论文部分内容阅读
针对传统粒子群路径规划不能根据不同环境调节路径节点数、搜索效率低、甚至在一些地形下得不到可行解的不足,提出一种基于变维粒子群的路径规划算法.通过动态改变粒子的维度,控制路径节点数目并调整节点分布,加快了算法收敛速度.在需要沿障碍物迂回才能通过的复杂障碍物的情况下,采用一次位置记忆的避障算法得到无障碍路径.仿真结果表明,该算法可获得较优的路径且收敛速度较快.
Aiming at the problem that path planning of traditional particle swarm optimization (PSO) can not adjust the number of nodes in different environments and the search efficiency is low, even though some feasible solutions are not available under some terrains, a path planning algorithm based on variable-dimensional particle swarm optimization Dimension, control the number of nodes in the path and adjust the distribution of nodes to speed up the convergence of the algorithm.In the case of complicated obstacles that need to be passed along the obstacle, a path avoidance algorithm based on location memory is used to get the obstacle-free path.The simulation results show that, The algorithm can obtain a better path and converge faster.