Multi-UAV trajectory planning based on differential evolution of Levy flights particle swarm optimization
Qi Tang, Dai Jiyang, Ying Jin, WU Guo-hui · 2023
Multi-UAV cooperative trajectory planning model with a complex battlefield environment is difficult to establish, and the solution is complex. Aiming at these problems, a more realistic optimal combination model is established, and a particle swarm optimization with based on levy flight and differential evolution (LFPSO-DE) algorithm based on embedded Levy flight strategy is proposed. First, this work establishes a multi-UAV cooperative trajectory planning problem model in a complex environment, and establishes a comprehensive cost function to represent the complex environment; Secondly, aiming at the problem that the PSO algorithm is easy to fall into the local extremum, the Levy flight strategy is introduced to improve the particle swarm position update formula, and the inertia weight and learning factor are optimized, and then combined with the improved DE algorithm, the convergence speed and accuracy of the particle swarm are improved , while enabling the algorithm to have a better ability to explore; Finally, LFPSO-DE algorithm is compared with other algorithms in a variety of test functions, and then applied to multi-UAV trajectory planning experiments. The experimental results show that the LFPSO-DE algorithm has a good convergence speed and can effectively deal with the problem of falling into a local extremum. The planned trajectory is better in terms of voyage, speed, and time-consuming voyage, which has practical application value.