Year: 2026
Type: article
Abstract: In response to the challenges of multiple unmanned aerial vehicles'(UAV) rapid strike missions against multiple enemy targets in a complex urban combat environment, where the optimization of multiple objectives such as energy consumption, flight risk and inter-UAV safety distance must be considered, this paper proposes a two-layer optimization algorithm based on the A* algorithm and the improved particle swarm optimization(PSO) algorithm. The method utilizes the A* algorithm to generate initial paths, which serve as initial solutions for the PSO algorithm, thereby enhancing the early-stage search efficiency. Meanwhile, a particle mechanism with mutation structures is introduced to improve the global search capability of the PSO algorithm in its solution space and to mitigate premature convergence. The simulation results demonstrate that the proposed two-layer optimization algorithm signi-ficantly improves search efficiency and effectively addresses the problem of local optima. The findings verify the feasibility and effectiveness of the proposed algorithm in multi-UAV path planning tasks in a complex urban combat environment.
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7156758716
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