Swarical, a Swarm-based hierarchical localization technique, enables miniature drones, known as Flying Light Specks (FLSs), to accurately and efficiently localize and illuminate complex 2D and 3D shapes. Its accuracy depends on the physical hardware (sensors) of FLSs, which are used to track neighboring FLSs in order to localize themselves. It uses the hardware specification to convert mesh files into point clouds that enable a swarm of FLSs to localize at the highest accuracy afforded by their hardware. Swarical considers a heterogeneous mix of FLSs with different orientations for their tracking sensors, ensuring a line of sight between a localizing FLS and its anchor FLS. We present an implementation using Raspberry cameras and ArUco markers. A comparison of Swarical with a state of the art decentralized localization technique shows that it is as accurate and more than 2x faster.

翻译：Swarical是一种基于群体智能的层级式定位技术，能够使被称为“飞行光斑”（FLS）的微型无人机精确高效地定位并照亮复杂的二维和三维形状。其精度依赖于FLS的物理硬件（传感器），这些传感器用于追踪相邻FLS以实现自身定位。该技术利用硬件规格将网格文件转换为点云，使FLS群体能够在其硬件允许的最高精度下完成定位。Swarical考虑了配备不同方向追踪传感器的异构FLS组合，确保定位中的FLS与其锚点FLS之间保持视线通畅。我们使用树莓派摄像头和ArUco标记实现了该系统。将Swarical与当前最先进的去中心化定位技术进行对比，结果表明两者精度相当，但Swarical的速度提升超过两倍。