Current Issue : October - December Volume : 2017 Issue Number : 4 Articles : 5 Articles
For better welding quality, accurate path teaching for actuators must be achieved before\nwelding. Due to machining errors, assembly errors, deformations, etc., the actual groove position may\nbe different from the predetermined path. Therefore, it is significant to recognize the actual groove\nposition using machine vision methods and perform an accurate path teaching process. However,\nduring the teaching process of a narrow butt joint, the existing machine vision methods may fail\nbecause of poor adaptability, low resolution, and lack of 3D information. This paper proposes\na 3D path teaching method for narrow butt joint welding. This method obtains two kinds of visual\ninformation nearly at the same time, namely 2D pixel coordinates of the groove in uniform lighting\ncondition and 3D point cloud data of the workpiece surface in cross-line laser lighting condition.\nThe 3D position and pose between the welding torch and groove can be calculated after information\nfusion. The image resolution can reach 12.5 �¼m. Experiments are carried out at an actuator speed of\n2300 mm/min and groove width of less than 0.1 mm. The results show that this method is suitable\nfor groove recognition before narrow butt joint welding and can be applied in path teaching fields of\n3D complex components....
In order to grab and place the sealing rings of battery lid quickly and accurately, an automatic assembling system for sealing rings\nbased on machine vision is developed in this paper. The whole system is composed of the light sources, cameras, industrial control\nunits, and a 4-degree-of-freedom industrial robot. Specifically, the sealing rings are recognized and located automatically with the\nmachine vision module. Then industrial robot is controlled for grabbing the sealing rings dynamically under the joint work of\nmultiple control units and visual feedback. Furthermore, the coordinates of the fast-moving battery lid are tracked by the machine\nvision module. Finally the sealing rings are placed on the sealing ports of battery lid accurately and automatically. Experimental\nresults demonstrate that the proposed system can grab the sealing rings and place them on the sealing port of the fast-moving\nbattery lid successfully.More importantly, the proposed system can improve the efficiency of the battery production line obviously....
Recovering depth information of objects from two-dimensional images is one of the very\nimportant and basic problems in the field of computer vision. In view of the shortcomings of\nexisting methods of depth estimation, a novel approach based on SIFT (the Scale Invariant Feature\nTransform) is presented in this paper. The approach can estimate the depths of objects in two images\nwhich are captured by an un-calibrated ordinary monocular camera. In this approach, above all,\nthe first image is captured. All of the camera parameters remain unchanged, and the second image\nis acquired after moving the camera a distance d along the optical axis. Then image segmentation\nand SIFT feature extraction are implemented on the two images separately, and objects in the images\nare matched. Lastly, an object�s depth can be computed by the lengths of a pair of straight line\nsegments. In order to ensure that the most appropriate pair of straight line segments are chosen,\nand also reduce computation, convex hull theory and knowledge of triangle similarity are employed.\nThe experimental results show our approach is effective and practical....
Camera distortion is a critical factor affecting the accuracy of camera calibration.\nA conventional calibration approach cannot satisfy the requirement of a measurement system\ndemanding high calibration accuracy due to the inaccurate distortion compensation. This paper\npresents a novel camera calibration method with an iterative distortion compensation algorithm.\nThe initial parameters of the camera are calibrated by full-field camera pixels and the corresponding\npoints on a phase target. An iterative algorithm is proposed to compensate for the distortion. A 2D\nfitting and interpolation method is also developed to enhance the accuracy of the phase target.\nCompared to the conventional calibration method, the proposed method does not rely on a distortion\nmathematical model, and is stable and effective in terms of complex distortion conditions. Both the\nsimulation work and experimental results show that the proposed calibration method is more than\n100% more accurate than the conventional calibration method....
Laser stripe center extraction is a key step for the profile measurement of line structured\nlight sensors (LSLS). To accurately obtain the center coordinates at sub-pixel level, an improved\ngray-gravity method (IGGM) was proposed. Firstly, the center points of the stripe were computed\nusing the gray-gravity method (GGM) for all columns of the image. By fitting these points using the\nmoving least squares algorithm, the tangential vector, the normal vector and the radius of curvature\ncan be robustly obtained. One rectangular region could be defined around each of the center points.\nIts two sides that are parallel to the tangential vector could alter their lengths according to the\nradius of the curvature. After that, the coordinate for each center point was recalculated within the\nrectangular region and in the direction of the normal vector. The center uncertainty was also analyzed\nbased on the Monte Carlo method. The obtained experimental results indicate that the IGGM is\nsuitable for both the smooth stripes and the ones with sharp corners. The high accuracy center points\ncan be obtained at a relatively low computation cost. The measured results of the stairs and the screw\nsurface further demonstrate the effectiveness of the method....
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