Improvement of the measurement update step of EKF-SLAM

Zeyneb Kurt Yavuz*, Sirma Yavuz

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

In this study, the measurement update step of the Extended Kalman Filter (EKF)-based Simultaneous Localization and Mapping (SLAM) is improved. The computational complexity of the measurement uncertainty matrix inversion operation in the measurement update step is reduced via using Jacobi iteration method. It is observed that, the calculation of the measurement uncertainty matrix inverse by using Jacobi iteration method generates numerically more stable results than naive single and batch update operations. Moreover, it produces more accurate results than the results of Cholesky decomposition with less complexity.

Original languageEnglish
Title of host publicationINES 2012 - IEEE 16th International Conference on Intelligent Engineering Systems, Proceedings
Pages61-65
Number of pages5
DOIs
Publication statusPublished - 1 Oct 2012
Externally publishedYes
EventIEEE 16th International Conference on Intelligent Engineering Systems, INES 2012 - Lisbon, Portugal
Duration: 13 Jun 201215 Jun 2012

Publication series

NameINES 2012 - IEEE 16th International Conference on Intelligent Engineering Systems, Proceedings

Conference

ConferenceIEEE 16th International Conference on Intelligent Engineering Systems, INES 2012
CountryPortugal
CityLisbon
Period13/06/1215/06/12

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