SCARA Self Posture Recognition Using a Monocular Camera

Detalhes bibliográficos
Autor(a) principal: Tinoco, Vitor
Data de Publicação: 2022
Outros Autores: Silva, Manuel F., Santos, Filipe N., Morais, Raul, Filipe, Vitor
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/21857
Resumo: Robotic manipulators rely on feedback obtained from rotary encoders for control purposes. This article introduces a vision-based feedback system that can be used in an agricultural context, where the shapes and sizes of fruits are uncertain. We aim to mimic a human, using vision and touch as manipulator control feedback. This work explores the use of a fish-eye lens camera to track a SCARA manipulator with coloured markers on its joints for the position estimation with the goal to reduce costs and increase reliability. The Kalman Filter and the Particle Filter are compared and evaluated in terms of accuracy and tracking abilities of the marker’s positions. The estimated image coordinates of the markers are converted to world coordinates using planar homography, as the SCARA manipulator has co-planar joints and the coloured markers share the same plane. Three laboratory experiments were conducted to evaluate the system’s performance in joint angle estimation of a manipulator. The obtained results are promising, for future cost effective agricultural robotic arms developments. Besides, this work presents solutions and future directions to increase the joint position estimation accuracy.
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spelling SCARA Self Posture Recognition Using a Monocular CameraVisual servoingSelf postureMonocular cameraMarker trackingSCARA manipulatorPlanar homographyRobotic manipulators rely on feedback obtained from rotary encoders for control purposes. This article introduces a vision-based feedback system that can be used in an agricultural context, where the shapes and sizes of fruits are uncertain. We aim to mimic a human, using vision and touch as manipulator control feedback. This work explores the use of a fish-eye lens camera to track a SCARA manipulator with coloured markers on its joints for the position estimation with the goal to reduce costs and increase reliability. The Kalman Filter and the Particle Filter are compared and evaluated in terms of accuracy and tracking abilities of the marker’s positions. The estimated image coordinates of the markers are converted to world coordinates using planar homography, as the SCARA manipulator has co-planar joints and the coloured markers share the same plane. Three laboratory experiments were conducted to evaluate the system’s performance in joint angle estimation of a manipulator. The obtained results are promising, for future cost effective agricultural robotic arms developments. Besides, this work presents solutions and future directions to increase the joint position estimation accuracy.IEEERepositório Científico do Instituto Politécnico do PortoTinoco, VitorSilva, Manuel F.Santos, Filipe N.Morais, RaulFilipe, Vitor2023-01-25T14:09:59Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/21857eng10.1109/ACCESS.2022.3155199info: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:RCAAP2023-03-13T13:18:11Zoai:recipp.ipp.pt:10400.22/21857Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:41:56.524136Repositório 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 SCARA Self Posture Recognition Using a Monocular Camera
title SCARA Self Posture Recognition Using a Monocular Camera
spellingShingle SCARA Self Posture Recognition Using a Monocular Camera
Tinoco, Vitor
Visual servoing
Self posture
Monocular camera
Marker tracking
SCARA manipulator
Planar homography
title_short SCARA Self Posture Recognition Using a Monocular Camera
title_full SCARA Self Posture Recognition Using a Monocular Camera
title_fullStr SCARA Self Posture Recognition Using a Monocular Camera
title_full_unstemmed SCARA Self Posture Recognition Using a Monocular Camera
title_sort SCARA Self Posture Recognition Using a Monocular Camera
author Tinoco, Vitor
author_facet Tinoco, Vitor
Silva, Manuel F.
Santos, Filipe N.
Morais, Raul
Filipe, Vitor
author_role author
author2 Silva, Manuel F.
Santos, Filipe N.
Morais, Raul
Filipe, Vitor
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Tinoco, Vitor
Silva, Manuel F.
Santos, Filipe N.
Morais, Raul
Filipe, Vitor
dc.subject.por.fl_str_mv Visual servoing
Self posture
Monocular camera
Marker tracking
SCARA manipulator
Planar homography
topic Visual servoing
Self posture
Monocular camera
Marker tracking
SCARA manipulator
Planar homography
description Robotic manipulators rely on feedback obtained from rotary encoders for control purposes. This article introduces a vision-based feedback system that can be used in an agricultural context, where the shapes and sizes of fruits are uncertain. We aim to mimic a human, using vision and touch as manipulator control feedback. This work explores the use of a fish-eye lens camera to track a SCARA manipulator with coloured markers on its joints for the position estimation with the goal to reduce costs and increase reliability. The Kalman Filter and the Particle Filter are compared and evaluated in terms of accuracy and tracking abilities of the marker’s positions. The estimated image coordinates of the markers are converted to world coordinates using planar homography, as the SCARA manipulator has co-planar joints and the coloured markers share the same plane. Three laboratory experiments were conducted to evaluate the system’s performance in joint angle estimation of a manipulator. The obtained results are promising, for future cost effective agricultural robotic arms developments. Besides, this work presents solutions and future directions to increase the joint position estimation accuracy.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-01-01T00:00:00Z
2023-01-25T14:09:59Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/21857
url http://hdl.handle.net/10400.22/21857
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1109/ACCESS.2022.3155199
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
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
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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
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