Paper
18 December 2023 Identification and location technology of refueling taper sleeve based on deep learning
Guoxing Hu, Haoguang Liu
Author Affiliations +
Proceedings Volume 12968, AOPC 2023: Optic Fiber Gyro ; 129681K (2023) https://doi.org/10.1117/12.3007578
Event: Applied Optics and Photonics China 2023 (AOPC2023), 2023, Beijing, China
Abstract
In the process of aerial refueling test flight and autonomous aerial refueling, it is necessary to measure the high-precision motion parameters of the Taper sleeve relative to the oil-receiving probe to provide data for the docking process. In this paper, aiming at the problems of intelligent identification and tracking of aerial refueling targets and high-precision stereo vision positioning, a multi-layer convolutional neural network with visual characteristics was constructed by deep learning theory, and the recognition results of Taper sleeve were corrected by using frame regression algorithm, so as to improve the Taper sleeve positioning accuracy from three dimensions: identification and tracking, optical calibration and measurement and solution. In this paper, combined with the test and flight verification, the solution accuracy is better than 0.09%, the identification success rate is better than 98%, and the Taper sleeve positioning accuracy is better than2cm+0.15%*L, which accords with the positioning accuracy of the refueling taper sleeve in the flight test.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Guoxing Hu and Haoguang Liu "Identification and location technology of refueling taper sleeve based on deep learning", Proc. SPIE 12968, AOPC 2023: Optic Fiber Gyro , 129681K (18 December 2023); https://doi.org/10.1117/12.3007578
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KEYWORDS
Deep learning

Education and training

Convolutional neural networks

Target recognition

Cameras

Convolution

Detection and tracking algorithms

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