关键词: 协同航迹规划, GWO, Tent映射, 动态权重, 多无人机

Abstract: To overcome the problems of poor cooperation， immersing local minimization， low convergence speed and poor solving accuracy in solving the collaborative route by GWO algorithm for multiple unmanned aerial vehicles， an improved GWO-based three-dimensional collaborative route planning algorithm for multiple unmanned aerial vehicles is proposed. Firstly， a three-dimensional collaborative trajectory planning mathematical model for multiple unmanned aerial vehicles is established， using the weighted sum of consumption cost， height cost， threat cost， spatial constraint， time constraint， and penalty term as the objective function. Secondly， the Greedy algorithm and Tent mapping are combined to improve the fitness of the population and preserve the diversity of the population to reduce the possibility of falling into local optima； then we optimize the convergence factor to improve the rate of convergence of the algorithm. Afterwards， we design a dynamic weight position update method to enhance the exploration and development capabilities of the algorithm. Finally， the improved GWO algorithm is applied to solve the trajectory planning problem of multiple unmanned aerial vehicles， and compared with GWO algorithm and CSGWO algorithm. The simulation results indicate that the proposed improved GWO algorithm enhance the solution accuracy by 64.8% and 16.7%， as well as the convergence speed by 28.5% and 25.4%， respectively. Additionally the synergy ability is significantly better than that of the comparison algorithms.

Key words:  , collaborative path planning； GWO； Tent mapping； dynamic weight； multiple unmanned aerial vehicles