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ABSTRACT: In computer numerical control machine tools, using machining simulation to prevent collision becomes more and more popular
due to its efficiency and low cost. However, if the entire digital model of the machining setup does not exist, the simulation
is not applicable. As a result, the operator has to manually check the numerical control program, which is a time-consuming
and error-prone process. In this paper, an on-machine vision system is presented to quickly construct the digital model based
on the actual machining setup. The total construction for a complex setup can be done within a few minutes. Several key technologies
have been developed. First, a 2D edge feature detection algorithm has been designed which will extract the edges of the object
of interest by processing both the real and virtual images. Second, a stereo vision system is developed which will obtain
the three-dimensional (3D) edge data of the object of interest. A new algorithm is presented to solve correspondence, which
is the key problem of the stereovision system. Furthermore, the 3D object recognition algorithm is developed to let the system
intelligently search for the matched solid model in the database and import it into the virtual environment with an accurate
pose. Finally, experiments are carried out to test the developed system.
KeywordsMachining setup-Edge detection-Correspondence-Object recognition
International Journal of Advanced Manufacturing Technology 04/2012; 48(1):251-265. · 1.10 Impact Factor
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Computers in Industry. 01/2010; 61:711-726.
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Advances in Visual Computing, 4th International Symposium, ISVC 2008, Las Vegas, NV, USA, December 1-3, 2008. Proceedings, Part II; 01/2008
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Advances in Visual Computing, 4th International Symposium, ISVC 2008, Las Vegas, NV, USA, December 1-3, 2008. Proceedings, Part II; 01/2008
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ABSTRACT: In computerized numerical control (CNC) machine tools, it is often a time-consuming and error-prone process to verify the Euclidean position accordance between the actual machining setup and its designed three-dimensional (3D) digital model. The model mainly contains the work piece and jigs. The mismatch between them will cause a failure of simulation to precisely detect the collision. The paper presents an on-machine 3D vision system to quickly verify the similarity between the actual setup and its digital model by real and virtual image processing. In this paper, the system is proposed first. Afterwards, a simple on-machine camera calibration process is presented. This calibration process determines all the camera's parameters with respect to the machine tool's coordinate frame. The accurate camera mathematical model (or virtual camera) is derived according to the actual imaging projection. Both camera-captured real images and system-generated virtual images are compensated to make them theoretically and practically identical. The mathematical equations have been derived. Using the virtual image as a reference and then superimposing the real image onto it, the operator can intuitively verify the Euclidean position in accordance to the actual setup and its 3D digital model.
Robotics and Computer-Integrated Manufacturing 26(1):46-55. · 1.17 Impact Factor
