• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.1026-1032
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• 2003

A biped walking robot which is developed as a platform for researching walking algorithm is briefly introduced. The developed walking robot has 6 degrees of freedom per one leg. The origins of the last three axis do not intersect at a point, so the kinematic analysis is cubmersome with the conventional method. In the former version of the robot, Jacobian-based inverse kinematics method is used. However, the Jacobian-based inverse kinematics method has drawbacks for the application in which knee is fully extended such as stair-case walking. The reason far that is the Jacobian becomes ill-conditioned near the singular points and the method is not able to give adequate solutions. So, a method for giving a closed-form inverse kinematics solution is proposed. The proposed method is based on careful consideration of the kinematic structure of the biped walking robot.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.525-533
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• 2008

This study presents a pansharpening method, so called FitPAN, to synthesize multispectral images at a higher resolution by exploiting a high-resolution image acquired in panchromatic modality. FitPAN is a modified version of the quadratic programming approach proposed in (Lee, 2008), which is designed to generate synthesized multispectral images similar to the multispectral images that would have been observed by the corresponding sensor at the same high resolution. The proposed scheme aims at reconstructing the multispectral images at the higher resolution with as less spectral distortion as possible. This study also proposes a sharpening process to eliminate some distortions appeared in the fused image of the higher resolution. It employs the Point-Jacobian MAP iteration utilizing the contextual information of the original panchromatic image. In this study, the new method was applied to the IKONOS 1m panchromatic and 4m multispectral data, and the results were compared with them of several current approaches. Experimental results demonstrate that the proposed scheme can achieve significant improvement in both spectral and block distortion.

• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.455-464
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• 2009

Lee(2009) proposed the boundary-adaptive despeckling method using a Bayesian model which is based on the lognormal distribution for image intensity and a Markov random field(MRF) for image texture. This method employs the Point-Jacobian iteration to obtain a maximum a posteriori(MAP) estimate of despeckled imagery. The boundary-adaptive algorithm is designed to use less information from more distant neighbors as the pixel is closer to boundary. It can reduce the possibility to involve the pixel values of adjacent region with different characteristics. The boundary-adaptive scheme was comprehensively evaluated using simulation data and the effectiveness of boundary adaption was proved in Lee(2009). This study, as an extension of Lee(2009), has suggested a modified iteration algorithm of MAP estimation to enhance computational efficiency and to combine classification. The experiment of simulation data shows that the boundary-adaption results in yielding clear boundary as well as reducing error in classification. The boundary-adaptive scheme has also been applied to high resolution Terra-SAR data acquired from the west coast of Youngjong-do, and the results imply that it can improve analytical accuracy in SAR application.

• Bulletin of the Korean Mathematical Society
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• v.51 no.5
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• pp.1503-1510
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• 2014

The aim of this work is to construct a general family of two dimensional differential systems which admits homoclinic solutions near a non-hyperbolic fixed point, such that a Jacobian matrix at this point is zero. We then discretize it by using Euler's method and look after the persistence of the homoclinic solutions in the obtained discrete system.

• Journal of Advanced Navigation Technology
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• v.10 no.2
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• pp.113-120
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• 2006

In this paper, a vision-based robust controller for tracking the desired trajectory a robot manipulator is proposed. The trajectory is generated to move the feature point into the desired position which the robot follows to reach to the desired position. To compensate the parametric uncertainties of the robot manipulator which contain in the control input, the robust controller is proposed. In addition, if there are uncertainties in the Jacobian, to compensate it, a vision-based robust controller which has control input is proposed as well in this paper. The stability of the closed-loop system is shown by Lyapunov method. The performance of the proposed method is demonstrated by simulations and experiments on a two degree of freedom 5-link robot manipulators.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.229-232
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• 2005

In this paper, an image-based "approach-align -grasp" visual servo control design is proposed for the problem of object grasping, which is based on the binocular stand-alone system. The basic idea consists of considering a vision system as a specific sensor dedicated a task and included in a control servo loop, and we perform automatic grasping follows the classical approach of splitting the task into preparation and execution stages. During the execution stage, once the image-based control modeling is established, the control task can be performed automatically. The proposed visual servoing control scheme ensures the convergence of the image-features to desired trajectories by using the Jacobian matrix, which is proved by the Lyapunov stability theory. And we also stress the importance of projective invariant object/gripper alignment. The alignment between two solids in 3-D projective space can be represented with view-invariant, more precisely; it can be easily mapped into an image set-point without any knowledge about the camera parameters. The main feature of this method is that the accuracy associated with the task to be performed is not affected by discrepancies between the Euclidean setups at preparation and at task execution stages. Then according to the projective alignment, the set point can be computed. The robot gripper will move to the desired position with the image-based control law. In this paper we adopt a constant Jacobian online. Such method describe herein integrate vision system, robotics and automatic control to achieve its goal, it overcomes disadvantages of discrepancies between the different Euclidean setups and proposes control law in binocular-stand vision case. The experimental simulation shows that such image-based approach is effective in performing the precise alignment between the robot end-effector and the object.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.894-896
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• 1997

This paper presents the continuation power flow system that is under development. The continuation power flow system provides robust solutions of power flow equations at any operating point. The robust convergency enables one to find solutions even at the point where power flow jacobian becomes singular. Basic concept of an algorithm and its application to static voltage stability analysis are presented.

• Honam Mathematical Journal
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• v.45 no.4
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• pp.648-654
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• 2023

Schwarz lemma at the non-smooth boundary point for holomorphic self-map on the intersection of two balls in ℂ² is obtained. At the complex tangent point in the corner of the boundary of the domain, the tangential eigenvalue of the complex Jacobian of the holomorphic map is estimated if the map is transversal.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.295-309
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• 2009

In this study, an iterative maximum a posteriori (MAP) approach using a Bayesian model of Markovrandom field (MRF) was proposed for despeckling images that contains speckle. Image process is assumed to combine the random fields associated with the observed intensity process and the image texture process respectively. The objective measure for determining the optimal restoration of this "double compound stochastic" image process is based on Bayes' theorem, and the MAP estimation employs the Point-Jacobian iteration to obtain the optimal solution. In the proposed algorithm, MRF is used to quantify the spatial interaction probabilistically, that is, to provide a type of prior information on the image texture and the neighbor window of any size is defined for contextual information on a local region. However, the window of a certain size would result in using wrong information for the estimation from adjacent regions with different characteristics at the pixels close to or on boundary. To overcome this problem, the new method is designed to use less information from more distant neighbors as the pixel is closer to boundary. It can reduce the possibility to involve the pixel values of adjacent region with different characteristics. The proximity to boundary is estimated using a non-uniformity measurement based on standard deviation of local region. The new scheme has been extensively evaluated using simulation data, and the experimental results show a considerable improvement in despeckling the images that contain speckle.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.79-89
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• 2008

Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series contaminated by noises resulted from mechanical problems or sensing environmental condition. There is also a high likelihood that during the data acquisition periods the target site corresponding to any given pixel may be covered by fog or cloud, thereby resulting in bad or missing observation. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. A feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. The experimental results of this simulation study show the potentiality of the proposed system to reconstruct the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather. This study provides fundamental information on the elements of the proposed system for right usage in application.