AURORA, a multi-sensor dataset for robotic ocean exploration

Bernardi, Marco; Hosking, William; Petrioli, Chiara; Bett, Brian ORCID:; Jones, Daniel ORCID:; Huvenne, Veerle ORCID:; Marlow, Rachel; Furlong, Maaten; McPhail, Stephen; Munafo, Andrea. 2022 AURORA, a multi-sensor dataset for robotic ocean exploration. The International Journal of Robotics Research. 027836492210786.

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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.

Item Type: Publication - Article
Digital Object Identifier (DOI):
Programmes: NOC Programmes > Ocean BioGeosciences
ISSN: 0278-3649
Date made live: 20 Jul 2022 12:53 +0 (UTC)

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