An Improved BSA with Dynamic Grouping Strategy and Its Application in UAV Path Planning

Zirui Zhao

doi:10.54097/38mpj028

Authors

Zirui Zhao

DOI:

https://doi.org/10.54097/38mpj028

Keywords:

DGSBSA algorithm, Path planning, Dynamic grouping, Reverse foraging, Convergence speed.

Abstract

Due to the issues of slow convergence speed and low accuracy in swarm intelligence algorithms for UAV path planning, this paper proposes An Improved Bird Swarm Algorithm with dynamic grouping strategy(DGSBSA).This method introduces strategies such as dynamic grouping and reverse foraging to enhance the algorithm's performance.During the iteration process, dynamic grouping is performed based on the positions of the bird swarm to enhance population diversity.The experimental results demonstrate that the proposed DGSBSA algorithm improves the algorithm's accuracy and enhances the convergence speed in the path planning process.

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