| Author: | Li, Xinwen |
| Title: | Monocular vision based precise positioning system for UAV aerial refueling |
| Degree: | M.Sc. |
| Year: | 2014 |
| Subject: | Aerodynamics. Drone aircraft Hong Kong Polytechnic University -- Dissertations |
| Department: | Faculty of Construction and Environment |
| Pages: | xi, 95 pages : illustrations (some color) ; 30 cm |
| Language: | English |
| Abstract: | A simplified monocular vision based positioning device for UAV aerial refueling has been developed in this dissertation. The monocular vision based positioning device is made by one camera and one laptop. By using the camera and no other sensors, the monocular vision based positioning device can provide the real-time relative coordinates of target in camera coordinate system and distance between the camera and the center of refueling pipe nozzle. The camera is set as monocular vision system to capture the images. Each frame of images are used by the positioning device to determine the distance and coordinates. The major steps of data processing of positioning is achieved by Canny Edge Detection algorithm followed by Circle Hough Transform algorithm. After literature review, Canny Edge Detection was selected as the edge detection algorithm and Coherent CHT algorithm was selected as the circle detection algorithm for the monocular vision based positioning device. The field tests of the monocular vision based positioning device are made to test the positioning performances of the device. Experiments results show that the integrity of the device developed in this dissertation is about 70%, and the error generated by the device is about 3.25% of its real distance in the direction of flying, 8.17% in the horizontal direction and 4.04% in vertical direction in the camera coordinate system. Some discussion of potential error sources and improvement are also made. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b27591219.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 4.28 MB | Adobe PDF | View/Open |
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