Advertisement

Insect-Inspired Odometry by Optic Flow Recorded with Optical Mouse Chips

  • Hansjürgen DahmenEmail author
  • Alain Millers
  • Hanspeter A. Mallot
Chapter

Abstract

Inspired by investigations in water striders (Gerrids) on the eye structure and visually controlled behaviour and subsequent simulations of self-motion estimates from optic flow, a device is presented that extracts self-motion parameters exclusively from flow. Optical mouse chips provided with adequate lenses serve as motion sensors. Pairs of sensors with opposite lines of sight are mounted on a sensor head. The optical axes of the sensor pairs are distributed over the largest possible solid angle. The device is fast, cheap and light. The calibration procedure and tests on the precision of self-motion estimates in outdoor experiments are reported.

Keywords

Outdoor Environment Fast Estimate Relative Nearness Opposite Line Water Strider 
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.
    Baird, E., Srinivasan, M.V., Zhang, S., Lamont, R., Cowling, A.: From Animals to Animats 9, Proceedings 9th International Conference on Simulation of Adaptive Behaviour, SAB, Rome. Visual Control of Flight Speed and Height in the Honeybee, pp. 40–51. Springer-Verlag Berlin Heidelberg (2006)Google Scholar
  2. 2.
    Baker, P., Fermüller, C., Aloimonos, Y., Pless, R.: A spherical eye from multiple cameras (makes better models of the world). Proceedings IEEE Computer Society Conference on Computer Vision and Pattern Recognition CVPR 2001, vol. 1, pp. 576–583 (2001)Google Scholar
  3. 3.
    Baker, P., Ogale, A.S., Fermüller, C., Aloimonos, Y.: The argus eye: A new tool for robotics. IEEE Robotics and Automation Magazine: Special Issue on Panoramic Robots 11 Nr. 4, 31–38 (2004)CrossRefGoogle Scholar
  4. 4.
    Chahl, J.S., Srinivasan, M.V.: Reflective surfaces for panoramic imaging. Applied Optics 36(31), 8275–8285 (1997)CrossRefGoogle Scholar
  5. 5.
    Dahmen, H.: Eye specialisation in waterstriders : an adaptation to life in a flat world. Journal of Comparative Physiology A 169, 623–632 (1991)Google Scholar
  6. 6.
    Dahmen, H., Franz, M.O., Krapp, H.G.: Extracting Egomotion from Optic Flow: Limits of Accuracy and Neural Matched Filters. Motion Vision, pp. 143–168. Springer-Verlag Berlin Heidelberg New York (2001)Google Scholar
  7. 7.
    Dahmen, H., Wüst, R.M., Zeil, J.: Extracting egomotion parameters from optic flow: principal limits for animals and machines. From Living Eyes to Seeing Machines, pp. 174–198. Oxford Univ Press (1997)Google Scholar
  8. 8.
    Egelhaaf, M.: Invertebrate Vision. The neural computation of visual motion information, pp. 399–461. Cambr. Univ. Press (2006)Google Scholar
  9. 9.
    Egelhaaf, M., Kern, R.: Vision in flying insects. Current Opinion in Neurobiology 12, 699–706 (2002)CrossRefGoogle Scholar
  10. 10.
    Egelhaaf, M., Kern, R., Lindemann, J.P., Braun, E., Geurten, B.: Active Vision in Blowflies : Strategies and Neuronal Mechanisms of Spatial Orientation. Chapter 4 of this book. Springer-Verlag Berlin Heidelberg (2009)Google Scholar
  11. 11.
    Franceschini, N., Ruffier, F., Serres, J.: Insect Pilots : Vertical and Horizontal Guidance. Chapter 3 of this book. Springer-Verlag Berlin Heidelberg (2009)Google Scholar
  12. 12.
    Franz, M.O., Krapp, H.G.: Wide-field motion-sensitive neurons and matched filters for optic flow fields. Biological Cybernetics 83, 185–197 (2000)CrossRefGoogle Scholar
  13. 13.
    Fry, S.N.: Experimental approaches toward a functional understanding of insect flight control. Chapter 1 of this book. Springer-Verlag Berlin Heidelberg (2009)Google Scholar
  14. 14.
    Gluckman, J., Nayar, S.K.: Ego-motion and omnidirectional cameras. Proceeding of the 6th International Conference on Computer vision (ICCV’03) (2003)Google Scholar
  15. 15.
    Grassi, V., Okamoto, J.: Development of an omnidirectional vision system. Journal of the Brazilian Society of Mechanical Science and Engineering XXVIII, No. 1, 58–68 (2006)Google Scholar
  16. 16.
    Junger, W.: Waterstriders (gerris paludum f) compensate for drift with a discontinuously working visual position servo. Journal of Comparative Physiology A 169, 633–639 (1991)Google Scholar
  17. 17.
    Junger, W., Dahmen, H.: Response to self-motion in waterstriders: visual discrimination between rotation and translation. Journal of Comparative Physiology A 169, 641–646 (1991)Google Scholar
  18. 18.
    Koenderink, J.J., van Doorn, A.J.: Facts on optic flow. Biological Cybernetics 56, 247–254 (1987)zbMATHCrossRefGoogle Scholar
  19. 19.
    Nayar, S.K.: Catadioptric omnidirectional camera. Proceedings IEEE Conference CVPR, pp. 482–488 (1997)Google Scholar
  20. 20.
    Shakernia, O., Vidal, R., Sastry, S.: Omnidirectional egomotion estimation from back-projection flow. IEEE Workshop on Omnidirectional Vision (2003)Google Scholar
  21. 21.
    Pless, R.: Using many cameras as one. Proc. IEEE CVPR’03, vol. 2, pp. 587–593 (2003)Google Scholar
  22. 22.
    Press, W., Flannery, B., Teukolsky, S., Vetterling, W. (eds.): Numerical Recipes in Pascal. Nonlinear Models, pp. 572–580. Cambridge University Press (1989)Google Scholar
  23. 23.
    Srinivasan, M., Zhang, S., Chahl, J., Barth, E., Venkatesh, S.: How honeybees make grazing landings on flat surfaces. Biological Cybernetics 83(3), 171–183 (2000)CrossRefGoogle Scholar
  24. 24.
    Srinivasan, M., Zhang, S., Lehrer, M., Collett, T.: Honeybee navigation en route to the goal: visual flight control and odometry. Journal of Experimental Biology 199(Pt 1), 237–244 (1996)Google Scholar
  25. 25.
    Srinivasan, M.V., Thurrowgood, S., Soccol, D.: From visual guidance in flying insects to autonomous aerial vehicles. Chapter 2 of this book. Springer-Verlag Berlin Heidelberg (2009)Google Scholar
  26. 26.
    Vassallo, R.F., Santos-Victor, J., Schneebeli, H.J.: A general approach for egomotion estimation with omnidirectional images. Proceedings of the Third Workshop on Omnidirectional Vision, 97–103 (2002)Google Scholar
  27. 27.
    Zeil, J., Boeddeker, N., Stürzl, W.: Visual Homing in Insects and Robots. Chapter 7 of this book. Springer-Verlag Berlin Heidelberg (2009)Google Scholar
  28. 28.
    Zufferey, J.C., Beyeler, A., Floreano, D.: Optic Flow to Steer and Avoid Collisions in 3D. Chapter 6 of this book. Springer-Verlag Berlin Heidelberg (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Hansjürgen Dahmen
    • 1
    Email author
  • Alain Millers
    • 1
  • Hanspeter A. Mallot
    • 1
  1. 1.Cognitive NeurosciencesUniversity of TübingenTübingenGermany

Personalised recommendations