H-SLAM: Rao-Blackwellized particle filter SLAM using Hilbert Maps

Occupancy Grid maps provide a probabilistic representation of space which is important for a variety of robotic applications like path planning and autonomous manipulation. In this paper, a SLAM (Simultaneous Localization and Mapping) framework capable of obtaining this representation online is pres...

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Detalles Bibliográficos
Autores: Vallicrosa Massaguer, Guillem, Ridao Rodríguez, Pere
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2018
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/15517
Acceso en línea:http://hdl.handle.net/10256/15517
Access Level:acceso abierto
Palabra clave:Vehicles submergibles
Submersibles
Vehicles autònoms
Autonomous vehicles
Robots mòbils
Mobile robots
Fons marins -- Mapes
Ocean bottom -- Maps
Algorismes computacionals
Computer algorithms
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spelling H-SLAM: Rao-Blackwellized particle filter SLAM using Hilbert MapsVallicrosa Massaguer, GuillemRidao Rodríguez, PereVehicles submergiblesSubmersiblesVehicles autònomsAutonomous vehiclesRobots mòbilsMobile robotsFons marins -- MapesOcean bottom -- MapsAlgorismes computacionalsComputer algorithmsOccupancy Grid maps provide a probabilistic representation of space which is important for a variety of robotic applications like path planning and autonomous manipulation. In this paper, a SLAM (Simultaneous Localization and Mapping) framework capable of obtaining this representation online is presented. The H-SLAM (Hilbert Maps SLAM) is based on Hilbert Map representation and uses a Particle Filter to represent the robot state. Hilbert Maps offer a continuous probabilistic representation with a small memory footprint. We present a series of experimental results carried both in simulation and with real AUVs (Autonomous Underwater Vehicles). These results demonstrate that our approach is able to represent the environment more consistently while capable of running onlineResearch funded by Ministerio de Educación, Cultura y Deporte (PhD grant ref. FPU12/05384 and ARCHROV project ref. DPI2014-57746-C3-3-R), and by the European Comission (EUMR project ref. H2020- INFRAIA-2017-1-twostage-731103)MDPI (Multidisciplinary Digital Publishing Institute)Ministerio de Economía y Competitividad (Espanya)2018info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionpeer-reviewedapplication/pdfhttp://hdl.handle.net/10256/15517http://hdl.handle.net/10256/15517Sensors (Switzerland), 2018, vol. 18, núm. 5, p. 1386Articles publicats (D-ATC)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)Inglésinfo:eu-repo/semantics/altIdentifier/doi/10.3390/s18051386info:eu-repo/semantics/altIdentifier/eissn/1424-8220info:eu-repo/grantAgreement/MINECO//DPI2014-57746-C3-3-Rinfo:eu-repo/grantAgreement/EC/H2020/731103Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10256/155172026-05-29T05:05:01Z
dc.title.none.fl_str_mv H-SLAM: Rao-Blackwellized particle filter SLAM using Hilbert Maps
title H-SLAM: Rao-Blackwellized particle filter SLAM using Hilbert Maps
spellingShingle H-SLAM: Rao-Blackwellized particle filter SLAM using Hilbert Maps
Vallicrosa Massaguer, Guillem
Vehicles submergibles
Submersibles
Vehicles autònoms
Autonomous vehicles
Robots mòbils
Mobile robots
Fons marins -- Mapes
Ocean bottom -- Maps
Algorismes computacionals
Computer algorithms
title_short H-SLAM: Rao-Blackwellized particle filter SLAM using Hilbert Maps
title_full H-SLAM: Rao-Blackwellized particle filter SLAM using Hilbert Maps
title_fullStr H-SLAM: Rao-Blackwellized particle filter SLAM using Hilbert Maps
title_full_unstemmed H-SLAM: Rao-Blackwellized particle filter SLAM using Hilbert Maps
title_sort H-SLAM: Rao-Blackwellized particle filter SLAM using Hilbert Maps
dc.creator.none.fl_str_mv Vallicrosa Massaguer, Guillem
Ridao Rodríguez, Pere
author Vallicrosa Massaguer, Guillem
author_facet Vallicrosa Massaguer, Guillem
Ridao Rodríguez, Pere
author_role author
author2 Ridao Rodríguez, Pere
author2_role author
dc.contributor.none.fl_str_mv Ministerio de Economía y Competitividad (Espanya)
dc.subject.none.fl_str_mv Vehicles submergibles
Submersibles
Vehicles autònoms
Autonomous vehicles
Robots mòbils
Mobile robots
Fons marins -- Mapes
Ocean bottom -- Maps
Algorismes computacionals
Computer algorithms
topic Vehicles submergibles
Submersibles
Vehicles autònoms
Autonomous vehicles
Robots mòbils
Mobile robots
Fons marins -- Mapes
Ocean bottom -- Maps
Algorismes computacionals
Computer algorithms
description Occupancy Grid maps provide a probabilistic representation of space which is important for a variety of robotic applications like path planning and autonomous manipulation. In this paper, a SLAM (Simultaneous Localization and Mapping) framework capable of obtaining this representation online is presented. The H-SLAM (Hilbert Maps SLAM) is based on Hilbert Map representation and uses a Particle Filter to represent the robot state. Hilbert Maps offer a continuous probabilistic representation with a small memory footprint. We present a series of experimental results carried both in simulation and with real AUVs (Autonomous Underwater Vehicles). These results demonstrate that our approach is able to represent the environment more consistently while capable of running online
publishDate 2018
dc.date.none.fl_str_mv 2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
peer-reviewed
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10256/15517
http://hdl.handle.net/10256/15517
url http://hdl.handle.net/10256/15517
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3390/s18051386
info:eu-repo/semantics/altIdentifier/eissn/1424-8220
info:eu-repo/grantAgreement/MINECO//DPI2014-57746-C3-3-R
info:eu-repo/grantAgreement/EC/H2020/731103
dc.rights.none.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI (Multidisciplinary Digital Publishing Institute)
publisher.none.fl_str_mv MDPI (Multidisciplinary Digital Publishing Institute)
dc.source.none.fl_str_mv Sensors (Switzerland), 2018, vol. 18, núm. 5, p. 1386
Articles publicats (D-ATC)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.81155

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