arXiv:2410.08379cs.ROcs.NE2024-10被引 8

小无人机可在350mm直径风管中稳定悬停,突破检修难题。

Flying in air ducts

  • 通过传感器实测风管内气流扰动,定位稳定悬停区
  • 在圆形风管底部三分之一处实现可靠悬停
  • 用低成本传感器+神经网络,适配小型巡检无人机

现代建筑中的风管难以人工进入检测。小型四旋翼无人机可穿越水平与垂直风管并越过障碍物,但其悬停功能受旋翼气流在风管内回流影响而失稳。本文通过机器人平台和力/力矩传感器,测绘了风管内悬停无人机的气动特性。结果显示,在圆形风管中,底部三分之一区域为稳定飞行推荐位置。据此开发基于神经网络的定位系统,利用低成本时间飞行传感器实现精准定位。实验表明,尺寸为180 mm的小型无人机可在直径不小于350 mm的风管中稳定悬停与飞行。该成果为无人机在风管内部检测开辟了新路径。

原文摘要 · Abstract (English)

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.

无人机风管检测气动分析神经网络

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