| Téléchargement | - Voir la version finale : Development of a sensor testbed for Maritime Autonomous Surface Ship situational awareness (PDF, 5.1 Mio)
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| Auteur | Rechercher : Gash, Robert M.1; Rechercher : Murrant, Kevin A.1; Rechercher : Mills, Jason W.1Identifiant ORCID : https://orcid.org/0000-0002-3040-9048 |
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| Affiliation | - Conseil national de recherches Canada. Génie océanique, côtier et fluvial
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| Format | Texte, Article |
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| Conférence | 28th International Conference on Port and Ocean Engineering under Arctic Conditions (POAC'25), July 13-17, 2025, St. John’s, Newfoundland and Labrador, Canada |
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| Sujet | ASV; EOIR Camera; image processing; LiDAR; MASS |
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| Résumé | The National Research Council of Canada's Ocean, Coastal and River Engineering Research Centre (NRC-OCRE) and Automotive and Surface Transportation Centre (NRC-AST), along with Transport Canada's Innovation Centre (TC-IC), have been collaborating over the past three years to develop systems and methodologies for investigating sensor performance on marine vehicles. A large portion of this effort has been dedicated to the development of a so-called “Maritime Autonomous Surface Ship (MASS) Sensor Testbed” - a platform for evaluation of various sensors utilized for marine vehicle situational awareness, particularly in the context of harsh environmental conditions.
Equipment suitable for deployment on model-scale and full-scale vessels in harsh environments was developed, and was deployed on a physical model-scale Offshore Supply Vessel and on a 5.5-meter Rigid Hull Inflatable Boat (RHIB) designed for autonomous surface research and development. Tank tests were performed in 2021 with a model-scale sensor testbed that informed the development of a full-scale sensor testbed. In 2024 and 2025, field trials were conducted in varying environmental conditions near port infrastructure while docking and maneuvering both in isolation as well as in coordination with an additional autonomous vessel platform (also capturing sensor data). |
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| Date de publication | 2025-08 |
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| Maison d’édition | Lulea University of Technology |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | ea9dcb3b-1ffa-4dcd-8609-455c24c7a25e |
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| Enregistrement créé | 2025-10-06 |
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| Enregistrement modifié | 2025-10-08 |
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