Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive control
Descripción del Articulo
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...
| Autor: | |
|---|---|
| Formato: | tesis de maestría |
| Fecha de Publicación: | 2017 |
| Institución: | Pontificia Universidad Católica del Perú |
| Repositorio: | PUCP-Institucional |
| Lenguaje: | inglés |
| OAI Identifier: | oai:repositorio.pucp.edu.pe:20.500.14657/146001 |
| 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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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.TesisengPontificia 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/masterThesisTesis de maestríareponame:PUCP-Institucionalinstname:Pontificia Universidad Católica del Perúinstacron:PUCPMaestro en Ingeniería de Control y AutomatizaciónMaestríaPontificia Universidad Católica del Perú. Escuela de PosgradoIngeniería de Control y Automatización10573987712037https://purl.org/pe-repo/renati/level#maestrohttp://purl.org/pe-repo/renati/type#tesis20.500.14657/146001oai:repositorio.pucp.edu.pe:20.500.14657/1460012024-06-10 10:55:08.948http://creativecommons.org/licenses/by-nc-nd/2.5/pe/info:eu-repo/semantics/openAccessmetadata.onlyhttps://repositorio.pucp.edu.peRepositorio Institucional de la PUCPrepositorio@pucp.pe |
| 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 |
| dc.type.other.none.fl_str_mv |
Tesis de maestría |
| 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.rights.es_ES.fl_str_mv |
info:eu-repo/semantics/openAccess |
| dc.rights.uri.*.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/2.5/pe/ |
| 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-Institucional instname:Pontificia Universidad Católica del Perú instacron:PUCP |
| instname_str |
Pontificia Universidad Católica del Perú |
| instacron_str |
PUCP |
| institution |
PUCP |
| reponame_str |
PUCP-Institucional |
| collection |
PUCP-Institucional |
| repository.name.fl_str_mv |
Repositorio Institucional de la PUCP |
| repository.mail.fl_str_mv |
repositorio@pucp.pe |
| _version_ |
1835639060979253248 |
| score |
13.945474 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
