Abstract
Here we propose a control design for a calibrated fly-brain-robotic interface. The interface uses the spiking activity of an identified visual interneuron in the fly brain, the H1-cell, to control the trajectory of a 2-wheeled robot such that it avoids collision with objects in the environment. Control signals will be based on a comparison between predicted responses – derived from the known robot dynamics and the H1-cell responses to visual motion in an isotropic distance distribution – and the actually observed spike rate measured during movements of the robot. The suggested design combines two fundamental concepts in biological sensorimotor control to extract task-specific information: active sensing and the use of efference copies (forward models). In future studies we will use the fly-robot interface to investigate multisensory integration.
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Huang, J.V., Krapp, H.G. (2014). 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) Biomimetic and Biohybrid Systems. Living Machines 2014. Lecture Notes in Computer Science(), vol 8608. Springer, Cham. https://doi.org/10.1007/978-3-319-09435-9_12
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DOI: https://doi.org/10.1007/978-3-319-09435-9_12
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