• Journal of the Korean Society for Precision Engineering
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• v.20 no.12
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• pp.73-79
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• 2003

Recently, the tole-robot operations to an unstructured environment have been widely researched. The human's interaction with the tole-robot system can be used to improve robot operation and performance for an unknown environment. The exact modeling based on real environment is fundamental and important process for this interaction. In this paper, we propose an extrinsic parameter calibration and data augmentation method that only uses a circular jig in the hand-eye laser virtual environment. Compared to other methods, easier estimation and overlay can be done by this algorithm. Experimental results using synthetic graphic demonstrate the usefulness of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1840-1843
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• 1997

The task environment of a robot is changing rapidly and task itself becomes complicated due to current industrial trends of multi-product and small lot size production. A convenient user-interfaced off-line programming(OLP) system is being developed in order to overcome the difficulty in teaching a robot task. Using the OLP system, operators can easily teach robot tasks off-line and verify feasibility of the task through simulation of a robot prior to the on-line execution. However, some task errors are inevitable by kinematic differences between the robot model in OLP and the actual robot. Three calibration methods using image information are proposed to compensate the kinematic differences. These methods compose of a relative position vector method, three point compensation method, and base line compensation method. To compensate a kinematic differences the vision system with one monochrome camera is used in the calibration experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.489-490
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• 2008

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.225-226
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• 2012

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.55-56
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• 2013

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.61-62
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• 2010

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.355-358
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• 1993

This paper introduces what calibration is and how it is operated. The steps of calibration methods are discussed, which are modeling, measurement, parameter identification and compensation. Using modified D-H model, a new algorithm for parameter identification is developed. This algorithm is very simple and applicable to off-line robot simulator.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.95-102
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• 2004

It is necessary to improve the exactness and adaptation of the working environment in the intelligent robot system. The vision sensor have been studied for this reason fur a long time. However, it is very difficult to perform the camera and robot calibrations because the three dimensional reconstruction and many processes are required for the real usages. This paper suggests the image based visual servoing to solve the problem of old calibration technique and supports OLP(Off-Line-Programming) path compensation. Virtual camera can be modeled from the real factors and virtual images obtained from virtual camera gives more easy perception process. Also, Initial path generated from OLP could be compensated by the pixel level acquired from the real and virtual, respectively. Consequently, the proposed visually assisted OLP teaching remove the calibration and reconstruction process in real working space. With a virtual simulation, the better performance is observed and the robot path error is calibrated by the image differences.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.372-374
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• 2009

In this research, an obstacle avoidance method is proposed. The common usage of a robot is indoor and the obstacles to the indoor robot is studied. The accurate detection of direction after overcoming the obstacles is necessary for performance of autonomous navigation and mission project. The sensors such as Laser, Ultrasound, PSD can be used to measure the obstacles. In this research, a PSD sensor is used to detect obstacles. It detects the height and width of obstacles located on the floor. Before measuring the obstacles, a calibration of the sensor was done and it produced a better accuracy. We have plotted an error graph using data obtained from the repeated experiments. The graph is fitted to a polynomial curve. The polynomial equation is used for the robot navigation. And in this research, a model of the error of the direction of the robot after overcoming obstacles was obtained also. The prototype of the obstacle and the error of the direction after overcoming the obstacles are modelled using a neural networks. The input of the neural network composed with the height of the obstacles, the speed of robot, the direction of wheels and the error of the direction. To implement the suggested algorithm, we set up a robot which is operated by a notebook computer. Experiment showed the suggested algorithm performed well.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.10
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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.