Abstract
To assess the responses of an identified optic-flow processing interneuron in the fly motion-vision pathway, the H1-cell, we performed semi-closed-loop experiments using a bio-hybrid two-wheeled robotic platform. We implemented a feedback-control architecture that established ‘wall following’ behaviour of the robot based on the H1-cell’s spike rate. The analysis of neuronal data suggests the spiking activity of the cell depends on both the momentary turning radius of the robot as well as the distance of the fly’s eyes from the walls of the experimental arena. A phenomenological model that takes into account the robot’s turning radius predicts spike rates that are in agreement with our experimental data. Consequently, measuring the turning radius using on-board sensors will enable us to extract distance information from H1-cell signals to further improve collision avoidance performance of our fly-robotic interface.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Fox, J.L., Frye, M.: Animal behavior: fly flight moves forward. Curr. Biol. 23, R278–R279 (2013)
Reiser, M.B., Dickinson, M.H.: Visual motion speed determines a behavioral switch from forward flight to expansion avoidance in Drosophila. J. Exp. Biol. 216, 719–732 (2013)
Krapp, H.G., Gabbiani, F.: Spatial distribution of inputs and local receptive field properties of a wide-field, looming sensitive neuron. J. Neurophysiol. 93, 2240–2253 (2005)
Wicklein, M., Strausfeld, N.J.: Organization and significance of neurons that detect change of visual depth in the hawk moth Manduca sexta. J. Comp. Neurol. 424, 356–376 (2000)
Blanchard, M., Rind, F.C., Verschure, P.F.M.J.: Collision avoidance using a model of the locust LGMD neuron. Robot. Auton. Syst. 30, 17–38 (2000)
Bertrand, O.J.N., Lindemann, J.P., Egelhaaf, M.: A bio-inspired collision avoidance model based on spatial information derived from motion detectors leads to common routes. PLoS Comput. Biol. 11, e1004339 (2015)
Kern, R., Boeddeker, N., Dittmar, L., Egelhaaf, M.: Blowfly flight characteristics are shaped by environmental features and controlled by optic flow information. J. Exp. Biol. 215, 2501–2514 (2012)
Hausen, K.: Functional characterization and anatomical identification of motion sensitive neurons in the lobula plate of the blowfly Calliphora erythrocephala. Z. Naturforsch. 31c, 629–633 (1976)
Krapp, H.G., Hengstenberg, R., Egelhaaf, M.: Binocular contributions to optic flow processing in the fly visual system. J. Neurophysiol. 85, 724–734 (2001)
Longden, K.D., Krapp, H.G.: Octopaminergic modulation of temporal frequency coding in an identified optic flow-processing interneuron. Front. Syst. Neurosci. 4, 153 (2010)
Maddess, T., Laughlin, S.B.: Adaptation of the motion-sensitive neuron H1 is generated locally and governed by contrast frequency. Proc. R. Soc. Lond. B Biol. Sci. 225, 251–275 (1985)
Lewen, G.D., Bialek, W., de Ruyter van Steveninck, R.R.: Neural coding of naturalistic motion stimuli. Netw. Bristol Engl. 12, 317–329 (2001)
Lindemann, J.P., Egelhaaf, M.: Texture dependence of motion sensing and free flight behavior in blowflies. Front. Behav. Neurosci. 6, 92 (2013)
Huang, J.V., Krapp, H.G.: Miniaturized electrophysiology platform for fly-robot interface to study multisensory integration. In: Lepora, N.F., Mura, A., Krapp, H.G., Verschure, P.F.M.J., Prescott, T.J. (eds.) Living Machines 2013. LNCS, vol. 8064, pp. 119–130. Springer, Heidelberg (2013)
Huang, J.V., Krapp, H.G.: A predictive model for closed-loop collision avoidance in a fly-robotic interface. In: Duff, A., Lepora, N.F., Mura, A., Prescott, T.J., Verschure, P.F.M.J. (eds.) Living Machines 2014. LNCS, vol. 8608, pp. 130–141. Springer, Heidelberg (2014)
Huang, J.V., Krapp, H.G.: Closed-loop control in an autonomous bio-hybrid robot system based on binocular neuronal input. In: Wilson, S.P., Verschure, P.F.M.J., Mura, A., Prescott, T.J. (eds.) Living Machines 2015. LNCS, vol. 9222, pp. 164–174. Springer, Heidelberg (2015)
Koenderink, J.J., van Doorn, A.J.: Facts on optic flow. Biol. Cybern. 56, 247–254 (1987)
Lindemann, J.P., Kern, R., van Hateren, J.H., Ritter, H., Egelhaaf, M.: On the computations analyzing natural optic flow: quantitative model analysis of the blowfly motion vision pathway. J. Neurosci. 25, 6435–6448 (2005)
Franceschini, N.: Pupil and pseudopupil in the compound eye of Drosophila. In: Wehner, R. (ed.) Information Processing in the Visual Systems of Anthropods, pp. 75–82. Springer, Heidelberg (1972)
Karmeier, K., Tabor, R., Egelhaaf, M., Krapp, H.G.: Early visual experience and the receptive-field organization of optic flow processing interneurons in the fly motion pathway. Vis. Neurosci. 18, 1–8 (2001)
Mauss, A.S., Pankova, K., Arenz, A., Nern, A., Rubin, G.M., Borst, A.: Neural circuit to integrate opposing motions in the visual field. Cell 162, 351–362 (2015)
Petrowitz, R., Dahmen, H., Egelhaaf, M., Krapp, H.G.: Arrangement of optical axes and spatial resolution in the compound eye of the female blowfly Calliphora. J. Comp. Physiol. 186, 737–746 (2000)
Acknowledgments
The authors would like to thank Caroline Golden for improving the proofreading the manuscript. This work was partially supported by US AFOSR/EOARD grant FA8655-09-1-3083 to HGK.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Huang, J.V., Wang, Y., Krapp, H.G. (2016). Wall Following in a Semi-closed-loop Fly-Robotic Interface. In: Lepora, N., Mura, A., Mangan, M., Verschure, P., Desmulliez, M., Prescott, T. (eds) Biomimetic and Biohybrid Systems. Living Machines 2016. Lecture Notes in Computer Science(), vol 9793. Springer, Cham. https://doi.org/10.1007/978-3-319-42417-0_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-42417-0_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-42416-3
Online ISBN: 978-3-319-42417-0
eBook Packages: Computer ScienceComputer Science (R0)