蚁群遗传融合算法在移动机器人路径规划中的应用  

Application of Ant Colony Genetic Algorithm in Path Planning of Mobile Robot

作　　者：于树科[1] 瞿国庆[1] 祁宏宇[1] 赵开新 

机构地区：[1]江苏商贸职业学院,江苏南通226011 [2]河南工学院,河南新乡453002

出　　处：《火力与指挥控制》2017年第12期88-91,共4页Fire Control & Command Control

基　　金：江苏省"333"工程科研基金(BRA2014096);江苏省第十四批"六大人才高峰"高层次人才培养基金(XYDXX-121);河南省高等学校重点科研基金资助项目(16A520084)

摘　　要：针对移动机器人路径规划的特点,把智能算法引入到机器人路径规划中。而单一蚁群算法和遗传算法,存在收敛速度慢、效率低或容易陷入局部最优等缺陷,对蚁群算法进行改进,提出一种改进蚁群遗传算法的融合方案,并把该方案应用到移动机器人路径规划中,在栅格环境下进行仿真测试,仿真结果表明该方案能有效提高最优路径的搜索效率,整体性能优于蚁群或遗传单一智能算法。In view of the characteristic of path planning for robot, Intelligent algorithm is introduced to the mobile robot path planning,And a single ant colony algorithm or genetic algorithm,has slow convergence speed,low efficiency or local optimization,In this paper,improving ant colony algorithm,a fusion scheme of improved ant colony genetic algorithm is proposed. and is applied to the path planning of mobile robot. The simulation test in grid environment,simulation results shows that the method can improve the efficiency of the optimal path searching effectively, the overall performance is better than the ant colony or genetic single intelligent algorithm.

关 键 词：路径规划 蚁群算法 遗传算法 最优路径 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]