Swarm sign language: motion-based communication between drones
It addresses the need for stealthy communication in swarm robotics, offering an alternative to radio transmissions that can be jammed.
This paper introduces motion-based visual communication for drones using planar trajectories as cues, achieving robust classification and segmentation of spatiotemporal sequences with a custom decoder trained via procedural generation.
In stealth-constrained swarm robotics, visual communication provides a critical alternative to active radio transmissions, which might be jammed. This research investigates motion-based communication for non-active information exchange, utilizing modular, dynamically feasible planar trajectories as visual cues. On the receiver drone end, a pose estimator tracks the transmitting drone's pose, feeding it into our custom 3DTrajDecoder. The decoder is designed to classify and segment the spatiotemporal sequence while simultaneously regressing its size and normal vector. To robustly train the decoder on both communicative and non-communicative trajectories, we developed a configurable online procedural generation pipeline. We validate our system through real-world testing and simulation to define its operating domain, supported by an extensive ablation study detailing our architectural choices and system limitations.