融合改进A^(*)算法与动态窗口法的移动机器人路径规划

Mobile robot path planning integrating improved A^(*)algorithm and dynamic window method

为解决移动机器人在随机障碍物环境的导航过程中,使用A星(简称A^(*))算法出现碰撞导致路径规划失败的问题,设计了一种融合改进A_(*)算法和动态窗口法(dynamic window approach,DWA)的全局动态路径规划方法。首先,从以下两方面改进传统A^(*)算法:混合使用4邻域和8邻域A^(*)搜索算法,与通过删除冗余路径点和转折点来提高路径的平滑性;接着将改进A^(*)算法与DWA融合,利用融合算法使移动机器人进行全局实时动态路径规划。Matlab仿真试验结果表明,改进后的A^(*)算法较传统A^(*)算法不会使机器人穿越障碍物及其顶点,这有效减少了碰撞,从而提高了安全性;融合DWA后,在获得全局最优路径的基础上,能避开静态随机障碍物和动态障碍物,这证明了融合算法有良好的路径规划能力。

A global dynamic path planning method based on the improved A star(A^(*))algorithm and the Dynamic Window Approach(DWA)is proposed to solve the problem of path planning failure caused by collisions using A^(*)algorithm in the navigation process of mobile robot in enviously with random obstacles.Firstly,the traditional A^(*)algorithm is improved from following two aspects,using the 4 neighborhood and 8 neighborhood A^(*)search algorithm are mixed to improving path smoothness by deleting redundant path points and turning points.Then,the improved A^(*)algorithm is combined with the DWA,and the fusion algorithm is used to conduct global real-time dynamic path planning for mobile robots.The Matlab simulation results show that the improved A^(*)algorithm does not make the robot cross obstacles and obstacle vertices compared with the traditional A^(*)algorithm,which effectively reduces collisions and improves the security.After the DWA is fused,the static random obstacles and dynamic obstacles can be avoided by the robot on the basis of obtaining the global optimal path,and results prove that the fusion algorithm has a good path planning ability.