Automatic vehicle parking using an evolution-obtained neural controller

Autores
Ronchetti, Franco; Lanzarini, Laura Cristina
Año de publicación
2011
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Within the problems that can be solved with autonomous robots, automatic parking is an area of great interest, since it presents a complex scenario where the agent must go through a series of obstacles to reach its goal. Existing solutions usually require some kind of external mark for monitoring or global vision that indicates where the agent is at a given time. This article presents an evolutionary strategy to generate a robotic controller based on a neural network that successfully solves the problem of vehicle parallel parking using only local information. The performance of the tness function is analyzed, focusing not only on the agent reaching its goal, but also on it doing so in a manner that is appropriate for the physics of a vehicle. Additionally, the Player/Stage simulator is broadly discussed, since it is one of the most widely used simulators nowadays in robotics.
Presentado en el XII Workshop Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Robotics
Self-modifying machines (e.g., neural networks)
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/18578
Acceder
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network_name_str SEDICI (UNLP)
spelling Automatic vehicle parking using an evolution-obtained neural controllerRonchetti, FrancoLanzarini, Laura CristinaCiencias InformáticasRoboticsSelf-modifying machines (e.g., neural networks)Within the problems that can be solved with autonomous robots, automatic parking is an area of great interest, since it presents a complex scenario where the agent must go through a series of obstacles to reach its goal. Existing solutions usually require some kind of external mark for monitoring or global vision that indicates where the agent is at a given time. This article presents an evolutionary strategy to generate a robotic controller based on a neural network that successfully solves the problem of vehicle parallel parking using only local information. The performance of the tness function is analyzed, focusing not only on the agent reaching its goal, but also on it doing so in a manner that is appropriate for the physics of a vehicle. Additionally, the Player/Stage simulator is broadly discussed, since it is one of the most widely used simulators nowadays in robotics.Presentado en el XII Workshop Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI)2011-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf71-80http://sedici.unlp.edu.ar/handle/10915/18578enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-10T11:56:57Zoai:sedici.unlp.edu.ar:10915/18578Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-10 11:56:58.022SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Automatic vehicle parking using an evolution-obtained neural controller
title Automatic vehicle parking using an evolution-obtained neural controller
spellingShingle Automatic vehicle parking using an evolution-obtained neural controller
Ronchetti, Franco
Ciencias Informáticas
Robotics
Self-modifying machines (e.g., neural networks)
title_short Automatic vehicle parking using an evolution-obtained neural controller
title_full Automatic vehicle parking using an evolution-obtained neural controller
title_fullStr Automatic vehicle parking using an evolution-obtained neural controller
title_full_unstemmed Automatic vehicle parking using an evolution-obtained neural controller
title_sort Automatic vehicle parking using an evolution-obtained neural controller
dc.creator.none.fl_str_mv Ronchetti, Franco
Lanzarini, Laura Cristina
author Ronchetti, Franco
author_facet Ronchetti, Franco
Lanzarini, Laura Cristina
author_role author
author2 Lanzarini, Laura Cristina
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Robotics
Self-modifying machines (e.g., neural networks)
topic Ciencias Informáticas
Robotics
Self-modifying machines (e.g., neural networks)
dc.description.none.fl_txt_mv Within the problems that can be solved with autonomous robots, automatic parking is an area of great interest, since it presents a complex scenario where the agent must go through a series of obstacles to reach its goal. Existing solutions usually require some kind of external mark for monitoring or global vision that indicates where the agent is at a given time. This article presents an evolutionary strategy to generate a robotic controller based on a neural network that successfully solves the problem of vehicle parallel parking using only local information. The performance of the tness function is analyzed, focusing not only on the agent reaching its goal, but also on it doing so in a manner that is appropriate for the physics of a vehicle. Additionally, the Player/Stage simulator is broadly discussed, since it is one of the most widely used simulators nowadays in robotics.
Presentado en el XII Workshop Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
description Within the problems that can be solved with autonomous robots, automatic parking is an area of great interest, since it presents a complex scenario where the agent must go through a series of obstacles to reach its goal. Existing solutions usually require some kind of external mark for monitoring or global vision that indicates where the agent is at a given time. This article presents an evolutionary strategy to generate a robotic controller based on a neural network that successfully solves the problem of vehicle parallel parking using only local information. The performance of the tness function is analyzed, focusing not only on the agent reaching its goal, but also on it doing so in a manner that is appropriate for the physics of a vehicle. Additionally, the Player/Stage simulator is broadly discussed, since it is one of the most widely used simulators nowadays in robotics.
publishDate 2011
dc.date.none.fl_str_mv 2011-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/18578
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dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
71-80
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instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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