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Description
Industrial robots are increasingly used in various fields of industrial production. At present, the working mode of most industrial robots is fixed and single, and when the working environment or target position changes, industrial robots cannot accurately grasp and need to be repositioned. In order to improve the autonomy and intelligence of its work, machine vision is gradually applied to combine with robot technology to give robots the ability to perceive the environment.With the increase of industrial demand, rapid and accurate recognition and positioning of objects with arbitrary posture in complex space environment has become a new research direction.To solve this problem, this paper studies hand-eye calibration and pose recognition in 3D vision system detection based on depth camera, and realizes industrial robots to grasp objects based on pose results of vision system. In order to solve the complex problem of mapping between camera coordinate system and industrial robot coordinate system, a robot calibration method is proposed, which can quickly and accurately obtain the transformation matrix between image coordinate system, camera coordinate system and robot coordinate system. The process of camera calibration and the model of the imaging system are analyzed in detail, and then the image processing algorithms used in the process of target location such as image segmentation, target classification, image matching, corner detection, target location and tracking are tested.
