Bio-inspired swarm of underwater robots: a review

群体行为 机器人 水下 群机器人 机器人学 人工智能 仿生学 无人机 群体智能 适应性 工程类 计算机科学 移动机器人 稳健性(进化) 系统工程 机器学习 生态学 地理 粒子群优化 生物 考古 基因 生物化学 遗传学
作者
Qiang Zhao,Tengfei Yang,Guoqiang Tang,Yan Yang,Fangyang Dong,Ziyue Xi,Yongjiu Zou,Minyi Xu,Shuai Li,Chen Wang,Guangming Xie
出处
期刊:Bioinspiration & Biomimetics [IOP Publishing]
卷期号:20 (4): 041002-041002 被引量:4
标识
DOI:10.1088/1748-3190/ade215
摘要

Abstract 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.
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