EKF based SLAM with FIM Inflation

Hamzah Ahmad, Toru Namerikawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


This paper deals with an analysis based on Fisher Information Matrix(FIM) for Extended Kalman Filter based Simultaneous Localization and Mapping(SLAM) problem. We show theoretically that the Cramer Rao Lower Bound is proportional to the number of landmarks, the magnitude of process and the measurement noises. In addition, we propose a method of adding a pseudo Positive semidefinite(PsD) matrix to the Fisher Information Matrix to decrease the computational cost in EKF based SLAM. The simulation results are convincing and realizes the improvement for EKF-based SLAM. Therefore, this method further improves the estimation in comparison with the normal EKF performance.

Original languageEnglish
Title of host publicationASCC 2011 - 8th Asian Control Conference - Final Program and Proceedings
Number of pages6
Publication statusPublished - 2011 Aug 29
Event8th Asian Control Conference, ASCC 2011 - Kaohsiung, Taiwan, Province of China
Duration: 2011 May 152011 May 18

Publication series

NameASCC 2011 - 8th Asian Control Conference - Final Program and Proceedings


Other8th Asian Control Conference, ASCC 2011
Country/TerritoryTaiwan, Province of China

ASJC Scopus subject areas

  • Control and Systems Engineering


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