Autonomous Aerial Refueling Systems Using Vision-Based Techniques
Summary
Autonomous aerial refuelling systems using vision-based techniques combine advanced computer vision, machine learning and control systems to enable unmanned and crewed aircraft to maintain continuous airborne operations. These systems typically employ cameras mounted on the receiver aircraft to detect, track and estimate the three-dimensional position and orientation of a tanker’s drogue or refuelling basket. Key phases include initial detection at distance, fine pose estimation for precise alignment, and continuous visual feedback during the final docking manoeuvre. Recent advances in lightweight deep neural networks, attention mechanisms and geometric modelling have substantially improved detection speed and accuracy, while dual-object pipelines and synthetic training datasets have addressed challenges in variable lighting and unstructured environments. The global significance of this research extends from military and commercial aviation to disaster relief and scientific monitoring, offering enhanced endurance and operational flexibility without reliance on ground infrastructure. Rigorous simulation and semi-physical experiments have demonstrated real-time performance at frame rates exceeding 40 fps and sub-decimetre positioning errors, marking an emerging maturity in autonomous aerial refuelling technology.
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Autonomous Aerial Refueling Systems Using Vision-Based Techniques publication trend
The graph below shows the total number of articles in autonomous aerial refueling systems using vision-based techniques across all publications each year (not limited to Nature Index journals).
Technical terms
Autonomous Aerial Refuelling (AAR): The process by which an aircraft receives fuel from a tanker mid-flight without human intervention.
Binocular Vision: A vision system employing two cameras to capture stereo images for depth perception and three-dimensional reconstruction.
Monocular Vision: A single-camera imaging approach that infers spatial information from shape, texture or motion cues.
Pose Estimation: The computation of an object’s position and orientation in three-dimensional space from image data.
Probe-and-Drogue System: A refuelling configuration in which a flexible hose (probe) from the receiver engages a drogue attached to the tanker to transfer fuel.
References
- Research of an Unmanned Aerial Vehicle Autonomous Aerial Refueling Docking Method Based on Binocular Vision. Drones (2023).
- Relative vectoring using dual object detection for autonomous aerial refueling. Neural Computing and Applications (2024).
- A Deep Neural Network Approach for Drogue Detection Using Laboratory-Chroma Key Images. IEEE Access (2024).
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