基于改进A*与DWA算法融合的温室机器人路径规划

根据温室环境下移动机器人作业的实时路径规划要求,提出一种基于改进A*算法与动态窗口法相结合的温室机器人路径规划算法.针对传统A*算法搜索算法拐点过多的问题,对关键点选取策略进行改进,融合动态窗口法,构建全局最优路径评价函数,采用超声传感器进行局部避障,实现实时最优的路径规划.仿真实验结果证明,与传统A*、Dijkstr...

Path Planning of Greenhouse Robot Based on Fusion of Improved A* Algorithm and Dynamic Window Approach

Path planning is the premise of greenhouse robot operation, and an optimal continuous barrier free path is planned with great significance. An algorithm based on the combination of improved A* algorithm and dynamic window approach was proposed to solve real-time path planning of mobile robot in greenhouse. The core was based on the search algorithm of traditional A* algorithm. Aiming at the problem of too many inflexion points, the key point selection strategy was improved. The dynamic window method was integrated to construct a global optimal path evaluation function. Local obstacle avoidance was achieved through ultrasonic sensors to achieve real-time optimal path planning. The simulation results showed that compared with the traditional A*, Dijkstra, RRT algorithms, the improved A* algorithm had a smoother path and higher efficiency, which was conducive to the motion control of the robot in the greenhouse, which showed the effectiveness of the algorithm. Considering the size of the robot, the grid map of the real environment was expanded to ensure the safety of the path. The experimental results showed that the fusion algorithm can satisfy the smoothness of path and effectively avoid obstacles. The mobile robot can achieve autonomous navigation, and the tracking error was kept within 0.22m, and the positioning error was no more than 0.28m, which met the actual needs. The research result had an important reference value for the application of greenhouse mobile robot navigation.