Abstract
Aiming at the problem that the accuracy of multi-part automatic assembly line sorting is not high, a set of machine vision-based recognition and positioning system is designed with KINECT as the RGB-D camera. The internal and external parameters of the RGB-D camera were calibrated using MATLAB; taking the automobile tire as the target part, because it is better for the system and more accurate, the feature invariant feature transformation (SIFT) algorithm is used to extract and match the feature points of the target part. The depth-based image obtains the spatial position parameters of the target part, thereby calculating the three-dimensional coordinates of the target part, and realizes the recognition and positioning functions of the system. The experimental results show that the visual positioning effectiveness is 96% in the unstructured indoor environment, and the system has good robustness and real-time performance.
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Liu, W., Li, F., Jing, C., Wan, Y., Su, B., & Helali, M. (2021). Recognition and location of typical automotive parts based on the RGB-D camera. Complex and Intelligent Systems, 7(4), 1759–1765. https://doi.org/10.1007/s40747-020-00182-z
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