H-SLAM: Rao-Blackwellized particle filter SLAM using Hilbert Maps
dc.contributor.author
dc.date.accessioned
2018-05-28T12:35:02Z
dc.date.available
2018-05-28T12:35:02Z
dc.date.issued
2018-05-01
dc.identifier.uri
dc.description.abstract
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
dc.description.sponsorship
Research 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)
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
MDPI (Multidisciplinary Digital Publishing Institute)
dc.relation
info:eu-repo/grantAgreement/MINECO//DPI2014-57746-C3-3-R/ES/ARQUEOLOGIA MARINA MEDIANTE LA COOPERACION HROV%2FAUV/
dc.relation.isformatof
Reproducció digital del document publicat a: https://doi.org/10.3390/s18051386
dc.relation.ispartof
Sensors (Switzerland), 2018, vol. 18, núm. 5, p. 1386
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Articles publicats (D-ATC)
dc.rights
Attribution 4.0 International
dc.rights.uri
dc.subject
dc.title
H-SLAM: Rao-Blackwellized particle filter SLAM using Hilbert Maps
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.relation.projectID
info:eu-repo/grantAgreement/EC/H2020/731103/EU/Marine robotics research infrastructure network/EUMarineRobots
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.identifier.idgrec
028444
dc.contributor.funder
dc.type.peerreviewed
peer-reviewed
dc.relation.FundingProgramme
dc.relation.ProjectAcronym
dc.identifier.eissn
1424-8220