A comprehensive review on the evolution of bio-inspired sensors from aquatic creatures

被引:7
作者
Zhao, Zetian [1 ]
Yang, Qi [2 ]
Li, Ruonan [1 ]
Yang, Jian
Liu, Qirui [2 ]
Zhu, Boyi [1 ]
Weng, Chubin [2 ]
Liu, Wenbin
Hu, Pengwei [4 ]
Ma, Li [5 ]
Qiao, Jianzhong [3 ]
Xu, Mengzhen [2 ]
Tian, He [1 ]
机构
[1] Tsinghua Univ, Beijing Natl Res Ctr Informat Sci & Technol BNRist, Sch Integrated Circuit, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Dept Hydraul Engn, Beijing 100084, Peoples R China
[3] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[4] Beihang Univ, Sch Instrumentat & Optoelect Engn, Beijing 100191, Peoples R China
[5] Chinese Acad Sci, Kunming Inst Zool, Kunming 650223, Yunnan, Peoples R China
基金
中国国家自然科学基金; 北京市自然科学基金; 美国海洋和大气管理局;
关键词
UNDERWATER ACOUSTIC COMMUNICATION; POLARIZATION SENSITIVITY; FLOW SENSORS; MODEL SYSTEM; FISH; VISION; ROBOT; ZEBRAFISH; LIGHT; DESIGN;
D O I
10.1016/j.xcrp.2024.102064
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The integration of sensors in underwater detectors is of paramount importance, enabling autonomous control and supporting auxiliary functions. However, traditional sensors have faced limitations, prompting the rapid advancement of sensor technologies. As a result, novel bio-inspired sensors have emerged, drawing inspiration from the remarkable adaptations and sensing capabilities of aquatic creatures. This review offers a comprehensive overview of the latest research and developments in the field of bio-inspired sensors inspired by aquatic creatures. It explains the various sensing principles and working principles of biological fish and encompasses an exploration of biological sensory mechanisms, various bioinspired sensor types, essential design principles, material preparations, diverse sensor modalities, and their wide-ranging applications. Of particular interest are their potential implications in revolutionizing fields such as environmental assessment, hydrodynamic and underwater imaging, as well as autonomous control in robotics. Moreover, we delve into the challenges faced in this nascent field, while also identifying future directions and underscoring the need for innovation and cross-disciplinary collaborations.
引用
收藏
页数:51
相关论文
共 202 条
[1]  
Abdulsadda A.T., 2011, Underwater Source Localization Using an IPMC-based Artificial Lateral Line, P2719
[2]   Fish optimize sensing and respiration during undulatory swimming [J].
Akanyeti, O. ;
Thornycroft, P. J. M. ;
Lauder, G. V. ;
Yanagitsuru, Y. R. ;
Peterson, A. N. ;
Liao, J. C. .
NATURE COMMUNICATIONS, 2016, 7
[3]   Insight into shark magnetic field perception from empirical observations [J].
Anderson, James M. ;
Clegg, Tamrynn M. ;
Veras, Luisa V. M. V. Q. ;
Holland, Kim N. .
SCIENTIFIC REPORTS, 2017, 7
[4]   From Biological Cilia to Artificial Flow Sensors: Biomimetic Soft Polymer Nanosensors with High Sensing Performance [J].
Asadnia, Mohsen ;
Kottapalli, Ajay Giri Prakash ;
Karavitaki, K. Domenica ;
Warkiani, Majid Ebrahimi ;
Miao, Jianmin ;
Corey, David P. ;
Triantafyllou, Michael .
SCIENTIFIC REPORTS, 2016, 6
[5]   Artificial fish skin of self-powered micro-electromechanical systems hair cells for sensing hydrodynamic flow phenomena [J].
Asadnia, Mohsen ;
Kottapalli, Ajay Giri Prakash ;
Miao, Jianmin ;
Warkiani, Majid Ebrahimi ;
Triantafyllou, Michael S. .
JOURNAL OF THE ROYAL SOCIETY INTERFACE, 2015, 12 (111)
[6]   Flexible and Surface-Mountable Piezoelectric Sensor Arrays for Underwater Sensing in Marine Vehicles [J].
Asadnia, Mohsen ;
Kottapalli, Ajay Giri Prakash ;
Shen, Zhiyuan ;
Miao, Jianmin ;
Triantafyllou, Michael .
IEEE SENSORS JOURNAL, 2013, 13 (10) :3918-3925
[7]  
Ashworth E., 2016, Exploration of the Relationship between Somatic and Otolith Growth, and Development of a Proportionality-Based Back-Calculation Approach Based on Traditional Growth Equations
[8]  
Au W.W.L., 1993, Characteristics of Dolphin Sonar Signals, P115
[9]   Survey on the Developments of Unmanned Marine Vehicles: Intelligence and Cooperation [J].
Bae, Inyeong ;
Hong, Jungpyo .
SENSORS, 2023, 23 (10)
[10]   Polarization-based underwater geolocalization with deep learning [J].
Bai, Xiaoyang ;
Liang, Zuodong ;
Zhu, Zhongmin ;
Schwing, Alexander ;
Forsyth, David ;
Gruev, Viktor .
ELIGHT, 2023, 3 (01)