| This paper based on Motoman up6 robot researches and structures a classification-and-grab system on the basis of machine vision. The system is made up of camera, image acquisition card, computer, robot and software. The system controls the robot to achieve picking and choosing in the way that the robot getting image of the object by the camera, analyzing the image with software, getting the coordinate and classification data of the object, then track the targets.At first, the paper studies the camera calibration, then implements the Direct Linear Transform algorithm on Matlab, and provides an easy solution to transform word coordinates into robot coordinates. Then, the paper studies several target detection algorithm principles, concentrates on and implements the target detection based on background subtraction and gray image thresholding. At the aspect of target recognition, this paper design and train the classifier by using the linear discriminant function according to the object's feature such as area and perimeter. At the aspect of vision track, this paper studies global nearest neighbor algorithm and multi-hypothesis tracking algorithm, implements the GNN algorithm and kalman filter in the c++ programming language and finally achieves the target track on conveyor. Finally, the paper researches the PC-based motion control of Motoman robot on the basis of Motocon32, so that the classification-and-grab programme can control robots grab the workpiece on contiguous moving conveyor in real time. In the process of research, some limitation of Motocom32 has been found, and the solution is proposed also.Through several experiments and tests, the author accomplishes the research and structure of a primary industrial robot classification-and-grab system. On-line experiments prove the research results of this paper that is this system as a link of industrial automation has practical significance in applications and reference value in theory. |
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