基于遗传算法和人工势场法的路径规划

Path planning based on genetic algorithms and artificial potential field

在移动机器人的研究中,路劲规划是一个最基本也最复杂的问题。为了得到适合于机器人行走,以及全局最优的路径,采用遗传算法与人工势场法相结合的方法进行机器人的路径规划。首先采用遗传算法规划出全局最优或近似最优的无碰撞路径;再通过改进的人工势场法优化路径,增加路径节点,使路径更平滑。仿真实验结果表明,使用该方法所规划的路径是有效的和可行的。

The path planning for the mobile robot under dynamic environment was researched with a new method, in which the genetic algorithms and improved artificial potential field were combined to get optimal global path suitable for mobile robots. An optimal or vice-optimal global path is planned with the genetic algorithms, and then the path is optimized by using the method of the improved artificial potential field, so that the robot can move smoothly along the path without collision of obstacles. This method makes full use of advantages of genetic algorithms and artificial potential field. The simulation results prove that this method is effective and feasible.