• Journal of the Korean Society of Industry Convergence
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• v.18 no.2
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• pp.129-138
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• 2015

This study describe a new method to control posture and velocity for a wheeled mobile robot using visual feedback control method with a position based visual feedback. To slove the problem of vibration phenomena which were shown in the previous researches using a simple switching function based on a threshold, the proposed visual servo control law introduces the fusion function based on a blending function. The chattering problem and rapid motion of the mobile robot can be eliminated. And we consider the nonlinearity of the wheeled mobile robot unlike the previous visual servo control laws using linear control methods to improve the performances of the visual servo control law. The proposed posture control law using visual servoing is verified by a theoretical analysis and simulation and experimental results.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.2016-2025
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• 1994

A hierarchical planning strategy for dextrous manipulation of multifingered hands with soft finger contact model is proposed. Dextrous manipulation planning can be divided into a high-level stage which specifies the position/orientation trajectories of the fingertips on the object and a low-level stage which determines the contact forces and joint trajectories for the fingers. In the low-level stage, various nonlinear optimization problems are formulated according to the contact modes and integrated into a manipulation planning algorithm to find contact forces and joint velocities at each time step. Montana's contact equations are used for the high-level planning. Quasi-static simulation results are presented and illustrated by employing a three-fingered hand manipulating a sphere to demonstrate the validity of the proposed low-level planning strategy.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.566-571
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• 1994

This paper presents in image-based visual servo control scheme for tracking a workpiece with a hand-eye coordinated robotic system using the fuzzy-neural-network. The goal is to control the relative position and orientation between the end-effector and a moving workpiece using a single camera mounted on the end-effector of robot manipulator. We developed a fuzzy-neural-network that consists of a network-model fuzzy system and supervised learning rules. Fuzzy-neural-network is applied to approximate the nonlinear mapping which transforms the features and theire change into the desired camera motion. In addition a control strategy for real-time relative motion control based on this approximation is presented. Computer simulation results are illustrated to show the effectiveness of the fuzzy-neural-network method for visual servoing of robot manipulator.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.845-850
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• 2009

Localization which estimates a robot's position and orientation in a given environment is very important for mobile robot navigation. Although low-cost sensors are preferred for practical service robots, they suffer from the inaccurate and insufficient range information. This paper proposes a novel approach to increasing the success rate of low-cost sensor-based localization. In this paper, both the previous and the current data obtained from the IR sensors are used for localization in order to utilize as much environment information as possible without increasing the number of sensors. The sensor model used in the monte carlo localization (MCL) is modified so that the accumulated range information may be used to increase the accuracy in estimating the current robot pose. The experimental results show that the proposed method can robustly estimate the robot's pose in indoor environments with several similar places.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.60-63
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• 2000

In this study, efficient force reflection algorithm is developed for the Haptic Display by using a proxy concept and friction model. When there are not any contacted obstacles the proxy is following human operator's command trajectory in the 3D virtual space. But when the operator's command trajectory is locating inside of the object, the proxy is constrained by the surface of the object. Here only with the information of the proxy position and operator's command trajectory at every time step, we can calculate the reflection force and its orientation. To display the friction force between two virtual stiff material which are sliding against each other, modified Karnopp's friction model is used. In the friction model, a damping term and a Stribeck effect term are included to display the relative velocity effect and stick-slip effect at the very low relative velocity region respectively.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.63.4-63
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• 2001

An x-ray vision can be a unique method to monitor and analyze the motion of mechanical parts in real time which are invisible from outside. Our problem is to identify the pose, i.e. the position and orientation of an object from x-ray projection images. It is assumed here that the x-ray imaging conditions that include the relative coordinates of the x-ray source and the image plane are predetermined and the object geometry is known. In this situation, an x-ray image of an object at a given pose can be estimated computationally by using a priori known x-ray projection image model. It is based on the assumption that a pose of an object can be determined uniquely to a given x-ray projection image. Thus, once we have the numerical model of x-ray imaging process, x-ray image of the known object at any pose could be estimated ...

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.534-539
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• 2013

Recently, the number of vehicles equipped with cameras that are generally used to recognize surroundings is increasing. For robust recognition, a huge amount of tests under various environments are performed. Furthermore, the installation position or orientation of the camera is also changed depending on the vehicle. This change also accompanies many tests. Correspondingly, a large cost and a great deal of manpower are required to perform these tests. This paper proposes a method to cut these costs while conducting enough tests through the construction of a database of videos and a geometric transformation of images.

• Journal of Mechanical Science and Technology
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• v.14 no.7
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• pp.782-788
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• 2000

In this paper, we present a new approach to visual feedback control using image-based visual servoing with stereo vision. In order to control the position and orientation of a robot with respect to an object, a new technique is proposed using binocular stereo vision. The stereo vision enables us to calculate an exact image Jacobian not only around a desired location but also at other locations. The suggested technique can guide a robot manipulator to the desired location without providing a priori knowledge such as the relative distance to the desired location or the model of an object even when the initial positioning error is large. This paper describes a model of stereo vision and how to generate feedback commands. The performance of the proposed visual servoing system is illustrated by experimental results and compared with conventional control methods for an assembly robot.

• Transactions of the Korean Society of Mechanical Engineers
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• v.6 no.3
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• pp.204-210
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• 1982

The mechanical behaviors of an elastic body containing another materials are studied with the statistical method since they are generally distributed at random in size, orientation, and position. As the basis of this research, the size, the shape, and the ratio of volume for another material assumed to be constant, and only the positions of another material are changed randomly. The stress intensity factor, the compliance, and the modulus of elasticity are investigated in two-dimensional state by using the Monte Carlo Method and the Finite Element Method. The methodology of the simulation analysis for the mechanical behavior of such material is also proposed.

• 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.