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基于蚁群粒子群融合的机器人路径规划算法 被引量:11

Robot Path Planning Based on Ant Colony Optimization and Particle Swarm Optimization
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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。 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.
出处 《计算机系统应用》 2011年第9期98-102,共5页 Computer Systems & Applications
基金 国家自然科学基金(60973095)
关键词 路径规划 蚁群算法 粒子群算法 信息素 path planning ant colony optimization (ACO) particle swarm optimization (PSO) pheromone
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