群体手语：基于运动的无人机间通信
Swarm sign language: motion-based communication between drones
AI总结：
针对隐身约束下的群体机器人，提出利用模块化平面轨迹作为视觉信号进行运动通信，设计3DTrajDecoder解码器实现轨迹分类与分割，并通过在线程序生成管道训练，经真实测试与仿真验证系统有效性。
摘要：
在隐身约束的群体机器人中，视觉通信为可能被干扰的主动无线电传输提供了关键替代方案。本研究探索基于运动的非主动信息交换通信，利用模块化的、动态可行的平面轨迹作为视觉线索。在接收无人机端，位姿估计器跟踪发射无人机的位姿，并将其输入我们定制的3DTrajDecoder。该解码器旨在分类和分割时空序列，同时回归其大小和法向量。为了在通信和非通信轨迹上鲁棒地训练解码器，我们开发了一个可配置的在线程序生成管道。我们通过真实世界测试和仿真来验证系统，以定义其操作域，并辅以详尽的消融研究，详细说明我们的架构选择和系统局限性。
英文摘要：
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.
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