Learning view graphs for robot navigation

Matthias O. Franz, Bernhard Schoelkopf, Philipp Georg, Hanspeter A. Mallot, Heinrich H. Buelthoff

Research output: Contribution to conferencePaper

9 Citations (Scopus)

Abstract

We present a purely vision-based scheme for learning a parsimonious representation of an open environment. Using simple exploration behaviours, our system constructs a graph of appropriately chosen views. To navigate between views connected in the graph, we employ a homing strategy inspired by findings of insect ethology. Simulations and robot experiments demonstrate the feasibility of the proposed approach.

Original languageEnglish
Pages138-147
Number of pages10
DOIs
Publication statusPublished - 1997
EventProceedings of the 1997 1st International Conference on Autonomous Agents - Marina del Rey, CA, USA
Duration: 1997 Feb 51997 Feb 8

Other

OtherProceedings of the 1997 1st International Conference on Autonomous Agents
CityMarina del Rey, CA, USA
Period97/2/597/2/8

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Franz, M. O., Schoelkopf, B., Georg, P., Mallot, H. A., & Buelthoff, H. H. (1997). Learning view graphs for robot navigation. 138-147. Paper presented at Proceedings of the 1997 1st International Conference on Autonomous Agents, Marina del Rey, CA, USA, . https://doi.org/10.1145/267658.267687