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Conference Paper

The view-graph approach to visual navigation and spatial memory

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Mallot,  HA
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Franz,  MO
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Schölkopf,  B
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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https://link.springer.com/content/pdf/10.1007%2FBFb0020244.pdf
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Citation

Mallot, H., Franz, M., Schölkopf, B., & Bülthoff, H. (1997). The view-graph approach to visual navigation and spatial memory. In W. Gerstner, A. Germond, M. Hasler, & J.-D. Nicoud (Eds.), Artificial Neural Networks - ICANN'97: 7th International Conference Lausanne, Switzerland, October 8–10, 1997 (pp. 751-756). Berlin, Germany: Springer.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-E9D6-C
Abstract
This paper describes a purely visual navigation scheme based on two elementary mechanisms (piloting and guidance) and a graph structure combining individual navigation steps controlled by these mechanisms. In robot experiments in real environments, both mechanisms have been tested, piloting in an open environment and guidance in a maze with restricted movement opportunities. The results indicate that navigation and path planning can be brought about with these simple mechanisms. We argue that the graph of local views (snapshots) is a general and biologically plausible means of representing space and integrating the various mechanisms of map behaviour.