Semantic Mapping with a Probabilistic Description Logic

  • Rodrigo Polastro
  • Fabiano Corrêa
  • Fabio Cozman
  • Jun OkamotoJr.
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6404)


Semantic mapping employs explicit labels to deal with sensor data in robotic mapping processes. In this paper we present a method for boosting performance of spatial mapping, through the use of a probabilistic ontology, expressed with a probabilistic description logic. Reasoning with this ontology allows segmentation and tagging of sensor data acquired by a robot during navigation; hence a robot can construct metric maps topologically. We report experiments with a real robot to validate our approach, thus moving closer to the goal of integrating mapping and semantic labeling processes.


Mobile Robot Sensor Data Description Logic Semantic Mapping Probabilistic Inclusion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Rodrigo Polastro
    • 1
  • Fabiano Corrêa
    • 1
  • Fabio Cozman
    • 1
  • Jun OkamotoJr.
    • 1
  1. 1.Escola Politécnica da Universidade de São PauloBrazil

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