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DOI:
计算机系统应用英文版:2011,20(9):98-102
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基于蚁群粒子群融合的机器人路径规划算法
(1.江南大学 物联网工程学院,无锡 214122;2.江南大学 机械工程学院,无锡 214122)
Robot Path Planning Based on Ant Colony Optimization and Particle Swarm Optimization
(1.School of Communication and Control Engineering, Jiangnan University, Wuxi 214122, China;2.School of Mechanical Engineering, Jiangnan University, Wuxi 214122, China)
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Received:December 19, 2010    Revised:January 11, 2011
中文摘要: 针对复杂环境下中移动机器人路径规划问题,提出了一种基于蚁群粒子群融合的路径规划算法.该算法首先利用粒子群路径规划的环境建模方法快速规划出起始点到目标点的初始路径.然后根据产生的路径进行信息素的分配,最后经改进的蚁群算法进行进一步寻优,从而找出最优路径.经仿真证明,该方法在寻得最优路径的基础上可大大降低寻优的时间,尤其是对于复杂环境下的路径规划,其效果尤为明显.
Abstract:A novel path planning approach based on particle swarm optimization (PSO) and ant colony optimization (ACO) algorithm is presented aiming at mobile robots in complex environment. Firstly the algorithm makes use of the method of environment modeling of particle swarm to quickly plan a initial path from the starting point to the goal point of the path. Then pheromone is distributed based on the paths generated before. At last, an improved ant colony optimization is used to find the eventually best path. The simulation shows that this method can greatly reduce the searching time, especially in complex environment.
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基金项目:国家自然科学基金(60973095)
引用文本:
王宪,王伟,宋书林,平雪良,彭力.基于蚁群粒子群融合的机器人路径规划算法.计算机系统应用,2011,20(9):98-102
WANG Xian,WANG Wei,SONG Shu-Lin,PING Xue-Liang,PENG Li.Robot Path Planning Based on Ant Colony Optimization and Particle Swarm Optimization.COMPUTER SYSTEMS APPLICATIONS,2011,20(9):98-102