• Journal of the Korean Society for Precision Engineering
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• v.18 no.6
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• pp.87-92
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• 2001

An error analysis is very important for a precision machine to estimate its performances. This study proposes a new parallel device, cubic parallel manipulator. Errors of the proposed cubic parallel manipulator include upper and down universal joint errors, due to the directional changes in the forces in the links, and actuation errors. An error analysis is presented based on an error model formed through the relation between the universal joint errors of the cubic parallel manipulator and the end effector accuracy. The analysis shows that the method can be used in predicting the accuracy of other cubic parallel devices.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.929-934
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• 2004

As 3D scanner develops, it can be used in measurement. To accomplish complete 3D measurement, the scanner has to view different sides of the target. It can be done by moving the scanner and fix it at every measuring point. By human, it would take so much time. However, by using robot, measuring time can be reduced and the procedure can be automated. It is suitable for 6R serial manipulator to do this kind of work in which the scanner should go any position in arbitrary orientation. We did inverse kinematics analysis by analytical and graphical methods. Then, we compared two methods.

• Ocean Systems Engineering
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• v.1 no.3
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• pp.195-205
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• 2011

A method for calibrating a laser profiling system for seafloor micro-topography measurements is described. The system consists of a digital camera and an arrangement of six red lasers that are mounted as a unit on a remotely operated vehicle (ROV). The lasers project as parallel planes onto the seafloor, creating profiles of the local topography that are interpreted from the digital camera image. The goal of the calibration was to determine the plane equations for the six lasers relative to the camera. This was accomplished in two stages. First, distortions in the digital image were corrected using an interpolation method based on a virtual pinhole camera model. Then, the laser planes were determined according to their intersections with a calibration target. The position and orientation of the target were obtained by a registration process. The selection of the target shape and size was found to be critical to a successful calibration at sea, due to the limitations in the manoeuvrability of the ROV.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.131-136
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• 1999

This paper proposes the robot inverse calibration method using a neural networks. A highorder networks called Pi-Sigma networks has been used. The Pi-Sigma networks uses linear summing units in the hidden layer and product unit in output layer. The inverse calibration model which compensates the difference of joint variables only between measuring value and analytic value about the desired pose(position, orientation) of a robot is proposed. The compensated values are determined by using the weights obtained from the learning process of the neural networks previously. To prove the reasonableness, the SCARA type direct drive robot(4-DOF) and anthropomorphic robot(6-DOF) are simulated. It shows that the proposed calibration method can reduce the errors of the joint variables from $\pm$2$^{\circ}$to $\pm$ 0.1$^{\circ}$.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.154-158
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• 2002

This paper describes a path tracking method for vision-based and autonomous mobile robot in a corridor. At first, we extract the ceiling-lamp of the corridor through simple preprocessing (gray, thresholding, labeling, etc.) for robot position and orientation. Then, we design the controller for path-tracking. Simulations conducted, and acceptable vehicle localization results were obtained to prove the feasibility of the proposed approach.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.6
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• pp.78-89
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• 1996

Every mechanical component is fabricated with the variations in its size and shape, and the allowable range of the variation is specified by the tolerance in the design stage. Geometric tolerances specify the size or the thickness of each shape entity itself or its relative position and orientation with respect to datums. Since the range of shape variation can be represented by the variation of the coordinate system attached to the shape, the transformation matrix of the coordinate system would mathematically express the range of shape variation if the interval numbers are inserted for the elements of the transformation matrix. For the shape entity specified by the geometric tolerance with reference to datums, its range of variation can be also derived by propagating the transformation matrices composed of interval numbers. The propagation depends upon the order of precedence of datums.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.137-145
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• 2008

We present the initial results of on-going research for building a novel Mobile Haptic Interface (MHI) that can provide an unlimited haptic workspace in large immersive virtual environments. When a user explores a large virtual environment, the MHI can sense the position and orientation of the user, place itself to an appropriate configuration, and deliver force feedback, thereby enabling a virtually limitless workspace. Our MHI (PoMHI v0.5) features with omnidirectional mobility, a collision-free motion planning algorithm, and force feedback for general environment models. We also provide experimental results that show the fidelity of our mobile haptic interface.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.199-204
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• 1999

The robot inverse calibration method using a neural networks is proposed in this paper. A high-order networks has been used in this study. The Pi-Sigma networks uses linear summing units in the hidden layer and product unit in output layer. The inverse calibration model which compensates the difference of joint variables only between measuring value and analytic value about the desired pose(position orientation) of a robot is proposed. The compensated values are determined by using the weights obtained from the learning process of the neural networks previously. To prove the reasonableness, the selected compliance automatic robot arm type direct drive robot and anthropomorphic robot are simulated. It shows that the proposed calibration method can reduce the errors of the joint variables from ${\pm}$0.15$^{\circ}$to ${\pm}$0.12$^{\circ}$.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.12
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• pp.86-94
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• 1997

This paper proposes the robot inverse calibration method using a neural networks. A high-order networks called Pi-Sigma networks has been used. The Pi-Sigma networks uses linear summing units in the hidden layer and product unit in output layer. The inverse calibration model which compensates the diff- erence of joint variables only between measuring value and analytic value about the desired pose(position, orientation) of a robot is proposed. The compensated values are determined by using the weights obtained from the learning process of the neural networks previously. To prove the reasonableness, the SCARA type direct drive robot(4-DOF) and anthropomorphic robot(6-DOF) are simulated. It shows that the proposed calibration method can reduce the errors of the joint variables from .+-. 5 .deg. to .+-. 0.1 .deg. .

• Journal of the Korean Society for Precision Engineering
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• v.10 no.1
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• pp.52-61
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• 1993

Developed in this research is a CAM system for 5-axis NC Machining of sculptured surfaces. We identify problems in generating 5-axis NC data and propose methods of overcoming them. Issues discussed in this paper are: kinematic modelling of NC machines; determination of cutter position (location and orientation); check of machine work-range; linear trajectory plann- ing ; calculation of feedrate number. The proposed system has been implemented in FORTRAN77 on the Personal IRIS EWS, and it also constitutes a module of the CAD/CAM system 'CASSET' developed in KIST CAD/CAM lab.