Bio-inspired swarm of underwater robots: a review.

IF 3.1 3区 计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY
Qiang Zhao, Tengfei Yang, Guoqiang Tang, Yan Yang, Fangyang Dong, Ziyue Xi, Yongjiu Zou, Minyi Xu, Shuai Li, Chen Wang, Guangming Xie
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引用次数: 0

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.

仿生水下机器人群:综述。
随着仿生学、机器人技术、传感技术等多学科研究的深入融合,蜂群机器人技术取得了重大进展,已在无人机蜂群、移动机器人蜂群、水下机器人蜂群等领域得到应用。然而,由于水下通信技术的限制,水下机器人群体的发展落后于空中和地面群体。本文主要探讨了群体智能在多个水下机器人群体中的应用与进展。受动物群体行为的启发,研究人员将这一概念转化为水下机器人群体的设计和控制策略。该方法利用了集体行为固有的自组织、鲁棒性和适应性,显著提高了水下机器人群体的性能。本文综述了水下机器人仿生群的研究现状,包括水下机器人群体的设计与分类、群体智能算法及其在水下机器人中的应用、水下机器人之间的通信机制等。此外,本文还强调了研究中需要解决的关键技术挑战,并提出了解决方案,并讨论了仿生水下蜂群在军事和民用领域的广阔应用前景,为未来的研究提供了明确的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Bioinspiration & Biomimetics
Bioinspiration & Biomimetics 工程技术-材料科学:生物材料
CiteScore
5.90
自引率
14.70%
发文量
132
审稿时长
3 months
期刊介绍: Bioinspiration & Biomimetics publishes research involving the study and distillation of principles and functions found in biological systems that have been developed through evolution, and application of this knowledge to produce novel and exciting basic technologies and new approaches to solving scientific problems. It provides a forum for interdisciplinary research which acts as a pipeline, facilitating the two-way flow of ideas and understanding between the extensive bodies of knowledge of the different disciplines. It has two principal aims: to draw on biology to enrich engineering and to draw from engineering to enrich biology. The journal aims to include input from across all intersecting areas of both fields. In biology, this would include work in all fields from physiology to ecology, with either zoological or botanical focus. In engineering, this would include both design and practical application of biomimetic or bioinspired devices and systems. Typical areas of interest include: Systems, designs and structure Communication and navigation Cooperative behaviour Self-organizing biological systems Self-healing and self-assembly Aerial locomotion and aerospace applications of biomimetics Biomorphic surface and subsurface systems Marine dynamics: swimming and underwater dynamics Applications of novel materials Biomechanics; including movement, locomotion, fluidics Cellular behaviour Sensors and senses Biomimetic or bioinformed approaches to geological exploration.
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