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Article

Task Allocation and Saturation Attack Approach for Unmanned Underwater Vehicles

1
Faculty of Science, Kunming University of Science and Technology, Kunming 650500, China
2
College of Software, Liaoning Technical University, Huludao 125000, China
3
College of Artificial Intelligence, Dalian Maritime University, Dalian 116026, China
4
College of International Collaboration, Dalian Maritime University, Dalian 11602, China
5
College of Business Administration, Liaoning Technical University, Huludao 125000, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Drones 2025, 9(2), 115; https://doi.org/10.3390/drones9020115
Submission received: 28 December 2024 / Revised: 31 January 2025 / Accepted: 31 January 2025 / Published: 4 February 2025
(This article belongs to the Special Issue Advances in Intelligent Coordination Control for Autonomous UUVs)

Abstract

In modern marine warfare, unmanned underwater vehicles (UUVs) have fast and efficient attack capabilities. However, existing research on UUV attack strategies is relatively limited, often ignoring the requirement for the effective allocation of different strategic value areas, which restricts its performance in the marine combat environment. To this end, this paper proposes an innovative UUV task allocation and saturation attack strategy. The strategy first divides the area according to the distribution density of enemy UUVs, and then reasonably allocates tasks according to the enemy’s regional value and the attack capability of our UUVs. Our UUVs then sail to the enemy area and are evenly distributed in the encirclement to ensure accurate saturation attacks. In the task allocation link, the grey wolf optimizer is improved by introducing Logistic chaos mapping and differential evolution mechanism, which improves the search efficiency and allocation accuracy. At the same time, the combination of the optimal matching algorithm and Bezier curve dynamic path control ensures the accuracy and flexibility of a coordinated attack. The simulation experimental results show that the strategy shows high attack efficiency and practicality in marine combat scenarios, providing an effective solution for UUV attack tasks in complex marine environments.
Keywords: UUVs; task allocation; saturation attack; collaboration; swarm intelligence UUVs; task allocation; saturation attack; collaboration; swarm intelligence

Share and Cite

MDPI and ACS Style

Chen, Q.; Liu, B.; Yu, C.; Yang, M.; Guo, H. Task Allocation and Saturation Attack Approach for Unmanned Underwater Vehicles. Drones 2025, 9, 115. https://doi.org/10.3390/drones9020115

AMA Style

Chen Q, Liu B, Yu C, Yang M, Guo H. Task Allocation and Saturation Attack Approach for Unmanned Underwater Vehicles. Drones. 2025; 9(2):115. https://doi.org/10.3390/drones9020115

Chicago/Turabian Style

Chen, Qiangqiang, Baisheng Liu, Changdong Yu, Mingkai Yang, and Haonan Guo. 2025. "Task Allocation and Saturation Attack Approach for Unmanned Underwater Vehicles" Drones 9, no. 2: 115. https://doi.org/10.3390/drones9020115

APA Style

Chen, Q., Liu, B., Yu, C., Yang, M., & Guo, H. (2025). Task Allocation and Saturation Attack Approach for Unmanned Underwater Vehicles. Drones, 9(2), 115. https://doi.org/10.3390/drones9020115

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