Abstract: According to the starting and ending points and planned departure time of different UAVs, a 3D track collaborative planning of multi-UAV considering task priority is established by considering time-space conflict, spatial distribution of restricted area, performance of UAVs and other factors. The objective is to minimize the total cost of trajectory length and delay time. A multi-strategy hiking optimization algorithm is designed to solve the model. Among them, a Logistic-Cubic hybrid mapping is used to initialize the population, a golden sinusoid strategy is integrated in the exploration phase of the algorithm, a position update strategy is developed to disturb individuals to avoid local convergence of the algorithm, and a hiker interaction strategy is used to find a shortcut to accelerate the convergence of the algorithm. The performance of the proposed algorithm is compared with other 5 classical algorithms to solve 12 benchmark functions, and the ablation experiment of its improved strategy is carried out to verify the feasibility of the proposed algorithm. Finally, taking the path planning of UAV in a real scene as an example, the influence of proposed model with and without delay time, task priority and spatio-temporal conflict on the scheduling results is analyzed. The solution performance of these algorithms is further compared to prove the superiority of our model and algorithm. The results show that: (1) compared with the traditional model, the total flight time, delay time and mileage of the proposed model are increased by 0.8%, 12.6% and 1.7% respectively, but it is more realistic; (2) The solution quality of proposed algorithm is 56.4%, 82.4%, 46.5%, 91.9% and 81.4% lower than that of HOA, DBO, GWO, PSO and SSA respectively, and its convergence is also 38.6%, 86.1%, 83.3%, 48.4% and 69.2% lower than that of them respectively.

Key words: multi-UAV, three-dimensional track collaborative planning, task priority, hiking optimization algorithm, multi-strategy