机器人路径规划的元胞自动机算法

A Cellular Automata Algorithm for Robot Path Planning

采用Moore型邻居规则建立机器人路径规划的元胞自动机模型和演化规则,通过对移动机器人的路径进行演化,讨论了周围环境已知情况下的移动机器人元胞自动机路径规划问题。在演化规则中增加危险度检测,使得机器人能够避免碰撞和穿越障碍,仿真实验结果表明,利用元胞自动机可以实现复杂环境的机器人路径搜索,避免死锁和碰撞,达到快速的最优路径。

A neighborhood cellular automata model and evolution rules for robot path planning are built using moor rule. Robot path planning under the condition of the known environment is discussed by evolution path for a mobile robot. With help of detection of risk factors in evolution rules,it is avoided for robot to collide with or cross over obstacles the results of simulation experiment show that path planning for the robot under a complex environment can be realized using cellular automata and the performance of a fast global optimal path planning is obtained.