Application and Improvement of Heuristic Function in A* Algorithm

Abstract

The A * algorithm is widely used in path planning due to its simplicity and effectiveness. In this paper, firstly, aiming at the difficulty in determining the heuristic function in the A * algorithm, performance comparison is made between the four heuristic functions such as Manhattan distance, Euclidean distance, Chebyshev distance and Diagonal distance. In the path planning, through these, we obtain the degree of influence of different heuristic functions on A * algorithm efficiency. At the same time, an improved heuristic function is proposed to select the cost coefficient of the Manhattan distance with a weighted measure. By comparing simulation results, the improved A * algorithm has some optimization in path planning with respect to search time, search range, path length and so on, and it's certain reference to the heuristic function design of A * algorithm.