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International Journal of Fuzzy Systems

, Volume 20, Issue 2, pp 672–686 | Cite as

An Improved Spinal Neural System-Based Approach for Heterogeneous AUVs Cooperative Hunting

  • Jianjun Ni
  • Liu Yang
  • Liuying Wu
  • Xinnan Fan
Article

Abstract

Cooperative hunting by a multi-AUV system in unknown 3D underwater environment is not only a research hot spot but also a challenging task. To conduct this task, each AUV needs to move quickly without obstacle collisions and cooperate with other AUVs considering the overall interests. In this paper, the heterogeneous AUVs cooperative hunting problem is studied, including two main tasks, namely the search and pursuit of targets, and a novel spinal neural system-based approach is proposed. In the search stage, a partition and column parallel search strategy is used in this paper, and a search formation control algorithm based on an improved spinal neural system is proposed. The presented search algorithm not only accomplishes the search task but also maintains a stable formation without obstacle collisions. In the cooperative pursuit stage, a dynamic alliance method based on bidirectional negotiation strategy and a pursuit direction assignment method based on improved genetic algorithm are presented, which can realize the pursuit task efficiently. Finally, some simulations are conducted and the results show that the proposed approach is capable of guiding multi-AUVs to achieve the hunting tasks in unknown 3D underwater environment efficiently.

Keywords

Heterogeneous AUVs system Cooperative hunting Spinal neural system Fuzzy rule Genetic algorithm 

Notes

Acknowledgements

The authors would like to thank the National Natural Science Foundation of China (61203365, 61573128), the Fundamental Research Funds for the Central Universities (2015B20114), the National Key Research Program of China (2016YFC0401606) and the Jiangsu Province Natural Science Foundation (BK2012149) for their support of this paper.

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Copyright information

© Taiwan Fuzzy Systems Association and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Jianjun Ni
    • 1
    • 2
  • Liu Yang
    • 1
  • Liuying Wu
    • 1
  • Xinnan Fan
    • 1
    • 2
  1. 1.College of IOT EngineeringHohai UniversityChangzhouChina
  2. 2.Jiangsu Universities and Colleges Key Laboratory of Special Robot TechnologyHohai UniversityChangzhouChina

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