• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.621-634
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• 2008

This paper addresses the problem of testing whether the means in several inverse Gaussian populations with heterogeneity are equal. The analysis of reciprocals for the equality of inverse Gaussian means needs the assumption of equal scale parameters. We propose Bayesian model selection procedures for testing equality of the inverse Gaussian means under the noninformative prior without the assumption of equal scale parameters. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the objective Bayesian model selection procedures based on the fractional Bayes factor and the intrinsic Bayes factor under the reference prior. Simulation study and real data analysis are provided.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1093-1098
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• 2000

This paper presents an efficient algorithm for including the kinematic calibration data into the motion controller to improve the positioning accuracy of the manipulators. Rather than spending several iterations for finding the inverse solution of the calibrated kinematics, our approach requires only the nominal inverse solution and the calibrated forward kinematics for providing a better position command promptly. Thus, real-time application is guaranteed whenever the manipulators nominal inverse solution can be expressed in a closed form. Experimental results show that the line tracking performances can be remarkably improved by employing our algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.66-72
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• 1999

Robot calibration is very important to improve the accuracy of robot manipulators. However, the calibration procedure is very time consuming and laborious work for users. In this paper, we propose a method of relative error compensation to make the calibration procedure easier. The method is completed by a Pi-Sigma network architecture which has sufficient capability to approximate the relative relationship between the accuracy compensations and robot configurations while maintaining an efficient network learning ability. By experiment of 4-DOF SCARA robot, KIRO-3, it is shown that both the error of joint angles and the positioning error of end effector are drop to 15$\%$. These results are similar to those of other calibration methods, but the number of measurement is remarkably decreased by the suggested compensation method.

• Journal of the Korean Statistical Society
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• v.14 no.2
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• pp.63-75
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• 1985

This paper considers a statistical calibration problem in which the standard as wel as the nonstandard measurement is subject to error. Since the classicla approach cannot handle this situation properly, a functional relationship model with additional feature of prediction is proposed. For the analysis of the problem four different approaches-two estimation techniques (ordinary and grouping least squares) combined with two prediction methods (classical and inverse prediction)-are considered. By Monte Carlo simulation the perromance of each approach is assessed in term of the probability of concentration. The simulation results indicate that the ordinary least squares with inverse prediction is generally preferred in interpolation while the grouping least squares with classical prediction turns out to be better in extrapolation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1040-1044
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• 2005

This paper presents a method for the robot localization and calibration using the ultrasonic and the radio frequency. The distance between the receiver and a beacon can be computed by using the difference between times of flight. The presented method uses the gradient of the maximum amplitude of the ultrasonic in order to measure the time of flight precisely. The measured three distances between the receiver and the beacon are used to compute the robot position by the direct inverse method and the iterated least square approximation method. This paper is defined the calibration as the problem to find the location of 3 beacons and 3 robots, and presents 3 methods for it and found the 2B2R method as the best among them.

• Journal of the Korean Statistical Society
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• v.17 no.1
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• pp.9-23
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• 1988

The classicla theory of statistical calibration assumes that the standard measurement is exact. From a realistic point of view, however, this assumption needs to be relaxed so that more meaningful calibration procedures may be developed. This paper presents a model which explicitly considers errors in both standard and nonstandard measurements. Under the assumption that replicated observations are available in the calibration experiment, three estimation techniques (ordinary least squares, grouping least squares, and maximum likelihood estimation) combined with two prediction methods (direct and inverse prediction) are compared in terms of the asymptotic mean square error of prediction.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.2
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• pp.168-172
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• 2001

The accuracy problem of robot manipulators has long been one of the principal concerns in robot design and control. A practical and economical way of enhancing the manipulator accuracy, without affecting its hardware, is kinematic calibration. In this paper an effective and practical method is presented for kinematic calibration of Stewart platforms. In our method differential errors in kinematical parameters are linearly related to differential errors in the platform pose, expressed through the forward kinematics. The algorithm is tested using simulated measurement in which measurement noise is included.

• 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.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1476-1481
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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. 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 parallel 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. 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. Optimal postures showed the same trend of orienting themselves on the boundaries of the search space.

• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.995-1006
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• 2008

This article deals with the one-sided hypothesis testing problem in inverse Gaussian distribution. We propose Bayesian hypothesis testing procedures for the one-sided hypotheses of the shape parameter under the noninformative prior. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the objective Bayesian hypothesis testing procedures based on the fractional Bayes factor, the median intrinsic Bayes factor and the encompassing intrinsic Bayes factor under the reference prior. Simulation study and a real data example are provided.