An improved particle filter for sparse environments

Detalhes bibliográficos
Autor(a) principal: Prestes,Edson
Data de Publicação: 2009
Outros Autores: Ritt,Marcus, Führ,Gustavo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Journal of the Brazilian Computer Society
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002009000300006
Resumo: In this paper, we combine a path planner based on Boundary Value Problems (BVP) and Monte Carlo Localization (MCL) to solve the wake-up robot problem in a sparse environment. This problem is difficult since large regions of sparse environments do not provide relevant information for the robot to recover its pose. We propose a novel method that distributes particle poses only in relevant parts of the environment and leads the robot along these regions using the numeric solution of a BVP. Several experiments show that the improved method leads to a better initial particle distribution and a better convergence of the localization process.
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spelling An improved particle filter for sparse environmentsboundary value problemsautonomous navigationenvironment explorationglobal localizationMonte Carlo localizationIn this paper, we combine a path planner based on Boundary Value Problems (BVP) and Monte Carlo Localization (MCL) to solve the wake-up robot problem in a sparse environment. This problem is difficult since large regions of sparse environments do not provide relevant information for the robot to recover its pose. We propose a novel method that distributes particle poses only in relevant parts of the environment and leads the robot along these regions using the numeric solution of a BVP. Several experiments show that the improved method leads to a better initial particle distribution and a better convergence of the localization process.Sociedade Brasileira de Computação2009-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002009000300006Journal of the Brazilian Computer Society v.15 n.3 2009reponame:Journal of the Brazilian Computer Societyinstname:Sociedade Brasileira de Computação (SBC)instacron:UFRGS10.1007/BF03194506info:eu-repo/semantics/openAccessPrestes,EdsonRitt,MarcusFühr,Gustavoeng2009-12-17T00:00:00Zoai:scielo:S0104-65002009000300006Revistahttps://journal-bcs.springeropen.com/PUBhttps://old.scielo.br/oai/scielo-oai.phpjbcs@icmc.sc.usp.br1678-48040104-6500opendoar:2009-12-17T00:00Journal of the Brazilian Computer Society - Sociedade Brasileira de Computação (SBC)false
dc.title.none.fl_str_mv An improved particle filter for sparse environments
title An improved particle filter for sparse environments
spellingShingle An improved particle filter for sparse environments
Prestes,Edson
boundary value problems
autonomous navigation
environment exploration
global localization
Monte Carlo localization
title_short An improved particle filter for sparse environments
title_full An improved particle filter for sparse environments
title_fullStr An improved particle filter for sparse environments
title_full_unstemmed An improved particle filter for sparse environments
title_sort An improved particle filter for sparse environments
author Prestes,Edson
author_facet Prestes,Edson
Ritt,Marcus
Führ,Gustavo
author_role author
author2 Ritt,Marcus
Führ,Gustavo
author2_role author
author
dc.contributor.author.fl_str_mv Prestes,Edson
Ritt,Marcus
Führ,Gustavo
dc.subject.por.fl_str_mv boundary value problems
autonomous navigation
environment exploration
global localization
Monte Carlo localization
topic boundary value problems
autonomous navigation
environment exploration
global localization
Monte Carlo localization
description In this paper, we combine a path planner based on Boundary Value Problems (BVP) and Monte Carlo Localization (MCL) to solve the wake-up robot problem in a sparse environment. This problem is difficult since large regions of sparse environments do not provide relevant information for the robot to recover its pose. We propose a novel method that distributes particle poses only in relevant parts of the environment and leads the robot along these regions using the numeric solution of a BVP. Several experiments show that the improved method leads to a better initial particle distribution and a better convergence of the localization process.
publishDate 2009
dc.date.none.fl_str_mv 2009-09-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002009000300006
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002009000300006
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1007/BF03194506
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Computação
publisher.none.fl_str_mv Sociedade Brasileira de Computação
dc.source.none.fl_str_mv Journal of the Brazilian Computer Society v.15 n.3 2009
reponame:Journal of the Brazilian Computer Society
instname:Sociedade Brasileira de Computação (SBC)
instacron:UFRGS
instname_str Sociedade Brasileira de Computação (SBC)
instacron_str UFRGS
institution UFRGS
reponame_str Journal of the Brazilian Computer Society
collection Journal of the Brazilian Computer Society
repository.name.fl_str_mv Journal of the Brazilian Computer Society - Sociedade Brasileira de Computação (SBC)
repository.mail.fl_str_mv jbcs@icmc.sc.usp.br
_version_ 1754734670003568640

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