Path Planning Based on Improved A * Algorithm

In order to solve the problem of collision or path pl anning failure when using the traditional A* algorithm to plan paths in environments with complex obstacles, this paper propo ses an improved A* algorithm. This algorithm designs an adjus table weight factor to realize the dynamic adjustment mechanis m of the heuristic function and improve the robot's search effic iency and path quality by optimizing the node selection strateg y. Experimental results show that in a variety of different map environments, the improved A* algorithm can reduce the path length by 28.14 % and the planning time by 48.41 % on averag e compared to the standard A* algorithm. The search efficienc y and path planning quality verify the effectiveness of the algor ithm.