A STATISTICAL APPROACH TO SIMULTANEOUS MAPPING AND LOCALIZATION FOR MOBILE ROBOTS

Simple item page
dc.contributor.authorAraneda, Anita
dc.contributor.authorFienberg, Stephen E.
dc.contributor.authorSoto, Alvaro
dc.date.accessioned2024-01-10T13:11:18Z
dc.date.available2024-01-10T13:11:18Z
dc.date.issued2007
dc.description.abstractMobile robots require basic information to navigate through an environment: they need to know where they are (localization) and they need to know where they are going. For the latter, robots need a map of the environment. Using sensors of a variety of forms, robots gather information as they move through in environment in order to build a map. In this paper we present a novel sampling algorithm to solving the simultaneous mapping and localization (SLAM) problem in indoor environments. We approach the problem from a Bayesian statistics perspective. The data correspond to a set of range tinder and odometer measurements, obtained at discrete time instants. We focus on the estimation of the posterior distribution over the space of possible maps given the data. By exploiting different factorizations of this distribution, we derive three sampling algorithms based oil importance sampling. We illustrate the results of our approach by testing the algorithms with two real data sets obtained through robot navigation inside office buildings at Carnegie Mellon University and the Pontificia Universidad Catolica de Chile.
dc.description.funderFondecyt
dc.description.funderNSF
dc.fechaingreso.objetodigital2024-05-15
dc.format.extent19 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1214/07-AOAS115
dc.identifier.issn1932-6157
dc.identifier.urihttps://doi.org/10.1214/07-AOAS115
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/78029
dc.identifier.wosidWOS:000261050400004
dc.information.autorucMatemática;Araneda A;S/I;87382
dc.information.autorucIngeniería;Soto A;S/I;73678
dc.issue.numero1
dc.language.isoen
dc.nota.accesocontenido completo
dc.pagina.final84
dc.pagina.inicio66
dc.publisherINST MATHEMATICAL STATISTICS
dc.revistaANNALS OF APPLIED STATISTICS
dc.rightsacceso abierto
dc.subjectBayesian models
dc.subjectgraphical models
dc.subjectHidden Markov models
dc.subjectimportance sampling
dc.subjectparticle filtering
dc.subjectSLAM
dc.subjectMODELS
dc.subjectINFERENCE
dc.subjectINDOOR
dc.subject.ods11 Sustainable Cities and Communities
dc.subject.odspa11 Ciudades y comunidades sostenibles
dc.titleA STATISTICAL APPROACH TO SIMULTANEOUS MAPPING AND LOCALIZATION FOR MOBILE ROBOTS
dc.typeartículo
dc.volumen1
sipa.codpersvinculados87382
sipa.codpersvinculados73678
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
The Annals of Applied Statistics - 2007 - A statistical approach to simultaneous mapping and localization for mobile robots.pdf
Size:
386.23 KB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Artículos de revistas