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dc.contributor.authorIla, Viorela Simona
dc.contributor.authorPorta Pleite, Josep Maria
dc.contributor.authorAndrade-Cetto, Juan
dc.contributor.otherInstitut de Robòtica i Informàtica Industrial
dc.date.accessioned2010-02-15T18:43:10Z
dc.date.available2010-02-15T18:43:10Z
dc.date.created2009
dc.date.issued2009
dc.identifier.citationIla, V.; Porta, J.; Andrade-Cetto, J. Amortized constant time state estimation in SLAM using a mixed Kalman-information filter. A: European Conference on Mobile Robots. "European Conference on Mobile Robots (ECMR) 4th". Mlini: 2009, p. 211-216.
dc.identifier.isbn978-953-6037-54-4
dc.identifier.urihttp://hdl.handle.net/2117/6376
dc.description.abstractThe computational bottleneck in all informationbased algorithms for SLAM is the recovery of the state mean and covariance. The mean is needed to evaluate model Jacobians and the covariance is needed to generate data association hypotheses. Recovering the state mean and covariance requires the inversion of a matrix of the size of the state. Current state recovery methods use sparse linear algebra tools that have quadratic cost, either in memory or in time. In this paper, we present an approach to state estimation that is worst case linear both in execution time and in memory footprint at loop closure, and constant otherwise. The approach relies on a state representation that combines the Kalman and the information-based state representations. The strategy is valid for any SLAM system that maintains constraints between robot poses at different time slices. This includes both Pose SLAM, the variant of SLAM where only the robot trajectory is estimated, and hierarchical techniques in which submaps are registered with a network of relative geometric constraints.
dc.format.extent6 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Informàtica::Robòtica
dc.subject.lcshKalman filtering
dc.titleAmortized constant time state estimation in SLAM using a mixed Kalman-information filter
dc.typeConference lecture
dc.subject.lemacKalman, Filtratge de
dc.contributor.groupUniversitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel·ligents
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.ecmr09.fer.hr/
dc.rights.accessOpen Access
local.identifier.drac2473661
dc.description.versionPostprint (published version)
local.citation.authorIla, V.; Porta, J.; Andrade-Cetto, J.
local.citation.contributorEuropean Conference on Mobile Robots
local.citation.pubplaceMlini
local.citation.publicationNameEuropean Conference on Mobile Robots (ECMR) 4th
local.citation.startingPage211
local.citation.endingPage216


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