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

2026-03-19

AI Summary

This work proposes a real-time optical communication system for multi-robot networks that overcomes the limitations of conventional RF communication—susceptibility to interference—and frame-based optical methods, which suffer from low frame rates, motion blur, and insufficient dynamic range under high-speed motion. By leveraging the microsecond temporal resolution and high dynamic range of event cameras, the system integrates high-frequency optical signal modulation/demodulation with a geometry-aware unscented Kalman filter (GA-UKF) to enable precise tracking and decoding of fast-moving optical transmitters. Experimental results demonstrate a text decoding accuracy exceeding 95% at transmission frequencies of 1 kHz or higher, with a processing speed seven times faster than the current state-of-the-art, thereby significantly advancing reliable optical communication in high-speed scenarios.

Technology Category

• Computer Vision: Motion & Tracking
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

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.

Problem

• optical communication
• event-based vision
• moving transmitters
• multi-robot systems
• real-time decoding

Innovation

• event-based vision
• optical communication
• moving transmitters
• Geometry-Aware Unscented Kalman Filter
• real-time decoding