PSO-RRT机器人可行路径搜索融合算法  

PSO-RRT robot feasible path search fusion algorithm

作　　者：宋云云 李兴鑫 SONG Yunyun;LI Xingxin(Faculty of Big Data and Information Engineering,Guiyang Institute of Humanities and Technology,Guiyang 550025,China)

机构地区：[1]贵阳人文科技学院大数据与信息工程学院,贵阳550025

出　　处：《智能计算机与应用》2025年第1期165-170,共6页Intelligent Computer and Applications

基　　金：贵阳人文科技学院校级科研基金项目(2023rwjs033)。

摘　　要：针对传统RRT算法在静态障碍环境下进行可行路径搜索时存在采样率低、搜索时间长等问题,提出了PSO-RRT算法。PSO-RRT算法是一种将PSO(粒子群)算法融合RRT(快速扩展随机树)算法中的机器人可行路径搜索算法。该算法主要引入一个采样拒绝率参数改变随机采样方式,使用PSO算法来优化RRT算法中的随机采样拒绝率、扩展步长等参数,以减小RRT算法的平均采样点数和搜索时间,提高搜索效率。在3种不同的障碍环境下进行仿真实验,验证了PSO-RRT融合算法的有效性,其算法的平均采样点数、平均搜索时长、平均路径长度等评价指标较优于对比算法。PSO-RRT is proposed to solve some problems of low sampling rate and long search time in the traditional RRT algorithm for feasible path search in static obstacle environments.PSO-RRT,a robot feasible path search algorithm,is proposed by integrating PSO(Particle Swarm Optimization) algorithm and RRT(Rapidly Exploring Random Tree) algorithm.In order to reduce the number of iterations and search time of the RRT algorithm and improve search efficiency,the PSO-RRT algorithm introduces a sampling rejection rate parameter to change the random sampling method,and uses PSO algorithm to optimize parameters such as the random sampling rejection rate and extension step size.The simulation experiments have verified the effectiveness of the PSO-RRT fusion algorithm proposed in this paper in three different obstacle environments,and the experimental results illustrate that the PSO-RRT algorithm outperforms the comparison algorithm in terms of iteration times,search time,and path length.

关 键 词：RRT算法 PSO算法 可行路径 参数优化 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]