Insect-Inspired Estimation of Self-Motion
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.
KeywordsMobile Robot Model Neuron Rotation Estimate Current Scene Translation Estimate
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- Gibson, J. J. (1950). The perception of the visual world. Houghton Mifflin, Boston.Google Scholar
- 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
- 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