改进Informed-RRT^(*)算法的移动机器人路径规划  

An Improved Informed-RRT^(*) Algorithm for Mobile Robot Path Planning

作　　者：葛超 张鑫源 王红 伦志新 GE Chao;ZHANG Xinyuan;WANG Hong;LUN Zhixin(School of Electrical Engineering,North China University of Science and Technology,Tangshan 063000,China;Computer Centre of Tangshan University,Tangshan 063000,China)

机构地区：[1]华北理工大学电气工程学院,河北唐山063000 [2]唐山学院计算中心,河北唐山063000

出　　处：《电光与控制》2025年第1期48-53,共6页Electronics Optics & Control

基　　金：河北省自然科学基金(F2021209006)。

摘　　要：针对Informed-RRT^(*)算法初始路径形成缓慢、失败率高及路径质量差的问题,提出基于人工势场法的选点策略。首先,筛选出优质采样点,同时,引入双向直连的贪心策略和动态步长策略,快速获得初始路径并尽快进入遍历寻优阶段;其次,通过新的采样策略及评价函数,保证规划路径更优;最后,对路径优化处理,所得路径更适合移动机器人的行驶。仿真实验结果表明,改进算法相比于Informed-RRT^(*)算法性能更优,其中,改进算法在不同环境中的成功率均为100%,同时也证明了在限定采样次数下改进算法的收敛速度、路径质量均优于原算法。To address the issues of slow initial path formation,high failure rate,and poor path quality of Informed-RRT^(*)algorithm,a point selection strategy based on the artificial potential field method is proposed to select high-quality sampling points.The greedy strategy with bidirectional direct connection and the dynamic step size strategy are introduced,so as to quickly obtain the initial path and enter the traversal optimization stage as soon as possible.Then,by implementing new sampling strategies and evaluation functions,the planned path is guaranteed to be more optimal.Finally,the path is optimized,so that the obtained path is more suitable for the operation process of mobile robots.The simulation results show that the improved algorithm has better performance than the Informed-RRT^(*)algorithm.All the success rates of the improved algorithm in different environments are 100%.It is also proved that the convergence rate and path quality of the improved algorithm are better than those of the original algorithm under limited sampling times.

关 键 词：移动机器 路径规划 人工势场法 动态步长 路径优化处理 Informed-RRT^(*) 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]