A Static Area Coverage Algorithm for Heterogeneous AUV Group Based on Biological Competition Mechanism

Author:

Guo Xuan,Chen Yuepeng,Zhao Dongming,Luo Guangyu

Abstract

Static area coverage of the heterogeneous autonomous underwater vehicle (AUV) group is widely used in many fields. With the use of the centroidal Voronoi tessellation (CVT) algorithm, the coverage problem can be resolved. However, the CVT method, which is optimized with the location evaluation function, cannot consider the heterogeneity of AUVs when the group performs the static area coverage task and will cause a waste of resources. In this paper, considering different AUVs’ task requirements and detection capabilities comprehensively, we propose a coverage control optimization algorithm based on a biological competition mechanism (BCM). By using BCM, the task load of each AUV can be distributed consistently. In addition, we provide strict proof of the consistency of the algorithm based on the Lyapunov method. Simulation results demonstrate that with the proposed algorithm, the location distribution of the heterogeneous AUV group for area coverage is close to the balanced value, and the performance is better than the CVT algorithm for static area coverage.

Publisher

Frontiers Media SA

Subject

Biomedical Engineering,Histology,Bioengineering,Biotechnology

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An ant colony path planning optimization based on opposition-based learning for AUV in irregular regions;Computing;2024-05-16

2. Coverage Integration of UAVs and UGVs for Sensory Distribution Mapping;2024 IEEE International Conference on Artificial Intelligence and Mechatronics Systems (AIMS);2024-02-21

3. Collaborative Path Planning of Multiple AUVs Based on Adaptive Multi-Population PSO;Journal of Marine Science and Engineering;2024-01-26

4. Adaptive Expected Reactive algorithm for Heterogeneous Patrolling Systems based on Target Uncertainty;2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC);2023-06

5. Cooperative Path Planning of Multiple Unmanned Surface Vehicles for Search and Coverage Task;Drones;2022-12-28

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