Neuromorphic object localization using resistive memories and ultrasonic transducers

Moro, Filippo; Hardy, Emmanuel; Fain, Bruno; Dalgaty, Thomas; Clémençon, Paul; De Prà, Alessio; Esmanhotto, Eduardo; Castellani, Niccolò; Blard, François; Gardien, François; Mesquida, Thomas; Rummens, François; Esseni, David; Casas, Jérôme; Indiveri, Giacomo; Payvand, Melika; Vianello, Elisa

doi:10.1038/s41467-022-31157-y

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Moro, F., Hardy, E., Fain, B., Dalgaty, T., Clémençon, P., De Prà, A., Esmanhotto, E., Castellani, N., Blard, F., Gardien, F., Mesquida, T., Rummens, F., Esseni, D., Casas, J., Indiveri, G., Payvand, M., & Vianello, E. (2022). Neuromorphic object localization using resistive memories and ultrasonic transducers. Nature Communications, 13(1), 3506. https://doi.org/10.1038/s41467-022-31157-y

Abstract

Real-world sensory-processing applications require compact, low-latency, and low-power computing systems. Enabled by their in-memory event-driven computing abilities, hybrid memristive-Complementary Metal-Oxide Semiconductor neuromorphic architectures provide an ideal hardware substrate for such tasks. To demonstrate the full potential of such systems, we propose and experimentally demonstrate an end-to-end sensory processing solution for a real-world object localization application. Drawing inspiration from the barn owl’s neuroanatom