Underwater Moving Object Detection Using Superficial Electromagnetic Flow Velometer Array-Based Artificial Lateral Line System

被引:14
|
作者
Wang, Zhangtao [1 ]
Wang, Shaoping [1 ,2 ,3 ]
Wang, Xingjian [1 ,2 ,3 ]
Luo, Xuesong [4 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[2] Beihang Univ, Ningbo Inst Technol, Ningbo 315800, Peoples R China
[3] Tianmushan Lab, Hangzhou 310023, Peoples R China
[4] Tsinghua Univ, Natl Engn Res Ctr Neuromodulat, Sch Aerosp Engn, Beijing 100084, Peoples R China
关键词
Artificial lateral line; autonomous underwater vehicle; flow perception; underwater wake flow; FISH; NAVIGATION; SENSOR;
D O I
10.1109/JSEN.2024.3370259
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Inspired by the flow perception ability of underwater organisms' lateral line system (LLS), recently, the artificial lateral line system (ALLS) has shown highly competitive application prospects in AUVs. However, the existing ALLS contains lots of movable parts, which are easily damaged and entangled and will generate flow resistance to the AUV carrier. Moreover, existing ALLS mainly focus on vibration object detection, while the studies on the more common and valuable translational moving objects are relatively less. In this article, a novel and practical theory for underwater moving object detection is proposed to achieve no-contact object velocity estimation via the measured object wake flow signal. The object motion-induced flow field and sensor signals are well studied. The signal-processing method is established based on the array signals' time delay features. A fully solid-state ALLS is proposed using a permanent magnet-based superficial electromagnetic flow velometer array without any movable parts. The experimental results prove that the proposed ALLS and the object velocity estimation method are ultrarobust to the object shape and object distance changes. The object velocity estimation accuracy of the proposed ALLS reaches 96.64%-99.96% within the range of 0-0.875 [m/s] and the maximum detection range reaches 0.14 [m] of the test 0.02 [m] width cuboid object at 0.5 [m/s].
引用
收藏
页码:12104 / 12121
页数:18
相关论文
共 42 条
  • [31] Moving object detection for unconstrained low-altitude aerial videos, a pose-independant detector based on Artificial Flow
    Castelli, Thomas
    Tremeau, Alain
    Konik, Hubert
    Dinet, Eric
    ISPA 2015 9TH INTERNATIONAL SYMPOSIUM ON IMAGE AND SIGNAL PROCESSING AND ANALYSIS, 2015, : 42 - 47
  • [32] Map-based localization and loop-closure detection from a moving underwater platform using flow features
    Muhammad, Naveed
    Fuentes-Perez, Juan Francisco
    Tuhtan, Jeffrey A.
    Toming, Gert
    Musall, Mark
    Kruusmaa, Maarja
    AUTONOMOUS ROBOTS, 2019, 43 (06) : 1419 - 1434
  • [33] Map-based localization and loop-closure detection from a moving underwater platform using flow features
    Naveed Muhammad
    Juan Francisco Fuentes-Perez
    Jeffrey A. Tuhtan
    Gert Toming
    Mark Musall
    Maarja Kruusmaa
    Autonomous Robots, 2019, 43 : 1419 - 1434
  • [34] Artificial Lateral Line Sensor for Robotic Fish Speed Measurement Based on Surface Flow Field Detection and Turbulence Noise Suppression
    Zhang, Zhuoliang
    Zhou, Chao
    Cheng, Long
    Fan, Junfeng
    Tan, Min
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2024, : 1 - 14
  • [35] Moving object detection using median-based scale invariant local ternary pattern for video surveillance system
    Kalirajan, K.
    Sudha, M.
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2017, 33 (03) : 1933 - 1943
  • [36] Real object-based holographic stereogram printing system using a high-resolution one-dimensional moving camera array
    Erdenebat, Munkh-Uchral
    Khuderchuluun, Anar
    Dashdavaa, Erkhembaatar
    Kwon, Ki-Chul
    Lee, Kwon-Yeon
    Gil, Sang-Keun
    Kim, Nam
    PRACTICAL HOLOGRAPHY XXXV: DISPLAYS, MATERIALS, AND APPLICATIONS, 2021, 11710
  • [37] Rapid Detection of Feline Calicivirus Using Lateral Flow Dipsticks Based on CRISPR/Cas13a System
    Zhang, Zichuang
    Li, Jing
    Zhang, Chengqi
    Bai, Xue
    Zhang, Tie
    ANIMALS, 2024, 14 (24):
  • [38] Power Line Detection for Aerial Images Using Object-Based Markov Random Field With Discrete Multineighborhood System
    Zhao, Le
    Yao, Hongtai
    Fan, Yajun
    Ma, Haihua
    Li, Zhihui
    Tian, Meng
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2024, 21 : 1 - 5
  • [39] Development of a smartphone-based lateral-flow imaging system using machine-learning classifiers for detection of Salmonella spp.
    Min, Hyun Jung
    Mina, Hansel A.
    Deering, Amanda J.
    Bae, Euiwon
    JOURNAL OF MICROBIOLOGICAL METHODS, 2021, 188
  • [40] Rapid and visual detection of hepatitis B virus using the ERA/Cas12f1_ge4.1-based lateral flow assay system
    Zhou, Xuan
    Tang, Honghua
    Luo, Gemiao
    Zou, Lintao
    Liu, Hangxi
    Wen, Piaoting
    Yang, Ruifu
    Deng, Zhongliang
    ANALYTICAL METHODS, 2025, 17 (07) : 1503 - 1510