Measurement system of large-scale high reflective component based on binocular vision
Keywords:
Binocular vision, Convolutional neural networkAbstract
A measurement system based on binocular vision and industrial robots was proposed to meet in-situ high-efficiency and high-precision measurement of large-scale high reflective components. Through target detection, the system could accurately segment the region of interest where the marking points were located, effectively reduce the false extraction caused by high reflective surface, and improve the robustness and measurement efficiency of binocular vision measurement system. At the same time, through controlling the movement of the robot end effectors, the measurement of the whole component in multi-position was completed, and then the measurement results of different positions were unified in the same coordinate system through the coordinate transformation relationship in multi-position. The experimental results show that in the range of 1.2 m × 1 m, the root-mean-square (RMS) of vision measurement precision can reach to 0.049 mm in nine positions. The whole measurement system can effectively complete the high-efficiency and high-precision measurement of the simulated cabin components. Copyright ©2021 Journal of Applied Optics. All rights reserved.
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