UAV Path Mountain Planning Based on SPSO
Ziqiang Luo, Shuhan Fang · 2024
Aiming at the 3D route planning problem of Unmanned Aerial Vehicle (UAV), this paper compares the planning results of a given route based on three meta-heuristic algorithms, namely, Spherical vector based Particle Swarm Optimization (SPSO), Grey Wolf Optimizer, (GWO), and Sparrow Search Algorithm (SSA) three meta-heuristic algorithms. Comparing the planning results of the established routes and deprive a suitable method for UAVs to plan their paths in the mountainous background. First, an objective function is constructed by taking the UAV's flight distance, flight altitude, route smoothness, and threat area cost into account. Secondly, this paper simulates the mountainous conditions, takes the UAV's take-off height and steering factors into account, optimizes using the above three optimization algorithms, and conducts several experiments in different maps to optimize the hyper-parameters in the optimization algorithms. Finally, considering the routes and influencing factors in all the maps, it is concluded that SPSO is more suitable for UAV path planning in mountainous environments.