A Flexible Autonomous Robotic Observatory Infrastructure for Bentho-Pelagic Monitoring

Autor: Guosong Zhang, Simone Marini, Laurenz Thomsen, Jacopo Aguzzi, Erik Rodriguez, Olav Rune Godø, Jan Albiez, Terje Torkelsen, Vanesa López-Vázquez, Javier Valencia, Sascha Flögel, Henning Wehde, Olaf Pfannkuche, Endre Grimsbø
Přispěvatelé: European Commission, Agencia Estatal de Investigación (España)
Rok vydání: 2020
Předmět:
0106 biological sciences
TheoryofComputation_COMPUTATIONBYABSTRACTDEVICES
Laser scanning
Computer science
Oceans and Seas
Video Recording
Cabled observatories
Oceanography
lcsh:Chemical technology
01 natural sciences
Biochemistry
Article
Analytical Chemistry
03 medical and health sciences
ecosystem component classification
Resource (project management)
Image processing
Observatory
Component (UML)
Animals
Humans
crawler
lcsh:TP1-1185
14. Life underwater
Electrical and Electronic Engineering
Fuel cells
Instrumentation
Ecosystem
Benthic and pelagic monitoring
Docking station
030304 developmental biology
0303 health sciences
Ecosystem component classification
Crawlers
010604 marine biology & hydrobiology
VDP::Technology: 500
Cabled observatory
Robotics
Acoustics
Anthozoa
Atomic and Molecular Physics
and Optics
VDP::Teknologi: 500
13. Climate action
Systems engineering
Environmental Monitoring
Subsea
Zdroj: Sensors
20:1614
Sensors, Vol 20, Iss 6, p 1614 (2020)
Sensors (Basel, Switzerland)
Volume 20
Issue 6
Digital.CSIC. Repositorio Institucional del CSIC
instname
ISSN: 1424-8220
0010-8707
Popis: Special issue 2019 Selected Papers from the IMEKO TC-19 International Workshop on Metrology for the Sea.-- 17 pages, 9 figures, 2 tables, supplementary material http://www.mdpi.com/1424-8220/20/6/1614/s1
This paper presents the technological developments and the policy contexts for the project “Autonomous Robotic Sea-Floor Infrastructure for Bentho-Pelagic Monitoring” (ARIM). The development is based on the national experience with robotic component technologies that are combined and merged into a new product for autonomous and integrated ecological deep-sea monitoring. Traditional monitoring is often vessel-based and thus resource demanding. It is economically unviable to fulfill the current policy for ecosystem monitoring with traditional approaches. Thus, this project developed platforms for bentho-pelagic monitoring using an arrangement of crawler and stationary platforms at the Lofoten-Vesterålen (LoVe) observatory network (Norway). Visual and acoustic imaging along with standard oceanographic sensors have been combined to support advanced and continuous spatial-temporal monitoring near cold water coral mounds. Just as important is the automatic processing techniques under development that have been implemented to allow species (or categories of species) quantification (i.e., tracking and classification). At the same time, real-time outboard processed three-dimensional (3D) laser scanning has been implemented to increase mission autonomy capability, delivering quantifiable information on habitat features (i.e., for seascape approaches). The first version of platform autonomy has already been tested under controlled conditions with a tethered crawler exploring the vicinity of a cabled stationary instrumented garage. Our vision is that elimination of the tether in combination with inductive battery recharge trough fuel cell technology will facilitate self-sustained long-term autonomous operations over large areas, serving not only the needs of science, but also sub-sea industries like subsea oil and gas, and mining
This project is funded by The Norwegian Research Council, Federal Ministry for Economic Affairs and Energy of Germany (03SX464C) and the HGF-project MOSES, Spanish Centre for the Development of Industrial Technology (EXP 00108707/SERA-20181020), and co-funded by European Union’s Horizon 2020 research and innovation program under the framework of ERA-NET Cofund MarTERA (Maritime and Marine Technologies for a new Era)
With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)
Databáze: OpenAIRE
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