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: | Consejo Nacional de Ciencia Tecnología e Innovación |
| Repositorio: | CONCYTEC-Institucional |
| Lenguaje: | inglés |
| OAI Identifier: | oai:repositorio.concytec.gob.pe:20.500.12390/1774 |
| Enlace del recurso: | https://hdl.handle.net/20.500.12390/1774 |
| Nivel de acceso: | acceso abierto |
| Materia: | Sensores remotos Control automático Control predictivo Robots móviles https://purl.org/pe-repo/ocde/ford#2.02.03 |
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CONC_60b1090eda60fbdc3bff7f83956b51cb |
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oai:repositorio.concytec.gob.pe:20.500.12390/1774 |
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CONC |
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CONCYTEC-Institucional |
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4689 |
| dc.title.none.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 Sensores remotos Control automático Control predictivo 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.author.fl_str_mv |
Barreto Guerra, Jean Paul |
| dc.subject.none.fl_str_mv |
Sensores remotos |
| topic |
Sensores remotos Control automático Control predictivo Robots móviles https://purl.org/pe-repo/ocde/ford#2.02.03 |
| dc.subject.es_PE.fl_str_mv |
Control automático Control predictivo Robots móviles |
| dc.subject.ocde.none.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.none.fl_str_mv |
2024-05-30T23:13:38Z |
| dc.date.available.none.fl_str_mv |
2024-05-30T23:13:38Z |
| dc.date.issued.fl_str_mv |
2017 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/masterThesis |
| format |
masterThesis |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12390/1774 |
| url |
https://hdl.handle.net/20.500.12390/1774 |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess |
| dc.rights.uri.none.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.none.fl_str_mv |
Pontificia Universidad Católica del Perú |
| publisher.none.fl_str_mv |
Pontificia Universidad Católica del Perú |
| dc.source.none.fl_str_mv |
reponame:CONCYTEC-Institucional instname:Consejo Nacional de Ciencia Tecnología e Innovación instacron:CONCYTEC |
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Consejo Nacional de Ciencia Tecnología e Innovación |
| instacron_str |
CONCYTEC |
| institution |
CONCYTEC |
| reponame_str |
CONCYTEC-Institucional |
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CONCYTEC-Institucional |
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Repositorio Institucional CONCYTEC |
| repository.mail.fl_str_mv |
repositorio@concytec.gob.pe |
| _version_ |
1839175649349074944 |
| spelling |
Publicationrp04726600Barreto Guerra, Jean Paul2024-05-30T23:13:38Z2024-05-30T23:13:38Z2017https://hdl.handle.net/20.500.12390/1774The 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.Fondo Nacional de Desarrollo Científico y Tecnológico - FondecytengPontificia Universidad Católica del Perúinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/2.5/pe/Sensores remotosControl automático-1Control predictivo-1Robots móviles-1https://purl.org/pe-repo/ocde/ford#2.02.03-1Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive controlinfo:eu-repo/semantics/masterThesisreponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC#PLACEHOLDER_PARENT_METADATA_VALUE#Magíster en Ingeniería de Control y AutomatizaciónIngeniería de Control y AutomatizaciónPontificia Universidad Católica del Perú. Escuela de Postgrado20.500.12390/1774oai:repositorio.concytec.gob.pe:20.500.12390/17742024-05-30 15:40:08.853http://creativecommons.org/licenses/by-nc-nd/2.5/pe/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="8f96c8c3-0860-47d2-8ffc-8d9e606c1b53"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Design of a mobile robot’s control system for obstacle identification and avoidance using sensor fusion and model predictive control</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2017</PublicationDate> <Authors> <Author> <DisplayName>Barreto Guerra, Jean Paul</DisplayName> <Person id="rp04726" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Pontificia Universidad Católica del Perú</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://creativecommons.org/licenses/by-nc-nd/2.5/pe/</License> <Keyword>Sensores remotos</Keyword> <Keyword>Control automático</Keyword> <Keyword>Control predictivo</Keyword> <Keyword>Robots móviles</Keyword> <Abstract>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.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1 |
| score |
13.436549 |
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).
