Adaptive step size-based wolf pack optimization algorithm for UAV path planning

With the increase in technological development and social needs, the diversity of missions that can be performed by UAVs has received widespread attention, so UAV path planning in variable environments has become an important prerequisite for completing UAV flight missions. This study focuses on the UAV path planning problem in complex environments and proposes a heuristic-based algorithm for wolf pack optimisation. Firstly, this paper uses the original terrain obstacle area and other factors to model the environment, customises a 3D equivalent terrain model and constructs a UAV trajectory planning scenario; then the wolf pack optimisation algorithm is used as the basis for optimising and modelling the wolf pack's wandering call and siege behaviour; finally, multiple sets of simulation experiments are conducted using the optimal flight distance between the starting point and the endpoint as the fitness function. The simulation results show that the Wolf Pack Optimisation algorithm has good global convergence and computational robustness, and has the advantages of good optimisation and fast convergence, shorter trajectory and more stable effect in UAV path planning.