Optimizing autonomous underwater vehicle routes with the aid of high resolution ocean models
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , |
Tipo de documento: | Livro |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/10216/123321 |
Resumo: | In underwater vehicle operations in areas such as estuaries, vehicles may face currents with magnitudes equal to or exceeding the vehicle's maximum forward speed. We propose a method which generates vehicle routes taking into account ocean current forecasts from high resolution ocean models, in order to both take advantage of the ocean current velocity and avoid its negative effects. We formulate the problem in an optimal control setting and derive the associated Hamilton-Jacobi-Bellman partial differential equation (PDE). We solve this PDE using a parallelized C++ implementation of a numerical method which allows us to obtain the solution in a few minutes on a mainstream computer. After obtaining the solution of the PDE, optimal trajectories with any initial condition can be computed efficiently. The method is illustrated using data from high-resolution ocean models of the Sado river estuary in Portugal. Two mission scenarios are analyzed, which highlight the influence of ocean currents on optimal trajectories and the benefits of considering ocean current forecasts in mission planning. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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Optimizing autonomous underwater vehicle routes with the aid of high resolution ocean modelsIn underwater vehicle operations in areas such as estuaries, vehicles may face currents with magnitudes equal to or exceeding the vehicle's maximum forward speed. We propose a method which generates vehicle routes taking into account ocean current forecasts from high resolution ocean models, in order to both take advantage of the ocean current velocity and avoid its negative effects. We formulate the problem in an optimal control setting and derive the associated Hamilton-Jacobi-Bellman partial differential equation (PDE). We solve this PDE using a parallelized C++ implementation of a numerical method which allows us to obtain the solution in a few minutes on a mainstream computer. After obtaining the solution of the PDE, optimal trajectories with any initial condition can be computed efficiently. The method is illustrated using data from high-resolution ocean models of the Sado river estuary in Portugal. Two mission scenarios are analyzed, which highlight the influence of ocean currents on optimal trajectories and the benefits of considering ocean current forecasts in mission planning.2019-06-172019-06-17T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/123321eng10.23919/oceans40490.2019.8962569Miguel AguiarJoão Borges de SousaJoão DiasJorge Estrela da SilvaRenato MendesAmérico Ribeiroinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T12:35:10Zoai:repositorio-aberto.up.pt:10216/123321Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:23:00.478751Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Optimizing autonomous underwater vehicle routes with the aid of high resolution ocean models |
title |
Optimizing autonomous underwater vehicle routes with the aid of high resolution ocean models |
spellingShingle |
Optimizing autonomous underwater vehicle routes with the aid of high resolution ocean models Miguel Aguiar |
title_short |
Optimizing autonomous underwater vehicle routes with the aid of high resolution ocean models |
title_full |
Optimizing autonomous underwater vehicle routes with the aid of high resolution ocean models |
title_fullStr |
Optimizing autonomous underwater vehicle routes with the aid of high resolution ocean models |
title_full_unstemmed |
Optimizing autonomous underwater vehicle routes with the aid of high resolution ocean models |
title_sort |
Optimizing autonomous underwater vehicle routes with the aid of high resolution ocean models |
author |
Miguel Aguiar |
author_facet |
Miguel Aguiar João Borges de Sousa João Dias Jorge Estrela da Silva Renato Mendes Américo Ribeiro |
author_role |
author |
author2 |
João Borges de Sousa João Dias Jorge Estrela da Silva Renato Mendes Américo Ribeiro |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Miguel Aguiar João Borges de Sousa João Dias Jorge Estrela da Silva Renato Mendes Américo Ribeiro |
description |
In underwater vehicle operations in areas such as estuaries, vehicles may face currents with magnitudes equal to or exceeding the vehicle's maximum forward speed. We propose a method which generates vehicle routes taking into account ocean current forecasts from high resolution ocean models, in order to both take advantage of the ocean current velocity and avoid its negative effects. We formulate the problem in an optimal control setting and derive the associated Hamilton-Jacobi-Bellman partial differential equation (PDE). We solve this PDE using a parallelized C++ implementation of a numerical method which allows us to obtain the solution in a few minutes on a mainstream computer. After obtaining the solution of the PDE, optimal trajectories with any initial condition can be computed efficiently. The method is illustrated using data from high-resolution ocean models of the Sado river estuary in Portugal. Two mission scenarios are analyzed, which highlight the influence of ocean currents on optimal trajectories and the benefits of considering ocean current forecasts in mission planning. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-06-17 2019-06-17T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/book |
format |
book |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10216/123321 |
url |
https://hdl.handle.net/10216/123321 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.23919/oceans40490.2019.8962569 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799135531500568576 |