UAV Flight Path Planning When Considering Coverage Radius of UAV

This paper defines the coverage radius of Unmanned Aerial Vehicle(UAV) as its own attribute such as detection radius, overlooking radius, attack radius and so on when UAV is regarded as a fixed particle at a certain height. Generally, when UAV reconnaissance, attack or material delivery to multiple targets, its flight path planning problem is transformed into Traveling Salesman Problem(TSP), but the coverage radius of UAV is not considered, and there may be path intersection and targets covered repeatedly in the planned path. Aiming at the problem of UAV path planning when considering UAV coverage radius, Ant Colony Optimization (ACO) and Density-Based Spatial Clustering of Applications with Noise(DBSCAN) are proposed to solve UAV flight path planning problem combined with geometric judgment, which can better solve the problem of path intersection in TSP, and the problem of targets covered repeatedly without considering UAV coverage radius, to achieve the goal of no intersection path and shorter path length. Python programming simulation is carried out for the proposed method, and the experimental results show that the proposed method can effectively avoid the problems flight path intersection and targets covered repeatedly, and greatly shorten the flight path length of UAV, which will greatly improve the flight efficiency of UAV.