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A regularised particle filter for context-aware sensor fusion applications

dc.contributor.authorMartí, Enrique
dc.contributor.authorGarcía, Jesús
dc.contributor.authorMolina, José Manuel
dc.contributor.editorHeiß, Hans-Ulrich
dc.contributor.editorPepper, Peter
dc.contributor.editorSchlingloff, Holger
dc.contributor.editorSchneider, Jörg
dc.date.accessioned2018-11-27T10:00:12Z
dc.date.available2018-11-27T10:00:12Z
dc.date.issued2011
dc.description.abstractParticle Filters are the most suitable filtering techique for some problems where the prediciton and update models are extremely non-linear. However, they suffer some problems as sample depletion which can drastically reduce their performance. There are multiple solutions to this problem. Some of them make assumptions that invalidate the filter for the most difficult scenarios. Some others increase the computational cost far beyond the bounds of real time applications. Context is a very important source of information for those systems that must work flawlessly in changing scenarios, but it introduces strong nonlinearities and uncertainties that filtering algorithms must deal with. This paper analyzes the performance and robustness of a recently developed regularisation technique for particle filters. The proposed scenarios include a navigation problem where a map is used to provide contextual information, because the final target for the particle filter is a mobile robot able to navigate both indoors and outdoors.en
dc.identifier.isbn978-88579-286-4
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/18815
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2011 – Informatik schafft Communities
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-192
dc.titleA regularised particle filter for context-aware sensor fusion applicationsen
dc.typeText/Conference Paper
gi.citation.endPage500
gi.citation.publisherPlaceBonn
gi.citation.startPage500
gi.conference.date4.-7. Oktober 2011
gi.conference.locationBerlin
gi.conference.sessiontitleRegular Research Papers

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