Contributo in atti di convegno, 2017, ENG, 10.1016/j.ifacol.2017.08.2504
Roberta Ferretti, Marco Bibuli, Massimo Caccia, Davide Chiarella, Angelo Odetti, Andrea Ranieri, Enrica Zereik, Gabriele Bruzzone
Consiglio Nazionale delle Ricerche - Istituto di Studi sui Sistemi Intelligenti per l'Automazione, Via De Marini 6, 16149 Genova, Italy
This paper reports the development of a new methodology for automatic detection and mapping of underwater vegetation by means of highly autonomous marine robotic platforms. In particular, the work describes the exploitation of a Remotely Operated Vehicle (ROV), equipped with a multi-parametric sensors package, for the exploration and characterization of sea-bottoms interested by the presence of the Posidonia oceanica seagrass, which represents a valuable indicator of the environmental health. The proposed methodology relies on the systematic exploration of the sea-bottom by means of the ROV acquiring acoustic data and video imagery of the seabed, in order to reconstruct a 2.5D model of the environment (i.e. an elevation map of the sea-bottom). The data collection is achieved by the employment of a single beam echosounder for seabed range measurements and a down-looking underwater camera. Furthermore, an acoustic data procedural analysis is developed to automatically detect the Posidonia presence, so that in future works it will be possible to operate also in low-visibility conditions. Data acquisition was carried out over different seafloor types in coastal area near Biograd Na Moru (Croatia) and the results are reported in the paper.
The 20th World Congress of the International Federation of Automatic Control, IFAC 2017, pp. 12386–12391, Toulouse, France, 9-14/7/2017
Posidonia detection, seabed mapping, Unmanned Marine Vehicles
Odetti Angelo, Ferretti Roberta, Caccia Massimo, Bruzzone Gabriele, Bibuli Marco, Zereik Enrica, Chiarella Davide, Ranieri Andrea
ILC – Istituto di linguistica computazionale "Antonio Zampolli", IMATI – Istituto di matematica applicata e tecnologie informatiche "Enrico Magenes", ISSIA – Istituto di studi sui sistemi intelligenti per l'automazione, INM – Istituto di iNgegneria del Mare
ID: 378517
Year: 2017
Type: Contributo in atti di convegno
Creation: 2017-11-21 16:56:04.000
Last update: 2023-04-19 15:04:00.000
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:378517
DOI: 10.1016/j.ifacol.2017.08.2504
ISI Web of Science (WOS): 000423965200064
Scopus: 2-s2.0-85044268156