• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.480-485
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• 2002

The purpose of this paper is the development of guidance algorithm for a mobile robot which is used to acquire the position and state information of the pipe defects such as crack, damage and through hole. The data used for the algorithm is the range data obtained by the range sensor which is based on an optical triangulation method. The sensor, which consists of a laser slit beam and a CCD camera, measures the 3D profile of the pipe's inner surface. After setting the range sensor on the robot, the robot is put into a pipe. While the camera and the LSB sensor part is rotated about the robot axis, a laser slit beam (LSB) is projected onto the inner surface of the pipe and a CCD camera captures the image. From the images the range data is obtained with respect to the sensor coordinate through a series of image processing and applying the sensor matrix. After the data is transformed into the robot coordinate, the position and orientation of the robot should be obtained in order to guide the robot. In addition, analyzing the data, 3D shape of the pipe is constructed and the numerical data for the defects of the pipe can be found. These data will be used for pipe maintenance and service.

• Journal of Mechanical Science and Technology
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• v.18 no.4
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• pp.640-648
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• 2004

This paper describes a new magnetization method for non-destructive testing with magneto-optical sensor (denoted as MO sensor) which have the following characteristic : high observation sensitivity, independence of the crack orientation, and precise imaging of a complex crack geometry such as multiple cracks. When a magnetic field is applied normally to the surface of a specimen which is significantly larger than its defects, approximately the same magnetic charge per unit area occurs on the surface of the specimen. If there is a crack in the specimen, magnetic charge per unit area has the same value at the bottom of the crack. The distribution of the vertical component of the magnetic flux density, B$\_$Z/, is almost uniform over the no-crack area (denoted as B$\_$Z,BASE/), while the magnetic flux density is smaller in the surroundings of the crack(denoted as B$\_$Z,CRACK/) If B$\_$Z, BASE/ is a bit larger than the saturated magnetic flux density of the MO sensor (B$\_$s/) , then small magnetic domains occur over the crack area and a large domain over the non-crack area because B$\_$Z,CRACK/ is smaller than B$\_$s/.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_1
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• pp.529-536
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• 2007

Registration between image and object space is a fundamental step in photogrammetry and computer vision. Along with rapid development of sensors - multi/hyper spectral sensor, laser scanning sensor, radar sensor etc., the needs for registration between different sensors are ever increasing. There are two important considerations on different sensor registration. They are sensor invariant feature extraction and correspondence between them. Since point to point correspondence does not exist in image and laser scanning data, it is necessary to have higher entities for extraction and correspondence. This leads to modify first, existing mathematical and geometrical model which was suitable for point measurement to line measurements, second, matching scheme. In this research, linear feature is selected for sensor invariant features and matching entity. Linear features are incorporated into mathematical equation in the form of extended collinearity equation for registration problem known as photo resection which calculates exterior orientation parameters. The other emphasis is on the scheme of finding matched entities in the aide of RANSAC (RANdom SAmple Consensus) in the absence of correspondences. To relieve computational load which is a common problem in sampling theorem, deterministic sampling technique and selecting 4 line features from 4 sectors are applied.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.1
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• pp.41-48
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• 2019

This paper deals with a method of aligning an aircraft fuselage and an inertial navigation sensor using three-dimensional coordinates obtained by an optical method. In order to verify the feasibility, we introduce the method to accurately align the coordinate system of the inertial navigation sensor and the aircraft reference coordinate system. It is verified through simulation that reflects the error level of the measuring device. In addition, optimization method based alignment algorithm is proposed for connection between optical sensor and inertial navigation sensor.

• Journal of Mechanical Science and Technology
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• v.17 no.10
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• pp.1431-1442
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• 2003

A new method of estimating the pose of a mobile-task robot is developed based upon an active calibration scheme. The utility of a mobile-task robot is widely recognized, which is formed by the serial connection of a mobile robot and a task robot. To be an efficient and precise mobile-task robot, the control uncertainties in the mobile robot should be resolved. Unless the mobile robot provides an accurate and stable base, the task robot cannot perform various tasks. For the control of the mobile robot, an absolute position sensor is necessary. However, on account of rolling and slippage of wheels on the ground, there does not exist any reliable position sensor for the mobile robot. This paper proposes an active calibration scheme to estimate the pose of a mobile robot that carries a task robot on the top. The active calibration scheme is to estimate a pose of the mobile robot using the relative position/orientation to a known object whose location, size, and shape are known a priori. For this calibration, a camera is attached on the top of the task robot to capture the images of the objects. These images are used to estimate the pose of the camera itself with respect to the known objects. Through the homogeneous transformation, the absolute position/orientation of the camera is calculated and propagated to get the pose of a mobile robot. Two types of objects are used here as samples of work-pieces: a polygonal and a cylindrical object. With these two samples, the proposed active calibration scheme is verified experimentally.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1403-1406
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• 1997

Generally, G.P.S(Global Positioning System) is using for the car navigation system but it has some restrictions such as the discontinuity of earth satellites and SA (Selective Availability). Recently, the hybrid navigation system combining with G.P.S and Dead-reckoning are much attractuve for improving the accuracy of a vehicle positioning. G.P.S called satellite navigation system, can measure its position by using satellites. Dead-Reckoning is the self-contained navigatioin system using a wheel sensor for the vehicle velocity and a gyro sensor for the vehicle angular velocity. Some algorithm could be generated for finding the vehicle position and orientation. In this paper, we developed a hybrid algotithm wiht G.P.S DR and Map-Matching.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2521-2524
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• 2003

Since inertial sensor errors which increase with time are caused by initial orientation error and sensor errors (accelerometer bias and gyro drift bias), the accuracy of these devices, while still improving, is not adequate for many of today's high-precision, long-duration sea, aircraft, and long-range missile missions. This paper presents a navigation error compensation scheme for Strap-Down Inertial Navigation System (SDINS) using Line-Of-Sight(LOS) vector from star sensor. To be specific, SDINS error model and measurement equation are derived, and Kalman filter is implemented. Simulation results show the bounded-ness of position and attitude errors.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.553-558
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• 2002

Physical sensor model in pushbroom satellite images can be made from sensor modeling by rotation parameters and attitude parameters on the satellite track. These parameters are determined by the information obtained from GPS, INS, or star tracker. Provided from satellite image, an auxiliary data error is connected directly with an error of rotation parameters and attitude parameters. This paper analyzed how obtaining satellite images influenced errors of rotation parameters and attitude parameters. furthermore, for detailed analysis, this paper generated simulated satellite image, which was changed variously by rotation parameters and attitude parameters of satellite sensor model. Simulated satellite image is generated by using high-resolution digital aerial image and DEM (Digital Elevation Model) data. Moreover, this paper determined correlation of rotation parameter and attitude parameters through error analysis of simulated satellite image that was generated by various rotation parameters and attitude parameters.

• The Journal of Korea Robotics Society
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• v.10 no.1
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• pp.16-23
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• 2015

This paper presents a method of improving the pose recognition accuracy of objects by using Kinect sensor. First, by using the SURF algorithm, which is one of the most widely used local features point algorithms, we modify inner parameters of the algorithm for efficient object recognition. The proposed method is adjusting the distance between the box filter, modifying Hessian matrix, and eliminating improper key points. In the second, the object orientation is estimated based on the homography. Finally the novel approach of Auto-scaling method is proposed to improve accuracy of object pose estimation. The proposed algorithm is experimentally tested with objects in the plane and its effectiveness is validated.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.888-893
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• 2005

Since inertial sensor errors which increase with time are caused by initial orientation error and sensor errors(accelerometer bias and gyro drift bias), the accuracy of these devices, while still improving, is not adequate for many of today's high-precision, long-duration sea, aircraft, and long-range flight missions. This paper presents a navigation error compensation scheme for Strap-Down Inertial Navigation System(SDINS) using star tracker. To be specific, SDINS error model and measurement equation are derived, and Kalman filter is implemented. Simulation results show the boundedness of position and attitude errors.