基于移动机器人路径规划的鼠群算法  

Mouse colony optimization algorithm for mobile robot path planning

作　　者：刘徐迅[1] 曹阳[1] 陈晓伟[2] 

机构地区：[1]武汉大学电子信息学院,武汉430072 [2]华南理工大学机械与汽车工程学院,广州510641

出　　处：《控制与决策》2008年第9期1060-1064,共5页Control and Decision

基　　金：国家自然科学基金项目(60132030);教育部博士点基金项目(20040486049)

摘　　要：研究静态环境下机器人路径规划问题,并根据老鼠觅食行为提出一种鼠群算法.该算法引入环境因子和经验因子,每次搜索后对路径进行经验因子更新,通过迭代的方式寻找静态环境下机器人最佳路径.同时提出一种禁忌策略,有效地避免了路径死锁问题.理论分析和实验结果表明,该算法能使机器人在有较多障碍的环境下迅速找到一条优化路径,而且安全避碰,与同类算法相比具有一定的优越性.Robot path planning in a static environment is studied and mouse colony optimization is proposed after studying the mice＇ behavior of searching for food. Environment factor and experience factor are introduced. By using iterative method, the experience factor is updated after each search to find the best robot path in a static environment. Prohibition strategies are developed and thus path deadlocks are effectively avoided. Theoretic analysis and experimental results show that this algorithm enables the robot to rapidly find the optimal path and safely avoid collisions and it has advantages over other algorithms of the kind.

关 键 词：移动机器人 路径规划 鼠群算法 蚁群算法 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]