An Improved DSA-Based Approach for Multi-AUV Cooperative Search.

Journal: Computational intelligence and neuroscience
Published Date: Dec 2, 2018

Abstract

Multi-AUV cooperative target search problem in unknown 3D underwater environment is not only a research hot spot but also a challenging task. To complete this task, each autonomous underwater vehicle (AUV) needs to move quickly without collision and cooperate with other AUVs to find the target. In this paper, an improved dolphin swarm algorithm- (DSA-) based approach is proposed, and the search problem is divided into three stages, namely, random cruise, dynamic alliance, and team search. In the proposed approach, the Levy flight method is used to provide a random walk for AUV to detect the target information in the random cruise stage. Then the self-organizing map (SOM) neural network is used to build dynamic alliances in real time. Finally, an improved DSA algorithm is presented to realize the team search. Furthermore, some simulations are conducted, and the results show that the proposed approach is capable of guiding multi-AUVs to achieve the target search task in unknown 3D underwater environment efficiently.

Authors

  • Jianjun Ni
    College of IOT Engineering, Hohai University, Changzhou 213022, China; Changzhou Key Laboratory of Special Robot and Intelligent Technology, Hohai University, Changzhou 213022, China.
  • Liu Yang
    Department of Ultrasound, Hunan Children's Hospital, Changsha, China.
  • Pengfei Shi
    College of IOT Engineering, Hohai University, Changzhou 213022, China; Changzhou Key Laboratory of Special Robot and Intelligent Technology, Hohai University, Changzhou 213022, China.
  • Chengming Luo
    Guangdong Provincial Key Laboratory of Chip and Integration Technology, School of Electronic Science and Engineering (School of Microelectronics), South China Normal University, Foshan 528225, People's Republic of China.

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