M.M. Nikolaiev, M.A. Novotarskyi
Èlektron. model. 2025, 47(6):84-101
https://doi.org/10.15407/emodel.47.06.084
ABSTRACT
Effective route optimization in the process of planning unmanned aerial vehicle trajectories plays a key role in ensuring operational safety, energy efficiency, and rational use of computing resources during autonomous navigation. This study presents a new hybrid optimization approach that combines the global capabilities of differential evolution with the deep local advantages of an improved whale behavior simulation algorithm. This integrated approach ensures obstacle avoidance, smooth trajectories, and efficient movement. The proposed method demonstrates faster convergence to optimal solutions compared to standard optimization algorithms. This is confirmed by a reduction in the total cost function. The Method makes it promising for practical application in complex and dynamic navigation conditions.
KEYWORDS
UAV, trajectory planning, differential evolution, evolutionary computation, optimization.
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