Artificial potential field-based swarm finding of the unmanned surface vehicles in the dynamic ocean environment

Author:

Tan Guoge1ORCID,Zhuang Jiayuan12ORCID,Zou Jin1,Wan Lei12,Sun Zhiyuan1

Affiliation:

1. College of Shipbuilding Engineering, Harbin Engineering University, Harbin, China

2. Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin, China

Abstract

Using multiple unmanned surface vehicle swarms to implement tasks cooperatively is the most advanced technology in recent years. However, how to find which swarm the unmanned surface vehicle belongs to is a meaningful job. So, this article proposed an artificial potential field-based swarm finding algorithm, which applies the potential field force directly to unmanned surface vehicles and leads them to their belonging swarm quickly and accurately. Meanwhile, the proposed algorithm can also maintain the formation stable while following the desired path. Based on the swarm finding algorithm, the artificial potential field-based collision avoidance method and the International Regulations for Preventing Collisions at Sea-based dynamic collision avoidance strategy are applied to the swarm control of multi-unmanned surface vehicles to enhance the performance in the dynamic ocean environment. Methods in this article are verified through numerical simulations to illustrate the feasibility and effectiveness of proposed schemes.

Funder

the National Natural Science Foundation of China

Publisher

SAGE Publications

Subject

Artificial Intelligence,Computer Science Applications,Software

Cited by 14 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. Model-Free Visual Servo Swarming of Manned-Unmanned Surface Vehicles With Visibility Maintenance and Collision Avoidance;IEEE Transactions on Intelligent Transportation Systems;2024-01

2. Formation Control for UAV-USVs Heterogeneous System with Collision Avoidance Performance;Journal of Marine Science and Engineering;2023-12-10

3. Groups of heterogeneous autonomous systems in area reconnaissance;2023 IEEE Symposium Sensor Data Fusion and International Conference on Multisensor Fusion and Integration (SDF-MFI);2023-11-27

4. Area reconnaissance with heterogeneous groups of autonomous systems;Emerging Imaging and Sensing Technologies for Security and Defence VIII;2023-10-17

5. Real-Time Emergency Collision Avoidance for Unmanned Surface Vehicles with COLREGS Flexibly Obeyed;Journal of Marine Science and Engineering;2022-12-18

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