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Measurement of Unmanned Aerial Vehicle Attitude Angles Based on a Single Captured Image.

Jin ZhangLijun RenHuaxia DengMengchao MaXiang ZhongPengcheng Wen
Published in: Sensors (Basel, Switzerland) (2018)
The limited load capacity and power resources of small-scale fixed-wing drones mean that it is difficult to employ internal high-precision inertial navigation devices to assist with the landing procedure. As an alternative, this paper proposes an attitude measurement system based on a monocular camera. The attitude angles are obtained from a single captured image containing five coded landmark points using the radial constraint method and three-dimensional coordinate transformations. The landing procedure is simulated for pitch angles from -15 ∘ to -40 ∘ , roll angles from -15 ∘ to +15 ∘ and yaw angles from -15 ∘ to +15 ∘ . For roll and pitch angles of approximately 0 ∘ and -25 ∘ , respectively, the accuracy of the method reaches 0.01 ∘ and 0.04 ∘ . This UAV attitude measurement system obtains an attitude angle by a single captured image, which has great potential for assisting with the landing of small-scale fixed-wing UAVs.
Keyphrases
  • deep learning
  • minimally invasive
  • magnetic resonance imaging
  • computed tomography
  • machine learning
  • image quality
  • mass spectrometry
  • dual energy