Simultaneous localization and mapping using extended Kalman filter

Sirma Yavuz*, Zeyneb Kurt, M. Serdar Biçer

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

In 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.

Translated title of the contributionSimultaneous localization and mapping using extended Kalman filter
Original languageTurkish
Title of host publication2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages700-703
Number of pages4
ISBN (Print)9781424444366
DOIs
Publication statusPublished - 9 Apr 2009
Externally publishedYes
Event2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009 - Antalya, Turkey
Duration: 9 Apr 200911 Apr 2009

Publication series

Name2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009

Conference

Conference2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009
Country/TerritoryTurkey
CityAntalya
Period9/04/0911/04/09

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