The Autonomous Underwater Vehicle Integrated with the Unmanned Surface Vessel Mapping the Southern Ionian Sea. The Winning Technology Solution of the Shell Ocean Discovery XPRIZE
The methods of data collection, processing, and assessment of the quality of the results of a survey conducted at the Southern Ionian Sea off the Messinian Peninsula, Greece are presented. Data were collected by the GEBCO-Nippon Foundation Alumni Team, competing in the Shell Ocean Discovery XPRIZE,...
| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/8/1344 |
| _version_ | 1827718078811602944 |
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| author | Karolina Zwolak Rochelle Wigley Aileen Bohan Yulia Zarayskaya Evgenia Bazhenova Wetherbee Dorshow Masanao Sumiyoshi Seeboruth Sattiabaruth Jaya Roperez Alison Proctor Craig Wallace Hadar Sade Tomer Ketter Benjamin Simpson Neil Tinmouth Robin Falconer Ivan Ryzhov Mohamed Elsaied Abou-Mahmoud |
| author_facet | Karolina Zwolak Rochelle Wigley Aileen Bohan Yulia Zarayskaya Evgenia Bazhenova Wetherbee Dorshow Masanao Sumiyoshi Seeboruth Sattiabaruth Jaya Roperez Alison Proctor Craig Wallace Hadar Sade Tomer Ketter Benjamin Simpson Neil Tinmouth Robin Falconer Ivan Ryzhov Mohamed Elsaied Abou-Mahmoud |
| author_sort | Karolina Zwolak |
| collection | DOAJ |
| description | The methods of data collection, processing, and assessment of the quality of the results of a survey conducted at the Southern Ionian Sea off the Messinian Peninsula, Greece are presented. Data were collected by the GEBCO-Nippon Foundation Alumni Team, competing in the Shell Ocean Discovery XPRIZE, during the Final Round of the competition. Data acquisition was conducted by the means of unmanned vehicles only. The mapping system was composed of a single deep water AUV (Autonomous Underwater Vehicle), equipped with a high-resolution synthetic aperture sonar HISAS 1032 and multibeam echosounder EM 2040, partnered with a USV (Unmanned Surface Vessel). The USV provided positioning data as well as mapping the seafloor from the surface, using a hull-mounted multibeam echosounder EM 304. Bathymetry and imagery data were collected for 24 h and then processed for 48 h, with the extensive use of cloud technology and automatic data processing. Finally, all datasets were combined to generate a 5-m resolution bathymetric surface, as an example of the deep-water mapping capabilities of the unmanned vehicles’ cooperation and their sensors’ integration. |
| first_indexed | 2024-03-10T20:16:22Z |
| format | Article |
| id | doaj.art-6882e288ed2640be96935620bbb435c0 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T20:16:22Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-6882e288ed2640be96935620bbb435c02023-11-19T22:32:01ZengMDPI AGRemote Sensing2072-42922020-04-01128134410.3390/rs12081344The Autonomous Underwater Vehicle Integrated with the Unmanned Surface Vessel Mapping the Southern Ionian Sea. The Winning Technology Solution of the Shell Ocean Discovery XPRIZEKarolina Zwolak0Rochelle Wigley1Aileen Bohan2Yulia Zarayskaya3Evgenia Bazhenova4Wetherbee Dorshow5Masanao Sumiyoshi6Seeboruth Sattiabaruth7Jaya Roperez8Alison Proctor9Craig Wallace10Hadar Sade11Tomer Ketter12Benjamin Simpson13Neil Tinmouth14Robin Falconer15Ivan Ryzhov16Mohamed Elsaied Abou-Mahmoud17Department of Navigation and Marine Hydrography, Faculty of Navigation and Naval Weapon, Polish Naval Academy, 81-127 Gdynia, PolandCenter for Coastal and Ocean Mapping, University of New Hampshire, Durham, NH 03824, USAINFOMAR, Geological Survey of Ireland, D04 K7X4 Dublin, IrelandGeological Institute of Russian Academy of Sciences, Moscow 119017, RussiaNational Institute of Water and Atmospheric Research, Wellington 6241, New ZealandEarth Analytic, Inc., Santa Fe, NM 87501, USAHydrographic and Oceanographic Department in the Japan Coast Guard, Tokyo 135-0064, JapanHydrographic Unit of the Ministry of Housing and Land, Ebene 72202, MauritiusCenter for Coastal and Ocean Mapping, University of New Hampshire, Durham, NH 03824, USAOcean Floor Geophysics, Burnaby, BC V5J 5J3, CanadaKongsberg Maritime AS-Subsea, 3183 Horten, NorwayYam-Yafo Marine Projects, Rishon Lezion 7570232, IsraelCenter for Coastal and Ocean Mapping, University of New Hampshire, Durham, NH 03824, USAHushcraft, Ltd., Tollesbury, Maldon CM9 8SE, UKSEA-KIT Int., Tollesbury, Maldon CM9 8SE, UKRobin Falconer Associates Ltd., Wellington 6241, New ZealandFederal State Budgetary Institution: Arctic and Antarctic Research Institute, Saint Petersburg 199397, RussiaPetroleum Geology Department, Faculty of Petroleum and Mining Science, University of Matrouh, Matrouh 51511, EgyptThe methods of data collection, processing, and assessment of the quality of the results of a survey conducted at the Southern Ionian Sea off the Messinian Peninsula, Greece are presented. Data were collected by the GEBCO-Nippon Foundation Alumni Team, competing in the Shell Ocean Discovery XPRIZE, during the Final Round of the competition. Data acquisition was conducted by the means of unmanned vehicles only. The mapping system was composed of a single deep water AUV (Autonomous Underwater Vehicle), equipped with a high-resolution synthetic aperture sonar HISAS 1032 and multibeam echosounder EM 2040, partnered with a USV (Unmanned Surface Vessel). The USV provided positioning data as well as mapping the seafloor from the surface, using a hull-mounted multibeam echosounder EM 304. Bathymetry and imagery data were collected for 24 h and then processed for 48 h, with the extensive use of cloud technology and automatic data processing. Finally, all datasets were combined to generate a 5-m resolution bathymetric surface, as an example of the deep-water mapping capabilities of the unmanned vehicles’ cooperation and their sensors’ integration.https://www.mdpi.com/2072-4292/12/8/1344autonomous underwater vehicleunmanned surface vesselmultibeam echosounderinterferometric sonarmapping resolutionmeasurement accuracy |
| spellingShingle | Karolina Zwolak Rochelle Wigley Aileen Bohan Yulia Zarayskaya Evgenia Bazhenova Wetherbee Dorshow Masanao Sumiyoshi Seeboruth Sattiabaruth Jaya Roperez Alison Proctor Craig Wallace Hadar Sade Tomer Ketter Benjamin Simpson Neil Tinmouth Robin Falconer Ivan Ryzhov Mohamed Elsaied Abou-Mahmoud The Autonomous Underwater Vehicle Integrated with the Unmanned Surface Vessel Mapping the Southern Ionian Sea. The Winning Technology Solution of the Shell Ocean Discovery XPRIZE Remote Sensing autonomous underwater vehicle unmanned surface vessel multibeam echosounder interferometric sonar mapping resolution measurement accuracy |
| title | The Autonomous Underwater Vehicle Integrated with the Unmanned Surface Vessel Mapping the Southern Ionian Sea. The Winning Technology Solution of the Shell Ocean Discovery XPRIZE |
| title_full | The Autonomous Underwater Vehicle Integrated with the Unmanned Surface Vessel Mapping the Southern Ionian Sea. The Winning Technology Solution of the Shell Ocean Discovery XPRIZE |
| title_fullStr | The Autonomous Underwater Vehicle Integrated with the Unmanned Surface Vessel Mapping the Southern Ionian Sea. The Winning Technology Solution of the Shell Ocean Discovery XPRIZE |
| title_full_unstemmed | The Autonomous Underwater Vehicle Integrated with the Unmanned Surface Vessel Mapping the Southern Ionian Sea. The Winning Technology Solution of the Shell Ocean Discovery XPRIZE |
| title_short | The Autonomous Underwater Vehicle Integrated with the Unmanned Surface Vessel Mapping the Southern Ionian Sea. The Winning Technology Solution of the Shell Ocean Discovery XPRIZE |
| title_sort | autonomous underwater vehicle integrated with the unmanned surface vessel mapping the southern ionian sea the winning technology solution of the shell ocean discovery xprize |
| topic | autonomous underwater vehicle unmanned surface vessel multibeam echosounder interferometric sonar mapping resolution measurement accuracy |
| url | https://www.mdpi.com/2072-4292/12/8/1344 |
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