Abstract
Aiming at the problem of UAV swarm trajectory planning, this paper constructs a mathematical model of UAV swarm trajectory planning, and uses an improved particle swarm optimization to optimize the solution. First of all, this paper constructs the environment model and the corresponding cost function, the cost function of the single aircraft trajectory, and the constraint function inside the UAV swarm. Then the objective function of UAV swarm trajectory optimization is constructed. After that, in view of the shortcoming of particle swarm optimization (PSO) that is easy to fall into local optimality, based on the multi-agent theory’s Holonic structure, the PSO is improved to optimize the objective function. Finally, the UAV swarm trajectory planning algorithm flow based on the improved PSO algorithm is constructed to realize the trajectory planning of the UAV swarm. Compared with the current mainstream improved PSO algorithm, the algorithm in this paper has better performance.
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Luo, J., Liu, J., Liang, Q. (2022). UAV Swarm Trajectory Planning Based on a Novel Particle Swarm Optimization. In: Wu, M., Niu, Y., Gu, M., Cheng, J. (eds) Proceedings of 2021 International Conference on Autonomous Unmanned Systems (ICAUS 2021). ICAUS 2021. Lecture Notes in Electrical Engineering, vol 861. Springer, Singapore. https://doi.org/10.1007/978-981-16-9492-9_51
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DOI: https://doi.org/10.1007/978-981-16-9492-9_51
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