An Egocentric Qualitative Spatial Knowledge Representation Based on Ordering Information for Physical Robot Navigation

  • Thomas Wagner
  • Kai Hübner
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3276)


Navigation is one of the most fundamental tasks to be accomplished by many types of mobile and cognitive systems. Most approaches in this area are based on building or using existing allocentric, static maps in order to guide the navigation process. In this paper we propose a simple egocentric, qualitative approach to navigation based on ordering information. An advantage of our approach is that it produces qualitative spatial information which is required to describe and recognize complex and abstract, i.e., translation-invariant behavior. In contrast to other techniques for mobile robot tasks, that also rely on landmarks it is also proposed to reason about their validity despite insufficient and insecure sensory data. Here we present a formal approach that avoids this problem by use of a simple internal spatial representation based on landmarks aligned in an extended panoramic representation structure.


Mobile Robot Plan Recognition Egocentric Representation Penalty Area Egocentric View 
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 2005

Authors and Affiliations

  • Thomas Wagner
    • 1
  • Kai Hübner
    • 2
  1. 1.Center for Computing Technologies (TZI)Universität BremenBremen
  2. 2.Bremen Institute of Safe Systems (BISS)Universität BremenBremen

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