移动机器人导航路径的自主学习粒子群规划方法  

Mobile Robot Navigation Path Planning Method Autonomous Learning Particle Swarm Algorithm

作　　者：吴妮妮[1] 王岫鑫 WU Ni-ni;WANG Xiu-xin(Changjiang Polytechnic,Hubei Wuhan 430074,China;Chongqing University of Posts and Telecommunications,College of Bioinformatics,Chongqing 400065,China)

机构地区：[1]长江职业学院,湖北武汉430074 [2]重庆邮电大学生物信息学院,重庆400065

出　　处：《机械设计与制造》2024年第7期342-346,共5页Machinery Design & Manufacture

基　　金：2020湖北省级教学改革研究项目(2020889);2021年湖北省中华职业教育社研究项目(HBZJ2021150)。

摘　　要：为了减小移动机器人行驶路径长度,提出了基于自主学习粒子群算法的导航路径规划方法。以减小路径长度为目标建立了路径规划模型;为了防止机器人发生碰撞,给出了障碍物膨化处理方法。在粒子群算法中引入了由多种粒子学习策略组成的学习策略池,并给出了粒子对学习策略进行选择的自主学习策略,从而提出了具有较强进化能力的自主学习粒子群算法。经算法性能测试,自主学习粒子群算法的优化能力强于传统粒子群算法和文献[11]改进粒子群算法;将自主学习粒子群算法应用于简单场景和复杂场景的路径规划,该算法规划的路径均值和标准差均小于传统粒子群算法,验证了自主学习粒子群算法在机器人路径规划中的优越性。In order to reduce the path length of mobile robot,a navigation path planning method based on autonomous learning particle swarm algorithm is proposed.A path planning model is established aiming at reducing the path length;In order to prevent collision of robot,the method of obstacle expansion is given.In particle swarm optimization,a learning strategy pool composed of multiple particle-learning strategies is introduced,and the autonomous learning strategy of selecting learning strategies by particles is given,thus an autonomous learning particle swarm optimization algorithm with strong evolutionary ability is proposed.Through the algorithm performance test,the optimization ability of the autonomous learning particle swarm optimization algorithm is better than the traditional particle swarm algorithm and the improved particle swarm algorithm in reference[11];The autonomous learning particle swarm algorithm is applied to the path planning of simple scene and complex scene.The mean and standard deviation of the path planning of the algorithm are both less than those of the traditional particle swarm algorithm,which verifies the superiority of the autonomous learning particle swarm optimization algorithm in robot path planning.

关 键 词：移动机器人 路径规划 学习策略池 自主学习策略 粒子群算法 

分 类 号：TH16[机械工程—机械制造及自动化] TP242[自动化与计算机技术—检测技术与自动化装置]