Lightweight aerial swarms have potential applications in scenarios where larger drones fail to operate efficiently. The primary foundation for lightweight aerial swarms is efficient relative localization, which enables cooperation and collision avoidance. Computing the real-time position is challenging due to extreme resource constraints. This paper presents an autonomous relative localization technique for lightweight aerial swarms without infrastructure by fusing ultra-wideband wireless distance measurements and the shared state information (e.g., velocity, yaw rate, height) from neighbors. This is the first fully autonomous, tiny, fast, and accurate relative localization scheme implemented on a team of 13 lightweight (33 grams) and resource-constrained (168MHz MCU with 192 KB memory) aerial vehicles. The proposed resource-constrained swarm ranging protocol is scalable, and a surprising theoretical result is discovered: the unobservability poses no issues because the state drift leads to control actions that make the state observable again. By experiment, less than 0.2m position error is achieved at the frequency of 16Hz for as many as 13 drones. The code is open-sourced, and the proposed technique is relevant not only for tiny drones but can be readily applied to many other resource-restricted robots. Video and code can be found at \textnormal{\url{https://shushuai3.github.io/autonomous-swarm/}}.

翻译：轻量级空中集群在大型无人机无法高效运行的场景中具有潜在应用价值。其核心基础在于高效的相对定位技术，以实现协同作业与碰撞规避。由于极端资源限制，实时位置计算面临严峻挑战。本文提出一种无需基础设施的轻量级空中集群自主相对定位技术，通过融合超宽带无线距离测量值与邻机共享状态信息（如速度、偏航率、高度）。该方案首次在由13架轻量化（33克）且资源受限（168MHz MCU处理器，192KB内存）的飞行器组成的集群中实现了完全自主、微型化、快速且精确的相对定位。所提出的资源受限集群测距协议具备良好可扩展性，并揭示了一个重要的理论发现：不可观测性不会构成系统性问题，因为状态漂移会引发控制动作，从而使系统状态重新恢复可观测性。实验表明，在16Hz更新频率下，多达13架无人机的位置误差可控制在0.2米以内。本研究成果已开源，所提技术不仅适用于微型无人机，也可直接应用于其他多种资源受限的机器人系统。演示视频与代码可通过以下链接获取：\textnormal{\url{https://shushuai3.github.io/autonomous-swarm/}}。