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Neuronal Distance Estimation by a Fly-Robot Interface

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Biomimetic and Biohybrid Systems (Living Machines 2017)

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Abstract

The ability of an autonomous robot to avoid collisions depends on distance estimates. In this paper, we focus on open-loop responses of the identified directional-selective H1-cell in the fly brain, recorded in animals that are mounted on a 2-wheeled robot. During oscillatory forward movement along a wall clad with a pattern of vertical stripes on one side of the robot, the H1-cell periodically increases and decreases its spike rate, where the response amplitude depends on two parameters: (i) the turning radius of the robot, and (ii) the distance between the wall and the mean forward trajectory of the robot. For small turning radii, we found a monotonic relationship between the H1-cell’s spike rate and wall distance. Our results suggest that, given a known turning radius, the responses of the H1-cell could be used in a negative feedback-loop to control the average forward trajectory of an autonomous robot that avoids collisions with potential obstacles in its environment.

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Acknowledgments

The authors would like to thank Naomi Ho for calibrating the robot firmware, Dr. Caroline Golden for improving the proofreading the manuscript. This work was partially supported by US AFOSR/EOARD grant FA8655-09-1-3083 to HGK.

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Correspondence to Jiaqi V. Huang .

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Huang, J.V., Krapp, H.G. (2017). Neuronal Distance Estimation by a Fly-Robot Interface. In: Mangan, M., Cutkosky, M., Mura, A., Verschure, P., Prescott, T., Lepora, N. (eds) Biomimetic and Biohybrid Systems. Living Machines 2017. Lecture Notes in Computer Science(), vol 10384. Springer, Cham. https://doi.org/10.1007/978-3-319-63537-8_18

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  • DOI: https://doi.org/10.1007/978-3-319-63537-8_18

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