Air ducts are integral to modern buildings but are challenging to access for inspection. Small quadrotor drones offer a potential solution, as they can navigate both horizontal and vertical sections and smoothly fly over debris. However, hovering inside air ducts is problematic due to the airflow generated by the rotors, which recirculates inside the duct and destabilizes the drone, whereas hovering is a key feature for many inspection missions. In this article, we map the aerodynamic forces that affect a hovering drone in a duct using a robotic setup and a force/torque sensor. Based on the collected aerodynamic data, we identify a recommended position for stable flight, which corresponds to the bottom third for a circular duct. We then develop a neural network-based positioning system that leverages low-cost time-of-flight sensors. By combining these aerodynamic insights and the data-driven positioning system, we show that a small quadrotor drone (here, 180 mm) can hover and fly inside small air ducts, starting with a diameter of 350 mm. These results open a new and promising application domain for drones.

翻译：风道是现代建筑的重要组成部分，但难以进入进行检测。小型四旋翼无人机提供了一种潜在的解决方案，因为它们能够在水平和垂直段内航行，并能平稳飞越碎屑。然而，在风道内部悬停存在困难，这是由于旋翼产生的气流会在风道内再循环，导致无人机失稳，而悬停是许多检测任务的关键特性。在本文中，我们使用机器人装置和力/力矩传感器，绘制了影响风道内悬停无人机的空气动力。基于收集的空气动力学数据，我们确定了一个推荐用于稳定飞行的位置，对于圆形风道，该位置对应于底部三分之一区域。随后，我们开发了一种基于神经网络的定位系统，该系统利用了低成本飞行时间传感器。通过结合这些空气动力学见解和数据驱动的定位系统，我们证明小型四旋翼无人机（此处为180毫米）能够在小型风道内悬停和飞行，起始直径为350毫米。这些结果为无人机开辟了一个崭新且前景广阔的应用领域。