Air-ground vehicles expand the road from ground to low altitude, which can effectively improve the traffic efficiency. However, there is still a lack of research on real-time accurate autonomous parking technology for its multi-modules docking stage. We propose a camera-based real-time recognition and localization framework. Firstly, the camera internal and external reference calibration is conducted to derive the real-world coordinate from image pixels. Then, the image feature extraction is adopted to detect representative features of ArUco markers. Finally, an optimization-based edge refinement method is proposed to achieve the accurate localization of the contours of ArUco markers. Our method achieves an average computational speed of 5.23 ms/frame and a maximum localization error of 3.47 mm for the detection in video sequences under various working conditions.
A Camera-Based Real-Time Parking Positioning Method for Air-Ground Vehicles
Lect. Notes Electrical Eng.
International Conference on Autonomous Unmanned Systems ; 2022 ; Xi'an, China September 23, 2022 - September 25, 2022
Proceedings of 2022 International Conference on Autonomous Unmanned Systems (ICAUS 2022) ; Kapitel : 96 ; 1062-1071
10.03.2023
10 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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