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Autonomous Aerial Refueling Ground Test Demonstration--A Sensor-in-the-Loop, Non-Tracking Method.

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This study introduces a novel autonomous aerial refueling (AAR) method for unmanned aerial vehicles (UAVs). It uses 3D LIDAR and computer vision to accurately guide refueling, enhancing flight endurance.

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3D Flash LIDARUAVautonomous aerial refuelingcomputer visionmarkerlessprobe and drogue

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Area of Science:

  • Robotics and Autonomous Systems
  • Computer Vision
  • Aerospace Engineering

Background:

  • Extending unmanned aerial vehicle (UAV) flight duration is crucial for mission effectiveness.
  • Traditional 2D imaging poses challenges in accurately reconstructing 3D spatial information for autonomous operations.

Purpose of the Study:

  • To develop a sensor-in-the-loop, non-tracking method for probe-and-drogue autonomous aerial refueling (AAR).
  • To overcome 3D reconstruction ambiguities using 3D point cloud data from a 3D Flash LIDAR camera.

Main Methods:

  • Integration of sensitivity-adjusted 3D Flash LIDAR with computer vision techniques.
  • Application of curve fitting and Random Sample Consensus (RANSAC) for drogue center estimation and relative positioning.
  • Development of a ground navigation robot for real-system feasibility demonstration.

Main Results:

  • The proposed method reliably estimates the drogue center in 3D space.
  • The ground robot successfully tracked a simulated drogue using real-time visual feedback.
  • Autonomous navigation demonstrated continuous gap reduction between the robot and the target drogue.

Conclusions:

  • The 3D LIDAR and computer vision approach enables robust autonomous aerial refueling.
  • This method enhances UAV capabilities for extended airborne missions.
  • Feasibility is confirmed through real-world system implementation and testing.