一种改进的未知动态环境下机器人混合路径规划方法

A Robot Hybrid Path Planning Algorithm Under Improved Unknown and Dynamic Environment

动态未知环境下的机器人路径规划是机器人导航领域的重要课题之一,采用传统的方法求解并不理想。针对这个问题,提出一种改进的机器人混合路径规划方法。首先利用改进的文化基因算法规划出较优的全局路径,指引机器人沿着全局路径行走,然后根据传感器探测到的局部环境信息,利用Morphin算法进行局部路径实时规划,使机器人有效地躲避动态障碍物。仿真实验表明,该算法在未知动态路径规划中具有良好的效果。

Robot path planning under dynamic and unknown environment is one of important issues in mobile robot navigation,which is difficult to deal with by traditional methods. Aiming at this problem,an improved hybrid path planning algorithm is proposed. In the proposed approach,an improved Memetic algorithm is used to obtain an optimal global path at first,which is used to navigate the robot. And then a Morphin algorithm is used to plan an optimal local path based on the information sensed to avoid dynamic obstacles. The simulation experiments results show that the proposed algorithm is of good efficiency in the path planning task under dynamic and unknown environment.