机械科学与技术2018，Vol.37Issue(2)：244-249,6.DOI:10.13433/j.cnki.1003-8728.2018.0213
粒子群优化算法融合行为动力学的路径规划方法研究
Research on Path Planning Method of Particle Swarm Optimization Algorithm and Fusion Behavior Dynamics
摘要
Abstract
When using competitive behavior dynamics coordination methods to mobile robot path planning in unknown environment,the robot motion velocity parameters are difficult determined and it is easy to generate parameter oscillation in behavior competition,leading to the path of planning not optimization.A new path planning method based on particle swarm optimization for behavior dynamics algorithm is proposed.In this method,the particle swarm optimization algorithm is used to integrate the basic behaviors in path planning process based on the behavior dynamics model,which instead of the behavior parameter coordination of the competitive behavior dynamics.So that the robot can automatically obtain the weight of each basic behavior according to the real-time environment information collected by the vision senor.By comparing the proposed method with the competitive behavior dynamic coordination methods,the experiment results verify the feasibility and superiority of the proposed method.关键词
移动机器人/路径规划/行为动力学/粒子群优化/未知环境Key words
mobile robot/path planning/behavior dynamics/particle swarm optimization/unknown environment分类
信息技术与安全科学引用本文复制引用
葛媛媛,张宏基,唐虹..粒子群优化算法融合行为动力学的路径规划方法研究[J].机械科学与技术,2018,37(2):244-249,6.基金项目
国家自然科学基金项目(10872160)与陕西省科技厅项目(2016GY-027)资助 （10872160）
