Towards automatic recognition of mining targets using an autonomous robot.

Quintana, J., Garcia, R., Neumann, L., Campos, R., Weiss, Tim, Köser, Kevin, Mohrmann, Jochen and Greinert, Jens (2019) Towards automatic recognition of mining targets using an autonomous robot. [Paper] In: OCEANS 2018 MTS/IEEE Charleston. , 22.-25.10.2018, Charleston, USA . OCEANS 2018 MTS/IEEE Charleston. ; Article number 8604491 . DOI 10.1109/OCEANS.2018.8604491.

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Abstract

Modern technology like cell phones, wind power plants or electric cars require resources such as certain metals or rare earth elements with limited deposits on land, or expensive or difficult to obtain. Consequently, resources in the oceans like polymetallic nodules, massive sulfides and cobalt crusts are becoming more and more interesting for mining companies. Since mining in the deep sea needs careful consideration and mapping of the concerned locations, might require ecological compensation areas, and is a huge endeavor with enormous costs, logistics and machinery, detailed exploration and spatial planning, resource quantification and environment mapping are inevitable steps early in the process. While traditionally, experts performed several manual steps of map creation, interpretation, target localization, sampling and resource estimation, this paper describes a new pipeline for manganese nodule detection combining acoustic and visual information, that is ultimately intended to run automatically on an Autonomous Underwater Vehicle (AUV) without any user interaction.

Document Type: Conference or Workshop Item (Paper)
Funder compliance: info:eu-repo/grantAgreement/EC/H2020/690416
Keywords: Automatic recognition, mining targets, AUV
Research affiliation: OceanRep > GEOMAR > FB2 Marine Biogeochemistry > FB2-MG Marine Geosystems
OceanRep > GEOMAR > FB2 Marine Biogeochemistry > FB2-MG Marine Geosystems > DeepSea Monitoring
DOI etc.: 10.1109/OCEANS.2018.8604491
ISSN: 0197-7385
Projects: ROBUST
Date Deposited: 04 Mar 2019 10:09
Last Modified: 04 Mar 2019 10:09
URI: http://oceanrep.geomar.de/id/eprint/45956

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