融合改进A^(*)算法和DWA算法的全局动态路径规划

Global dynamic path planning integrating improved A^(*)algorithm and DWA algorithm

针对常规A^(*)算法存在的路径规划中冗余节点过多、拐点过多、规划路径与障碍间的距离过短、容易产生碰撞等问题,提出了一种将改进A^(*)算法与动态窗口法相结合的新方法。该算法通过对栅格地图中的障碍栅格进行量化处理,提取环境信息,并根据这些信息对A*算法的启发函数和子节点选择策略进行调整。此外,为了优化路径的平滑度和安全性,设计了一种路径节点平滑处理算法。仿真实验结果表明,融合动态窗口法的融合算法不仅能够保证所规划路径的全局最优性,而且能够有效地避开随机障碍物。

Traditional A^(*)algorithm suffers from many redundant nodes and inflection points in path planning.Moreover,collision easily occurs when the distance between paths and obstacles is too small.To overcome these problems,this paper proposes a path planning algorithm which integrates the improved A^(*)algorithm with the dynamic window method.The algorithm extracts environmental information by quantifying the obstacle rasters in the raster map,and adjusts the heuristic function and sub-node selection strategy of the A^(*)algorithm according to this information.In addition,to optimize the smoothness and safety of the path,a path node smoothing processing algorithm is built.Our simulation experiments show the fusion algorithm after incorporating the dynamic window method ensures the global optimality of the path and effectively avoids random obstacles.