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Research on Cooperative Perception of MUSVs in Complex Ocean Conditions

Since the working environment of Multiple Unmanned Surface Vehicles (MUSVs) is accompanied by a large number of uncertainties and various hazards, in order to ensure the collision avoidance capability of MUSVs in complex marine environments, the perception of complex marine environments by MUSVs is...

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Detalles Bibliográficos
Autores principales: Yin, Lili, Zhang, Rubo, Gu, Hengwen, Li, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7957737/
https://www.ncbi.nlm.nih.gov/pubmed/33670851
http://dx.doi.org/10.3390/s21051657
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author Yin, Lili
Zhang, Rubo
Gu, Hengwen
Li, Peng
author_facet Yin, Lili
Zhang, Rubo
Gu, Hengwen
Li, Peng
author_sort Yin, Lili
collection PubMed
description Since the working environment of Multiple Unmanned Surface Vehicles (MUSVs) is accompanied by a large number of uncertainties and various hazards, in order to ensure the collision avoidance capability of MUSVs in complex marine environments, the perception of complex marine environments by MUSVs is the first problem that needs to be solved. A cooperative perception framework with uncertain event detection, cooperative collision avoidance pattern recognition and environmental ontology model is proposed to realize the cooperative perception process of MUSVs using ontology and Bayesian network theory. The cooperative perception approach was validated by simulating experiments. Results show the effectiveness of cooperative perception approach.
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spelling pubmed-79577372021-03-16 Research on Cooperative Perception of MUSVs in Complex Ocean Conditions Yin, Lili Zhang, Rubo Gu, Hengwen Li, Peng Sensors (Basel) Article Since the working environment of Multiple Unmanned Surface Vehicles (MUSVs) is accompanied by a large number of uncertainties and various hazards, in order to ensure the collision avoidance capability of MUSVs in complex marine environments, the perception of complex marine environments by MUSVs is the first problem that needs to be solved. A cooperative perception framework with uncertain event detection, cooperative collision avoidance pattern recognition and environmental ontology model is proposed to realize the cooperative perception process of MUSVs using ontology and Bayesian network theory. The cooperative perception approach was validated by simulating experiments. Results show the effectiveness of cooperative perception approach. MDPI 2021-02-28 /pmc/articles/PMC7957737/ /pubmed/33670851 http://dx.doi.org/10.3390/s21051657 Text en © 2021 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yin, Lili
Zhang, Rubo
Gu, Hengwen
Li, Peng
Research on Cooperative Perception of MUSVs in Complex Ocean Conditions
title Research on Cooperative Perception of MUSVs in Complex Ocean Conditions
title_full Research on Cooperative Perception of MUSVs in Complex Ocean Conditions
title_fullStr Research on Cooperative Perception of MUSVs in Complex Ocean Conditions
title_full_unstemmed Research on Cooperative Perception of MUSVs in Complex Ocean Conditions
title_short Research on Cooperative Perception of MUSVs in Complex Ocean Conditions
title_sort research on cooperative perception of musvs in complex ocean conditions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7957737/
https://www.ncbi.nlm.nih.gov/pubmed/33670851
http://dx.doi.org/10.3390/s21051657
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