A Novel A*-Based Path Planning Algorithm Optimized for Grid Maps

To achieve navigation control for AGV in grid maps, this paper proposes an improved A* algorithm as the global path planning algorithm for AGV. Firstly, to address the issue that the search efficiency of the A* algorithm is greatly affected by the heuristic function, a dynamic weight coefficient in the form of an exponential function is introduced to dynamically adjust the heuristic function, which improves the search efficiency of the A* algorithm to a certain extent. Secondly, in order to reduce the impact of the exponential operation on the search efficiency of the improved algorithm and considering that the results of exponential function calculations in the improved algorithm are only used to compare the cost values between different nodes, this paper introduces the fast power approximation method to evaluate the exponential function. Through simulation experiments, it is verified that compared with the traditional A* algorithm, the performance of the improved A* algorithm is significantly improved in terms of search time and total cost of planned path. Finally, to address the problem of too many turning actions caused by the large number of inflection points in the planned path in the grid maps, this paper uses the cubic B-spline curve to smooth the path, which significantly improves the relevant issues caused by the turning points during the driving process of AGV. After analysis, the improved A* algorithm proposed in this paper effectively improves the search efficiency and enhances the applicability of the planned path.