• International Journal of CAD/CAM
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• v.6 no.1
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• pp.173-181
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• 2006

In this paper, an integration framework of Geometric Constraint Solving Engine and AutoCAD is presented, and a dynamic geometric constraint system is introduced. According to inherent orientation features of geometric entities and various Object Snap results of AutoCAD, the' proposed system can automatically construct an under-constrained geometric constraint model during interactive drawing. And then the directed constraint graph in a geometric constraint model is realtime modified in order to produce an optimal constraint solving sequence. Due to the open object-oriented characteristics of AutoCAD, a set of user-defined entities including basic geometric elements and graphics constraint relations are defined through derivation. And the custom-made Object Reactor and Command Reactor are also constructed. Several powerful characteristics are achieved based on these user-defined entities and reactors, including synchronously processing geometric constraint information while saving and opening DWG files, visual constraint relations, and full adaptability to Undo/Redo operations. These characteristics of the proposed system can help the designers more easily manage geometric entities and constraint relations between them.

• Korean Journal of Computational Design and Engineering
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• v.3 no.4
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• pp.211-222
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• 1998

Parametric design is an important modeling paradigm in CAD/CAM applications, enabling efficient design modifications and variations. One of the major issues in parametric design is to develop a geometric constraint solver that can handle a large set of geometric configurations efficiently and robustly. In this appear, we propose a new approach to geometric constraint solving that employs a graph-based method to solve the ruler-and-compass constructible configurations and a numerical method to solve the ruler-and-compass non-constructible configurations, in a way that combines the advantages of both methods. The geometric constraint solving process consists of two phases: 1) planning phase and 2) execution phase. In the planning phase, a sequence of construction steps is generated by clustering the constrained geometric entities and reducing the constraint graph in sequence. in the execution phase, each construction step is evaluated to determine the geometric entities, using both approaches. By combining the advantages of the graph-based constructive approach with the universality of the numerical approach, the proposed approach can maximize the efficiency, robustness, and extensibility of geometric constraint solver.

• Korean Journal of Computational Design and Engineering
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• v.6 no.2
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• pp.78-88
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• 2001

In order to adopt feature-based parametric modeling, CAD/CAM applications must have a geometric constraint solver that can handle a large set of geometric configurations efficiently and robustly. In this paper, we describe a graph constructive approach to solving geometric constraint problems. Usually, a graph constructive approach is efficient, however it has its limitation in scope; it cannot handle ruler-and-compass non-constructible configurations and under-constrained problems. To overcome these limitations. we propose an algorithm that isolates ruler-and-compass non-constructible configurations from ruler-and-compass constructible configurations and applies numerical calculation methods to solve them separately. This separation can maximize the efficiency and robustness of a geometric constraint solver. Moreover, the solver can handle under-constrained problems by classifying under-constrained subgraphs to simplified cases by applying classification rules. Then, it decides the calculating sequence of geometric entities in each classified case and calculates geometric entities by adding appropriate assumptions or constraints. By extending the clustering types and defining several rules, the proposed approach can overcome limitations of previous graph constructive approaches which makes it possible to develop an efficient and robust geometric constraint solver.

• The Journal of Korean Association of Computer Education
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• v.8 no.1
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• pp.73-80
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• 2005

To achieve a natural and plausible interaction with deformable objects and to setup the desirable initial conditions of simulation, user should be able to define and control the geometric constraints intuitively. In addition, user should be able to utilize the simulation as a problem solving platform by experimenting various simulation situations without major modification of the simulator. The proposed physically based geometric constraint simulation system solves the problem using a non-linear finite element method approach to represent deformable objects and constraint forces are generated by defining geometric constraints on the nodes of the object to maintain the restriction. It allows user to define and modify geometric constraints and an algorithm converts these geometric constraints into constraint forces which seamlessly integrate controllability to the simulation system. Simulator can handle linear, angular, inequality based geometric constraints on the objects. Our experimental results show that constraints are maintained in the tight error bound and preserve desired shape of deformable object during the entire simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.1
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• pp.51-62
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• 2008

This paper proposes a second-order implicit constraint enforcement method which yields enhanced controllability compared to a first-order implicit constraints enforcement method. Although the proposed method requires solving a linear system twice, it yields superior accuracy from the constraints error perspective and guarantees the precise and natural movement of objects, in contrast to the first-order method. Thus, the proposed method is the most suitable for exact prediction simulations. This paper describes the numerical formulation of second-order implicit constraints enforcement. To prove its superiority, the proposed method is compared with the firstorder method using a simple two-link simulation. In this paper, there is a reasonable discussion about the comparison of constraints error and the analysis of dynamic behavior using kinetic energy and potential energy.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.9
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• pp.84-93
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• 1996

This paper describes the development of new feature positioning method which embedded into the top-down assembly modeling system supporting conceptual design. In this work, the user provides the geometric constraints representing the position and size of features, then the system calculates their proper solution. The use of geometric constraints which are easy to understand intuitively enables the user to represent his design intents about geometric shapes, and enables the system to propagate the changes automatically when some editing occurs. To find the proper solution of given constraints, the Selective Solving Method in which the redundant or conflict equations are detected and discarded is devised. The validity of feature shapes satisfying the constraints can be maintained by this technique, and under or over constrained user-defined constraints can also be estimated. The problems such as getting the initial guess, controlling the multiple solutions, and dealing with objects of rotational symmetry are also resolved. Through this work, the feature based modeling system can support more general and convenient modeling method, and keeps the model being valid during modifying models.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.7
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• pp.1604-1618
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• 1995

In the process of mechanical assembly design, assembly modeling systems have been used mainly for the design verification before manufacturing by enabling to check the interference and/ or the dynamic and kinematic performance. However, the conventional assembly modeling systems have a shortcoming that they can not be used in the initial design stage but can be used only after the design is fully completed. In other words conventional assembly modeling systems provide bottom-up modeling which means that the detailed modeling of components must precede the definition of relationships between them. To resolve this problem, an assembly modeling system is proposed to provide a top-down modeling environment in which components and assembly can be modeled simultaneously. To this end, an assembly data structure suitable for top-down assembly modeling has been established. Feature positioning Module(FPM) using geometric constraints has been also developed. The Sekective Solving Method proposed for FPM is based on the priority between the constraint equations and enables the designer's intent expressed by geometric constraints to be maintained throughout the whole modeling process. Finally, the feature based modeling technique using two-level features has been developed. Two-level features include an abstract model and a detailed model in a merged form in non-manifold data frame.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.1
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• pp.142-156
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• 2015

A new method for ship Inner Shell optimization, which is called Parametric Inner Shell Optimization Method (PISOM), is presented in this paper in order to improve both hull performance and design efficiency of transport ship. The foundation of PISOM is the parametric Inner Shell Plate (ISP) model, which is a fully-associative model driven by dimensions. A method to create parametric ISP model is proposed, including geometric primitives, geometric constraints, geometric constraint solving etc. The standard optimization procedure of ship ISP optimization based on parametric ISP model is put forward, and an efficient optimization approach for typical transport ship is developed based on this procedure. This approach takes the section area of ISP and the other dominant parameters as variables, while all the design requirements such as propeller immersion, fore bottom wave slap, bridge visibility, longitudinal strength etc, are made constraints. The optimization objective is maximum volume of cargo oil tanker/cargo hold, and the genetic algorithm is used to solve this optimization model. This method is applied to the optimization of a product oil tanker and a bulk carrier, and it is proved to be effective, highly efficient, and engineering practical.

• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.954-957
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• 2004

Based on the authors' previous work, where a geometric constraint handling technique for stiffener layout optimization problem using geometry algorithms was proposed, stiffener layout optimization to maximize natural frequencies of a curved three-dimensional shell structure was performed with a projection method. The original geometry of the shell structure was first projected on a two-dimensional plane, and then the whole optimization process was performed with the projected geometry of the shell except that the original shell structure was used for the eigenproblem solving. The projection method can be applied to baseline structures with a one-to-one correspondence between original and projected geometries such as automobile hoods and roofs.