A Performance Analysis of Omnidirectional Vision Based Simultaneous Localization and Mapping

  • Hayrettin Erturk
  • Gurkan Tuna
  • Tarik Veli Mumcu
  • Kayhan Gulez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7389)


This paper presents a performance analysis of omnidirectional vision based Simultaneous Localization and Mapping (SLAM). In omnidirectional vision based SLAM; robots perform vision based SLAM using only monocular omnidirectional cameras. In this paper, we mainly investigate the use of an omnidirectional camera for Extended Kalman Filter (EKF) based SLAM. To evaluate the success of omnidirectional vision based SLAM, we have also conducted the same simulations using a laser range finder (LRF). Main contributions of this paper are the use of an omnidirectional camera to perform SLAM in the Unified System for Automation and Robot Simulation (USARSim) environment, which is controlled by MATLAB in our study. The results of USARSim simulations show that depending on the environmental conditions omnidirectional cameras can be used as an alternative to other range bearing sensors and stereo cameras.


Omnidirectional camera SLAM USARSim MATLAB 


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  1. 1.
    Dissanayake, G., Newman, P., Clark, S., Durrant-Whyte, H.F., Csorba, M.: A Solution to The Simultaneous Localization and Map Building (SLAM) Problem. IEEE Transactions on Robotics and Automation 17(3), 229–241 (2001)CrossRefGoogle Scholar
  2. 2.
    Williams, S.B.: Efficient Solutions to Autonomous Mapping and Navigation Problems, Ph.D. Dissertation, University of Sydney (2001)Google Scholar
  3. 3.
    Suttasupa, Y., Sudsang, A., Niparnan, N.: 3D SLAM for Omnidirectional Camera. In: Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics, pp. 828–833 (2009)Google Scholar
  4. 4.
    Kim, S., Oh, S.-Y.: SLAM in Indoor Environments Using Omnidirectional Vertical and Horizontal Line Features. Journal of Intelligent and Robotic Systems 51, 31–43 (2008)CrossRefGoogle Scholar
  5. 5.
    Kim, J., Yoon, K.-J., Kim, J.-S., Kweon, I.: Visual SLAM by Single-Camera Catadioptric Stereo. In: Proc. of the SICE-ICASE International Joint Conference (2006)Google Scholar
  6. 6.
    Rituerto, A., Puig, L., Guerrero, J.J.: Visual SLAM with An Omnidirectional Camera. In: Proceedings of the 2010 International Conference on Pattern Recognition, pp. 348–351 (2010)Google Scholar
  7. 7.
    Burbridge, C., Spacek, L., Condell, J., Nehmzow, U.: Monocular Omnidirectional Vision based Robot Localisation and Mapping. In: Proc. of the TAROS 2008 (2008)Google Scholar
  8. 8.
    Li, M., Imou, K., Wakabayashi, K.: 3D Positioning for Mobile Robot Using Omnidirectional Vision. In: Proceedings of the 2010 International Conference on Intelligent Computing Technology and Automation, pp. 7–11 (2010)Google Scholar
  9. 9.
    Nayar, S.K.: Omnidirectional Video Camera. In: Proceedings of the DARPA Image Understanding Workshop (1997)Google Scholar
  10. 10.
    Baker, S., Nayar, S.K.: A Theory of Single-Viewpoint Catadioptric Image Formation. International Journal of Computer Vision 35, 1–22 (1999)CrossRefGoogle Scholar
  11. 11.
    Schmits, T., Visser, A.: An Omnidirectional Camera Simulation for the USARSim World. In: Iocchi, L., Matsubara, H., Weitzenfeld, A., Zhou, C. (eds.) RoboCup 2008. LNCS, vol. 5399, pp. 296–307. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  12. 12.
  13. 13.
    MATLAB USARSim Toolbox (2010),
  14. 14.
    FRAPS show fps, Record Video Game Movies, screen capture software (2011),
  15. 15.
    Scaramuzza, D., Siegwart, R.: Appearance-Guided Monocular Omnidirectional Visual Odometry for Outdoor Ground Vehicles. IEEE Transactions on Robotics 24(5), 1015–1026 (2008)CrossRefGoogle Scholar
  16. 16.
    Scaramuzza, D., Martinelli, A., Siegwart, R.: Appearance-based SLAM with Map Loop Closing Using an Omnidirectional Camera. In: Proceedings of the IEEE International Conference on Intelligent Robots and Systems, IROS 2006 (2006)Google Scholar
  17. 17.
    Nguyen, Q., Visser, A.: A Color Based Rangefinder for an Omnidirectional Camera. In: Proc. of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2009), pp. 41–48 (2009)Google Scholar
  18. 18.
  19. 19.

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hayrettin Erturk
    • 1
  • Gurkan Tuna
    • 2
  • Tarik Veli Mumcu
    • 3
  • Kayhan Gulez
    • 3
  1. 1.Electrical-Electronics Faculty, Electrical Eng. Dept.Yildiz Technical UniversityIstanbulTurkey
  2. 2.Department of Computer ProgrammingTrakya UniversityEdirneTurkey
  3. 3.Yildiz Technical UniversityElectrical-Electronics Faculty, Control and Automation Eng. Dept.IstanbulTurkey

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