Rotary UAV Path Planning in Rough Terrain Based on MOSA-PSO Method

In this paper, a path planning algorithm based on multi-objective simulated annealing - particle swarm optimization (MOSA-PSO) method is proposed for rotary unmanned aerial vehicles (R-UAVs) in rough terrain, which improves the iterative updating strategy of the original particle swarm optimization (PSO) algorithm. A vibration function, the reference point method and the simulated annealing (SA) method are introduced into the MOPSO algorithm, to improve optimizing solution and the convergence speed of the algorithm while ensuring the diversity of solutions during the iterations. One simulation experiment is carried out in the rough terrain from Guilin, China. Compared with the non-dominated sorting genetic algorithm II (NSGA-II) and the modified MOPSO, the convergence speed and the optimized result of the proposed algorithm are significantly improved.