Using augmented state Kalman filter to localize multi autonomous underwater vehicles

Detalhes bibliográficos
Autor(a) principal: Botelho,Silvia
Data de Publicação: 2007
Outros Autores: Neves,Renato, Taddei,Lorenzo, Oliveira,Vinícius
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Journal of the Brazilian Computer Society
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002007000200006
Resumo: The present paper describes a system for the construction of visual maps ("mosaics") and motion estimation for a set of AUVs (Autonomous Underwater Vehicles). Robots are equipped with down-looking camera which is used to estimate their motion with respect to the seafloor and built an online mosaic. As the mosaic increases in size, a systematic bias is introduced in its alignment, resulting in an erroneous output. The theoretical concepts associated with the use of an Augmented State Kalman Filter (ASKF) were applied to optimally estimate both visual map and the fleet position.
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spelling Using augmented state Kalman filter to localize multi autonomous underwater vehiclesMulti-RobotsAutonomous Underwater VehiclesMosaicsRobotic LocalizationThe present paper describes a system for the construction of visual maps ("mosaics") and motion estimation for a set of AUVs (Autonomous Underwater Vehicles). Robots are equipped with down-looking camera which is used to estimate their motion with respect to the seafloor and built an online mosaic. As the mosaic increases in size, a systematic bias is introduced in its alignment, resulting in an erroneous output. The theoretical concepts associated with the use of an Augmented State Kalman Filter (ASKF) were applied to optimally estimate both visual map and the fleet position.Sociedade Brasileira de Computação2007-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002007000200006Journal of the Brazilian Computer Society v.13 n.2 2007reponame:Journal of the Brazilian Computer Societyinstname:Sociedade Brasileira de Computação (SBC)instacron:UFRGS10.1007/BF03192410info:eu-repo/semantics/openAccessBotelho,SilviaNeves,RenatoTaddei,LorenzoOliveira,Viníciuseng2008-07-28T00:00:00Zoai:scielo:S0104-65002007000200006Revistahttps://journal-bcs.springeropen.com/PUBhttps://old.scielo.br/oai/scielo-oai.phpjbcs@icmc.sc.usp.br1678-48040104-6500opendoar:2008-07-28T00:00Journal of the Brazilian Computer Society - Sociedade Brasileira de Computação (SBC)false
dc.title.none.fl_str_mv Using augmented state Kalman filter to localize multi autonomous underwater vehicles
title Using augmented state Kalman filter to localize multi autonomous underwater vehicles
spellingShingle Using augmented state Kalman filter to localize multi autonomous underwater vehicles
Botelho,Silvia
Multi-Robots
Autonomous Underwater Vehicles
Mosaics
Robotic Localization
title_short Using augmented state Kalman filter to localize multi autonomous underwater vehicles
title_full Using augmented state Kalman filter to localize multi autonomous underwater vehicles
title_fullStr Using augmented state Kalman filter to localize multi autonomous underwater vehicles
title_full_unstemmed Using augmented state Kalman filter to localize multi autonomous underwater vehicles
title_sort Using augmented state Kalman filter to localize multi autonomous underwater vehicles
author Botelho,Silvia
author_facet Botelho,Silvia
Neves,Renato
Taddei,Lorenzo
Oliveira,Vinícius
author_role author
author2 Neves,Renato
Taddei,Lorenzo
Oliveira,Vinícius
author2_role author
author
author
dc.contributor.author.fl_str_mv Botelho,Silvia
Neves,Renato
Taddei,Lorenzo
Oliveira,Vinícius
dc.subject.por.fl_str_mv Multi-Robots
Autonomous Underwater Vehicles
Mosaics
Robotic Localization
topic Multi-Robots
Autonomous Underwater Vehicles
Mosaics
Robotic Localization
description The present paper describes a system for the construction of visual maps ("mosaics") and motion estimation for a set of AUVs (Autonomous Underwater Vehicles). Robots are equipped with down-looking camera which is used to estimate their motion with respect to the seafloor and built an online mosaic. As the mosaic increases in size, a systematic bias is introduced in its alignment, resulting in an erroneous output. The theoretical concepts associated with the use of an Augmented State Kalman Filter (ASKF) were applied to optimally estimate both visual map and the fleet position.
publishDate 2007
dc.date.none.fl_str_mv 2007-12-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002007000200006
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002007000200006
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1007/BF03192410
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Computação
publisher.none.fl_str_mv Sociedade Brasileira de Computação
dc.source.none.fl_str_mv Journal of the Brazilian Computer Society v.13 n.2 2007
reponame:Journal of the Brazilian Computer Society
instname:Sociedade Brasileira de Computação (SBC)
instacron:UFRGS
instname_str Sociedade Brasileira de Computação (SBC)
instacron_str UFRGS
institution UFRGS
reponame_str Journal of the Brazilian Computer Society
collection Journal of the Brazilian Computer Society
repository.name.fl_str_mv Journal of the Brazilian Computer Society - Sociedade Brasileira de Computação (SBC)
repository.mail.fl_str_mv jbcs@icmc.sc.usp.br
_version_ 1754734669950091264

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