基于光节点模型的PRM路径规划优化算法研究  

Research on PRM Path Planning OptimizationAlgorithm Based on Optical Node Model

作　　者：韩超 杨杰[1] HAN Chao;YANG Jie(College of Mechanical and Electrical Engineering,Qingdao University,Qingdao 266071,China)

机构地区：[1]青岛大学机电工程学院,山东青岛266071

出　　处：《青岛大学学报（工程技术版）》2022年第4期36-42,共7页Journal of Qingdao University(Engineering & Technology Edition)

摘　　要：针对移动机器人存在的使用传统概率路线图算法(probabilistic roadmap,PRM)经过狭窄空间规划路径无解的问题,本文主要对一种模拟光照节点模型的PRM路径规划优化算法进行研究。采用光照方法,将每个节点视为光源,在未照亮的区域生成随机节点,直至光照区域能将起始点和目标点连通,生成无向有权图的边,为了测试优化PRM算法的性能,将其与传统PRM算法进行仿真测试。仿真结果表明,与传统PRM算法相比,优化后的算法可使移动机器人经过狭窄直线通道时采用较少的随机采样点,并且在较短时间内找到一条可行路径。该优化算法减少了路径中的节点数量,提高了路径平滑度和程序运行效率,解决传统PRM算法路径规划无解的问题,缩短了在狭窄直线地图中规划路径的时间,提高了程序运行效率。该研究具有广泛的应用前景。Aiming at the problem that there is no solution to the path planning of mobile robot through narrow space using the traditional probabilistic roadmap(PRM),this paper mainly studies a PRM path planning optimization algorithm simulating the lighting node model.Using the illumination method,each node is regarded as a light source,and random nodes are generated in the unlighted area until the illumination area can connect the starting point with the target point and generate the edge of the undirected weighted graph.In order to test the performance of the optimized PRM algorithm,it is simulated with the traditional PRM algorithm.The simulation results show that compared with the traditional PRM algorithm,the optimized algorithm can make the mobile robot use fewer random sampling points when passing through the narrow linear channel,and find a feasible path in a short time.The optimization algorithm reduces the number of nodes in the path,improves the smoothness of the path and the running efficiency of the program,solves the problem of no solution in the path planning of the traditional PRM algorithm,shortens the time of planning the path in the narrow straight line map,and improves the running efficiency of the program.This research has broad application prospects.

关 键 词：概率路线图算法 路径规划 自主移动机器人 基于采样的运动规划 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]