Some Room for GLVQ: Semantic Labeling of Occupancy Grid Maps

  • Sven Hellbach
  • Marian Himstedt
  • Frank Bahrmann
  • Martin Riedel
  • Thomas Villmann
  • Hans-Joachim Böhme
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 295)


This paper aims at an approach for labeling places within a grid cell environment. For that we propose a method that is based on non-negative matrix factorization (NMF) to extract environment specific features from a given occupancy grid map. NMF also computes a description about where on the map these features need to be applied. We use this description after certain pre-processing steps as an input for generalized learning vector quantization (GLVQ) to achieve the classification or labeling of the grid cells. Our approach is evaluated on a standard data set from University of Freiburg, showing very promising results.


NMF GLVQ semantic labeling occupancy grid maps 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Sven Hellbach
    • 1
  • Marian Himstedt
    • 1
  • Frank Bahrmann
    • 1
  • Martin Riedel
    • 2
  • Thomas Villmann
    • 2
  • Hans-Joachim Böhme
    • 1
  1. 1.Artificial Intelligence and Cognitive Robotics LabsUniversity of Applied Sciences DresdenDresdenGermany
  2. 2.Computational Intelligence and TechnomathematicsUniversity of Applied Sciences MittweidaMittweidaGermany

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