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Consistency of SLAM-EKF Algorithms for Indoor Environments

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Abstract

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.

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Authors and Affiliations

  1. Intelligent Control Group, Universidad Politecnica de Madrid, UPM, C/Jose Gutierrez Abascal, 2, 28006, Madrid, Spain

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

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  1. Diego Rodriguez-Losada
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  2. Fernando Matia
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  3. Luis Pedraza
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  4. Agustin Jimenez
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  5. Ramon Galan
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Correspondence to Diego Rodriguez-Losada.

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Rodriguez-Losada, D., Matia, F., Pedraza, L. et al. Consistency of SLAM-EKF Algorithms for Indoor Environments. J Intell Robot Syst 50, 375–397 (2007). https://doi.org/10.1007/s10846-007-9171-8

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  • DOI: https://doi.org/10.1007/s10846-007-9171-8

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