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Semantic Modelling of Space

  • Andrzej Pronobis
  • Patric Jensfelt
  • Kristoffer Sjöö
  • Hendrik Zender
  • Geert-Jan M. Kruijff
  • Oscar Martinez Mozos
  • Wolfram Burgard
Part of the Cognitive Systems Monographs book series (COSMOS, volume 8)

Introduction

A cornerstone for robotic assistants is their understanding of the space they are to be operating in: an environment built by people for people to live and work in. The research questions we are interested in in this chapter concern spatial understanding, and its connection to acting and interacting in indoor environments. Comparing the way robots typically perceive and represent the world with findings from cognitive psychology about how humans do it, it is evident that there is a large discrepancy. If robots are to understand humans and vice versa, robots need to make use of the same concepts to refer to things and phenomena as a person would do. Bridging the gap between human and robot spatial representations is thus of paramount importance.

Keywords

Support Vector Machine Mobile Robot Indoor Environment Semantic Modelling Intelligent Robot 
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

  • Andrzej Pronobis
    • 1
  • Patric Jensfelt
    • 1
  • Kristoffer Sjöö
    • 1
  • Hendrik Zender
    • 2
  • Geert-Jan M. Kruijff
    • 2
  • Oscar Martinez Mozos
    • 3
  • Wolfram Burgard
    • 3
  1. 1.Centre for Autonomous SystemsRoyal Institute of Technology (KTH)StockholmSweden
  2. 2.DFKI GmbHSaarbrückenGermany
  3. 3.Department of Computer ScienceAlbert-Ludwigs-Universität FreiburgFreiburgGermany

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