• Journal of the Korean Society for Precision Engineering
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• v.13 no.2
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• pp.94-101
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• 1996

The equations of motion for a basic industrial robotic system which has a rigid or a flexible arm are derived by Lagrange's equation, respectively. Especially, for the deflection of the flexible arm, the assumed mode method is employed. These equations are highly nonlinear equations with nonlinear coupling between the variables of motion. In order to design the control law for the rigid-arm robot, Hunt-Su's nonlinear transformation method and Marino's feedback equivalence condition are used with linear quadratic regulator(LQR) theory. The control law for the rigid-arm robot is employed to input the desired path and to provide the required nonlinear transformations for the flexible-arm robot to follow. By using the implicit Euler method to solve the nonlinear equations, the comparison of the motions between the flexible and the rigid robots and the effect of flexibility are examined.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.8
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• pp.500-505
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• 2003

In this paper, the method to register multiple sets of skull CT images to absolute coordinate system is proposed. Contrary to correspondence paired mapping of previous techniques, four anatomical landmark points, three coplanar points and one non-coplanar point, compose three principal axes simple and unique for efficient registration by means of rigid body transformation. Throughout the numerical simulation with added random noises, the error performances in terms of different rotation and rounding-off of landmark points, and incorrect localization of anatomical landmark and target points are quantitatively analyzed to generalize the proposed technique. Experiments using real skull CT images demonstrate the feasibility for an efficient use in clinical practice.

• The KIPS Transactions:PartA
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• v.16A no.2
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• pp.61-68
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• 2009

We present a fast 3D shape deformation method that achieves smoothly deformed result by approximating a rigid transformation based on moving least squares (MLS). Our modified MLS formulation reduces the computation cost for computing the optimal transformation of each point and still keeps the rigidity of the deformed results. Even complex geometric shapes are easily, intuitively, and interactively deformed by manipulating point and ellipsoidal handles.

• Structural Engineering and Mechanics
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• v.67 no.5
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• pp.439-455
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• 2018

Within a probabilistic framework, this paper addresses the determination of the static structural response of beams and frames with partially restrained (semi-rigid) connections. The flexibility of the nodal connections is incorporated via an idealized linear-elastic behavior of the beam constraints through the use of rotational springs, which are here considered uncertain for taking into account the largely scattered results observed in experimental findings. The analysis is conducted via the Probabilistic Transformation Method, by modelling the spring stiffness terms (or equivalently, the fixity factors of the beam) as uniformly distributed random variables. The limit values of the Eurocode 3 fixity factors for steel semi-rigid connections are assumed. The exact probability density function of a few indicators of the structural response is derived and discussed in order to identify to what extent the uncertainty of the beam constraints affects the resulting beam response. Some design considerations arise which point out the paramount importance of probability-based approaches whenever a comprehensive experimental background regarding the stiffness of the beam connection is lacking, for example in steel frames with semi-rigid connections or in precast reinforced concrete framed structures. Indeed, it is demonstrated that resorting to deterministic approaches may lead to misleading (and in some cases non-conservative) outcomes from a design viewpoint.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.180-194
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• 2021

For small image registration, feature-based approaches are likely to fail as feature detectors cannot detect enough feature points from low-resolution images. The classic FFT approach's prediction accuracy is high, but the registration time can be relatively long, about several seconds to register one image pair. To achieve real-time and high-precision rigid registration for small images, we apply deep neural networks for supervised rigid transformation prediction, which directly predicts the transformation parameters. We train deep registration models with rigidly transformed CIFAR-10 images and STL-10 images, and evaluate the generalization ability of deep registration models with transformed CIFAR-10 images, STL-10 images, and randomly generated images. Experimental results show that the deep registration models we propose can achieve comparable accuracy to the classic FFT approach for small CIFAR-10 images (32×32) and our LSTM registration model takes less than 1ms to register one pair of images. For moderate size STL-10 images (96×96), FFT significantly outperforms deep registration models in terms of accuracy but is also considerably slower. Our results suggest that deep registration models have competitive advantages over conventional approaches, at least for small images.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.8 no.2
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• pp.75-86
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• 2004

In this study, a recursive algorithm for generating the equations of motion of a chain of rigid rods is presented. The methods rests upon the idea of replacing the rigid body by a dynamically equivalent constrained system of particles. The concepts of linear and angular momentums are used to generate the rigid body equations of motion without either introducing any rotational coordinates or the corresponding transformation matrices. For open-chain, the equations of motion are generated recursively along the serial chains. For closed-chain, the system is transformed to open-chain by cutting suitable kinematic joints with the addition of cut-joints kinematic constraints. An example of a closed-chain of rigid rods is chosen to demonstrate the generality and simplicity of the proposed method.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.47-51
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• 2005

Using satellite images, an optimal solution to water motion has been presented in this study. Since temperature patterns are suitable tracers in water motion, Sea Surface Temperature (SST) images of Caspian Sea taken by MODIS sensor on board Terra satellite have been used in this study. Two daily SST images with 24 hours time interval are used as input data. Computation of templates correspondence between pairs of images is crucial within motion algorithms using non-rigid body objects. Image matching methods have been applied to estimate water body motion within the two SST images. The least squares matching technique, as a flexible technique for most data matching problems, offers an optimal spatial solution for the motion estimation. The algorithm allows for simultaneous local radiometric correction and local geometrical image orientation estimation. Actually, the correspondence between the two image templates is modeled both geometrically and radiometrically. Geometric component of the model includes six geometric transformation parameters and radiometric component of the model includes two radiometric transformation parameters. Using the algorithm, the parameters are automatically corrected, optimized and assessed iteratively by the least squares algorithm. The method used in this study, has presented more efficient and robust solution compared to the traditional motion estimation schemes.

• Journal of Mechanical Science and Technology
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• v.18 no.2
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• pp.193-202
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• 2004

This paper presents a computer method for the dynamic analysis of a system of rigid bodies in plane motion. The formulation rests upon the idea of replacing a rigid body by a dynamically equivalent constrained system of particles. Newton's second law is applied to study the motion of the resulting system of particles without introducing any rotational coordinates. A velocity transformation is used to transform the equations of motion to a reduced set. For an open-chain, this process automatically eliminates all of the non-working constraint forces and leads to an efficient integration of the equations of motion. For a closed-chain, suitable joints should be cut and few cut-joints constraint equations should be included. An example of a closed-chain is used to demonstrate the generality and efficiency of the proposed method.

• Structural Engineering and Mechanics
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• v.35 no.1
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• pp.53-65
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• 2010

The rigid body inertia properties of a structure including the mass, the center of gravity location, the mass moments and principal axes of inertia are required for structural dynamic analysis, modeling of mechanical systems, design of mechanisms and optimization. The analytical approaches such as solid or finite element modeling can not be used efficiently for estimating the rigid body inertia properties of complex structures. Several experimental approaches have been developed to determine the rigid body inertia properties of a structure via Frequency Response Functions (FRFs). In the present work two experimental methods are used to estimate the rigid body inertia properties of a frame. The first approach consists of using the amount of mass as input to estimate the other inertia properties of frame. In the second approach, the property of orthogonality of modes is used to derive the inertia properties of a frame. The accuracy of the estimated parameters is evaluated through the comparison of the experimental results with those of the theoretical Solid Work model of frame. Moreover, a thorough discussion about the effect of accuracy of measured FRFs on the estimation of inertia properties is presented.

• Structural Engineering and Mechanics
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• v.21 no.2
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• pp.205-220
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• 2005

This paper presents the possibilities of adapting artificial neural networks (ANNs) to predict the dimensionless parameters related to the maximum contact pressures of an elasticity problem. The plane symmetric double receding contact problem for a rigid stamp and two elastic strips having different elastic constants and heights is considered. The external load is applied to the upper elastic strip by means of a rigid stamp and the lower elastic strip is bonded to a rigid support. The problem is solved under the assumptions that the contact between two elastic strips also between the rigid stamp and the upper elastic strip are frictionless, the effect of gravity force is neglected and only compressive normal tractions can be transmitted through the interfaces. A three layered ANN with backpropagation (BP) algorithm is utilized for prediction of the dimensionless parameters related to the maximum contact pressures. Training and testing patterns are formed by using the theory of elasticity with integral transformation technique. ANN predictions and theoretical solutions are compared and seen that ANN predictions are quite close to the theoretical solutions. It is demonstrated that ANNs is a suitable numerical tool and if properly used, can reduce time consumed.