Reference trajectory tracking control of a nonholonomic mobile robotwith inertial sensor fusion

Detalhes bibliográficos
Ano de defesa: 2018
Autor(a) principal: Forte, Marcus Davi do Nascimento
Orientador(a): Nogueira, Fabrício Gonzalez
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Mobile robot
Sensor fusion
LQR Control
Kalman filter
Link de acesso: http://www.repositorio.ufc.br/handle/riufc/55347
Resumo: This work presents a study on differential drive wheeled mobile robots regarding its localization estimation using sensor fusion techniques and control over a reference trajectory. The robot’s posture is an extremely important variable to be estimated, specially for autonomous mobile robots as it has to drive along a path without manual intervention. Posture estimation provided by individual sensors has shown to be inaccurate or straightforward mismatched, leading to a need of data fusion from different sources. Sensors such as accelerometer, gyroscope and magnetometer each have its own intrinsic constructive limitations. However, by combining all their flaws into a linear model allows optimal estimators, such as Kalman Filter (KF), to be used and produce estimates close to real life behavior. For the trajectory tracking and disturbance rejection, a linear control strategy for a linearized mobile robot model is applied. The system is modeled with error states to be carried out by a Linear Quadratic Regulator (LQR) controller along with a feedforward reference control action so that the reference trajectory is accordingly tracked.
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spelling Forte, Marcus Davi do NascimentoCorreia, Wilkley BezerraNogueira, Fabrício Gonzalez2020-11-17T13:52:36Z2020-11-17T13:52:36Z2018FORTE, Marcus Davi do Nascimento. Reference trajectory tracking control of a nonholonomic mobile robotwith inertial sensor fusion. 2018. 88 f. Dissertação (mestrado) – Universidade Federal do Ceará, Centro de Tecnologia, Programa de Pós-Graduação em Engenharia Elétrica, Fortaleza, 2018.http://www.repositorio.ufc.br/handle/riufc/55347This work presents a study on differential drive wheeled mobile robots regarding its localization estimation using sensor fusion techniques and control over a reference trajectory. The robot’s posture is an extremely important variable to be estimated, specially for autonomous mobile robots as it has to drive along a path without manual intervention. Posture estimation provided by individual sensors has shown to be inaccurate or straightforward mismatched, leading to a need of data fusion from different sources. Sensors such as accelerometer, gyroscope and magnetometer each have its own intrinsic constructive limitations. However, by combining all their flaws into a linear model allows optimal estimators, such as Kalman Filter (KF), to be used and produce estimates close to real life behavior. For the trajectory tracking and disturbance rejection, a linear control strategy for a linearized mobile robot model is applied. The system is modeled with error states to be carried out by a Linear Quadratic Regulator (LQR) controller along with a feedforward reference control action so that the reference trajectory is accordingly tracked.This work presents a study on differential drive wheeled mobile robots regarding its localization estimation using sensor fusion techniques and control over a reference trajectory. The robot’s posture is an extremely important variable to be estimated, specially for autonomous mobile robots as it has to drive along a path without manual intervention. Posture estimation provided by individual sensors has shown to be inaccurate or straightforward mismatched, leading to a need of data fusion from different sources. Sensors such as accelerometer, gyroscope and magnetometer each have its own intrinsic constructive limitations. However, by combining all their flaws into a linear model allows optimal estimators, such as Kalman Filter (KF), to be used and produce estimates close to real life behavior. For the trajectory tracking and disturbance rejection, a linear control strategy for a linearized mobile robot model is applied. The system is modeled with error states to be carried out by a Linear Quadratic Regulator (LQR) controller along with a feedforward reference control action so that the reference trajectory is accordingly tracked.Mobile robotSensor fusionLQR ControlKalman filterReference trajectory tracking control of a nonholonomic mobile robotwith inertial sensor fusioninfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisengreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFCinfo:eu-repo/semantics/openAccessORIGINAL2018_dis_mdnforte.pdf2018_dis_mdnforte.pdfapplication/pdf10950580http://repositorio.ufc.br/bitstream/riufc/55347/1/2018_dis_mdnforte.pdfe5a1b556e3c87be8b551286224d4e541MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repositorio.ufc.br/bitstream/riufc/55347/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52riufc/553472022-05-10 10:34:23.941oai:repositorio.ufc.br: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Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2022-05-10T13:34:23Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false
dc.title.pt_BR.fl_str_mv Reference trajectory tracking control of a nonholonomic mobile robotwith inertial sensor fusion
title Reference trajectory tracking control of a nonholonomic mobile robotwith inertial sensor fusion
spellingShingle Reference trajectory tracking control of a nonholonomic mobile robotwith inertial sensor fusion
Forte, Marcus Davi do Nascimento
Mobile robot
Sensor fusion
LQR Control
Kalman filter
title_short Reference trajectory tracking control of a nonholonomic mobile robotwith inertial sensor fusion
title_full Reference trajectory tracking control of a nonholonomic mobile robotwith inertial sensor fusion
title_fullStr Reference trajectory tracking control of a nonholonomic mobile robotwith inertial sensor fusion
title_full_unstemmed Reference trajectory tracking control of a nonholonomic mobile robotwith inertial sensor fusion
title_sort Reference trajectory tracking control of a nonholonomic mobile robotwith inertial sensor fusion
author Forte, Marcus Davi do Nascimento
author_facet Forte, Marcus Davi do Nascimento
author_role author
dc.contributor.co-advisor.none.fl_str_mv Correia, Wilkley Bezerra
dc.contributor.author.fl_str_mv Forte, Marcus Davi do Nascimento
dc.contributor.advisor1.fl_str_mv Nogueira, Fabrício Gonzalez
contributor_str_mv Nogueira, Fabrício Gonzalez
dc.subject.por.fl_str_mv Mobile robot
Sensor fusion
LQR Control
Kalman filter
topic Mobile robot
Sensor fusion
LQR Control
Kalman filter
description This work presents a study on differential drive wheeled mobile robots regarding its localization estimation using sensor fusion techniques and control over a reference trajectory. The robot’s posture is an extremely important variable to be estimated, specially for autonomous mobile robots as it has to drive along a path without manual intervention. Posture estimation provided by individual sensors has shown to be inaccurate or straightforward mismatched, leading to a need of data fusion from different sources. Sensors such as accelerometer, gyroscope and magnetometer each have its own intrinsic constructive limitations. However, by combining all their flaws into a linear model allows optimal estimators, such as Kalman Filter (KF), to be used and produce estimates close to real life behavior. For the trajectory tracking and disturbance rejection, a linear control strategy for a linearized mobile robot model is applied. The system is modeled with error states to be carried out by a Linear Quadratic Regulator (LQR) controller along with a feedforward reference control action so that the reference trajectory is accordingly tracked.
publishDate 2018
dc.date.issued.fl_str_mv 2018
dc.date.accessioned.fl_str_mv 2020-11-17T13:52:36Z
dc.date.available.fl_str_mv 2020-11-17T13:52:36Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv FORTE, Marcus Davi do Nascimento. Reference trajectory tracking control of a nonholonomic mobile robotwith inertial sensor fusion. 2018. 88 f. Dissertação (mestrado) – Universidade Federal do Ceará, Centro de Tecnologia, Programa de Pós-Graduação em Engenharia Elétrica, Fortaleza, 2018.
dc.identifier.uri.fl_str_mv http://www.repositorio.ufc.br/handle/riufc/55347
identifier_str_mv FORTE, Marcus Davi do Nascimento. Reference trajectory tracking control of a nonholonomic mobile robotwith inertial sensor fusion. 2018. 88 f. Dissertação (mestrado) – Universidade Federal do Ceará, Centro de Tecnologia, Programa de Pós-Graduação em Engenharia Elétrica, Fortaleza, 2018.
url http://www.repositorio.ufc.br/handle/riufc/55347
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da Universidade Federal do Ceará (UFC)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
instacron_str UFC
institution UFC
reponame_str Repositório Institucional da Universidade Federal do Ceará (UFC)
collection Repositório Institucional da Universidade Federal do Ceará (UFC)
bitstream.url.fl_str_mv http://repositorio.ufc.br/bitstream/riufc/55347/1/2018_dis_mdnforte.pdf
http://repositorio.ufc.br/bitstream/riufc/55347/2/license.txt
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repository.name.fl_str_mv Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)
repository.mail.fl_str_mv bu@ufc.br || repositorio@ufc.br
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