基于细胞自动机的移动机器人路径规划算法

针对移动机器人全局最优路径规划问题,提出一种基于细胞自动机的路径规划算法.该算法首先将移动机器人的起点、目标点和空间障碍物定义为一组离散的细胞状态,建立环境的细胞自动机模型;然后由机器人移动的曼哈顿距离设计演化规则;最后根据演化后的细胞状态搜索最优路径.对简单和复杂环境下的机器人路径规划问题进行了仿真实验,实验结果验证了该算法的有效性.

Robot path planning algorithm based on cellular automata

For global optimal path planning of mobile robot, a path planning algorithm based on cellular automata is
proposed. This algorithm defines the robot’s starting point, target point and the obstacle points in the environment as a
group of discrete cellular states, and builds cellullar automata model of environment, then designs evolution rules by the
robot’s Manhattan distance. Finally, the optimal path can be found out according to the cellular states after evolution. The
simulation results show the effectiveness of the proposed algorithm.