UAV flight path planning optimization

Hui Li (), Zhangpeng Qiu (), Xiaoyi Han (), Ming Zhang (), Dan Liao () and Haiyan Jin ()
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Hui Li: University of Electronic and Science of China
Zhangpeng Qiu: University of Electronic and Science of China
Xiaoyi Han: University of Electronic and Science of China
Ming Zhang: University of Electronic and Science of China
Dan Liao: University of Electronic and Science of China
Haiyan Jin: University of Electronic and Science of China

Telecommunication Systems: Modelling, Analysis, Design and Management, 2024, vol. 87, issue 2, No 4, 329-342

Abstract: 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.

Keywords: UAV; Flight path planning; Optimization; Path stability (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11235-024-01167-w

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