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Dan Pan

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Proceedings Article | 6 September 2022 Paper

3D cruise dynamic programming algorithm for UAV based on improved GWO

Zhibin Wen, Kaiwen Xu, Dan Pan, Kaijun Yu

Proceedings Volume 12332, 1233222 (2022) https://doi.org/10.1117/12.2652471

KEYWORDS: Unmanned aerial vehicles, Radar, 3D modeling, Optimization (mathematics), Evolutionary algorithms, Computer programming, Signal attenuation, Computer simulations, Particle swarm optimization, Algorithm development

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In order to solve the problem of the gray wolf algorithm (GWO) in the dynamic programming of UAVs, due to the reduction of the attenuation factor, the individual wolves move to the head wolf area, resulting in poor global convergence effect and low optimization accuracy of the algorithm. A 3D cruise dynamic programming algorithm for UAVs based on the Grey Wolf (IGWO) strategy based on Levi flight and random walk strategy is proposed. Build a three-dimensional model of UAV cruise; weigh factors such as cruise trajectory length, radar area, no-fly threat, and heading change to construct a fitness function; with the help of Levi flight and random walk strategies, it is discussed to find an appropriate solution according to different optimization problems. parameters, to achieve higher-precision optimization, and to ensure the method of the optimization process in the middle and late stages; finally, the dynamic planning algorithm for UAV cruise in complex three-dimensional maps is obtained. Taking the cruise in the designated mission space as an example, the simulation verifies that the IGWO algorithm can make up for the shortcomings of GWO, and the planned path can avoid threats, and it takes time and the path length is small. The experimental results show that it is reasonable and effective to use the IGWO algorithm to perform flight missions in three-dimensional space.

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