Abstract
In modern warfare, the use of UAVs for reconnaissance, search and rescue missions is very common, and it is essential to plan the flight path of UAVs. However, in the face of complex battlefield environment, the existing flight path planning algorithms have the problems of long time consumption and unstable path. Therefore, this paper studies the UAV flight path planning optimization in complex battlefield environment. First, we construct the battlefield environment model. Then, by analyzing the UAV flight constraints existing in battlefield environment, the objective function is obtained. And the problem of UAV flight path planning optimization is transformed into a nonlinear combinatorial optimization problem. On this basis, an Adaptive Adjustment Flight Path Planning algorithm (AA-FPP) is proposed. The AA-FPP algorithm adaptively adjusts the absorption coefficient of fireflies by using chaotic strategy. It adjusts the control position updating formula by using time-varying inertia weight to enhance its global searching ability. Then, random factors based on Boltzmann selection strategy are introduced to perturb the iterative solutions in AA-FPP. It expands the search space of the path and enhances the convergence efficiency. Finally, simulation results show that the AA-FPP algorithm can successfully plan a flight path that reduces static/dynamic threat intensity. And it has greater advantages in path stability and planning time consumption.
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Hui Li and Zhangpeng Qiu designed the related algorithms and wrote the main manuscript text. Dan Liao designed the main architecture. Ming Zhang and Hanyan Jin had carried out simulation experiments on the proposed detection method. All authors reviewed the manuscript.
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This work was supported in part by the National Natural Science Foundation of China under Grant 61971105, Sichuan science and technology program under Grant 2022YFG0173 and 2023YFG0296.
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Li, H., Qiu, Z., Han, X. et al. UAV flight path planning optimization. Telecommun Syst 87, 329–342 (2024). https://doi.org/10.1007/s11235-024-01167-w
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DOI: https://doi.org/10.1007/s11235-024-01167-w