Scholarlink

<p>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. 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 is not the center of 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 how to improve the stability of a small quadrotor drone (here, 180 mm) inside small air ducts (down to 350 mm diameter) and fly autonomously over 2 m.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Flying in air ducts

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月13日

查看全文
  • Thomas Martin,
  • Adrien Guénard,
  • Vladislav Tempez,
  • Lucien Renaud,
  • Thibaut Raharijaona,
  • Franck Ruffier,
  • Jean-Baptiste Mouret

摘要

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. 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 is not the center of 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 how to improve the stability of a small quadrotor drone (here, 180 mm) inside small air ducts (down to 350 mm diameter) and fly autonomously over 2 m.