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dc.contributor.authorSilva Junior, Edson Prestes ept_BR
dc.contributor.authorRitt, Marcus Rolf Peterpt_BR
dc.contributor.authorFühr, Gustavopt_BR
dc.date.accessioned2013-06-19T01:43:54Zpt_BR
dc.date.issued2009pt_BR
dc.identifier.issn0104-6500pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/72580pt_BR
dc.description.abstractIn 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.en
dc.format.mimetypeapplication/pdf
dc.language.isoengpt_BR
dc.relation.ispartofJournal of the Brazilian Computer Society. Porto Alegre. Vol. 15, n. 3 (2009 Sept.), p. 55-64pt_BR
dc.rightsOpen Accessen
dc.subjectBoundary value problemsen
dc.subjectComputação gráficapt_BR
dc.subjectAutonomous navigationen
dc.subjectAnimacao : Computacao graficapt_BR
dc.subjectEnvironment explorationen
dc.subjectGlobal localizationen
dc.subjectMonte Carlo localizationen
dc.titleAn improved particle filter for sparse environmentspt_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb000733094pt_BR
dc.type.originNacionalpt_BR


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