A 3D UAV path planning model based on improved A* algorithm and DEM data

Abstract

Unmanned aerial vehicles (UAVs) have been widely used in different tasks. Path planning is the most important factor in the operation of UAVs. This paper proposes a 3D path planning method based on an improved A* algorithm to train the UAV to fly in a real-world environment. The terrain data is first processed with a digital elevation model (DEM). Then the cost function, which balances route efficiency and environmental factors such as weather threats, is built. The available action space for the UAV is reduced considering the manoeuvrability of the vehicle. An improved A* algorithm is used to solve the search model, and the efficiency is enhanced by optimizing the data structure and building a weighted A* algorithm. Simulation results show that the method performed well in planning an optimal path in a 3D environment, and the algorithm is simple and efficient. This work contributes to path planning for UAVs in different missions.