• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2008.11a
• /
• pp.9-10
• /
• 2008

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.10
• /
• pp.98-103
• /
• 1997

Given the small bit allocation for motion information in very low bit-rate coding, motion estimation using the block matching algorithm(BMA) fails to maintain an acceptable level of prediction errors. The reson is that the motion model, or spatial transformation, assumed in block matching cannot approximate the motion in the real world precisely with a small number of parameters. In order to overcome the drawback of the conventional block matching algorithm, several triangle-based methods which utilize triangular patches insead of blocks have been proposed. To estimate the motions of image sequences, these methods usually have been based on the combination of optical flow equation, affine transform, and iteration. But the compuataional cost of these methods is expensive. This paper presents a fast motion estimation algorithm using a multiple linear regression model to solve the defects of the BMA and the triange-based methods. After describing the basic 2-D triangle-based method, the details of the proposed multiple linear regression model are presented along with the motion estimation results from one standard video sequence, representative of MPEG-4 class A data. The simulationresuls show that in the proposed method, the average PSNR is improved about 1.24 dB in comparison with the BMA method, and the computational cost is reduced about 25% in comparison with the 2-D triangle-based method.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.10a
• /
• pp.425-428
• /
• 1997

Effectiveness of corrective machining algorithm is verified experimentally in this paper by performing corrective lapping work to single side and double sides hydrostatic tables. Lapping is applied as machining method. Machining information is calculated from measured motion errors by applying the algorithm, without information on rail profile. It is possible to acquire 0.13pm of linear motion error, 1.40arcsec of angular motion error in the case of single side table, and 0.07pm of linear motion error, 1.42arcsec of angular motion error in the case of double sides table. The experiment is performed by the unskilled person after he experienced a little of preliminary machining. Experimental results show that corrective machining algorithm is very effective, and anyone can improve the accuracy of hydrostatic table by using the algorithm.

• Journal of the Korean Society for Precision Engineering
• /
• v.30 no.6
• /
• pp.607-614
• /
• 2013

In this study, effect of the sensor gain error is theoretically analyzed and simulated when mixed sequential two-prove method(MTPM) is applied for the precision measurement of straightness error of a linear motion table. According to the theoretical analysis, difference of the gain errors between two displacement sensors increases measurement error dramatically and alignment error of the straightedge is also amplified by the sensor gain difference. On the other hand, if the gain errors of the two sensors are identical, most of error terms are cancelled out and the alignment error doesn't give any influence on the measurement error. Also the measurement error of the straightness error is minimized compared with that of the straightedge's form error owing to close relationship between straightness error and angular motion error of the table in the error terms.

• Journal of KSNVE
• /
• v.6 no.5
• /
• pp.567-574
• /
• 1996

This paper concerns an articulated space robot with flexible links. The equations of its motion are derived by means of the Lagrangian mechanics. Assuming that magnitude of elastic motions are relatively small, the perturbation approach is taken to separate the original equations of motion into linear and nonlinear equations. Th effect the desired payload motion, open loop control inputs are first determined based on the nonlinear equations. One the other hand, in order to reduce the positional errors during the maneuver, vibration suppression is actively done with a feedforward control for disturbance cancellation to some extent. Additionally, for performance robustness against residual disturbance, an LQ control modified to have a prescribed degree of stability is applied based on the linear equations. Measurement equations are formulated to be used for the maximum likelihood estimator to reconstruct states from the original robot equations of motion. Finally, numerical simulations show effectiveness of the proposed control design scheme.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.177.3-177
• /
• 2001

In this paper, the design of the in-motion alignment system of Strapdown Inertial Navigation System(SDINS) using Robust Extended Kalman Filter(REKF) is presented. The compensation of errors in the aided navigation system is accomplished by the indirect feedback filtering. The performance of the aided navigation algorithm is very sensitive to the accuracy of the initial estimate, which is the characteristic of the EKF. Unfortunately, the initial attitude error can be very large during the in-motion alignment. To overcome the in-motion alignment under large initial attitude error problem, the REKF using linear robust filtering technique is proposed. The linear robust H$_2$ filter can be adopted for nonlinear ...

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.10
• /
• pp.33-39
• /
• 2019

In this paper, we propose a parametric model for analyzing the motion information obtained from the acceleration sensors to measure the activity of the human body. The motion of the upper body and the lower body does not occur at the same time, and the motion analysis method using a single motion sensor involves a lot of errors. In this study, the 3-axis accelerometer is attached to the arms and legs, the body's activity data are measured, the momentum of the arms and legs are calculated for each channel, and the linear predictive coefficient is obtained for each channel. The periodicity of the upper body and the lower body is determined by analyzing the correlation between the channels. The linear predictive coefficient and the periodic value are used as data to measure the type of exercise and the amount of exercise. In the proposed method, we measured four types of movements such as walking, stair climbing, slow hill climbing, and fast hill descending. In order to verify the usefulness of the parameters, the recognition results are presented using the linear predictive coefficient and the periodic value for each motion as the neural network input.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.4
• /
• pp.456-465
• /
• 2006

The problem of recursive filtering far linear discrete-time systems with uncertainties is considered. A new suboptimal filtering algorithm is herein proposed. It is based on the fusion formula, which represents an optimal mean-square linear combination of local Kalman estimates with weights depending on cross-covariances between local filtering errors. In contrast to the optimal weights, the suboptimal weights do not depend on current measurements, and thus the proposed algorithm can easily be implemented in real-time. High accuracy and efficiency of the suboptimal filtering algorithm are demonstrated on the following examples: damper harmonic oscillator motion and vehicle motion constrained to a plane.

• Journal of Mechanical Science and Technology
• /
• v.17 no.4
• /
• pp.538-544
• /
• 2003

Although many methodologies exist for determining the constrained equations of motion, most of these methods depend on numerical approaches such as the Lagrange multiplier's method expressed in differential/algebraic systems. In 1992, Udwadia and Kalaba proposed explicit equations of motion for constrained systems based on Gauss's principle and elementary linear algebra without any multipliers or complicated intermediate processes. The generalized inverse method was the first work to present explicit equations of motion for constrained systems. However, numerical integration results of the equation of motion gradually veer away from the constraint equations with time. Thus, an objective of this study is to provide a numerical integration scheme, which modifies the generalized inverse method to reduce the errors. The modified equations of motion for constrained systems include the position constraints of index 3 systems and their first derivatives with respect to time in addition to their second derivatives with respect to time. The effectiveness of the proposed method is illustrated by numerical examples.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1438-1441
• /
• 2005

To establish of standard technique of nano-length measurement in 2D plane, new AFM system has been designed. In this system, measurement uncertainty is dominantly affected by the Abbe error of XY scanning stage. No linear stage is perfectly straight; in other words, every scanning stage is subject to tilting, pitch and yaw motion. In this paper, an AFM system with minimum offset of XY sensing is designed. And XY scanning stage is designed to minimize rotation angle because Abbe errors occur through the multiply of offset and rotation angle. To minimize the rotation angle optimal design has performed by maximizing the stiffness ratio of motion direction to the parasitic motion direction of each stage. This paper describes the design scheme of full AFM system, especially about XY stage. Full range of fabricated XY scanner is $100um\times{100um}$. And tilting, pitch and yaw motion are measured by autocollimator to evaluate the performance of XY stage. Using this AFM system, 3um pitch specimen was measured. As a result, the uncertainty of total system has been evaluated.