Abstract
We describe a new experimental approach whereby an indoor flying robot evolves the ability to navigate in a textured room using only visual information and neuromorphic control. The architecture of a spiking neural circuit, which is connected to the vision system and to the motors, is genetically encoded and evolved on the physical robot without human intervention. The flying robot consists of a small wireless airship equipped with a linear camera and a set of sensors used to measure its performance. Evolved spiking circuits can manage to fly the robot around the room by exploiting a combination of visual features, robot morphology, and interaction dynamics.
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Zufferey, JC., Floreano, D., van Leeuwen, M., Merenda, T. (2002). Evolving Vision-Based Flying Robots. In: Bülthoff, H.H., Wallraven, C., Lee, SW., Poggio, T.A. (eds) Biologically Motivated Computer Vision. BMCV 2002. Lecture Notes in Computer Science, vol 2525. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36181-2_59
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DOI: https://doi.org/10.1007/3-540-36181-2_59
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