In view of the multi-disciplinary integration of intelligent manufacturing engineering, a robot sorting experiment system based on 3D vision are designed.The hardware experiment platform is built using Kinect camera, industrial robot, PC, and end-effector, while a Support Vector Machine (SVM) algorithm is designed to recognize target objects.Additionally, a method of cavity burr repair is proposed which combines median filter preprocessing with nearest neighbor interpolation.To check whether the target objects overlap or block each other, a strategy based on Hough transform is designed to calculate the object's center position and another strategy based on point cloud registration to estimate the object's pose.Then a series of robot sorting experiments are carried out under the guidance of upper computer interactive interface.The experiment results show that the system can accurately identify and stably sort the target objects of specific shape and color.The designed experiments involve knowledges and technologies related to robot, machine learning, image processing, software & hardware design, etc.In view of its strong comprehensiveness and openness, the proposed system can provide a comprehensive and innovative practice platform for intelligent manufacturing engineering laboratory.