• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.758-765
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• 2001

This paper proposes a method to automatically extract stable visual landmarks from sensory data. Given a 2D occupancy map, a mobile robot first extracts vertical line features which are distinct and on vertical planar surfaces, because they are expected to be observed reliably from various viewpoints. Since the feature information such as position and length includes uncertainty due to errors of vision and motion, the robot then reduces the uncertainty by matching the planar surface containing the features to the map. As a result, the robot obtains modeled stable visual landmarks from extracted features. This extraction process is performed on-line to adapt to an actual changes of lighting and scene depending on the robot’s view. Experimental results in various real scenes show the validity of the proposed method.

• Journal of radiological science and technology
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• v.31 no.3
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• pp.287-292
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• 2008

Position information of radiation interactions in detection material is essential to reconstruct a radiation source image. With most position sensing techniques, the position information of a single interaction inside the detectors can be precisely obtained. Each interaction position of multi-scattering inside scintillators, however, can not be individually measured and only the average of the scattering positions can be obtained, which causes the uncertainty in the measured interaction position. In this paper, the position uncertainties due to the multi-scattering were calculated by Monte Carlo simulation. The simulation model was a 50 by 50 by 5 mm $LaCl_3$(Ce) scintillator(pixel size is 2 by 2 by 5mm) which was utilized for the dual collimation camera. The dual collimation camera uses the information from both photoelectric effect and Compton scattering, and therefore, position uncertainties for both partial and full energy deposition of radiation interactions are calculated. In the case of partial energy deposition(PED), the standard deviations of positions are less than $1{\sim}2mm$, which means the uncertainty caused by multi-scattering is not significant. Because the effect of the multi-scattering with PED is insignificant, the multi-scattering has little effect on the performance of Compton imaging of dual collimation camera. In the case of full energy deposition(FED), however, the standard deviation of the positions is about twice that of the pixel size of the 1stdetector, except for 122keV incident radiations. Therefore, the standard deviations caused by multi-scatterings should be considered in the design of the coded mask of the dual collimation camera to avoid artifact on the reconstructed image. The position uncertainties of the FEDs are much larger than those of the PEDs for all radiation energies and the ratio of PEDs to FEDs increases when the incident radiation energy increases. The position uncertainties of both PEDs and FEDs are dependent on the incident radiation energy.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.511-518
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• 2013

To implement an automatic picking system (APS) in distribution center with high precision and high dynamics, this paper presents a design of a linear induction motor (LIM) drive and robust position controller based on integral variable structure control (IVSC) scheme. The force disturbance as well as the mechanical parameter variation such as the mass and friction coefficient gives a direct influence on the position control performance of APS. To guarantee a robust control performance in the presence of such uncertainty, a robust position controller is designed. A Simulink library is developed for the LIM model from the state equation. Through this model and comparative simulation based on Matlab - Simulink, it is proved that the proposed scheme has a robust control nature and is most suitable for APS.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.24-30
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• 2016

The accuracy of small and low-cost CCD cameras is insufficient to provide data for precisely tracking unmanned aerial vehicles (UAVs). This study shows how a quad rotor UAV can hover on a human targeted tracking object by using data from a CCD camera rather than imprecise GPS data. To realize this, quadcopter UAVs need to recognize their position and posture in known environments as well as unknown environments. Moreover, it is necessary for their localization to occur naturally. It is desirable for UAVs to estimate their position by solving uncertainty for quadcopter UAV hovering, as this is one of the most important problems. In this paper, we describe a method for determining the altitude of a quadcopter UAV using image information of a moving object like a walking human. This method combines the observed position from GPS sensors and the estimated position from images captured by a fixed camera to localize a UAV. Using the a priori known path of a quadcopter UAV in the world coordinates and a perspective camera model, we derive the geometric constraint equations that represent the relation between image frame coordinates for a moving object and the estimated quadcopter UAV's altitude. Since the equations are based on the geometric constraint equation, measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the quadcopter UAV. The Kalman filter scheme is applied for this method. Its performance is verified by a computer simulation and experiments.

• 한국전산유체공학회:학술대회논문집
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• 2004.10a
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• pp.131-136
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• 2004

Thermal control of satellite propellant tank is achieved by patch heaters enabled by thermostat's behavior. It is important to attach the thermostat on the appropriate position of the propellant tank. However its position cannot be given with exact numerics because tank is spherical. Actually the position for thermostat is designated in relevant drawing approximately, therby, the engineer practices depending on his own experience and intuition. The sensitivity analysis for the position of thermostat is performed such that the influence on the thermal behavior and control of tank is examined quantatively. When assembling tank module, the reasonable performance on the thermal control is believed with possible human errors if the uncertainty in the position of thermostat is not quite large.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.9
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• pp.159-165
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• 1999

Based on the cable-extension transducers, a new technique for two dimensional position measurement is developed in this paper. This new technique includes the use of two such transducers and the planar position is determined through triangulation. This paper also presents uncertainty analysis results for establishing sensor design specifications. An actual prototyped sensor system is built and its accuracy is verified through h\both experiments with coordinate measurement machines and its application to the real-time control of a high load wheeled mobile robot. This new type of position sensor can be easily used in a wide variety of automation applications in industry for two dimensional position measurements with high accuracy over a relatively large range, and it is both cast effective and robust against hostile environments.

• Transactions of The Korea Fluid Power Systems Society
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• v.3 no.2
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• pp.14-20
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• 2006

A controller design procedure for an electro-hydraulic positioning systems has been developed using $H{\infty}$ control. The generalized plant models and weighting function for multiplicative uncertainty modelling error was presented along with $H{\infty}$ controller designs in order to investigate the robust stability and performance. Both disturbance rejection and command tracking performances were improved with the $H{\infty}$ controller, and the better uniformity of time response is achieved across wide range of operating conditions than the PID, LQR and LQG control scheme. The multiplicative uncertainty case was specifically suited for the design of an electro-hydraulic positioning control systems using $H{\infty}$ control.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1820-1823
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• 1997

For the Cartesian space position controlled robot, it is required to have the accurate mapping from the Cartesian space to the joint space in order to command the desired joint trajectories correctly. since the actual mapping from Cartesian space to joint space is obtained at the joint coordinate not at the actuator coordinate, uncertainty in Jacobian can be present. In this paper, two feasible neural network schemes are proposed to compensate for the kinematic Jacobian uncertainties. Uncertainties in Jacobian can be compensated by identifying either actuator Jacobian off-line or the inverse of that in on-line fashion. the case study of the stenciling robot is examined.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.2
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• pp.118-126
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• 2014

In this paper, a new method is proposed for the five-degree-of-freedom precision alignment and stitching of three-dimensional surface-profile data sets. The control parameters for correcting thealignment error are calculated from the surface profile data for overlapped areas among the adjacent measuring areas by using the "least squares method" and "maximum lag position of cross correlation function." To ensure the alignment and stitching reliability, the relationships betweenthe alignment uncertainty, overlapped area, and signal-to-noise level of the measured profile data are investigated. Based on the results of this uncertainty analysis, an appropriate size is proposed for the overlapped area according to the specimen's surface texture and noise level.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.4
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• pp.92-103
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• 1993

In this paper, we propose an adaptive classifier based on uncertainty of features for 3D planar object recognition. First, we investigate the uncertainty of depth information and the feature values of 3D planar object by numerical method. And, we observed that the statistical behavior of feature is dependent on the position and orientation of objects. After that, the approximation of the statistical behavior is executed. Subsequently, the recognition procedure is executed by the adaptive classifier. By computer simulation, we confirmed that the proposed classifier is useful for 3D planar object recognition.