PoseFly: On-site Pose Parsing of Swarming Drones via 4-in-1 Optical Camera Communication

Drones are gaining more interest from the industry and the research community as a result of their many advantages, including low cost, small size, adaptability, and ease of use, as well as their potential applications. However, current control of swarming drones relies on stand-alone modes and centralized radio frequency control from a base station on the ground which is devoid of drone-to-drone communication. This method has drawbacks, including a crowded RF spectrum with mutual interference, high latency, and a lack of on-site drone-to-drone interactions. Because of its high spatial multiplexing capability, Line of Sight (LoS) security capabilities, broader bandwidth, and intuitive vision manner, Optical Camera Communication (OCC) is considered to be a potential alternative for sensing and communication in drone clusters. In this paper, we first utilize the rolling shutter effect in drone sensing and communication and propose PoseFly, a 4-in-1 AI-assisted OCC with drone identification, on-site localization, quick-link communication and lighting. We implement PoseFly prototypes on commercial drones, cameras and LEDs. Our experiments show our PoseFly achieves nearly 100% accuracy for distance estimation (20m), drone identification (12m), angle and speed estimation (4m) and 5 Kbps average quick-link throughput at up to 4 m on current prototypes.