Opendata, web and dolomites


Robotic subsea exploration technologies

Total Cost €


EC-Contrib. €






Project "ROBUST" data sheet

The following table provides information about the project.


Organization address
postcode: CB21 6AL

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Project website
 Total cost 5˙986˙722 €
 EC max contribution 5˙986˙722 € (100%)
 Programme 1. H2020-EU.3.5.3. (Ensuring the sustainable supply of non-energy and non-agricultural raw materials)
 Code Call H2020-SC5-2015-one-stage
 Funding Scheme RIA
 Starting year 2015
 Duration (year-month-day) from 2015-12-01   to  2020-01-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    TWI LIMITED UK (CAMBRIDGE) coordinator 987˙536.00
2    LZH LASERZENTRUM HANNOVER EV DE (HANNOVER) participant 1˙237˙784.00
3    UNIVERSITA DEGLI STUDI DI GENOVA IT (GENOVA) participant 900˙130.00
4    GRAAL TECH SRL IT (GENOVA) participant 789˙967.00
5    ALS MARINE CONSULTANTS LTD CY (LEMESOS) participant 663˙250.00
6    CORONIS COMPUTING SL ES (GIRONA) participant 659˙375.00
8    NEOLASE GMBH DE (HANNOVER) participant 190˙643.00
9    CGG SERVICES SAS FR (MASSY) participant 9˙036.00


 Project objective

There is a need to develop an autonomous, reliable, cost effective technology to map vast terrains, in terms of mineral and raw material contents which will aid in reducing the cost of mineral exploration, currently performed by ROVs and dedicated SSVs and crew. Furthermore there is a need to identify, in an efficient and non-intrusive manner (minimum impact to the environment), the most rich mineral sites. This technology will aid the seabed mining industry, reduce the cost of exploration and especially the detailed identification of the raw materials contained in a mining sites and enable targeted mining only of the richest resources existing.

The ROBUST proposal aims to tackle the aforementioned issue by developing sea bed in situ material identification through the fusion of two technologies, namely laser-based in-situ element-analyzing capability merged with underwater AUV (Autonomous Underwater Vehicle) technologies for sea bed 3D mapping. This will enable resource identification done by robotic control enabled by the synergy between AUV hovering and manipulator capabilities. The underwater robotic laser process is the Laser Induced Breakdown Spectroscopy (LIBS), used for identification of materials on the sea bed. The AUV Robotic vehicle will dive, identify the resources that are targeted for LIBS scanning through 3D real time mapping of the terrain (hydro-acoustically, laser scanners, photogrammetry) and position the LIBS in the required locations of mineral deposits on the ocean floor to autonomously perform qualitative and quantitative analyses.


List of deliverables.
Operational requirements of the AUV Documents, reports 2020-04-23 21:35:13
3D sea bed mapping, target identification and volume measurement Documents, reports 2020-04-23 21:35:13
Requirements for LIBS operation in 6000 m sea depth Documents, reports 2020-04-23 21:35:13
Operational requirements of the arm Documents, reports 2020-04-23 21:35:13
Assessment of the sea bed mining geology and characteristics Documents, reports 2020-04-23 21:35:13
Project Website Websites, patent fillings, videos etc. 2020-04-23 21:35:13

Take a look to the deliverables list in detail:  detailed list of ROBUST deliverables.


year authors and title journal last update
List of publications.
2020 Klemen Istenič, Nuno Gracias, Aurélien Arnaubec, Javier Escartín, Rafael Garcia
Automatic scale estimation of structure from motion based 3D models using laser scalers in underwater scenarios
published pages: 13-25, ISSN: 0924-2716, DOI: 10.1016/j.isprsjprs.2019.10.007
ISPRS Journal of Photogrammetry and Remote Sensing 159 2020-04-23
2019 Klemen Istenič, Nuno Gracias, Aurélien Arnaubec, Javier Escartín, Rafael Garcia
Scale Accuracy Evaluation of Image-Based 3D Reconstruction Strategies Using Laser Photogrammetry
published pages: 2093, ISSN: 2072-4292, DOI: 10.3390/rs11182093
Remote Sensing 11/18 2020-04-23

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The information about "ROBUST" are provided by the European Opendata Portal: CORDIS opendata.

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