• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2737-2742
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• 2003

Kinematic calibration enhances absolute accuracy by compensating for the fabrication tolerances and installation errors. Effectiveness of calibration procedures depends greatly on the measurements performed. While the Cartesian postures are measured completely, all of the geometric parameters can be identified to their true values. With partial pose measurements, however, few geometric parameters may not be identifiable and effectiveness of the calibration results may vary significantly within the workspace. QR decomposition of the identification Jacobian matrix can reveal the non-identifiable parameters. Selecting postures for measurement is also an important issue for efficient calibration procedure. Typically, the condition number of the identification Jacobian is minimized to find optimum postures. This paper investigates identifiable parameters and optimum postures for four different calibration procedures - measuring postures completely with inverse kinematic residuals, measuring postures completely with forward kinematics residuals, measuring only the three position components, and restraining the mobility of the end-effector using a constraint link. The study is performed for a six degree-of-freedom fully parallel HexaSlide type paralle manipulator, HSM. Results verify that all parameters are identifiable with complete posture measurements. For the case of position measurements, one and for the case of constraint link, three parameters were found non-identifiable. Optimal postures showed the same trend of orienting themselves on the boundaries of the search space.

• ETRI Journal
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• v.38 no.3
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• pp.551-559
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• 2016

In this paper, we propose a hybrid sensor calibration scheme for mobile crowdsensing applications. As the number of newly produced mobile devices containing embedded sensors continues to rise, the potential to use mobile devices as a sensor data source increases. However, because mobile device sensors are generally of a lower performance and cost than dedicated sensors, sensor calibration is crucial. To enable more accurate measurements of natural phenomena through the use of mobile device sensors, we propose a hybrid sensor calibration scheme for such sensors; the scheme makes use of mobile device sensors and existing sensing infrastructure, such as weather stations, to obtain dense data. Simulation results show that the proposed scheme supports low mean square errors. As a practical application of our proposed scheme, we built a temperature map of a city using six mobile phone sensors and six reference sensors. Thanks to the mobility of the sensors and the proposed scheme, our map presents more detailed information than infrastructure-based measurements.

• Journal of Mechanical Science and Technology
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• v.17 no.1
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• pp.23-31
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• 2003

This paper introduces a constraint operator for the kinematic calibration of a parallel mechanism. By adopting the concept of a constraint operator, the movement between two poses is constrained. When the constrained movements are satisfied, the active joint displacements are taken and inputted into the kinematic model to compute the theoretical movements. A cost function is derived by the errors between the theoretical movement and the actual movement. The parameters that minimize the cost function are estimated and substituted into the kinematic model for a kinematic calibration. A single constraint plane is employed as a mechanical fixture to constrain the movement, and three digital indicators are used as the sensing devices to determine whether the constrained movement is satisfied. This calibration system represents an effective, low cost and feasible technique for a parallel mechanism. A calibration algorithm is developed with a constraint operator and implemented on a parallel manipulator constructed for a machining center tool.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.10
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• pp.569-574
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• 2003

Computer vision system is broadly adapted like as autonomous vehicle system, product line inspection, etc., because it has merits which can deal with environment flexibly. However, for applying it for that industry, it has to clear the problem that recognize position parameter of itself. So that computer vision system stands in need of camera calibration to solve that. Camera calibration consists of the intrinsic parameter which describe electrical and optical characteristics and the extrinsic parameter which express the pose and the position of camera. And these parameters have to be reorganized as the environment changes. In traditional methods, however, camera calibration was achieved at off-line condition so that estimation of parameters is in need again. In this paper, we propose a method to the calibration of camera using line correspondence in image sequence varied environment. This method complements the corresponding errors of the point corresponding method statistically by the extraction of line. The line corresponding method is strong by varying environment. Experimental results show that the error of parameter estimated is within 1% and those is effective.

• Journal of Korean Society on Water Environment
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• v.40 no.4
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• pp.179-194
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• 2024

Biophysicochemical processes in water environments and treatment systems have been great concerns of engineers and scientists for controlling the fate and transport of contaminants. These processes are practically formulated as mathematical models written in coupled differential equations. However, because these process-based mathematical models consist of a large number of model parameters, they are complicated in analytical or numerical computation. Users need to perform substantial trials and errors to achieve the best-fit simulation to measurements, relying on arbitrary selection of fitting parameters. Therefore, this study adopted a Bayesian calibration method to estimate best-fit model parameters in a systematic way and evaluated the applicability of the calibration method to biophysicochemical processes of water environments and treatment systems. The Bayesian calibration method was applied to the microbial growth-decay kinetics and flocculation kinetics, of which experimental data were obtained with batch kinetic experiments. The Bayesian calibration method was proven to be a reasonable, effective way for best-fit parameter estimation, demonstrating not only high-quality fitness, but also sensitivity of each parameter and correlation between different parameters. This state-of-the-art method will eventually help scientists and engineers to use complex process-based mathematical models consisting of various biophysicochemical processes.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.8-17
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• 2011

Recently, fusion camera systems that consist of depth sensors and color cameras have been widely developed with the advent of a new type of sensor, time-of-flight (TOF) depth sensor. The physical limitation of depth sensors usually generates low resolution images compared to corresponding color images. Therefore, the pre-processing module, such as camera calibration, three dimensional warping, and hole filling, is necessary to generate the high resolution depth map that is placed in the image plane of the color image. However, the result of the pre-processing step is usually inaccurate due to errors from the camera calibration and the depth measurement. Therefore, in this paper, we present a depth map upsampling method robust these errors. First, the confidence of the measured depth value is estimated by the interrelation between the color image and the pre-upsampled depth map. Then, the detailed depth map can be generated by the modified kernel regression method which exclude depth values having low confidence. Our proposed algorithm guarantees the high quality result in the presence of the camera calibration errors. Experimental comparison with other data fusion techniques shows the superiority of our proposed method.

• Journal of the Korean Society of Radiology
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• v.7 no.1
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• pp.93-98
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• 2013

The purpose of this study is to investigate the calibration of an optically stimulated luminescent nanoDot dosimeter(OSLnD) to 6 MV photon beam. Dose ranges of the calibration of linear and non-linear from the analysis of dose response of the OSLnD were decided. To evaluate the accuracy of calibration equation and the calibration, the sets of the calibration and quality control dosimeter were used to make. The calibrations were performed by the linear and the non-linear in the dose range of 0~300 cGy and 20~1300 cGy, respectively. The errors of the calibration were acquired less than 0.1% respectively from the measurement of the quality control dosimeters for the calibration of linear and the non-linear. This study provides the calibration equation of the OSLnD to the 6 MV photon beam.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.2 s.20
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• pp.87-95
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• 2002

Real-time Kinematic GPS enables high accuracy Positioning by real time. If ambiguity use an integer solution, can obtain accuracy of several 'mm', and can obtain accuracy of tens 'em' if use real solution. In this study, We accomplish surveying by existent traditional surveying techniques (Total Station), Static GPS techniques and RTK-GPS techniques by Field Calibration about uniformity measuring point and then compared and ana1yzed each techniques positioning accuracy etc.. Result that achieve by Static-GPS in Plane area, about all measuring points, expressed error fewer than 3cm. Result that achieve RTK-GPS Surveying by Field Calibration in Plane area, could know that RTK-GPS techniques by Field Calibration is available in Plane area because expressing errors fewer than all 6cm, except case that do not get fixed solution of ambiguity Field Calibration RTK-GPS could know economically than existent conventional type measurement and existent GPS's measurement techniques that efficiency is very high.

• Transactions of the Korean hydrogen and new energy society
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• v.19 no.1
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• pp.64-70
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• 2008

This paper briefly discusses the main sources of errors and their solutions for measuring hydrogen uptake from gas phase by the Sieverts technique. Correction of volumetric errors of apparatus, density of hydrogen storage material, estimation of temperature gradient are investigated. Systematic errors and the change of density of the host material according to the pressure have been the subject of much controversy in recent years. We considered the standard ball calibration, temperature gradient distribution, pretreatment of hydrogen storage materials to minimize errors. We could lessen the miscalculations after applying those methods to Equilibrium pressure-composition isotherm data.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.610-618
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• 2011

For improved localization around the indoor/outdoor transit area of buildings, this paper proposes an efficient algorithm combining the measurements from the WLAN (Wireless Local Area Network) and the GPS (Global Positioning System) for. The proposed hybrid localization algorithm considers both multipath errors and NLOS (Non-Line-of-Sight) errors, which occur in most wireless localization systems. To detect and isolate multipath errors occurring in GPS measurements, the propose algorithm utilizes conventional multipath test statistics. To convert WLAN signal strength measurements to range estimates in the presence of NLOS errors, a simple and effective calibration algorithm is designed to compute conversion parameters. By selecting and combining the reliable GPS and WLAN measurements, the proposed hybrid localization algorithm provides more accurate location estimates. An experiment result demonstrates the performance of the proposed algorithm.