移动机器人全局路径规划的增强蚁群优化算法  

Enhanced ant Colony Optimization Algorithm for Global Path Planning of Mobile Robots

作　　者：高敏[1] 周之平[1] 黎明[1] 

机构地区：[1]南昌航空大学,江西南昌330063

出　　处：《南昌航空大学学报（自然科学版）》2011年第4期48-53,共6页Journal of Nanchang Hangkong University(Natural Sciences)

基　　金：国家自然科学基金(60963002);江西省自然科学基金(2009GZS0090)

摘　　要：针对复杂环境下移动机器人全局路径规划问题,提出了一种增强蚁群优化算法。该算法通过改进信息素初始化和状态转移概率,避免了路径死锁;将视野区域内的确定性搜索与随机性搜索相结合,改善了迂回曲折现象;引入局部信息素扩散机制,提高了算法的全局优化能力。仿真结果表明:当环境中障碍物分布密集或存在大量的凹形区域时,新算法能有效地规划出较为理想的安全路径,规划时间可满足实际应用要求。An enhanced ant colony optimization algorithm is proposed to plan global path of mobile robots under complicated environments.The path-locked phenomenon is avoided through modifying both initial environment pheromone and state transition probability.The determinant search based on interest area of viewpoint,combined with stochastic search,improves the roundabout of trajectory.Local pheromone diffusion mechanism is introduced to advance global optimization performance.The experimental results show that the new algorithm can provide desirable safety path under the complex situation which contains overly dense obstacles or many concave regions,and computational time can meet the requirement of particle applications.

关 键 词：移动机器人 路径规划 蚁群算法 信息素扩散 死锁 迂回 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]