Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive control

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The aim of this master thesis is to design a control system based on model predictive control (MPC) with sensor data fusion for obstacle avoidance. Since the amount of obtained data is larger due to multiple sensors, the required sampling time has to be larger enough in comparison with the calculati...

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Detalles Bibliográficos
Autor: Barreto Guerra, Jean Paul
Formato: tesis de maestría
Fecha de Publicación:2017
Institución:Pontificia Universidad Católica del Perú
Repositorio:PUCP-Tesis
Lenguaje:inglés
OAI Identifier:oai:tesis.pucp.edu.pe:20.500.12404/9507
Enlace del recurso:http://hdl.handle.net/20.500.12404/9507
Nivel de acceso:acceso abierto
Materia:Control automático
Control predictivo
Sensores remotos
Robots móviles
https://purl.org/pe-repo/ocde/ford#2.02.03
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dc.title.es_ES.fl_str_mv Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive control
title Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive control
spellingShingle Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive control
Barreto Guerra, Jean Paul
Control automático
Control predictivo
Sensores remotos
Robots móviles
https://purl.org/pe-repo/ocde/ford#2.02.03
title_short Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive control
title_full Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive control
title_fullStr Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive control
title_full_unstemmed Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive control
title_sort Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive control
author Barreto Guerra, Jean Paul
author_facet Barreto Guerra, Jean Paul
author_role author
dc.contributor.advisor.fl_str_mv Morán Cárdenas, Antonio Manuel
Hopfgarten, Siegbert
dc.contributor.author.fl_str_mv Barreto Guerra, Jean Paul
dc.subject.es_ES.fl_str_mv Control automático
Control predictivo
Sensores remotos
Robots móviles
topic Control automático
Control predictivo
Sensores remotos
Robots móviles
https://purl.org/pe-repo/ocde/ford#2.02.03
dc.subject.ocde.es_ES.fl_str_mv https://purl.org/pe-repo/ocde/ford#2.02.03
description The aim of this master thesis is to design a control system based on model predictive control (MPC) with sensor data fusion for obstacle avoidance. Since the amount of obtained data is larger due to multiple sensors, the required sampling time has to be larger enough in comparison with the calculation time of the optimal problem. Then it is proposed a simplification of the mobile robot model in order to reduce this optimization time. The sensor data fusion technique uses the range information of a laser scanner and the data of a mono-camera acquired from image processing techniques. In image processing different detection algorithms are proposed such as shape and color detection. Therefore an estimation of the obstacles dimension and distance is explained obtaining accurate results. Finally a data fusion for obstacle determination is developed in order to use this information in the optimization control problem as a path constraint. The obtained results show the mobile robot behavior in trajectories tracking and obstacle avoidance problems by comparing two different sampling times. It is concluded that the mobile robot reaches the final desired position while avoiding the detected obstacles along the trajectory.
publishDate 2017
dc.date.accessioned.es_ES.fl_str_mv 2017-10-14T00:51:18Z
dc.date.available.es_ES.fl_str_mv 2017-10-14T00:51:18Z
dc.date.created.es_ES.fl_str_mv 2017
dc.date.issued.fl_str_mv 2017-10-14
dc.type.es_ES.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.12404/9507
url http://hdl.handle.net/20.500.12404/9507
dc.language.iso.es_ES.fl_str_mv eng
language eng
dc.relation.ispartof.fl_str_mv SUNEDU
dc.rights.es_ES.fl_str_mv info:eu-repo/semantics/openAccess
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eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/2.5/pe/
dc.publisher.es_ES.fl_str_mv Pontificia Universidad Católica del Perú
dc.publisher.country.es_ES.fl_str_mv PE
dc.source.none.fl_str_mv reponame:PUCP-Tesis
instname:Pontificia Universidad Católica del Perú
instacron:PUCP
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institution PUCP
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spelling Morán Cárdenas, Antonio ManuelHopfgarten, SiegbertBarreto Guerra, Jean Paul2017-10-14T00:51:18Z2017-10-14T00:51:18Z20172017-10-14http://hdl.handle.net/20.500.12404/9507The aim of this master thesis is to design a control system based on model predictive control (MPC) with sensor data fusion for obstacle avoidance. Since the amount of obtained data is larger due to multiple sensors, the required sampling time has to be larger enough in comparison with the calculation time of the optimal problem. Then it is proposed a simplification of the mobile robot model in order to reduce this optimization time. The sensor data fusion technique uses the range information of a laser scanner and the data of a mono-camera acquired from image processing techniques. In image processing different detection algorithms are proposed such as shape and color detection. Therefore an estimation of the obstacles dimension and distance is explained obtaining accurate results. Finally a data fusion for obstacle determination is developed in order to use this information in the optimization control problem as a path constraint. The obtained results show the mobile robot behavior in trajectories tracking and obstacle avoidance problems by comparing two different sampling times. It is concluded that the mobile robot reaches the final desired position while avoiding the detected obstacles along the trajectory.Ziel dieser Masterarbeit ist, einen Steuerungsentwurf auf Basis der modellprädiktiven Regelung (MPC) mit Sensordatenfusion und zur Hindernisvermeidung. Da die Menge der erhaltenen Daten aufgrund mehrerer Sensoren größer ist, muss die erforderliche Abtastzeit im Vergleich zur Rechenzeit des optimalen Problems größer sein. In der Arbeit wird eine Vereinfachung des mobilen Robotermodells vorgeschlagen, um diese Optimierungszeit zu reduzieren. Die Sensordaten-Fusionstechnik verwendet die Bereichsinformation eines Laserscanners und die Daten einer Monokamera, die durch Bildverarbeitungstechniken gewonnen werden. Bei der Bildverarbeitung werden verschiedene Erfassungsalgorithmen vorgeschlagen, wie z. B. Muster- und Farbdetektion. Eine Schätzung der Hindernisdimension und -distanz wird erklärt, um genaue Ergebnisse zu erzielen. Schließlich wird eine Datenfusion zur Hindernisbestimmung entwickelt, um diese Information im Optimalsteuerungsproblem als Pfadbeschränkung zu nutzen. Die erzielten Ergebnisse zeigen das Verhalten des mobilen Roboters bei Trajektorienverfolgungsund Hindernisvermeidungsproblemen, indem zwei verschiedene Abtastzeiten verglichen werden. Es wird gefolgert, dass der mobile Roboter die endgültige gewünschte Position erreicht, während die erkannten Hindernisse entlang der Trajektorie vermieden werden.Fondo Nacional de Desarrollo Científico y Tecnológico - FondecytTesisengPontificia Universidad Católica del PerúPEinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/2.5/pe/Control automáticoControl predictivoSensores remotosRobots móvileshttps://purl.org/pe-repo/ocde/ford#2.02.03Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive controlinfo:eu-repo/semantics/masterThesisreponame:PUCP-Tesisinstname:Pontificia Universidad Católica del Perúinstacron:PUCPSUNEDUMaestro en Ingeniería de Control y AutomatizaciónMaestríaPontificia Universidad Católica del Perú. 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Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive control
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