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International Conference on Spatial Cognition

Spatial Cognition 2014: Spatial Cognition IX pp 283–298Cite as

Dimensions of Uncertainty in Evidential Grid Maps

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8684))

Abstract

We show how a SLAM algorithm based on belief function theory can produce evidential occupancy grid maps that provide a mobile robot with additional information about its environment. While uncertainty in probabilistic grid maps is usually measured by entropy, we show that for evidential grid maps, uncertainty can be expressed in a three-dimensional space and we propose appropriate measures for quantifying uncertainty in these different dimensions. We analyze these measures in a practical mapping example containing typical sources of uncertainty for SLAM. As a result of the evidential representation, the robot is able to distinguish between different sources of uncertainty (e.g., a lack of measurements vs. conflicting measurements) which are indistinguishable in the probabilistic framework.

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Author information

Authors and Affiliations

  1. Cognitive Neuroinformatics, University of Bremen, Germany

    Thomas Reineking & Joachim Clemens

Authors
  1. Thomas Reineking
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  2. Joachim Clemens
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Editor information

Editors and Affiliations

  1. Universität Bremen, Enrique-Schmidt-Str. 5, 28359, Bremen, Germany

    Christian Freksa  & Thomas Barkowsky  & 

  2. Department of Computer Science, Universität Freiburg, Georges-Köhler-Allee 52, 79110, Freiburg, Germany

    Bernhard Nebel

  3. University of California, 93106, Santa Barbara, CA, USA

    Mary Hegarty

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© 2014 Springer International Publishing Switzerland

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Reineking, T., Clemens, J. (2014). Dimensions of Uncertainty in Evidential Grid Maps. In: Freksa, C., Nebel, B., Hegarty, M., Barkowsky, T. (eds) Spatial Cognition IX. Spatial Cognition 2014. Lecture Notes in Computer Science(), vol 8684. Springer, Cham. https://doi.org/10.1007/978-3-319-11215-2_20

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  • DOI: https://doi.org/10.1007/978-3-319-11215-2_20

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11214-5

  • Online ISBN: 978-3-319-11215-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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