Research and Simulation of the A* Algorithm in Matlab

With the rapid advancement of artificial intelligence and networking, path planning has found widespread applications across various domains, including artificial intelligence, mechanical control, robotics, and the automotive industry. The A* algorithm is a very common path-planning algorithm. Traditional research mainly focuses on the application of the A* algorithm and its combination with other algorithms, while neglecting the study of the A* algorithm itself, such as its heuristic function. This article will conduct an in-depth study of the A* algorithm using MATLAB, introduce the weighted A* and dynamic A* algorithm, and study the parameter influence and improvement of the A* algorithm. Research has shown that when the weight is greater than 1, it will reduce the optimality of the results; Smaller weights usually lead to better exploration, but the search process may slow down. The dynamic A* algorithm has many characteristics such as dynamic updates and reverse search. Therefore, this study is of great significance for improving the efficiency of path planning.