Efficient UAV Path Planning with Multiconstraints in a 3D Large Battlefield Environment

Abstract

This study introduces an improvedA*algorithm for the real-time path planning of Unmanned Air Vehicles (UAVs) in a 3D large-scale battlefield environment to solve the problem that UAVs require high survival rates and low fuel consumption. The algorithm is able to find the optimal path between two waypoints in the target space and comprehensively takes factors such as altitude, detection probability, and path length into account. It considers the maneuverability constraints of the UAV, including the safety altitude, climb rate, and turning radius, to obtain the final flyable path. Finally, the authors test the algorithm in an approximately 2,500,000 square meter area containing radars, no-fly zones, and extreme weather conditions to measure its feasibility, stability, and efficiency.