Zhao Qiang, Yang Tengfei, Tang Guoqiang, Yang Yan, Dong Fangyang, Xi Ziyue, Zou Yongjiu, Xu Minyi, Li Shuai, Wang Chen, Xie Guangming
Marine Engineering College, Dalian Maritime University, Dalian, People's Republic of China.
College of Mechanical and Control Engineering, Baicheng Normal University, Baicheng, People's Republic of China.
Bioinspir Biomim. 2025 Jun 19;20(4). doi: 10.1088/1748-3190/ade215.
With the in-depth integration of research across multiple disciplines, such as biomimetics, robotics, and sensing technology, significant advancements have been made in swarm robotics technology, which has been applied in areas including drone swarms, mobile robot swarms, and underwater robot swarms. However, due to the limitations of underwater communication technologies, underwater robot swarms have lagged behind aerial and ground swarms in their development. This paper primarily explores the applications and advancements of swarm intelligence (SI) in multiple underwater robot swarms. Inspired by the behavior of animal swarms, researchers have translated this concept into the design and control strategies of underwater robot swarms. This approach draws on the self-organization, robustness, and adaptability inherent in collective behaviors, significantly enhancing the performance of underwater robot swarms. This paper provides a comprehensive review of the current research status of bio-inspired swarming of multiple underwater robots, including the design and classification of swarm underwater robots, SI algorithms and their applications in multiple underwater robots, and communication mechanisms for underwater robots. Furthermore, this paper highlights critical technical challenges that need to be addressed in research, along with proposed solutions, and discusses the vast application prospects of bio-inspired underwater swarming in military and civilian fields, providing clear directions for future research.
随着仿生学、机器人技术和传感技术等多学科研究的深度融合，群体机器人技术取得了重大进展，并已应用于无人机群、移动机器人群和水下机器人群等领域。然而，由于水下通信技术的限制，水下机器人群的发展落后于空中和地面机器人群。本文主要探讨群体智能（SI）在多个水下机器人群中的应用和进展。受动物群体行为的启发，研究人员已将这一概念转化为水下机器人群的设计和控制策略。这种方法借鉴了集体行为中固有的自组织、鲁棒性和适应性，显著提高了水下机器人群的性能。本文全面综述了受生物启发的多个水下机器人群体的研究现状，包括群体水下机器人的设计与分类、群体智能算法及其在多个水下机器人中的应用，以及水下机器人的通信机制。此外，本文突出了研究中需要解决的关键技术挑战以及提出的解决方案，并讨论了受生物启发的水下群体在军事和民用领域的广阔应用前景，为未来研究提供了明确方向。
