Augmented state Kalman filtering for AUV navigation

Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic...

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Detalles Bibliográficos
Autores: García Campos, Rafael, Puig, Jordi, Ridao Rodríguez, Pere, Cufí i Solé, Xavier
Tipo de recurso: artículo
Fecha de publicación:2002
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/2349
Acceso en línea:http://hdl.handle.net/10256/2349
Access Level:acceso abierto
Palabra clave:Imatges -- Processament
Kalman, Filtre de
Robots mòbils
Robots submarins
Image processing
Kalman filtering G
Mobile robots
Underwater robots
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spelling Augmented state Kalman filtering for AUV navigationGarcía Campos, RafaelPuig, JordiRidao Rodríguez, PereCufí i Solé, XavierImatges -- ProcessamentKalman, Filtre deRobots mòbilsRobots submarinsImage processingKalman filtering GMobile robotsUnderwater robotsAddresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle positionIEEE2002info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10256/2349http://hdl.handle.net/10256/2349© IEEE International Conference on Robotics and Automation : 2002 : Proceedings : ICRA '02, 2002, vol. 4, p. 4010-4015Articles publicats (D-ATC)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)Inglésinfo:eu-repo/semantics/altIdentifier/doi/10.1109/ROBOT.2002.1014362info:eu-repo/semantics/altIdentifier/isbn/0-7803-7272-7Tots els drets reservatsinfo:eu-repo/semantics/openAccessoai:recercat.cat:10256/23492026-05-29T05:05:01Z
dc.title.none.fl_str_mv Augmented state Kalman filtering for AUV navigation
title Augmented state Kalman filtering for AUV navigation
spellingShingle Augmented state Kalman filtering for AUV navigation
García Campos, Rafael
Imatges -- Processament
Kalman, Filtre de
Robots mòbils
Robots submarins
Image processing
Kalman filtering G
Mobile robots
Underwater robots
title_short Augmented state Kalman filtering for AUV navigation
title_full Augmented state Kalman filtering for AUV navigation
title_fullStr Augmented state Kalman filtering for AUV navigation
title_full_unstemmed Augmented state Kalman filtering for AUV navigation
title_sort Augmented state Kalman filtering for AUV navigation
dc.creator.none.fl_str_mv García Campos, Rafael
Puig, Jordi
Ridao Rodríguez, Pere
Cufí i Solé, Xavier
author García Campos, Rafael
author_facet García Campos, Rafael
Puig, Jordi
Ridao Rodríguez, Pere
Cufí i Solé, Xavier
author_role author
author2 Puig, Jordi
Ridao Rodríguez, Pere
Cufí i Solé, Xavier
author2_role author
author
author
dc.subject.none.fl_str_mv Imatges -- Processament
Kalman, Filtre de
Robots mòbils
Robots submarins
Image processing
Kalman filtering G
Mobile robots
Underwater robots
topic Imatges -- Processament
Kalman, Filtre de
Robots mòbils
Robots submarins
Image processing
Kalman filtering G
Mobile robots
Underwater robots
description Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position
publishDate 2002
dc.date.none.fl_str_mv 2002
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10256/2349
http://hdl.handle.net/10256/2349
url http://hdl.handle.net/10256/2349
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1109/ROBOT.2002.1014362
info:eu-repo/semantics/altIdentifier/isbn/0-7803-7272-7
dc.rights.none.fl_str_mv Tots els drets reservats
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Tots els drets reservats
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
dc.source.none.fl_str_mv © IEEE International Conference on Robotics and Automation : 2002 : Proceedings : ICRA '02, 2002, vol. 4, p. 4010-4015
Articles publicats (D-ATC)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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