Architecture for autonomous navigation of inspection robots on energy underground distribution cables

Detalhes bibliográficos
Autor(a) principal: Estrada, Emanuel
Data de Publicação: 2010
Outros Autores: Silveira, Luan, Corrêa, Ulisses, Oliveira, Vinicius De, Botelho, Silvia Silva da Costa
Tipo de documento: Artigo
Idioma: por
Título da fonte: Vetor (Online)
Texto Completo: https://periodicos.furg.br/vetor/article/view/1680
Resumo: This work presents an architecture developed to navigation system in real and simulated robots designed to inspect underground pipes with energy distribution cables. The platform based on this architecture permits to develop and validate the navigation system in a simulation environment and, subsequently, to test and validate in the real environment. In this sense, the platform includes aspects related with sensors simulation, computational vision and planning applied in this kind of environment. The computation platform integrates Hough Transform and Artificial Neural Networks to detect obstacles and infer the best action in the environment.
id FURG-7_ad836b18123f22d1b130869f4f420c84
oai_identifier_str oai:periodicos.furg.br:article/1680
network_acronym_str FURG-7
network_name_str Vetor (Online)
repository_id_str
spelling Architecture for autonomous navigation of inspection robots on energy underground distribution cablesArquitetura de navegação autônoma de linhas subterrâneas de distribuição de energiaNavegação de Robôs MóveisRedes Neurais ArtificiaisTransformada de HoughThis work presents an architecture developed to navigation system in real and simulated robots designed to inspect underground pipes with energy distribution cables. The platform based on this architecture permits to develop and validate the navigation system in a simulation environment and, subsequently, to test and validate in the real environment. In this sense, the platform includes aspects related with sensors simulation, computational vision and planning applied in this kind of environment. The computation platform integrates Hough Transform and Artificial Neural Networks to detect obstacles and infer the best action in the environment.Este trabalho apresenta a arquitetura desenvolvida para um sistema de navegação de robôs, reais e simulados, designados para inspecionar ambientes de distribuição de energia, constituídos por cabos em dutos subterrâneos. A plataforma baseada nesta arquitetura permite o desenvolvimento e validação do sistema de navegação em um ambiente simulado e, subsequentemente, em um ambiente real. Neste sentido, a plataforma inclui aspectos relacionados com simulação de sensores, visão computacional e planejamento aplicado a este tipo de ambiente. A plataforma computacional integra transformada de Hough e Redes Neurais para detectar obstáculos e inferir a melhor ação a ser tomada no ambiente.Universidade Federal do Rio Grande2010-12-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.furg.br/vetor/article/view/1680VETOR - Journal of Exact Sciences and Engineering; Vol. 18 No. 1 (2008); 32-45VETOR - Revista de Ciências Exatas e Engenharias; v. 18 n. 1 (2008); 32-452358-34520102-7352reponame:Vetor (Online)instname:Universidade Federal do Rio Grande (FURG)instacron:FURGporhttps://periodicos.furg.br/vetor/article/view/1680/820Copyright (c) 2014 VETOR - Revista de Ciências Exatas e Engenhariasinfo:eu-repo/semantics/openAccessEstrada, EmanuelSilveira, LuanCorrêa, UlissesOliveira, Vinicius DeBotelho, Silvia Silva da Costa2023-03-22T15:42:40Zoai:periodicos.furg.br:article/1680Revistahttps://periodicos.furg.br/vetorPUBhttps://periodicos.furg.br/vetor/oaigmplatt@furg.br2358-34520102-7352opendoar:2023-03-22T15:42:40Vetor (Online) - Universidade Federal do Rio Grande (FURG)false
dc.title.none.fl_str_mv Architecture for autonomous navigation of inspection robots on energy underground distribution cables
Arquitetura de navegação autônoma de linhas subterrâneas de distribuição de energia
title Architecture for autonomous navigation of inspection robots on energy underground distribution cables
spellingShingle Architecture for autonomous navigation of inspection robots on energy underground distribution cables
Estrada, Emanuel
Navegação de Robôs Móveis
Redes Neurais Artificiais
Transformada de Hough
title_short Architecture for autonomous navigation of inspection robots on energy underground distribution cables
title_full Architecture for autonomous navigation of inspection robots on energy underground distribution cables
title_fullStr Architecture for autonomous navigation of inspection robots on energy underground distribution cables
title_full_unstemmed Architecture for autonomous navigation of inspection robots on energy underground distribution cables
title_sort Architecture for autonomous navigation of inspection robots on energy underground distribution cables
author Estrada, Emanuel
author_facet Estrada, Emanuel
Silveira, Luan
Corrêa, Ulisses
Oliveira, Vinicius De
Botelho, Silvia Silva da Costa
author_role author
author2 Silveira, Luan
Corrêa, Ulisses
Oliveira, Vinicius De
Botelho, Silvia Silva da Costa
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Estrada, Emanuel
Silveira, Luan
Corrêa, Ulisses
Oliveira, Vinicius De
Botelho, Silvia Silva da Costa
dc.subject.por.fl_str_mv Navegação de Robôs Móveis
Redes Neurais Artificiais
Transformada de Hough
topic Navegação de Robôs Móveis
Redes Neurais Artificiais
Transformada de Hough
description This work presents an architecture developed to navigation system in real and simulated robots designed to inspect underground pipes with energy distribution cables. The platform based on this architecture permits to develop and validate the navigation system in a simulation environment and, subsequently, to test and validate in the real environment. In this sense, the platform includes aspects related with sensors simulation, computational vision and planning applied in this kind of environment. The computation platform integrates Hough Transform and Artificial Neural Networks to detect obstacles and infer the best action in the environment.
publishDate 2010
dc.date.none.fl_str_mv 2010-12-06
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.furg.br/vetor/article/view/1680
url https://periodicos.furg.br/vetor/article/view/1680
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.furg.br/vetor/article/view/1680/820
dc.rights.driver.fl_str_mv Copyright (c) 2014 VETOR - Revista de Ciências Exatas e Engenharias
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2014 VETOR - Revista de Ciências Exatas e Engenharias
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal do Rio Grande
publisher.none.fl_str_mv Universidade Federal do Rio Grande
dc.source.none.fl_str_mv VETOR - Journal of Exact Sciences and Engineering; Vol. 18 No. 1 (2008); 32-45
VETOR - Revista de Ciências Exatas e Engenharias; v. 18 n. 1 (2008); 32-45
2358-3452
0102-7352
reponame:Vetor (Online)
instname:Universidade Federal do Rio Grande (FURG)
instacron:FURG
instname_str Universidade Federal do Rio Grande (FURG)
instacron_str FURG
institution FURG
reponame_str Vetor (Online)
collection Vetor (Online)
repository.name.fl_str_mv Vetor (Online) - Universidade Federal do Rio Grande (FURG)
repository.mail.fl_str_mv gmplatt@furg.br
_version_ 1797041761175994368

Registros relacionados