• 센서학회지
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• 제13권1호
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• pp.27-34
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• 2004

Camera calibration is an important and fundamental procedure for the application of a vision sensor to 3D problems. Recently many camera calibration methods have been proposed particularly in the area of robot vision. However, the reliability of data used in calibration has been seldomly considered in spite of its importance. In addition, a camera model can not guarantee good results consistently in various conditions. This paper proposes methods to overcome such uncertainty problems of data and camera models as we often encounter them in practical camera calibration steps. By the use of the RANSAC (Random Sample Consensus) algorithm, few data having excessive magnitudes of errors are excluded. Artificial neural networks combined in a two-step structure are trained to compensate for the result by a calibration method of a particular model in a given condition. The proposed methods are useful because they can be employed additionally to most existing camera calibration techniques if needed. We applied them to a linear camera calibration method and could get improved results.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 춘계학술대회 논문집
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• pp.179-183
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• 2002

This paper presents a new approach to the calibration of a SCARA robot orientation with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. radial distortion causes an inward or outward displacement of a given Image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 추계학술대회(한국공작기계학회)
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• pp.117-121
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• 2001

This paper presents a new approach to the calibration of a SCARA robot orientation with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.

• 한국CDE학회논문집
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• 제17권1호
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• pp.35-44
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• 2012

Many automobile manufacturers are doing experiment on manufacturing environments by using an augmented reality technology. However, system layout and process simulation by using the virtual reality technology have been performed actively more than by using the augmented reality technology in practical use so far. Existing automobile assembly by using the augmented reality requires the precise calibrating work after setting the robot because the existing augmented reality system for the automobile assembly system configuration does not include the end tip deflection and the robot joints deflection due to the heavy weight of product and gripper. Because the robot is used mostly at the automobile assembly, the deflection problem of the robot joint and the product in the existing augmented reality system need to be improved. Moreover camera lens calibration has to be performed precisely to use augmented reality. In order to improve this problem, this paper introduces a method of the software based calibration to apply the augmented reality effectively to the automobile assembly system. On the other hand, the camera lens calibration module and the direct compensation module of the virtual object displacement for the augmented reality were designed and implemented. Furthermore, the developed automobile assembly system oriented AR-system was verified by the practical test.

• 한국정밀공학회지
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• 제20권10호
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• pp.82-88
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• 2003

Many visual servoing algorithms have been recently developed by the robot vision researchers. They do not, however, consider the stability of servoing system. The camera calibration is the most important factor to the control stability and performance of position based visual servoing. In this article we describe the ECL(End Point Closed Loop) servoing can make no steady state error for the control of 6-DOF robot of which accuracy is dependent on the camera calibration and kinematics. And we propose a dynamic calibration algorithm, which can improve stability and performance of ECL visual servoing. To verify the potential of our approach, we run assembly experiments and present our finding.

• 대한기계학회논문집A
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• 제21권1호
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• pp.62-72
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• 1997

High flexibility and productivity using industrial robots are being achieved in manufacturing lines with off-line robot programmings. A good off-line programming system should have functions of robot modelling, trajectory planning, graphical teach-in, kinematic and dynamic simulations. Simulated results, however, can hardly be applied to on-line tasks until any calibration procedure is accompained. This paper proposes a visual calibration scheme in order to provide a calibration tool for our own off-line programming system of SCARA robots. The suggested scheme is based on the position-based visual servoings, and the perspective projection. The scheme requires only one camera as it uses saved kinematic data for three-dimensional visual calibration. Predicted images are generated and then compared with camera images for updating positions and orientations of objects. The scheme is simple and effective enough to be used in real time robot programming.

• 로봇학회논문지
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• 제15권4호
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• pp.350-356
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• 2020

Workers have been replaced by mobile manipulators for factory automation in recent years. One of the typical tasks for automation is that a mobile manipulator moves to a target location and picks and places an object on the worktable. However, due to the pose estimation error of the mobile platform, the robot cannot reach the exact target position, which prevents the manipulator from being able to accurately pick and place the object on the worktable. In this study, we developed an automatic alignment system using a low-cost camera mounted on the end-effector of a collaborative robot. Camera calibration and pose estimation methods were also proposed for the automatic alignment system. This algorithm uses a markerboard composed of markers to calibrate the camera and then precisely estimate the camera pose. Experimental results demonstrate that the mobile manipulator can perform successful pick and place tasks on various conditions.

• 센서학회지
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• 제14권4호
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• pp.278-285
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• 2005

This paper describes techniques of camera calibration and artificial landmarks detection for the automatic charging of a mobile robot, equipped with a fish-eye camera in the direction of its operation for movement or surveillance purposes. For its identification from the surrounding environments, three landmarks employed with infrared LEDs, were installed at the charging station. When the robot reaches a certain point, a signal is sent to the LEDs for activation, which allows the robot to easily detect the landmarks using its vision camera. To eliminate the effects of the outside light interference during the process, a difference image was generated by comparing the two images taken when the LEDs are on and off respectively. A fish-eye lens was used for the vision camera of the robot but the wide-angle lens resulted in a significant image distortion. The radial lens distortion was corrected after linear perspective projection transformation based on the pin-hole model. In the experiment, the designed system showed sensing accuracy of ${\pm}10$ mm in position and ${\pm}1^{\circ}$ in orientation at the distance of 550 mm.

• 제어로봇시스템학회논문지
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• 제13권3호
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• pp.224-229
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• 2007

This paper presents a camera calibration method using several images for three dimensional measurement applications such as stereo systems, mobile robots, and visual inspection systems in factories. Conventional calibration methods that use single image suffer from errors related to reference point extraction in image, lens distortion, and numerical analysis of nonlinear optimization. The camera parameter values obtained from images of same camera is not same even though we use same calibration method. The camera parameters that are obtained from several images of different view for a calibration target is usaully not same with large error values and we can not assume a special probabilistic distribution when we estimate the parameter values. In this paper, the median value of camera parameters from several images is used to improve estimation of the camera values in an iterative step with nonlinear optimization. The proposed method is proved by experiments using real images.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.44-47
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• 1997

Building a reliable mobile robot - one that can navigate without failures for long periods of time - requires that the uncertainty which results from control and sensing is bounded. This paper proposes a new mobile robot localization method using artificial landmarks. For a mobile robot localization, the proposed method uses a camera calibration(only extrinsic parameters). We use the FANUC arc mate to estimate the posture error, and the result shows that the position error is less than 1 cm and the orientation error less than 1 degrees.