In order to solve the problem of low target recognition accuracy, it is difficult to locate and grasp. Through the improvement of the algorithm, the object is identified and captured. It is divided into four aspects: the first recognition target object; the second three-dimensional reconstruction of the position of the target object centroid; the third attitude estimation for the target object; and the fourth for the hand-eye calibration. In the target recognition, the target is first extracted by the SURF algorithm combined with the Grabcut algorithm. In the position solving, the world coordinates of the centroid of the target object are obtained by template matching. In the attitude estimation, the flow of the algorithm is to use the matching point pair to obtain the slope of the object bus in the left picture, and then randomly take two points whose slope is equal to the slope of the left picture bus, and obtain the attitude of the target object through the world coordinates of the two points. In the grab, the eye used in the hand, first establish the workpiece coordinate system, then coordinate transformation, and obtain the inverse solution through the robot parameters. The results show that the error is in a small range and the robot can achieve the grab in the effective working range. The reliability of the algorithm and the correctness of the overall experiment can be seen.
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高智伟,谭晓东,刘客. 基于双目视觉的物体识别定位与抓取[J]. 科学技术与工程, 2020, 20(20): 8285-8291. GAO Zhi-wei, TAN Xiao-dong, Liu Ke. Object Recognition and Capture Based on Binocular Vision[J]. Science Technology and Engineering,2020,20(20):8285-8291.