A genetic algorithm approach using voronoi diagram for path planning

Autores
Benavides, Facundo; Tejera, Gonzalo; Pedemonte, Martín; Casella, Serrana
Año de publicación
2011
Idioma
español castellano
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In the context of Mobile Robotics, the e cient resolution of the Path Planning problem is a key task. The model of the environment and the search algorithm are basic issues in the resolution of the problem. This paper highlights the main features of Path Planning proposal for mobile robots in static environments. In our proposal, the path planning is based on Voronoi diagrams, where obstacles in the environment are considered as the generating points of the diagram, and a genetic algorithm is used to nd a path without collisions from the robot initial to target position. This work combines some ideas presented by Roque and Doering, who use Voronoi diagrams for modelling the environment, and other ideas presented by Zhang et al. who adopt a genetic algorithm for computing paths on a regular grid based environment, considering certain quality attributes.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Autonomous Mobile Robots
Path Planning
Voronoi diagrams
Genetic Algorithms
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/125239
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/125239
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network_name_str SEDICI (UNLP)
spelling A genetic algorithm approach using voronoi diagram for path planningBenavides, FacundoTejera, GonzaloPedemonte, MartínCasella, SerranaCiencias InformáticasAutonomous Mobile RobotsPath PlanningVoronoi diagramsGenetic AlgorithmsIn the context of Mobile Robotics, the e cient resolution of the Path Planning problem is a key task. The model of the environment and the search algorithm are basic issues in the resolution of the problem. This paper highlights the main features of Path Planning proposal for mobile robots in static environments. In our proposal, the path planning is based on Voronoi diagrams, where obstacles in the environment are considered as the generating points of the diagram, and a genetic algorithm is used to nd a path without collisions from the robot initial to target position. This work combines some ideas presented by Roque and Doering, who use Voronoi diagrams for modelling the environment, and other ideas presented by Zhang et al. who adopt a genetic algorithm for computing paths on a regular grid based environment, considering certain quality attributes.Sociedad Argentina de Informática e Investigación Operativa2011-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf48-59http://sedici.unlp.edu.ar/handle/10915/125239spainfo:eu-repo/semantics/altIdentifier/issn/1850-2784info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-17T10:12:52Zoai:sedici.unlp.edu.ar:10915/125239Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-17 10:12:53.244SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A genetic algorithm approach using voronoi diagram for path planning
title A genetic algorithm approach using voronoi diagram for path planning
spellingShingle A genetic algorithm approach using voronoi diagram for path planning
Benavides, Facundo
Ciencias Informáticas
Autonomous Mobile Robots
Path Planning
Voronoi diagrams
Genetic Algorithms
title_short A genetic algorithm approach using voronoi diagram for path planning
title_full A genetic algorithm approach using voronoi diagram for path planning
title_fullStr A genetic algorithm approach using voronoi diagram for path planning
title_full_unstemmed A genetic algorithm approach using voronoi diagram for path planning
title_sort A genetic algorithm approach using voronoi diagram for path planning
dc.creator.none.fl_str_mv Benavides, Facundo
Tejera, Gonzalo
Pedemonte, Martín
Casella, Serrana
author Benavides, Facundo
author_facet Benavides, Facundo
Tejera, Gonzalo
Pedemonte, Martín
Casella, Serrana
author_role author
author2 Tejera, Gonzalo
Pedemonte, Martín
Casella, Serrana
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Autonomous Mobile Robots
Path Planning
Voronoi diagrams
Genetic Algorithms
topic Ciencias Informáticas
Autonomous Mobile Robots
Path Planning
Voronoi diagrams
Genetic Algorithms
dc.description.none.fl_txt_mv In the context of Mobile Robotics, the e cient resolution of the Path Planning problem is a key task. The model of the environment and the search algorithm are basic issues in the resolution of the problem. This paper highlights the main features of Path Planning proposal for mobile robots in static environments. In our proposal, the path planning is based on Voronoi diagrams, where obstacles in the environment are considered as the generating points of the diagram, and a genetic algorithm is used to nd a path without collisions from the robot initial to target position. This work combines some ideas presented by Roque and Doering, who use Voronoi diagrams for modelling the environment, and other ideas presented by Zhang et al. who adopt a genetic algorithm for computing paths on a regular grid based environment, considering certain quality attributes.
Sociedad Argentina de Informática e Investigación Operativa
description In the context of Mobile Robotics, the e cient resolution of the Path Planning problem is a key task. The model of the environment and the search algorithm are basic issues in the resolution of the problem. This paper highlights the main features of Path Planning proposal for mobile robots in static environments. In our proposal, the path planning is based on Voronoi diagrams, where obstacles in the environment are considered as the generating points of the diagram, and a genetic algorithm is used to nd a path without collisions from the robot initial to target position. This work combines some ideas presented by Roque and Doering, who use Voronoi diagrams for modelling the environment, and other ideas presented by Zhang et al. who adopt a genetic algorithm for computing paths on a regular grid based environment, considering certain quality attributes.
publishDate 2011
dc.date.none.fl_str_mv 2011-08
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/125239
url http://sedici.unlp.edu.ar/handle/10915/125239
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1850-2784
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
48-59
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
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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