用低成本摄像头和外置计算实现纳米无人机厘米级室内定位
Vision-based indoor localization of nano drones in controlled environment with its applications
- 外置单目相机+云端控制，通过三路PID调节实时修正飞行速度
- 实测定位误差仅3.1厘米，系统总成本仅50美元
- 适合教学实验、多机协同等对精度要求不苛刻的场景
在无GPS信号的环境中导航无人机是一项复杂挑战，尤其对体积小、负载轻、算力有限的纳米飞行器（NAVs）更为严峻。本文提出一种基于外置计算、外置单目摄像头及改进开源算法的定位方法。在外部计算机上运行三个并行的比例-积分-微分（PID）控制器，通过无线通信向NAVs发送速度校正指令，实现在定制化受控环境中的稳定飞行。系统实现3.1厘米定位误差，整体搭建成本仅为50美元，在成本敏感的应用中表现最优。验证应用包括将无人机精准降落于移动地面车辆、三维空间路径规划以及多台纳米无人机协同定位。相关代码已开源，地址为https://github.com/simmubhangu/eyantra_drone，旨在推动该领域研究。
原文摘要 · Abstract (English)
Navigating unmanned aerial vehicles in environments where GPS signals are unavailable poses a compelling and intricate challenge. This challenge is further heightened when dealing with Nano Aerial Vehicles (NAVs) due to their compact size, payload restrictions, and computational capabilities. This paper proposes an approach for localization using off-board computing, an off-board monocular camera, and modified open-source algorithms. The proposed method uses three parallel proportional-integral-derivative controllers on the off-board computer to provide velocity corrections via wireless communication, stabilizing the NAV in a custom-controlled environment. Featuring a 3.1cm localization error and a modest setup cost of 50 USD, this approach proves optimal for environments where cost considerations are paramount. It is especially well-suited for applications like teaching drone control in academic institutions, where the specified error margin is deemed acceptable. Various applications are designed to validate the proposed technique, such as landing the NAV on a moving ground vehicle, path planning in a 3D space, and localizing multi-NAVs. The created package is openly available at https://github.com/simmubhangu/eyantra_drone to foster research in this field.
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