复杂环境下的移动机器人路径规划

为了提高移动机器人在复杂环境下的路径规划能力, 通过双层路径规划思想研究了移动机器人路径规划问题：用栅格法对机器人工作环境进行建模,首先采用改进的遗传算法进行全局路径规划,解决了由于交叉概率和变异概率选择不当导致最优个体丢失的问题；然后,在规划好的全局路径的基础上利用改进的人工势场法进行局部动态避障,解决了局部极小点问题。结果表明：移动机器人能够在复杂环境下规划出一条无碰撞的优化路径。可见改进算法的有效性。

The Path Planning of Mobile Robots in Complex Environment

In order to improve the path planning ability of mobile robots in complex environment, a two-level path planning idea was used to investigate the path planning of mobile robots: The mobile robots working environment was modeled with the grid method. First, the improved genetic algorithm was used to plan the global path, and the problem of optimal individual loss caused by the improper selection of crossover probability and mutation probability was solved; Then, the improved artificial potential field algorithm was used to avoid the local dynamic obstacles based on global path, and the problem of local minima was solved. The results show that an optimization without collision path can be planned by mobile robots in complex environment. It is concluded that the improved algorithm is effective.