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Environment Topological Structure Recognition for Robot Navigation

  • Enver Sangineto
  • Marco R. Iarusso
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)

Abstract

Robot navigation using only abstract, topological information on the environment is strongly related to the possibility for a robot to unambiguously match information coming from its sensors with the basic elements of the environment. In this paper we present an approach to this challenging problem based on the direct recognition of the topological structure of the environment.

Keywords

Mobile Robot Robot Navigation Splitting Line Polygonal Approximation Direct Recognition 
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.

References

  1. 1.
    Anelli, M., Micarelli, A., Sangineto, E.: A deformation tolerant version of the generalized Hough transform for image retrieval. In: Fifteenth European Conference on Artificial Intelligence (ECAI 2002), Lyon, France (2002)Google Scholar
  2. 2.
    Borenstein, J., Everett, H.R., Feng, L.: Navigating mobile robot: sensors and techniques. A. K. Peters, Ltd., Wellesley (1996)zbMATHGoogle Scholar
  3. 3.
    Cantoni, V., Lombardi, L., Porta, M., Sicard, N.: Vanishing point detection: representation analysis and new approaches. In: 11th International Conference on Image Analysis and Processing (ICIAP 2001), pp. 90–94 (2001)Google Scholar
  4. 4.
    Courtney, J.W., Magee, M.J., Aggarwal, J.K.: Robot guidanceusing computer vision. Pattern Recognition 17(6), 585–592 (1984)CrossRefGoogle Scholar
  5. 5.
    Dulimarta, H.S., Jain, A.K.: Mobile robot localization in indoor environment. Pattern Recognition 30(1), 99–111 (1997)CrossRefGoogle Scholar
  6. 6.
    Fiala, M.: Linear markers for robot navigation with panoramic vision. In: 1st Canadian Conference on Computer and Robot Vision (CRV 2004) (2004)Google Scholar
  7. 7.
    Forsyth, D.A., Ponce, J.: Computer Vision: A Modern Approach. Prentice-Hall, Englewood Cliffs (2003) ISBN: 0130851981Google Scholar
  8. 8.
    Kosaka, A., Kak, A.C.: Fast vision-guided robot navigation using model-based reasoning and prediction of uncertainties. CVGIP 56(3), 271–329 (1992)zbMATHCrossRefGoogle Scholar
  9. 9.
    Lee, W.H., Roh, K.S., Kweon, I.S.: Self-localization of a mobile robot without camera calibration using projective invariants. Pattern Recognition Letters 21, 45–60 (2000)CrossRefGoogle Scholar
  10. 10.
    Thrun, S.: Learning metric-topological maps for inddor mobile robot navigation. Artificial Intelligence 99, 21–71 (1998)zbMATHCrossRefGoogle Scholar
  11. 11.
    Trahanias, P.E., Velissaris, S., Orphanoudakis, S.C.: Visual recognition of workspace landmarks for topological navigation. Autonomous Robots 7, 143–158 (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Enver Sangineto
    • 1
  • Marco R. Iarusso
    • 1
    • 2
  1. 1.Centro di Ricerca in Matematica Pura ed Applicata (CRMPA) 
  2. 2.Dipartimento di Informatica e Automazione (DIA)Universitá Roma 3RomeItaly

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