徐义晗, 程乐, 宋艳红, 郭艾华. 双向ACO算法应用于静态机器人全局路径规划研究[J]. 微电子学与计算机, 2012, 29(1): 97-101.
引用本文: 徐义晗, 程乐, 宋艳红, 郭艾华. 双向ACO算法应用于静态机器人全局路径规划研究[J]. 微电子学与计算机, 2012, 29(1): 97-101.
XU Yi-han, CHENG Le, SONG Yan-hong, GUO Ai-hua. Ant Colony Algorithm for Mobile Robot Path Planning[J]. Microelectronics & Computer, 2012, 29(1): 97-101.
Citation: XU Yi-han, CHENG Le, SONG Yan-hong, GUO Ai-hua. Ant Colony Algorithm for Mobile Robot Path Planning[J]. Microelectronics & Computer, 2012, 29(1): 97-101.

双向ACO算法应用于静态机器人全局路径规划研究

Ant Colony Algorithm for Mobile Robot Path Planning

  • 摘要: 提出双向蚁群算法并应用于静态环境下的机器人全局路径规划问题.对栅格法环境建模进行改进, 将传统的栅格法改进为膨胀栅格法;使用双向蚁群算法在出发点和目标点设置带有不同标记的两族蚂蚁相向爬行完成搜索, 启发信息主要通过目标点、出发点和蚂蚁的当前位置二维坐标值计算得出;信息素存储采用方向信息素矩阵.仿真实验证明:即使在障碍物非常复杂的地理环境, 用本算法也能迅速规划出最优路径.

     

    Abstract: In this paper, we puposed a Two Directions ant colony algorithm and apply it to robot path planning in static environment.We changed grid method into expdnded grid method for the environmental models.The optimal path search is finished by two trible's ants opposite crowing from starting point and ending point.Heuristic information is calculated by the coordinate of Starting point, ending point and the posion of ant.Pheromone is reserved by direction pheromone matrix.Resultsof simulation experiments demonstrate that even in obstacles very complicated geographical environment the best path can be found in short time.

     

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