Real-Time Optical Communication Using Event-Based Vision with Moving Transmitters

TL;DR

This paper presents a real-time optical communication system using event-based vision to track moving transmitters and decode messages with high accuracy, overcoming limitations of traditional cameras in dynamic environments.

Contribution

It introduces a novel system combining event cameras and a Geometry-Aware Unscented Kalman Filter for fast, accurate decoding of optical signals from moving transmitters.

Findings

Achieves over 95% decoding accuracy during motion

7x faster processing speed than previous methods

Maintains high tracking accuracy at ≥1 kHz transmission frequency

Abstract

In multi-robot systems, traditional radio frequency (RF) communication struggles with contention and jamming. Optical communication offers a strong alternative. However, conventional frame-based cameras suffer from limited frame rates, motion blur, and reduced robustness under high dynamic range lighting. Event cameras support microsecond temporal resolution and high dynamic range, making them extremely sensitive to scene changes under fast relative motion with an optical transmitter. Leveraging these strengths, we develop a complete optical communication system capable of tracking moving transmitters and decoding messages in real time. Our system achieves over $95\%$ decoding accuracy for text transmission during motion by implementing a Geometry-Aware Unscented Kalman Filter (GA-UKF), achieving 7x faster processing speed compared to the previous state-of-the-art method, while maintaining equivalent tracking accuracy at transmitting frequencies $\geq$ 1 kHz.