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Real-Time Stereo-Based Ocean Surface Mapping for Robotic Floating Platforms: Concept and Methodology

Consider the case of a small, unmanned boat that is performing an autonomous mission. Naturally, such a platform might need to approximate the ocean surface of its surroundings in real-time. Much like obstacle mapping in autonomous (off-road) rovers, an approximation of the ocean surface in a vessel...

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Detalles Bibliográficos
Autores principales: Greenberg, Or, Ben-Moshe, Boaz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10143577/
https://www.ncbi.nlm.nih.gov/pubmed/37112198
http://dx.doi.org/10.3390/s23083857
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author Greenberg, Or
Ben-Moshe, Boaz
author_facet Greenberg, Or
Ben-Moshe, Boaz
author_sort Greenberg, Or
collection PubMed
description Consider the case of a small, unmanned boat that is performing an autonomous mission. Naturally, such a platform might need to approximate the ocean surface of its surroundings in real-time. Much like obstacle mapping in autonomous (off-road) rovers, an approximation of the ocean surface in a vessel’s surroundings in real-time can be used for improved control and optimized route planning. Unfortunately, such an approximation seems to require either expensive and heavy sensors or external logistics that are mostly not available for small or low-cost vessels. In this paper, we present a real-time method for detecting and tracking ocean waves around a floating object that is based on stereo vision sensors. Based on a large set of experiments, we conclude that the presented method allows reliable, real-time, and cost-effective ocean surface mapping suitable for small autonomous boats.
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spelling pubmed-101435772023-04-29 Real-Time Stereo-Based Ocean Surface Mapping for Robotic Floating Platforms: Concept and Methodology Greenberg, Or Ben-Moshe, Boaz Sensors (Basel) Article Consider the case of a small, unmanned boat that is performing an autonomous mission. Naturally, such a platform might need to approximate the ocean surface of its surroundings in real-time. Much like obstacle mapping in autonomous (off-road) rovers, an approximation of the ocean surface in a vessel’s surroundings in real-time can be used for improved control and optimized route planning. Unfortunately, such an approximation seems to require either expensive and heavy sensors or external logistics that are mostly not available for small or low-cost vessels. In this paper, we present a real-time method for detecting and tracking ocean waves around a floating object that is based on stereo vision sensors. Based on a large set of experiments, we conclude that the presented method allows reliable, real-time, and cost-effective ocean surface mapping suitable for small autonomous boats. MDPI 2023-04-10 /pmc/articles/PMC10143577/ /pubmed/37112198 http://dx.doi.org/10.3390/s23083857 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Greenberg, Or
Ben-Moshe, Boaz
Real-Time Stereo-Based Ocean Surface Mapping for Robotic Floating Platforms: Concept and Methodology
title Real-Time Stereo-Based Ocean Surface Mapping for Robotic Floating Platforms: Concept and Methodology
title_full Real-Time Stereo-Based Ocean Surface Mapping for Robotic Floating Platforms: Concept and Methodology
title_fullStr Real-Time Stereo-Based Ocean Surface Mapping for Robotic Floating Platforms: Concept and Methodology
title_full_unstemmed Real-Time Stereo-Based Ocean Surface Mapping for Robotic Floating Platforms: Concept and Methodology
title_short Real-Time Stereo-Based Ocean Surface Mapping for Robotic Floating Platforms: Concept and Methodology
title_sort real-time stereo-based ocean surface mapping for robotic floating platforms: concept and methodology
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10143577/
https://www.ncbi.nlm.nih.gov/pubmed/37112198
http://dx.doi.org/10.3390/s23083857
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