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<p>Formation control remains a critical challenge in cooperative multi-agent systems, particularly for Unmanned Underwater Vehicles (UUVs). Conventional approaches often suffer from several limitations, including reliance on global information, limited adaptability, high computational complexity, and poor scalability. To address these issues, we propose a novel bio-inspired formation control method for UUV swarms, drawing inspiration from the self-organizing behavior of fish schools. Our method integrates three key components: (1) a coordinated motion strategy without predefined targets that enables individual UUVs to align their movements via simple left or right rotations based solely on local neighbor interactions; (2) a target-directed movement strategy that guides UUVs toward specified regions; and (3) a dispersion control strategy that prevents overcrowding by regulating local spatial distributions. Simulation results confirm that the method achieves robust formation control and efficient area coverage using only local perception. Validation in a 9-UUV simulation environment demonstrates the approach’s flexibility, decentralization, and computational efficiency, making it particularly suitable for large-scale swarms with limited sensing and processing capabilities.</p>

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A Minimalistic and Decentralised Approach to Formation Control for Crowded UUV Swarms Inspired by Fish Schooling

  • 期刊论文

  • 发表日期：

    2025年8月21日

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  • Xuhang Wu,
  • Xiangyang Deng,
  • Bang Wen,
  • Shengzhi Yue,
  • Siyang Shao,
  • Fumin Zhang,
  • Fang Wang,
  • Yuanshan Lin

摘要

Formation control remains a critical challenge in cooperative multi-agent systems, particularly for Unmanned Underwater Vehicles (UUVs). Conventional approaches often suffer from several limitations, including reliance on global information, limited adaptability, high computational complexity, and poor scalability. To address these issues, we propose a novel bio-inspired formation control method for UUV swarms, drawing inspiration from the self-organizing behavior of fish schools. Our method integrates three key components: (1) a coordinated motion strategy without predefined targets that enables individual UUVs to align their movements via simple left or right rotations based solely on local neighbor interactions; (2) a target-directed movement strategy that guides UUVs toward specified regions; and (3) a dispersion control strategy that prevents overcrowding by regulating local spatial distributions. Simulation results confirm that the method achieves robust formation control and efficient area coverage using only local perception. Validation in a 9-UUV simulation environment demonstrates the approach’s flexibility, decentralization, and computational efficiency, making it particularly suitable for large-scale swarms with limited sensing and processing capabilities.