The use of underwater hyperspectral imaging deployed on remotely operated vehicles methods and applications

被引:56
|
作者
Johnsen, Geir [1 ]
Ludvigsen, Martin [2 ]
Sorensen, Asgeir [2 ]
Aas, Lars Martin Sandvik [3 ]
机构
[1] Norwegian Univ Sci & Technol NTNU, Dept Biol, Ctr Autonomous Marine Operat & Syst AMOS, N-7491 Trondheim, Norway
[2] NTNU, Dept Marine Technol, Ctr Autonomous Marine Operat & Syst AMOS, N-7491 Trondheim, Norway
[3] Ecotone AS, Havnegata 9, N-7010 Trondheim, Norway
来源
IFAC PAPERSONLINE | 2016年 / 49卷 / 23期
关键词
Remotely Operated Vehicle (ROV); Underwater Hyrperspectral Imager (UHI); mapping of seafloor; habitat mapping; habitat monitoring; ecosystem management and decision making;
D O I
10.1016/j.ifacol.2016.10.451
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Currently a new underwater hyperspectral imager (UHI) have been deployed on Remotely Operated Vehicles (ROV) for a more automated identification, mapping and monitoring of bio-geo-chemical objects of interest (001). Sea floor maps based on UHI can he used to classify 001 based on specific optical fingerprints providing spectral upwelling radiance or reflectance with up to 1 nm spectral resolution in the visible range for each image pixel. Different habitats comprising soft bottom, deep and cold water coral reefs, sponge habitats, pipeline monitoring and kelp forest maps are examples for UHT based mapping. Characterising material surface on man-made objects such as corrosion on pipelines and subsea structures and archaeological objects are other examples. The overall image quality and identification success of OOI can be optimized if movements of the ROV is controlled by a dynamic position (DP) system and corresponding speed, altitude, pitch, roll and yaw control. Likewise, illumination control is important to provide proper light intensity, spectral composition and illumination evenness of OOI to enhance data quality. The benefits of using UHI for seafloor habitat mapping can he evaluated by four categories of resolution. These are A) spatial resolution (image pixel size), B) spectral resolution (1-10 nm, 400-800 nm), C) radiometric resolution (dynamic range, bits per pixel), and D) temporal resolution for time-series and monitoring. These categories of resolution are discussed with respect to 001 identification and mapping using different case examples. (C) 2016 IFAC (International Federation of automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码:476 / 481
页数:6
相关论文
共 50 条
  • [21] Using remotely operated and autonomous underwater vehicles for archaeological survey and excavation
    Yoerger, DR
    [J]. AMERICAN JOURNAL OF ARCHAEOLOGY, 1996, 100 (02) : 363 - 364
  • [22] Dynamic surface fault tolerant control for underwater remotely operated vehicles
    Baldini, Alessandro
    Ciabattoni, Lucio
    Felicetti, Riccardo
    Ferracuti, Francesco
    Freddi, Alessandro
    Monteriu, Andrea
    [J]. ISA TRANSACTIONS, 2018, 78 : 10 - 20
  • [23] Towable Instrumentation for use with a hand-deployed Remotely Operated Vehicle
    Barker, Laughlin D. L.
    Kim, Stacy L.
    Saenz, Benjamin T.
    Osborne, D. J.
    Daly, Kendra L.
    [J]. OCEANS 2016 MTS/IEEE MONTEREY, 2016,
  • [24] Dexterous Underwater Manipulation from Onshore Locations Streamlining Efficiencies for Remotely Operated Underwater Vehicles
    Birk, Andreas
    Doernbach, Tobias
    Mueller, Christian Atanas
    Luczynski, Tomasz
    Chavez, Arturo Gomez
    Koehntopp, Daniel
    Kupcsik, Andras
    Calinon, Sylvain
    Tanwani, Ajay K.
    Antonelli, Gianluca
    di Lillo, Paolo
    Simetti, Enrico
    Casalino, Giuseppe
    Indiveri, Giovanni
    Ostuni, Luigi
    Turetta, Alessio
    Caffaz, Andrea
    Weiss, Peter
    Gobert, Thibaud
    Chemisky, Bertrand
    Gancet, Jeremi
    Siedel, Torsten
    Govindaraj, Shashank
    Martinez, Xavier
    Letier, Pierre
    [J]. IEEE ROBOTICS & AUTOMATION MAGAZINE, 2018, 25 (04) : 24 - 33
  • [25] MATHEMATICAL MODEL & ROBOT DESIGN OF AUTONOMOUS UNDERWATER VEHICLES (AUV) AND REMOTELY OPERATED VEHICLES (ROV)
    Farkas, Felix-Attila
    Kalman, Kacso
    Cigan, Vlad
    Cazan, Rares
    Vuscan, Gheorghe Ioan
    [J]. ACTA TECHNICA NAPOCENSIS SERIES-APPLIED MATHEMATICS MECHANICS AND ENGINEERING, 2012, 55 (02): : 413 - 418
  • [27] High-speed on/off control for remotely operated underwater vehicles propulsion
    Zhu, Kangwu
    Chen, Yuanjie
    Li, Wei
    Wang, Feng
    Gu, Linyi
    [J]. PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON FLUID POWER TRANSMISSION AND CONTROL, 2009, : 74 - 81
  • [28] Object detection/tracking toward underwater photographs by remotely operated vehicles (ROVs)
    Zhang, Lanyong
    Li, Chengyu
    Sun, Hongfang
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2022, 126 : 163 - 168
  • [29] Passive arm based dynamic positioning system for remotely operated underwater vehicles
    Hsu, L
    Costa, RR
    Lizarralde, F
    da Cunha, JPVS
    [J]. ICRA '99: IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-4, PROCEEDINGS, 1999, : 407 - 412
  • [30] A Generalized Simulation Framework for Tethered Remotely Operated Vehicles in Realistic Underwater Environments
    Ganoni, Ori
    Mukundan, Ramakrishnan
    Green, Richard
    [J]. DRONES, 2019, 3 (01) : 1 - 34