid the premature convergence problem effectively and obtain the optimal path from starting point to target point.Thus,the effectiveness and practicability of this method were proved.