用事件相机实现高速移动设备的实时光通信，抗干扰强且精度高。
Real-Time Optical Communication Using Event-Based Vision with Moving Transmitters
- 基于事件相机与几何感知无迹卡尔曼滤波，实现实时追踪与解码
- 运动中文字传输准确率超95%，处理速度比之前快7倍
- 适合高速移动机器人、无人机等对实时性要求高的场景
在多机器人系统中，传统射频通信易受竞争和干扰影响。光通信是有效替代方案，但传统帧式相机受限于帧率低、运动模糊以及高动态光照下的鲁棒性差。事件相机具备微秒级时间分辨率和高动态范围，对相对运动中的光学发射源变化极为敏感。我们构建了一套完整的光通信系统，可实时追踪移动发射源并解码信息。通过引入几何感知无迹卡尔曼滤波（GA-UKF），系统在传输频率≥1 kHz条件下，实现了超过95%的文本解码准确率，处理速度比先前最优方法快7倍，同时保持相当的跟踪精度。
原文摘要 · Abstract (English)
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.
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