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arXiv · 2303.07169

Dynamic Event-based Optical Identification and Communication

Axel von Arnim·Jules Lecomte·Naima Elosegui Borras·Stanislaw Wozniak·Angeliki Pantazi
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Abstract

Optical identification is often done with spatial or temporal visual pattern recognition and localization. Temporal pattern recognition, depending on the technology, involves a trade-off between communication frequency, range and accurate tracking. We propose a solution with light-emitting beacons that improves this trade-off by exploiting fast event-based cameras and, for tracking, sparse neuromorphic optical flow computed with spiking neurons. The system is embedded in a simulated drone and evaluated in an asset monitoring use case. It is robust to relative movements and enables simultaneous communication with, and tracking of, multiple moving beacons. Finally, in a hardware lab prototype, we demonstrate for the first time beacon tracking performed simultaneously with state-of-the-art frequency communication in the kHz range.

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Axel von Arnim, Jules Lecomte, Naima Elosegui Borras, Stanislaw Wozniak, Angeliki Pantazi. 2023-03-13. Dynamic Event-based Optical Identification and Communication. https://doi.org/10.3389/fnbot.2024.1290965

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