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Adaptive Sampling of Ocean Processes Using an AUV with a Gaussian Proxy Model

Berget, Gunhild Elisabeth; Fossum, Trygve Olav; Johansen, Tor Arne; Eidsvik, Jo; Rajan, Kanna
Journal article, Peer reviewed
Published version
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1-s2.0-S2405896318321980-main.pdf (1.263Mb)
URI
http://hdl.handle.net/11250/2579599
Date
2018
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  • Institutt for teknisk kybernetikk [2188]
  • Publikasjoner fra CRIStin - NTNU [19812]
Original version
IFAC-PapersOnLine. 2018, 51 (29), 238-243.   10.1016/j.ifacol.2018.09.509
Abstract
This paper presents methods for building and exploiting compact spatial models on board an autonomous underwater vehicle (AUV) towards tracking suspended material plumes. The research is aiming to improve real-time monitoring of dispersal dynamics connected to marine industries such as oil and mine tailing. By exploiting in-situ information from sensors, the AUV is able to assimilate and adapt the mission capitalizing on all the information available. The spatial model is built using Gaussian process approximations and an objective function for path planning is suggested to maximize the value of the collected information.
Publisher
Elsevier
Journal
IFAC-PapersOnLine

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