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.


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    Title :

    A Camera-Based Real-Time Parking Positioning Method for Air-Ground Vehicles


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Fu, Wenxing (editor) / Gu, Mancang (editor) / Niu, Yifeng (editor) / Wu, Lingyun (author) / Wang, Weida (author) / Yang, Chao (author) / Yue, Xing (author) / Xiang, Changle (author) / Li, Ying (author)

    Conference:

    International Conference on Autonomous Unmanned Systems ; 2022 ; Xi'an, China September 23, 2022 - September 25, 2022



    Publication date :

    2023-03-10


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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