Autonomous Robots

, Volume 5, Issue 1, pp 111–125 | Cite as

Learning View Graphs for Robot Navigation

  • Matthias O. Franz
  • Bernhard Schölkopf
  • Hanspeter A. Mallot
  • Heinrich H. Bülthoff


We present a purely vision-based scheme for learning a topological representation of an open environment. The system represents selected places by local views of the surrounding scene, and finds traversable paths between them. The set of recorded views and their connections are combined into a graph model of the environment. To navigate between views connected in the graph, we employ a homing strategy inspired by findings of insect ethology. In robot experiments, we demonstrate that complex visual exploration and navigation tasks can thus be performed without using metric information.

visual navigation topological maps environment modeling exploration cognitive maps mobile robots omnidirectional sensor 


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Copyright information

© Kluwer Academic Publishers 1998

Authors and Affiliations

  • Matthias O. Franz
    • 1
  • Bernhard Schölkopf
    • 1
  • Hanspeter A. Mallot
    • 1
  • Heinrich H. Bülthoff
    • 1
  1. 1.Max-Planck-Institut für biologische KybernetikTübingenGermany

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