Neuromorphic audio-visual sensor fusion on a sound-localizing robot.

Frontiers in Neuroscience
Vincent Yue-Sek ChanAndré van Schaik

Abstract

This paper presents the first robotic system featuring audio-visual (AV) sensor fusion with neuromorphic sensors. We combine a pair of silicon cochleae and a silicon retina on a robotic platform to allow the robot to learn sound localization through self motion and visual feedback, using an adaptive ITD-based sound localization algorithm. After training, the robot can localize sound sources (white or pink noise) in a reverberant environment with an RMS error of 4-5° in azimuth. We also investigate the AV source binding problem and an experiment is conducted to test the effectiveness of matching an audio event with a corresponding visual event based on their onset time. Despite the simplicity of this method and a large number of false visual events in the background, a correct match can be made 75% of the time during the experiment.

Citations

Nov 4, 2015·Frontiers in Neuroscience·Anja T ZaiShih-Chii Liu
Apr 12, 2016·Frontiers in Neuroscience·Anup VanarseAlexander Rassau
Mar 16, 2019·Applied Optics·Damien JoubertChristophe Lavergne
Jul 1, 2017·Frontiers in Neuroscience·Lorenzo VannucciCecilia Laschi
Jan 26, 2021·Frontiers in Neurorobotics·Andrea Cherubini, David Navarro-Alarcon
Jun 18, 2021·Frontiers in Neural Circuits·Mohammad-Hassan Tayarani-Najaran, Michael Schmuker

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BETA
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MATLAB

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