Abstract
With the advent of the industrial 4.0 era of intelligent manufacturing, industrial production is becoming more and more unmanned, such as drones, self-driving cars, industrial robotic arms, unmanned aerial vehicles, etc. This paper proposes an improved A* path planning algorithm, which achieves fast and accurate path planning to find the target location. Aiming at the problems of blind expansion, large number of sampling nodes, and slow speed of the traditional A* algorithm, this paper proposes an improved A* path planning algorithm, which retains the heuristic function and uses a fixed sampling function to find the fixed sampling points, and makes the starting point and the target point simultaneously perform path planning towards the sampling points. Thus, the problems of a large number of sampling nodes and slow speed are solved. The simulation results show that compared with the traditional A* algorithm, the number of sampling nodes is reduced by 65.30%, and compared with the A* algorithm with heuristic function, the number of sampling points is reduced by 55.35%. At the same time, the optimal path is retained. It meets the requirements of path planning.