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International Conference on Spatial Information Theory

COSIT 2015: Spatial Information Theory pp 403–425Cite as

Learning Spatial Models for Navigation

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9368))

Abstract

Typically, autonomous robot navigation relies on a detailed, accurate map. The associated representations, however, do not readily support human-friendly interaction. The approach reported here offers an alternative: navigation with a spatial model and commonsense qualitative spatial reasoning. Both are based on research about how people experience and represent space. The spatial model quickly develops as the result of incremental learning while the robot moves through its environment. In extensive empirical testing, qualitative spatial reasoning principles that reference this model support increasingly effective navigation in a variety of built spaces.

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Acknowledgments

This work was supported in part by the National Science Foundation under IIS 11-17000, IIS 11-16843 and CNS 08-51901, and by The City University of New York, Collaborative Incentive Research Grant 1642. We thank Tuna Ozgelen, Eric Schneider, and our anonymous reviewers for their insights and guidance. Tereza Shterenberg produced the map in Fig. 6.

Author information

Authors and Affiliations

  1. Hunter College and The Graduate Center of The City University of New York, New York, NY, 10065, USA

    Susan L. Epstein, Anoop Aroor & Matthew Evanusa

  2. University of Liverpool, Liverpool, UK

    Elizabeth I. Sklar & Simon Parsons

  3. Kings College, London, UK

    Elizabeth I. Sklar

Authors
  1. Susan L. Epstein
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  2. Anoop Aroor
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  3. Matthew Evanusa
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  4. Elizabeth I. Sklar
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  5. Simon Parsons
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Corresponding author

Correspondence to Susan L. Epstein .

Editor information

Editors and Affiliations

  1. University of Zurich, Zurich, Switzerland

    Sara Irina Fabrikant

  2. ETH Zurich, Zurich, Switzerland

    Martin Raubal

  3. School of Computer Science and Informatics, University College Dublin, Dublin, Ireland

    Michela Bertolotto

  4. University of Winchester, Winchester, United Kingdom

    Clare Davies

  5. Dept. of Geography and Env. Studies, University of New Mexico, Albuquerque, New Mexico, USA

    Scott Freundschuh

  6. College of Arts and Science, University of Saskatchewan, Saskatoon, Canada

    Scott Bell

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Epstein, S.L., Aroor, A., Evanusa, M., Sklar, E.I., Parsons, S. (2015). Learning Spatial Models for Navigation. In: Fabrikant, S., Raubal, M., Bertolotto, M., Davies, C., Freundschuh, S., Bell, S. (eds) Spatial Information Theory. COSIT 2015. Lecture Notes in Computer Science(), vol 9368. Springer, Cham. https://doi.org/10.1007/978-3-319-23374-1_19

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  • DOI: https://doi.org/10.1007/978-3-319-23374-1_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23373-4

  • Online ISBN: 978-3-319-23374-1

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