基于A^(*)与DWA算法的混合路径规划算法研究

Research on Hybrid Path Planning Algorithm Based on A^(*) and DWA Algorithm

为使移动机器人能在各种环境中高效工作,需要根据实际的地形选择合适的路径规划算法。为此,使用A^(*)与DWA(Dynamic Window Approach)算法结合的混合路径规划算法,在仿真环境下搭建U型、 S型、 L型、狭窄通道型4种典型地形进行寻路实验,同时改进了建图的权重递归公式消除对前一时刻数据依赖,提高了算法效率。结果表明,该混合路径规划算法相较于单一算法具有较快的寻路速度和良好的避障能力,其在L型地形下的寻路速度最快,在U型地形和S型地形下则速度较慢。

To make AGV(Automated Guided Vehicle) work efficiently in various environments, it is necessary to select a suitable path planning algorithm according to the actual terrain. We use the A^(*)and DWA(Dynamic Window Approach) hybrid path planning algorithm and build four typical terrains, U-shaped, S-shaped, L-shaped and narrow passage in the simulation environment to conduct pathfinding experiments. Furthermore, we improve the weight recursive formula of Gmapping, remove the dependence on the previous moment data and improve the efficiency of the algorithm. The results show that the hybrid path planning algorithm has faster pathfinding speed and better obstacle avoidance ability than the single algorithm. It has the fastest pathfinding speed in L-shaped terrain and was relatively slow in U-shaped terrain and S-shaped terrain.