Object perception in underwater environments: a survey on sensors and sensing methodologies

被引:52
|
作者
Huy, Dinh Quang [2 ]
Sadjoli, Nicholas [1 ,2 ]
Azam, Abu Bakr [2 ,3 ]
Elhadidi, Basman [4 ]
Cai, Yiyu [2 ,3 ]
Seet, Gerald [2 ]
机构
[1] SAAB, Singapore, Singapore
[2] Nanyang Technol Univ, SAAB NTU Joint Lab, Singapore, Singapore
[3] Nanyang Technol Univ, Energy Res Inst, Singapore, Singapore
[4] Nazarbayev Univ, Sch Engn & Digital Sci, Astana, Kazakhstan
关键词
Underwater robotic; Object perception; Turbid environment; IMAGE-RESOLUTION ENHANCEMENT; AUTOMATIC INTERPRETATION; SUPER RESOLUTION; CFAR PROCESSORS; TARGET TRACKING; SONAR; SEQUENCES; RECONSTRUCTION; FUSION;
D O I
10.1016/j.oceaneng.2022.113202
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Underwater robots play a critical role in the marine industry. Object perception is the foundation for the au-tomatic operations of submerged vehicles in dynamic aquatic environments. However, underwater perception encounters multiple environmental challenges, including rapid light attenuation, light refraction, or back -scattering effect. These problems reduce the sensing devices' signal-to-noise ratio (SNR), making underwater perception a complicated research topic. This paper describes the state-of-the-art sensing technologies and object perception techniques for underwater robots in different environmental conditions. Due to the current sensing modalities' various constraints and characteristics, we divide the perception ranges into close-range, medium-range, and long-range. We survey and describe recent advances for each perception range and suggest some potential future research directions worthy of investigating in this field.
引用
收藏
页数:25
相关论文
共 50 条
  • [1] A Survey of Sensing Methodologies in Smart Grids
    Alhariry, Alaa
    Brown, Spencer
    Eshenbaugh, Douglas
    Whitt, Nathan
    Browne, Aidan F.
    SOUTHEASTCON 2021, 2021, : 351 - 355
  • [2] A mosaicking technique for object identification in underwater environments
    Nunes, Alexandra Pereira
    Silva Gaspar, Ana Rita
    Pinto, Andry M.
    Matos, Anibal Castilho
    SENSOR REVIEW, 2019, 39 (03) : 387 - 396
  • [3] A Survey on Methodologies for Runtime Prediction on Grid Environments
    Seneviratne, Sena
    Witharana, Sanjeeva
    2014 7TH INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION FOR SUSTAINABILITY (ICIAFS), 2014,
  • [4] Underwater robot sensing technology: A survey
    Cong, Yang
    Gu, Changjun
    Zhang, Tao
    Gao, Yajun
    FUNDAMENTAL RESEARCH, 2021, 1 (03): : 337 - 345
  • [5] A hierarchical classification system for object recognition in underwater environments
    Foresti, GL
    Gentili, S
    IEEE JOURNAL OF OCEANIC ENGINEERING, 2002, 27 (01) : 66 - 78
  • [6] Data Augmentation Method for Object Detection in Underwater Environments
    Noh, Jung-min
    Jang, Ga-Ram
    Ha, Kyoung-Nam
    Park, Jae-Han
    2019 19TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS 2019), 2019, : 324 - 328
  • [7] Design and validation of object recognition methodologies for underwater fluorescence LIDAR applications
    Matteoli, Stefania
    Zotta, Laura
    Diani, Marco
    Corsini, Giovanni
    REMOTE SENSING OF THE OCEAN, SEA ICE, COASTAL WATERS, AND LARGE WATER REGIONS 2014, 2014, 9240
  • [8] Detection of Underwater Moving Object Based on the Compressed Sensing
    Qi Jie
    Sun Weitao
    Sun Haixin
    Lin Congren
    Yao Guangtao
    2016 IEEE/OES CHINA OCEAN ACOUSTICS SYMPOSIUM (COA), 2016,
  • [9] Biomimetic multilayer flexible sensors for multifunctional underwater sensing
    Sun, Yafei
    Yang, Yongli
    Yao, Dahu
    Gao, Xiping
    Chen, Jing
    Wang, Hui
    You, Tianyan
    Dong, Yonghe
    Lu, Yuhao
    Lu, Chang
    Pang, Xinchang
    CHEMICAL ENGINEERING JOURNAL, 2024, 492
  • [10] Remote sensing platforms and sensors: A survey
    Toth, Charles
    Jozkow, Grzegorz
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2016, 115 : 22 - 36