Improved 3D UAV Path Planning Algorithm Based on Combined DWA and APF

In this paper, an improved path planning algorithm for three-dimensional unmanned aerial vehicles (UAVs) combining the dynamic window approach (DWA) and the artificial potential field (APF) method is investigated. Firstly, the application background of UAVs in 3D space and the importance of path planning are introduced, and the limitations of traditional path planning methods in complex environments are pointed out. Subsequently, the basic principles of the DWA algorithm and its application in path planning are elaborated in detail, including the key steps such as velocity space, trajectory prediction and evaluation of UAVs, and the shortcomings of DWA in macro-obstacle avoidance are analyzed. In order to solve this problem, this paper proposes to integrate the APF algorithm into DWA, which guides the UAV to move along the optimal path by establishing an artificial potential field to simulate the gravitational force of the target point and the repulsive force of the obstacles. The potential field is constructed by calculating the sum of the distance between the UAV and the target point and the distance of the obstacle, and weighted and superimposed into the objective function of the DWA in order to improve the obstacle avoidance ability and the efficiency of path planning. Finally, the effectiveness of the proposed algorithm is verified by simulation experiments. The experiments are conducted in 3D space by randomly generating obstacles and executing the basic DWA algorithm and the improved algorithm, and the results show that the improved algorithm is able to avoid obstacles earlier and plan better paths when facing dense obstacles. This shows that the improved algorithm proposed in this paper has a better application prospect in the UAV path planning problem in three-dimensional space, and can provide safe, efficient, and flexible flight paths for UAVs to meet the needs in different application scenarios.