Real-time drogue recognition and 3D locating for UAV autonomous aerial refueling based on monocular machine vision

Drogue recognition and 3D locating is a key problem during the docking phase of the autonomous aerial refueling (AAR). To solve this problem, a novel and effective method based on monocular vision is presented in this paper. Firstly, by employing computer vision with red-ring-shape feature, a drogue detection and recognition algorithm is proposed to guarantee safety and ensure the robustness to the drogue diversity and the changes in environmental conditions, without using a set of infrared light emitting diodes (LEDs) on the parachute part of the drogue. Secondly, considering camera lens distortion, a monocular vision measurement algorithm for drogue 3D locating is designed to ensure the accuracy and real-time performance of the system, with the drogue attitude provided. Finally, experiments are conducted to demonstrate the effectiveness of the proposed method. Experimental results show the performances of the entire system in contrast with other methods, which validates that the proposed method can recognize and locate the drogue three dimensionally, rapidly and precisely.