Dynamic visual monitoring method for railway shunting
A shunting and dynamic technology, applied in the field of visual recognition, can solve the problems of the influence of the locomotive docking accuracy, low ranging accuracy, and lack of precision, and achieve the effects of accurate locomotive positioning, enlarged detection angle, and less lack of precision.
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Embodiment 1
[0039] The invention provides a dynamic visual monitoring method for railway shunting, which is characterized in that: its specific operation method is:
[0040] Step 1: Use the Zhang Zhengyou calibration method to complete the calibration of the monocular camera:
[0041] A calibration plate with a square of 52mm and a length and width of 9×6 is selected, and the images of the calibration plate at different positions are calibrated using the calibrator application in the Matlab software, and the calibration results of 4 basic magnifications are obtained. Finally, the internal parameter matrix such as the focal length and optical axis offset of the monocular camera is obtained;
[0042] Step 2: Installation and calibration of millimeter wave radar:
[0043] Use a small-sized level ruler to calibrate the pitch angle and roll angle of the millimeter-wave radar to be horizontal. When yaw angle is calibrated, use the angle ruler to determine that the inverse coordinate of the met...
Embodiment 2
[0067] The present invention mainly realizes the distance measurement problem of the locomotive during the docking process of the train through the fusion of two millimeter-wave radars, a monocular vision camera and a laser range finder. The present invention utilizes the fusion of multiple sensors to play each Each sensor has its own detection advantages, and finally realizes accurate identification and distance measurement of the front of the vehicle.
[0068] (1) The millimeter-wave radar is mainly responsible for the medium and long-distance measurement tasks of the target. The purpose of setting up two millimeter-wave radars is to increase the accuracy of the measurement results and the robustness of the fault diagnosis.
[0069] (2) The monocular vision camera is mainly responsible for the recognition and detection task of the docking locomotive, using the deep learning algorithm and the track detection algorithm of the station to comprehensively obtain the image informat...
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