UAV route planning based on improved particle swarm optimization algorithm
To solve the problem that particle swarm optimization algorithm is easy to fall into local optimal,an improved particle swarm optimization algorithm is proposed and applied to the UAV flight route planning.Firstly,the mathematical model for UAV route planning was established.Then,on the basis of particle swarm optimization algorithm,the Logistic chaotic mapping was used to initialize the population,adaptive parameter adjustment mechanism was adopted,and Levy flight strategy was introduced into the algorithm process.Finally,benchmark function testing and route planning simulation were carried out for the improved algorithm.The benchmark function testing ver-ified that the improved algorithm can improve the problem of falling into local optima for unimodal and multimodal functions,and effectively improved search accuracy.Simulation results show that the improved algorithm has a significant improvement in search efficiency and the quality of the ob-tained route.
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