Consistency of SLAM-EKF Algorithms for Indoor Environments |
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Authors: | Diego Rodriguez-Losada Fernando Matia Luis Pedraza Agustin Jimenez Ramon Galan |
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Affiliation: | (1) Intelligent Control Group, Universidad Politecnica de Madrid, UPM, C/Jose Gutierrez Abascal, 2, 28006 Madrid, Spain |
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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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Keywords: | Mobile robots Simultaneous Localization And Mapping Extended Kalman Filter Consistency Linearization errors Indoor environments |
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