Research on AGV Path Planning based on Improved A* algorithm

Abstract

Path planning is an important field for AGV, and A* algorithm is one of the fastest shortest path algorithms, which is often used in a variety of path planning methods. This paper proposes an improved A* algorithm based on path planning in grid map, aiming at the low efficiency of traditional A* algorithm in searching the map and the existence of many redundant points and turning points in the path. The algorithm uses the weighted Manhattan distance as the heuristic function, and the coefficient changes with the distance. In addition, a turning penalty mechanism is added to the heuristic function to reduce the occurrence of turning points. Finally, a reduction strategy is added to the search function based on the location of the current point and the end point to reduce the search of redundant points. The results of python simulation experiments show that this improved A* algorithm can effectively reduce the redundant points and turns in the search, and improve the search efficiency and the smoothness of the path in the path planning.