A nonlinear weighted whale optimization algorithm improved by cosine function for UAV path planning

The importance of the UAV path-planning problem lies in ensuring the safe and efficient completion of tasks by UAVs while maximizing resource utilization and minimizing risks. Addressing this issue, a new algorithm named Nonlinear Weighted Whale Optimization Algorithm Improved by Cosine Function for UAV Path Planning (COSWOA) is proposed. This algorithm overcomes the drawbacks of the basic WOA algorithm, such as low solution precision, slow convergence speed, and susceptibility to local optima, by employing a nonlinear dynamic variation strategy based on the cosine function and incorporating nonlinear inertia weights. Simulation results demonstrate that compared to GA, WOA, and GWO algorithms, the COSWOA algorithm can rapidly generate higher-quality paths for UAVs and exhibits better robustness.

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Publication Details

Journal
IET conference proceedings.
Published
2025-01-01
DOI
https://doi.org/10.1049/icp.2024.3022
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
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article

A nonlinear weighted whale optimization algorithm improved by cosine function for UAV path planning

Yunhua Li, Weiguang Yang, Yan Shi, Xiangyu Zhang et al.
IET conference proceedings.
Robotic Path Planning Algorithms
article

A nonlinear weighted whale optimization algorithm improved by cosine function for UAV path planning

Yunhua Li, Weiguang Yang, Yan Shi, Xiangyu Zhang, Liman Yang
article en

Abstract

The importance of the UAV path-planning problem lies in ensuring the safe and efficient completion of tasks by UAVs while maximizing resource utilization and minimizing risks. Addressing this issue, a new algorithm named Nonlinear Weighted Whale Optimization Algorithm Improved by Cosine Function for UAV Path Planning (COSWOA) is proposed. This algorithm overcomes the drawbacks of the basic WOA algorithm, such as low solution precision, slow convergence speed, and susceptibility to local optima, by employing a nonlinear dynamic variation strategy based on the cosine function and incorporating nonlinear inertia weights. Simulation results demonstrate that compared to GA, WOA, and GWO algorithms, the COSWOA algorithm can rapidly generate higher-quality paths for UAVs and exhibits better robustness.

IET conference proceedings.Vol. 2024(13)
Beihang University (CN)
Life below water
Openalex Percentile: Top 100%
Robotic Path Planning Algorithms
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