Obtaining the Inverse Distance Map from a Non-SVP Hyperbolic Catadioptric Robotic Vision System

  • Bernardo Cunha
  • José Azevedo
  • Nuno Lau
  • Luis Almeida
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5001)


The use of single viewpoint catadioptric vision systems is a common approach in mobile robotics, despite the constraints imposed by those systems. A general solution to calculate the robot centered distances map on non-SVP catadioptric setups, exploring a back-propagation ray-tracing approach and the mathematical properties of the mirror surface is discussed in this paper. Results from this technique applied in the robots of the CAMBADA team (Cooperative Autonomous Mobile Robots with Advanced Distributed Architecture) are presented, showing the effectiveness of the solution.


Omnidirectional vision robot vision visualization 


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  1. 1.
    Zivkovic, Z., Booij, O.: How did we built our hyperbolic mirror omni-directional camera - practical issues and basic geometry. Intelligent Systems Laboratory Amsterdam, University of Amsterdam, IAS technical report IAS-UVA-05-04 (2006)Google Scholar
  2. 2.
    Wolf, J.: Omnidirectional vision system for mobile robot localization in the Robocup environment. Master’s thesis, Graz, University of Technology (2003)Google Scholar
  3. 3.
    Menegatti, E., Nori, F., Pagello, E., Pellizzari, C., Spagnoli, D.: Designing an omnidirectional vision system for a goalkeeper robot. In: Birk, A., Coradeschi, S., Tadokoro, S. (eds.) RoboCup 2001. LNCS (LNAI), vol. 2377, pp. 78–87. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  4. 4.
    Menegatti, E., Pretto, A., Pagello, E.: Testing omnidirectional vision-based Monte Carlo localization under occlusion. In: Intelligent Robots and Systems (IROS 2004). IEEE/RSJ, vol. 3, pp. 2487–2493 (2004)Google Scholar
  5. 5.
    Lima, P., Bonarini, A., Machado, C., Marchese, F., Marques, C., Ribeiro, F., Sorrenti, D.: Omni-directional catadioptric vision for soccer robots. Robotics and Autonomous Systems 36(2-3), 87–102 (2001)MATHCrossRefGoogle Scholar
  6. 6.
    Baker, S., Nayar, S.K.: A theory of single-viewpoint catadioptric image formation. International Journal of Computer Vision 35(2), 175–196 (1999)CrossRefGoogle Scholar
  7. 7.
    Benosman, R., Kang, S.B.: Panoramic Vision. Springer, Heidelberg (2001)MATHGoogle Scholar
  8. 8.
    Blinn, J.F.: A Homogeneous Formulation for Lines in 3D Space. In: SIGGRAPH 1977, pp. 237–241 (1977)Google Scholar
  9. 9.
    Foley, J.D., van Dam, A., Feiner, S.K., Hughes, J.F.: Computer Graphics: Principles and Practice in C, 2nd edn. Addison-Wesley Professional (1995)Google Scholar
  10. 10.
    Zhang, Z.: A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(11), 1330–1334 (2000)CrossRefGoogle Scholar
  11. 11.
    Hartley, R., Zisserman, A.R.: Multiple View Geometry in Computer Vision, Cambridge University Press (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Bernardo Cunha
    • 1
  • José Azevedo
    • 1
  • Nuno Lau
    • 1
  • Luis Almeida
    • 1
  1. 1.LSE-IEETA/DETIUniversidade de AveiroPortugal

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