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Cristin-resultat-ID:
1956588
Sist endret:
1. februar 2022, 09:52
NVI-rapporteringsår:
2021
Resultat
Vitenskapelig artikkel
2021
Vision-based pose estimation for autonomous operations in aquacultural fish farms
Christian Schellewald
Annette Stahl
og
Eleni Kelasidi
Tidsskrift
Tidsskrift
IFAC-PapersOnLine
ISSN 2405-8963
e-ISSN 2405-8963
NVI-nivå 1
Finn i kanalregisteret
Om resultatet
Om resultatet
Vitenskapelig artikkel
Publiseringsår: 2021
Publisert online: 2021
Volum: 54
Hefte: 16
Sider: 438 - 443
Open Access
Lenker
Lenker
original online (doi)
https://doi.org/10.1016/j.ifacol.2021.10.128
Institusjonsarkiv
hdl.handle.net/11250/2976611
Beskrivelse
Beskrivelse
Engelsk
Tittel
Vision-based pose estimation for autonomous operations in aquacultural fish farms
Sammendrag
There is a largely increasing demand for the usage of Unmanned Underwater Vehicles (UUVs) including Remotely Operated Vehicles (ROVs) for underwater aquaculture operations thereby minimizing the risks for diving accidents associated with such operations. ROVs are commonly used for short-distance inspection and intervention operations. Typically, these vehicles are human-operated and improving the sensing capabilities for visual scene interpretation will contribute significantly to achieve the desired higher degree of autonomy within ROV operations in such a challenging environment. In this paper we propose and investigate an approach enabling the underwater robot to measure its distance to the fishnet and to estimate its orientation with respect to the net. The computer vision based system exploits the 2D Fast Fourier Transform (FFT) for distance estimation from a camera to a regular net-structure in an aquaculture installation. The approach is evaluated in a simulation as well as demonstrated in real-world recordings.
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Bidragsytere
Bidragsytere
Christian Schellewald
Forfatter
ved Havbruk ved SINTEF Ocean
Annette Stahl
Forfatter
ved Institutt for teknisk kybernetikk ved Norges teknisk-naturvitenskapelige universitet
Eleni Kelasidi
Forfatter
ved Havbruk ved SINTEF Ocean
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