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AURORA, a multi-sensor dataset for robotic ocean exploration
Bernardi, M.; Hosking, B.; Petrioli, C.; Bett, B.J.; Jones, D.; Huvenne, V.A.I.; Marlow, R.; Furlong, M.; McPhail, S.; Munafo, A. (2022). AURORA, a multi-sensor dataset for robotic ocean exploration. International Journal of Robotics Research 41(5): 461-469. https://dx.doi.org/10.1177/02783649221078612
In: International Journal of Robotics Research. SAGE PUBLICATIONS LTD: London. ISSN 0278-3649; e-ISSN 1741-3176
Peer reviewed article  
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Author keywords
    Autonomous underwater vehicles; imaging camera; sidescan sonar; multibeam echosounder; underwater navigation
Auteurs  Top 
  • Bernardi, M.
  • Hosking, B.
  • Petrioli, C.
  • Bett, B.J.
  • Jones, D.
  • Huvenne, V.A.I.
  • Marlow, R.
  • Furlong, M.
  • McPhail, S.
  • Munafo, A.
Abstract
    The current maturity of autonomous underwater vehicles (AUVs) has made their deployment practical and cost-effective, such that many scientific, industrial and military applications now include AUV operations. However, the logistical difficulties and high costs of operating at sea are still critical limiting factors in further technology development, the benchmarking of new techniques and the reproducibility of research results. To overcome this problem, this paper presents a freely available dataset suitable to test control, navigation, sensor processing algorithms and others tasks. This dataset combines AUV navigation data, sidescan sonar, multibeam echosounder data and seafloor camera image data, and associated sensor acquisition metadata to provide a detailed characterisation of surveys carried out by the National Oceanography Centre (NOC) in the Greater Haig Fras Marine Conservation Zone (MCZ) of the U.K in 2015.
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