Path Planning for UAVs with Improved Spherical Vector-Based Particle Swarm Optimization

Because of the advantages in fast search speed and high search efficiency, particle swarm optimization (PSO) algorithm has been commonly applied in solving path planning problems for the unmanned aerial vehicles (UAVs). However, for the environment with obstacles, as the planning space becomes complicated, calculated amounts and the running time of the algorithm will explosively increase, which greatly reduce the performance of PSO algorithm. To accommodate to multi-obstacle environments, an improved spherical vector-based particle swarm optimization (ISPSO) is put forward in this paper. Firstly, based on actual unmanned aerial vehicle (UAV) parameters and constraints, a cost function was established, converting the path planning problem into an optimization problem. Secondly, the ISPSO algorithm with a parameter adjustment mechanism is proposed such that the best flight path can be figured out. Finally, simulation is carried out to confirm the planning performance of the proposed ISPSO algorithm.