The increasing complexity of marine operations has intensified the need for intelligent robotic systems to support ocean observation, exploration, and resource management. Underwater swarm robotics offers a promising framework that extends the capabilities of individual autonomous platforms through collective coordination. Inspired by natural systems, such as fish schools and insect colonies, bio-inspired swarm approaches enable distributed decision-making, adaptability, and resilience under challenging marine conditions. Yet research in this field remains fragmented, with limited integration across algorithmic, communication, and hardware design perspectives. This review synthesises bio-inspired coordination mechanisms, communication strategies, and system design considerations for underwater swarm robotics. It examines key marine-specific algorithms, including the Artificial Fish Swarm Algorithm, Whale Optimisation Algorithm, Coral Reef Optimisation, and Marine Predators Algorithm, highlighting their applications in formation control, task allocation, and environmental interaction. The review also analyses communication constraints unique to the underwater domain and emerging acoustic, optical, and hybrid solutions that support cooperative operation. Additionally, it examines hardware and system design advances that enhance system efficiency and scalability. A multi-dimensional classification framework evaluates existing approaches across communication dependency, environmental adaptability, energy efficiency, and swarm scalability. Through this integrated analysis, the review unifies bio-inspired coordination algorithms, communication modalities, and system design approaches. It also identifies converging trends, key challenges, and future research directions for real-world deployment of underwater swarm systems.

翻译：随着海洋作业复杂性的日益增加，对支持海洋观测、勘探与资源管理的智能机器人系统的需求愈发迫切。水下群体机器人提供了一个有前景的框架，通过集体协调扩展了单个自主平台的能力。受鱼群和昆虫群落等自然系统的启发，仿生群体方法能够在充满挑战的海洋环境下实现分布式决策、适应性与鲁棒性。然而，该领域的研究仍较为零散，在算法、通信和硬件设计视角之间的整合有限。本综述综合了水下群体机器人的仿生协调机制、通信策略与系统设计考量。文章审视了关键的海洋专用算法，包括人工鱼群算法、鲸鱼优化算法、珊瑚礁优化算法和海洋捕食者算法，重点阐述了它们在编队控制、任务分配和环境交互中的应用。综述还分析了水下领域特有的通信约束，以及支持协同作业的新兴声学、光学和混合解决方案。此外，文章探讨了提升系统效率和可扩展性的硬件与系统设计进展。一个多维分类框架从通信依赖性、环境适应性、能源效率和群体可扩展性等方面评估了现有方法。通过这一整合分析，本综述统一了仿生协调算法、通信模式与系统设计方法。文章还指出了水下群体系统实际部署中的融合趋势、关键挑战以及未来的研究方向。