Zonotopic Linear Parameter Varying SLAM Applied to Autonomous Vehicles

This article presents an approach to address the problem of localisation within the autonomous driving framework. In particular, this work takes advantage of the properties of polytopic Linear Parameter Varying (LPV) systems and set-based methodologies applied to Kalman filters to precisely locate b...

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Detalles Bibliográficos
Autores: Facerias, Marc, Puig, Vicenç, Alcalá Baselga, Eugenio
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/296184
Acceso en línea:http://hdl.handle.net/10261/296184
Access Level:acceso abierto
Palabra clave:Autonomous driving
LPV modelling
Optimal estimation
Interval methods
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spelling Zonotopic Linear Parameter Varying SLAM Applied to Autonomous VehiclesFacerias, MarcPuig, VicençAlcalá Baselga, EugenioAutonomous drivingLPV modellingOptimal estimationInterval methodsThis article presents an approach to address the problem of localisation within the autonomous driving framework. In particular, this work takes advantage of the properties of polytopic Linear Parameter Varying (LPV) systems and set-based methodologies applied to Kalman filters to precisely locate both a set of landmarks and the vehicle itself. Using these techniques, we present an alternative approach to localisation algorithms that relies on the use of zonotopes to provide a guaranteed estimation of the states of the vehicle and its surroundings, which does not depend on any assumption of the noise nature other than its limits. LPV theory is used to model the dynamics of the vehicle and implement both an LPV-model predictive controller and a Zonotopic Kalman filter that allow localisation and navigation of the robot. The control and estimation scheme is validated in simulation using the Robotic Operating System (ROS) framework, where its effectiveness is demonstrated.This work has been co-financed by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the project SaCoAV (ref. MINECO PID2020- 114244RB-I00), by the European Regional Development Fund of the European Union in the framework of the ERDF Operational Program of Catalonia 2014–2020 (ref. 001-P-001643 Looming Factory), and by the DGR of Generalitat de Catalunya (SAC group ref. 2017/SGR/482). The author is also supported by an Industrial PhD AGAUR grant (Ref. 2019 DI 040).Molecular Diversity Preservation InternationalAgencia Estatal de Investigación (España)European CommissionMinisterio de Ciencia, Innovación y Universidades (España)Generalitat de CatalunyaConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2023202320222023info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/296184reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114244RB-I00http://dx.doi.org/10.3390/s22103672Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2961842026-05-22T06:33:51Z
dc.title.none.fl_str_mv Zonotopic Linear Parameter Varying SLAM Applied to Autonomous Vehicles
title Zonotopic Linear Parameter Varying SLAM Applied to Autonomous Vehicles
spellingShingle Zonotopic Linear Parameter Varying SLAM Applied to Autonomous Vehicles
Facerias, Marc
Autonomous driving
LPV modelling
Optimal estimation
Interval methods
title_short Zonotopic Linear Parameter Varying SLAM Applied to Autonomous Vehicles
title_full Zonotopic Linear Parameter Varying SLAM Applied to Autonomous Vehicles
title_fullStr Zonotopic Linear Parameter Varying SLAM Applied to Autonomous Vehicles
title_full_unstemmed Zonotopic Linear Parameter Varying SLAM Applied to Autonomous Vehicles
title_sort Zonotopic Linear Parameter Varying SLAM Applied to Autonomous Vehicles
dc.creator.none.fl_str_mv Facerias, Marc
Puig, Vicenç
Alcalá Baselga, Eugenio
author Facerias, Marc
author_facet Facerias, Marc
Puig, Vicenç
Alcalá Baselga, Eugenio
author_role author
author2 Puig, Vicenç
Alcalá Baselga, Eugenio
author2_role author
author
dc.contributor.none.fl_str_mv Agencia Estatal de Investigación (España)
European Commission
Ministerio de Ciencia, Innovación y Universidades (España)
Generalitat de Catalunya
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Autonomous driving
LPV modelling
Optimal estimation
Interval methods
topic Autonomous driving
LPV modelling
Optimal estimation
Interval methods
description This article presents an approach to address the problem of localisation within the autonomous driving framework. In particular, this work takes advantage of the properties of polytopic Linear Parameter Varying (LPV) systems and set-based methodologies applied to Kalman filters to precisely locate both a set of landmarks and the vehicle itself. Using these techniques, we present an alternative approach to localisation algorithms that relies on the use of zonotopes to provide a guaranteed estimation of the states of the vehicle and its surroundings, which does not depend on any assumption of the noise nature other than its limits. LPV theory is used to model the dynamics of the vehicle and implement both an LPV-model predictive controller and a Zonotopic Kalman filter that allow localisation and navigation of the robot. The control and estimation scheme is validated in simulation using the Robotic Operating System (ROS) framework, where its effectiveness is demonstrated.
publishDate 2022
dc.date.none.fl_str_mv 2022
2023
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/296184
url http://hdl.handle.net/10261/296184
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114244RB-I00
http://dx.doi.org/10.3390/s22103672
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Molecular Diversity Preservation International
publisher.none.fl_str_mv Molecular Diversity Preservation International
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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