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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2603.19477 |
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| _version_ | 1866912975343845376 |
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| author | Dhillon, Harmeet Katyal, Pranay Long, Brendan Walia, Rohan Cleaveland, Matthew Leahy, Kevin |
| author_facet | Dhillon, Harmeet Katyal, Pranay Long, Brendan Walia, Rohan Cleaveland, Matthew Leahy, Kevin |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_19477 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Real-Time Optical Communication Using Event-Based Vision with Moving Transmitters Dhillon, Harmeet Katyal, Pranay Long, Brendan Walia, Rohan Cleaveland, Matthew Leahy, Kevin Robotics 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. |
| title | Real-Time Optical Communication Using Event-Based Vision with Moving Transmitters |
| topic | Robotics |
| url | https://arxiv.org/abs/2603.19477 |