基于改进A ^(*)算法的无人车路径规划研究

Research on Unmanned Vehicle Path Planning Based on Improved A^(*)Algorithm

针对传统A^(*)算法应用无人车路径规划实用性低的问题,提出了一种改进A^(*)算法。首先,对障碍物膨胀,确保路径安全性;其次,在原算法基础上融合JPS搜索策略,对子节点跳跃搜索,减小内存占用提高搜索效率;最后,利用Floyd算法对规划出的路径进行平滑处理。为确定算法可行性,对算法进行仿真实验,实验结果表明改进A^(*)算法规划出的路径效率更高,不会与障碍物发生碰撞,拐点数量少,路径总转折角度小,与原算法相比具有较明显优势,适合用于无人车的路径规划。

Aiming at the low practicability of traditional A^(*)algorithm in unmanned vehicle path planning,an improved A^(*)algorithm was proposed.Firstly,obstacles were expanded to ensure the path safety.Then,based on the original algorithm,JPS search strategy is integrated to search child nodes by jumping,which reduces memory consumption and improves search efficiency.Finally,Floyd algorithm is used to smooth the planned path.In order to determine the feasibility of the algorithm,a simulation experiment is conducted on the algorithm.The experimental results show that the path planned by the improved A^(*)algorithm has higher efficiency,no collision with obstacles,less inflection points,and small total turning Angle of the path.Compared with the original algorithm,it has obvious advantages and is suitable for unmanned vehicle path planning.