基于改进人工鱼群算法的无人机三维航迹规划OA

In the unmanned aerial vehicle(UAV)trajectory planning algorithm,to address the is-sues of easily falling into local optima and inefficient optimization in the traditional artificial fish swarm algorithm(AFSA),a step size attenuation function is introduced,and an adaptive step size artificial fish swarm algorithm(AS-AFSA)is proposed to achieve adaptive convergence in both glob-al and local aspects of trajectory planning.Furthermore,an optimization strategy for the individual fitness weight of artificial fish is provided to improve the convergence speed and accuracy of the AF-SA.Simulation results show that the improved algorithm performs exceptionally well in UAV trajecto-ry planning scenarios.Under the same number of iterations,the fitness is improved by 4.5%com-pared to the wolf colony algorithm(WCA)and 2.5%compared to the traditional AFSA.