DocumentCode :
233689
Title :
Drogue recognition and location for UAV Autonomous Aerial Refueling based on camera calibration
Author :
Zhi Jianhui ; Dong Xinmin ; Kong Xingwei ; Wang Xufeng
Author_Institution :
Sch. of Aeronaut. & Astronaut. Eng., Air Force Eng. Univ., Xi´an, China
fYear :
2014
fDate :
28-30 July 2014
Firstpage :
624
Lastpage :
629
Abstract :
In order to improve the docking success rate in Autonomous Aerial Refueling(AAR), and reduce the calculation error of drogue position, the camera calibration method has been combined with MeanShift-KalmanFilter (MS-KF) algorithm in this paper to solve the problem of drogue recognition and location. Based on the pin-hole camera model, adaptive corner detection method was applied to pick up feature points in calibration board. Then, three camera calibration external factors had have been investigated by contrastive experiments. The conclusion of the above experiments was utilized to initialize camera calibration conditions. Finally, MS-KF algorithm was introduced in hardware-in-loop test for drogue recognition and location. The experimental results validate the effectiveness of the proposed algorithm.
Keywords :
Kalman filters; aerospace engineering; autonomous aerial vehicles; calibration; cameras; control engineering computing; edge detection; MS-KF algorithm; UAV autonomous aerial refueling; adaptive corner detection method; calibration board; camera calibration conditions; camera calibration method; docking success rate; drogue recognition; hardware-in-loop test; meanshift-Kalman filter algorithm; pin-hole camera model; Accuracy; Calibration; Cameras; Feature extraction; Light sources; Lighting; Machine vision; Autonomous Aerial Refueling; Calibration External Factors; Camera Calibration; Drogue Recognition and Location; Machine Vision;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2014 33rd Chinese
Conference_Location :
Nanjing
Type :
conf
DOI :
10.1109/ChiCC.2014.6896697
Filename :
6896697
Link To Document :
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