Journal of Intelligent and Robotic Systems

, Volume 50, Issue 4, pp 375–397 | Cite as

Consistency of SLAM-EKF Algorithms for Indoor Environments

  • Diego Rodriguez-Losada
  • Fernando Matia
  • Luis Pedraza
  • Agustin Jimenez
  • Ramon Galan


The solution to the Simultaneous Localization And Mapping (SLAM) problem using an Extended Kalman Filter (EKF) is probably the most extended in the literature despite the recently reported inconsistency of its estimation. There has been an important lack of successful SLAM-EKF implementations for indoor environments that could build monolithic large maps with features conveying angular information. In this paper we analyze the source and factors of the SLAM-EKF inconsistency in indoor environments (where the landmarks contain angular information) and we review current existing approaches presenting novel solutions to this problem that let us build indoor large monolithic feature based maps.


Mobile robots Simultaneous Localization And Mapping Extended Kalman Filter Consistency Linearization errors Indoor environments 


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Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  • Diego Rodriguez-Losada
    • 1
  • Fernando Matia
    • 1
  • Luis Pedraza
    • 1
  • Agustin Jimenez
    • 1
  • Ramon Galan
    • 1
  1. 1.Intelligent Control GroupUniversidad Politecnica de Madrid, UPMMadridSpain

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