Real-Time Optical Communication Using Event-Based Vision with Moving Transmitters
This addresses communication challenges in multi-robot systems by providing a robust alternative to RF, though it appears incremental as it builds on event camera technology with specific improvements.
The paper tackles the problem of optical communication in multi-robot systems by developing a system using event-based vision to track moving transmitters and decode messages in real time, achieving over 95% decoding accuracy for text transmission during motion and 7x faster processing speed compared to the previous state-of-the-art method.
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.