Cooperative Online Path Planning for UAVs Based on DMPC and Improved Grey Wolf Optimizer

Online path planning for multiple fixed-wing UAVs in 3D aerial space is a complex optimization problem with high dimenswn and multiple constramts, which requrres efficient solving methods. In this paper, distributed model predictive control (DMPC) method is adopted to accomplish online path planning for multiple UAVs. In order to reduce the computation time of DMPC, an Improved grey wolfoptimizer (GWO) is designed where pheromone factors are incorporated into GWO to strengthen the exploration ability of the original GWO. In addition, pheromones are optimally selected based on the hierarchy of wolves to gnide subsequent iterations so that the convergence speed of the optimizer can be increased. Simulation examples show the supenontles of the proposed method by comparing with various existing optimizers.