Techniques for Controlling Swarms of Robots

Detalhes bibliográficos
Autor(a) principal: Luciano Cunha de Araujo Pimenta
Data de Publicação: 2009
Tipo de documento: Tese
Idioma: por
Título da fonte: Repositório Institucional da UFMG
Texto Completo: http://hdl.handle.net/1843/GASP-7Y5F4W
Resumo: This thesis addresses the problem of controlling very large groups of robots, refereed as swarms. Scalable solutions in which there is no need for labelling the robots are proposed. All the robots run the same software and the success of the task execution does not depend on specific members of the group. Robustness to dynamic addition and deletion of agents is also an advantage of our approaches. In the first methodology, we model the swarm as a fluid immersed in a region where a field of external forces, which is free of local minima, is defined. In this case, the Smoothed Particle Hydrodynamics (SPH) method is applied to model the robotic fluid', more specifically, to model the interactions among the robots of the group. The Finite Element Method (FEM) is also used in this work to compute the fields that determine external forces. This approach is instantiated in a pattern generation task and also in a coverage task. In the second methodology, a problem of optimal environment coverage using robots equipped with sensors is addressed by means of tools from the Locational Optimization theory. Three important extensions of well-known results in the literature are presented: (i) sensors with different footprints, (ii) disk-shaped robots, and (iii) nonconvex polygonal environments. Both approaches are verified in simulations. The first technique is also implemented and tested in actual robots.
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spelling Techniques for Controlling Swarms of RobotscooperaçãorobóticaenxamesEngenharia elétricaThis thesis addresses the problem of controlling very large groups of robots, refereed as swarms. Scalable solutions in which there is no need for labelling the robots are proposed. All the robots run the same software and the success of the task execution does not depend on specific members of the group. Robustness to dynamic addition and deletion of agents is also an advantage of our approaches. In the first methodology, we model the swarm as a fluid immersed in a region where a field of external forces, which is free of local minima, is defined. In this case, the Smoothed Particle Hydrodynamics (SPH) method is applied to model the robotic fluid', more specifically, to model the interactions among the robots of the group. The Finite Element Method (FEM) is also used in this work to compute the fields that determine external forces. This approach is instantiated in a pattern generation task and also in a coverage task. In the second methodology, a problem of optimal environment coverage using robots equipped with sensors is addressed by means of tools from the Locational Optimization theory. Three important extensions of well-known results in the literature are presented: (i) sensors with different footprints, (ii) disk-shaped robots, and (iii) nonconvex polygonal environments. Both approaches are verified in simulations. The first technique is also implemented and tested in actual robots.Esta tese aborda o problema de controle de grandes grupos de robôs, referidos como enxames. São propostas soluções escaláveis as quais não necessitam da identificação única dos robôs. Todos os robôs executam o mesmo código e o sucesso na execução de uma tarefa não depende de membros específicos do grupo. Robustez à adição e remoção dinâmica de agentes também é uma vantagem das abordagens propostas. Na primeira metodologia, o enxame é modelado como um fluido imerso numa região onde um campo de forças externas livre de mínimos locais é definido. Neste caso, utiliza-se o método de Hidrodinâmica de Partículas Suavizadas (HPS) para modelar o fluido robótico'', mais especificamente, para modelar as interações entre robôs do grupo. O Método de Elementos Finitos (MEF) também é utilizado neste trabalho para calcular os campos vetoriais que determinam as forças externas. Esta abordagem é instanciada num problema de geração de padrões e também num problema de cobertura de ambientes. Na segunda metodologia, um problema de cobertura ótima de ambientes utilizando robôs equipados com sensores é tratado por meio de ferramentas provenientes da teoria de Otimização Locacional. São apresentadas três extensões importantes de resultados já conhecidos na literatura: (i) sensores com diferentes campos de visão, (ii) robôs com formato circular e (iii) ambientes poligonais não-convexos. Ambas metodologias são verificadas em simulações. A primeira metodologia é também implementada e testada em robôs reais.Universidade Federal de Minas GeraisUFMGRenato Cardoso MesquitaGuilherme Augusto Silva PereiraLuiz ChaimowiczElson Jose da SilvaGeovany Araújo BorgesMarco Henrique TerraLuciano Cunha de Araujo Pimenta2019-08-11T11:45:57Z2019-08-11T11:45:57Z2009-02-02info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttp://hdl.handle.net/1843/GASP-7Y5F4Winfo:eu-repo/semantics/openAccessporreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMG2019-11-14T14:21:41Zoai:repositorio.ufmg.br:1843/GASP-7Y5F4WRepositório InstitucionalPUBhttps://repositorio.ufmg.br/oairepositorio@ufmg.bropendoar:2019-11-14T14:21:41Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
dc.title.none.fl_str_mv Techniques for Controlling Swarms of Robots
title Techniques for Controlling Swarms of Robots
spellingShingle Techniques for Controlling Swarms of Robots
Luciano Cunha de Araujo Pimenta
cooperação
robótica
enxames
Engenharia elétrica
title_short Techniques for Controlling Swarms of Robots
title_full Techniques for Controlling Swarms of Robots
title_fullStr Techniques for Controlling Swarms of Robots
title_full_unstemmed Techniques for Controlling Swarms of Robots
title_sort Techniques for Controlling Swarms of Robots
author Luciano Cunha de Araujo Pimenta
author_facet Luciano Cunha de Araujo Pimenta
author_role author
dc.contributor.none.fl_str_mv Renato Cardoso Mesquita
Guilherme Augusto Silva Pereira
Luiz Chaimowicz
Elson Jose da Silva
Geovany Araújo Borges
Marco Henrique Terra
dc.contributor.author.fl_str_mv Luciano Cunha de Araujo Pimenta
dc.subject.por.fl_str_mv cooperação
robótica
enxames
Engenharia elétrica
topic cooperação
robótica
enxames
Engenharia elétrica
description This thesis addresses the problem of controlling very large groups of robots, refereed as swarms. Scalable solutions in which there is no need for labelling the robots are proposed. All the robots run the same software and the success of the task execution does not depend on specific members of the group. Robustness to dynamic addition and deletion of agents is also an advantage of our approaches. In the first methodology, we model the swarm as a fluid immersed in a region where a field of external forces, which is free of local minima, is defined. In this case, the Smoothed Particle Hydrodynamics (SPH) method is applied to model the robotic fluid', more specifically, to model the interactions among the robots of the group. The Finite Element Method (FEM) is also used in this work to compute the fields that determine external forces. This approach is instantiated in a pattern generation task and also in a coverage task. In the second methodology, a problem of optimal environment coverage using robots equipped with sensors is addressed by means of tools from the Locational Optimization theory. Three important extensions of well-known results in the literature are presented: (i) sensors with different footprints, (ii) disk-shaped robots, and (iii) nonconvex polygonal environments. Both approaches are verified in simulations. The first technique is also implemented and tested in actual robots.
publishDate 2009
dc.date.none.fl_str_mv 2009-02-02
2019-08-11T11:45:57Z
2019-08-11T11:45:57Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1843/GASP-7Y5F4W
url http://hdl.handle.net/1843/GASP-7Y5F4W
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Minas Gerais
UFMG
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
UFMG
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFMG
instname:Universidade Federal de Minas Gerais (UFMG)
instacron:UFMG
instname_str Universidade Federal de Minas Gerais (UFMG)
instacron_str UFMG
institution UFMG
reponame_str Repositório Institucional da UFMG
collection Repositório Institucional da UFMG
repository.name.fl_str_mv Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)
repository.mail.fl_str_mv repositorio@ufmg.br
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