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Simultaneous Localization and Mapping Using Extended Kalman Filter

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dc.contributor.authorYavuz, Sirma
dc.contributor.authorKurt, Zeyneb
dc.contributor.authorBicer, M. Serdar
dc.date.accessioned2026-06-27T13:06:34Z
dc.date.issued2009
dc.description.abstractIn this study an offline statistical estimation algorithm based on Extended Kalman Filter method is developed to solve the SLAM (Simultaneous Localization and Map Building) problem. For the application, a robot equipped with only simple and cheap sensors is used. Two of the most frequent problems in SLAM algorithms which are known as loop closing and data association are effectively solved by Extended Kalman Filter method.en
dc.identifier.endpage917
dc.identifier.isbn978-1-4244-4435-9
dc.identifier.startpage914
dc.identifier.urihttps://hdl.handle.net/20.500.14981/49844
dc.identifier.wos000273935600229
dc.language.isotur
dc.publisherIEEE
dc.relation.conferenceIEEE 17th Signal Processing and Communications Applications Conference
dc.relation.ispartof2009 IEEE 17TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE, VOLS 1 AND 2
dc.subjectComputer Science
dc.subjectEngineering
dc.subjectTelecommunications
dc.titleSimultaneous Localization and Mapping Using Extended Kalman Filter
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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