Advertisement

Insect-Inspired Estimation of Self-Motion

  • Matthias O. Franz
  • Javaan S. Chahl
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2525)

Abstract

The tangential neurons in the fly brain are sensitive to the typical optic flow patterns generated during self-motion. In this study, we examine whether a simplified linear model of these neurons can be used to estimate self-motion from the optic flow. We present a theory for the construction of an optimal linear estimator incorporating prior knowledge about the environment. The optimal estimator is tested on a gantry carrying an omnidirectional vision sensor. The experiments show that the proposed approach leads to accurate and robust estimates of rotation rates, whereas translation estimates turn out to be less reliable.

Keywords

Mobile Robot Model Neuron Rotation Estimate Current Scene Translation Estimate 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Gibson, J. J. (1950). The perception of the visual world. Houghton Mifflin, Boston.Google Scholar
  2. [2]
    Hausen, K., Egelhaaf, M. (1989). Neural mechanisms of course control in insects. In: Stavenga, D. C., Hardie, R. C. (eds.), Facets of vision. Springer, Heidelberg, 391–424.Google Scholar
  3. [3]
    Krapp, H. G., Hengstenberg, B., & Hengstenberg, R. (1998). Dendritic structure and receptive field organization of optic low processing interneurons in the fly. J. of Neurophysiology, 79, 1902–1917.Google Scholar
  4. [4]
    Franz, M. O. & Krapp, H C. (2000). Wide-field, motion-sensitive neurons and matched filters for optic flow fields. Biol. Cybern., 83, 185–197.CrossRefGoogle Scholar
  5. [5]
    Koenderink, J. J., & van Doorn, A. J. (1987). Facts on optic flow. Biol. Cybern., 56, 247–254.CrossRefzbMATHGoogle Scholar
  6. [6]
    Chahl, J. S, & Srinivasan, M. V. (1997). Reflective surfaces for panoramic imaging. Applied Optics, 36(31), 8275–8285.CrossRefGoogle Scholar
  7. [7]
    Srinivasan, M. V. (1994). An image-interpolation technique for the computation of optic flow and egomotion. Biol. Cybern., 71, 401–415.CrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Matthias O. Franz
    • 1
  • Javaan S. Chahl
    • 2
  1. 1.MPI für biologische KybernetikTübingenGermany
  2. 2.Center of Visual Sciences RSBSAustralian National UniversityCanberraAustralia

Personalised recommendations