Abstract
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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© 2023 Beijing HIWING Sci. and Tech. Info Inst
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Wu, L., Wang, W., Yang, C., Yue, X., Xiang, C., Li, Y. (2023). A Camera-Based Real-Time Parking Positioning Method for Air-Ground Vehicles. In: Fu, W., Gu, M., Niu, Y. (eds) Proceedings of 2022 International Conference on Autonomous Unmanned Systems (ICAUS 2022). ICAUS 2022. Lecture Notes in Electrical Engineering, vol 1010. Springer, Singapore. https://doi.org/10.1007/978-981-99-0479-2_96
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DOI: https://doi.org/10.1007/978-981-99-0479-2_96
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