Orientation estimation fusing a downward looking camera and inertial sensors for a hovering UAV

Autores
Gastón, Araguás; Claudio, Paz; David, Gaydou; Gonzalo Pérez, Paina
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
—Nowadays, a particular kind of UAVs (Unmanned Aerial Vehicle) known as quadcopters or quadrotors have become very popular. This is mainly due to their reduced size and high maneuverability which allow them to operate in indoor environments. The requirement for orientation estimation in these vehiclesistwofold: for low levelstability control, and for high level navigation and motion planning. Orientation estimation is usually carried out fusing measurements of different sensors including inertial sensor, magnetic compass, sonar, GPS, camera, etc. As is known, GPS signal is not available in indoor environments and the Earth’s magnetic field is highly disturbed by ferromagnetic structures. In the present work we describe a new approach for quadrotor orientation estimation fusing inertial measurements with a downward looking camera. Inertial sensor are used for orientation estimation based on the gravity vector, and the camera providesinformation related to the heading direction. The camera heading or yaw angle estimation is based on spectral features extracted from the floor plane. Experimental results show the performance of the presented approach applied to a hovering UAV.
Fil: Gastón, Araguás. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.
Fil: Claudio, Paz. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.
Fil: David, Gaydou. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.
Fil: Gonzalo Pérez, Paina. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.
Peer Reviewed
Materia
Unmaned aerial vehicle
Yaw angle
Orientation estimation
Nivel de accesibilidad
acceso abierto
Condiciones de uso
Attribution-NonCommercial-NoDerivatives 4.0 International
Repositorio
Repositorio Institucional Abierto (UTN)
Institución
Universidad Tecnológica Nacional
OAI Identificador
oai:ria.utn.edu.ar:20.500.12272/14294
Acceder
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oai_identifier_str oai:ria.utn.edu.ar:20.500.12272/14294
network_acronym_str RIAUTN
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network_name_str Repositorio Institucional Abierto (UTN)
spelling Orientation estimation fusing a downward looking camera and inertial sensors for a hovering UAVGastón, AraguásClaudio, PazDavid, GaydouGonzalo Pérez, PainaUnmaned aerial vehicleYaw angleOrientation estimation—Nowadays, a particular kind of UAVs (Unmanned Aerial Vehicle) known as quadcopters or quadrotors have become very popular. This is mainly due to their reduced size and high maneuverability which allow them to operate in indoor environments. The requirement for orientation estimation in these vehiclesistwofold: for low levelstability control, and for high level navigation and motion planning. Orientation estimation is usually carried out fusing measurements of different sensors including inertial sensor, magnetic compass, sonar, GPS, camera, etc. As is known, GPS signal is not available in indoor environments and the Earth’s magnetic field is highly disturbed by ferromagnetic structures. In the present work we describe a new approach for quadrotor orientation estimation fusing inertial measurements with a downward looking camera. Inertial sensor are used for orientation estimation based on the gravity vector, and the camera providesinformation related to the heading direction. The camera heading or yaw angle estimation is based on spectral features extracted from the floor plane. Experimental results show the performance of the presented approach applied to a hovering UAV.Fil: Gastón, Araguás. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.Fil: Claudio, Paz. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.Fil: David, Gaydou. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.Fil: Gonzalo Pérez, Paina. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.Peer ReviewedIEEE2025-12-03T20:48:49Z2013info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articulopdfapplication/pdfhttps://hdl.handle.net/20.500.12272/1429410.1109/ICAR.2013.6766576enginfo:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Gastón, Araguás; Claudio, Paz; David, Gaydou; Gonzalo Pérez, Paina.https://creativecommons.org/licenses/by-nc-nd/4.0/reponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica Nacional2026-10-01T11:58:48Zoai:ria.utn.edu.ar:20.500.12272/14294instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-10-01 11:58:49.209Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse
dc.title.none.fl_str_mv Orientation estimation fusing a downward looking camera and inertial sensors for a hovering UAV
title Orientation estimation fusing a downward looking camera and inertial sensors for a hovering UAV
spellingShingle Orientation estimation fusing a downward looking camera and inertial sensors for a hovering UAV
Gastón, Araguás
Unmaned aerial vehicle
Yaw angle
Orientation estimation
title_short Orientation estimation fusing a downward looking camera and inertial sensors for a hovering UAV
title_full Orientation estimation fusing a downward looking camera and inertial sensors for a hovering UAV
title_fullStr Orientation estimation fusing a downward looking camera and inertial sensors for a hovering UAV
title_full_unstemmed Orientation estimation fusing a downward looking camera and inertial sensors for a hovering UAV
title_sort Orientation estimation fusing a downward looking camera and inertial sensors for a hovering UAV
dc.creator.none.fl_str_mv Gastón, Araguás
Claudio, Paz
David, Gaydou
Gonzalo Pérez, Paina
author Gastón, Araguás
author_facet Gastón, Araguás
Claudio, Paz
David, Gaydou
Gonzalo Pérez, Paina
author_role author
author2 Claudio, Paz
David, Gaydou
Gonzalo Pérez, Paina
author2_role author
author
author
dc.subject.none.fl_str_mv Unmaned aerial vehicle
Yaw angle
Orientation estimation
topic Unmaned aerial vehicle
Yaw angle
Orientation estimation
dc.description.none.fl_txt_mv —Nowadays, a particular kind of UAVs (Unmanned Aerial Vehicle) known as quadcopters or quadrotors have become very popular. This is mainly due to their reduced size and high maneuverability which allow them to operate in indoor environments. The requirement for orientation estimation in these vehiclesistwofold: for low levelstability control, and for high level navigation and motion planning. Orientation estimation is usually carried out fusing measurements of different sensors including inertial sensor, magnetic compass, sonar, GPS, camera, etc. As is known, GPS signal is not available in indoor environments and the Earth’s magnetic field is highly disturbed by ferromagnetic structures. In the present work we describe a new approach for quadrotor orientation estimation fusing inertial measurements with a downward looking camera. Inertial sensor are used for orientation estimation based on the gravity vector, and the camera providesinformation related to the heading direction. The camera heading or yaw angle estimation is based on spectral features extracted from the floor plane. Experimental results show the performance of the presented approach applied to a hovering UAV.
Fil: Gastón, Araguás. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.
Fil: Claudio, Paz. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.
Fil: David, Gaydou. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.
Fil: Gonzalo Pérez, Paina. Universidad Tecnológica Nacional. Facultad Regional Córdoba. Centro de Investigación en Informática para la Ingeniería; Argentina.
Peer Reviewed
description —Nowadays, a particular kind of UAVs (Unmanned Aerial Vehicle) known as quadcopters or quadrotors have become very popular. This is mainly due to their reduced size and high maneuverability which allow them to operate in indoor environments. The requirement for orientation estimation in these vehiclesistwofold: for low levelstability control, and for high level navigation and motion planning. Orientation estimation is usually carried out fusing measurements of different sensors including inertial sensor, magnetic compass, sonar, GPS, camera, etc. As is known, GPS signal is not available in indoor environments and the Earth’s magnetic field is highly disturbed by ferromagnetic structures. In the present work we describe a new approach for quadrotor orientation estimation fusing inertial measurements with a downward looking camera. Inertial sensor are used for orientation estimation based on the gravity vector, and the camera providesinformation related to the heading direction. The camera heading or yaw angle estimation is based on spectral features extracted from the floor plane. Experimental results show the performance of the presented approach applied to a hovering UAV.
publishDate 2013
dc.date.none.fl_str_mv 2013
2025-12-03T20:48:49Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.12272/14294
10.1109/ICAR.2013.6766576
url https://hdl.handle.net/20.500.12272/14294
identifier_str_mv 10.1109/ICAR.2013.6766576
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
Gastón, Araguás; Claudio, Paz; David, Gaydou; Gonzalo Pérez, Paina.
https://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
Gastón, Araguás; Claudio, Paz; David, Gaydou; Gonzalo Pérez, Paina.
https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.format.none.fl_str_mv pdf
application/pdf
dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
dc.source.none.fl_str_mv reponame:Repositorio Institucional Abierto (UTN)
instname:Universidad Tecnológica Nacional
reponame_str Repositorio Institucional Abierto (UTN)
collection Repositorio Institucional Abierto (UTN)
instname_str Universidad Tecnológica Nacional
repository.name.fl_str_mv Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacional
repository.mail.fl_str_mv gestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.ar
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score 13.364332

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