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Updated: Jan 31, 2026

The Application of Open Searching-based Approaches for the Identification of Acinetobacter baumannii O-linked Glycopeptides
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An Improved DSA-Based Approach for Multi-AUV Cooperative Search.

Jianjun Ni1,2,3, Liu Yang1, Pengfei Shi1,2

  • 1College of IOT Engineering, Hohai University, Changzhou 213022, China.

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|January 11, 2019
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This study introduces an improved dolphin swarm algorithm (DSA) for multi-AUV cooperative target search in unknown underwater environments. The approach enhances search efficiency through staged operations and dynamic alliances.

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Oceanography

Background:

  • Cooperative target search using multiple autonomous underwater vehicles (AUVs) in unknown 3D environments presents significant challenges.
  • Efficient navigation, collision avoidance, and coordinated searching are critical for mission success.

Purpose of the Study:

  • To develop an efficient and robust approach for multi-AUV cooperative target search in unknown 3D underwater environments.
  • To enhance the performance of autonomous underwater vehicles in collaborative search missions.

Main Methods:

  • The proposed approach integrates Levy flight for random exploration, self-organizing map (SOM) neural networks for real-time dynamic alliance formation, and an improved dolphin swarm algorithm (DSA) for team search.
  • The search strategy is divided into three distinct stages: random cruise, dynamic alliance, and team search.

Main Results:

  • Simulations demonstrate the effectiveness of the proposed method in guiding multiple AUVs to successfully complete target search tasks.
  • The approach enables efficient cooperative searching in complex, unknown underwater environments.

Conclusions:

  • The improved dolphin swarm algorithm-based approach provides an efficient solution for multi-AUV cooperative target search.
  • The staged strategy and dynamic alliance formation significantly contribute to the success of underwater search missions.