• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.145-148
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• 1996

In moving object tracking based on the visual sensory feedback, a prerequisite is to determine which feature or which object is to be tracked and then the feature or the object identification precedes the tracking. In this paper, we focus on the object identification not image feature identification. The target identification is realized by finding out corresponding line segments to the hypothesized model segments of the target. The key idea is the combination of the Mahalanobis distance with the geometrica relationship between model segments and extracted line segments. We demonstrate the robustness and feasibility of the proposed target identification algorithm by a moving vehicle identification and tracking in the video traffic surveillance system over images of a road scene.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.768-771
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• 1997

Geometric probing addresses the problem of determining geometric aspects of a structure from the mathematics and results of a physical measuring device such as a probe. This paper presents a new algorithm to recognize the shape of an unknown object by using a robot hand with a force and torque sensor. The new algorithm is called S.E.P.(Shape Exploration Procedure) which finds the global shape of an unknown object. The proposed method is composed of three major parts, finding contact informations such as contact point, calculation of shape information such as curvature, and expression of global shape from these informations. Comparing with the conventional approaches, the advantages of the proposed method are explained and verified by conducting experiments with a 3-dof SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2033-2036
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• 2004

A novel approach to estimate the real time moving trajectory of an object is proposed in this paper. The object position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Kalman filter and neural networks are utilized. Since the Kalman filter needs to approximate a non-linear system into a linear model to estimate the states, there always exist errors as well as uncertainties again. To resolve this problem, the neural networks are adopted in this approach, which have high adaptability with the memory of the input-output relationship. Kohonen Network(Self-Organized Map) is selected to learn the motion trajectory since it is spatially oriented. The superiority of the proposed algorithm is demonstrated through the real experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2731-2736
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• 2003

In highly informative, perception-rich environments that we call Omniscient Spaces, robots interact with physical objects which in turn afford robots the information showing how the objects should be manipulated. Object manipulation is commonly believed one of the most basic tasks in robot applications. However, no approaches including visual servoing seem satisfactory in unstructured environments such as our everyday life. Thus, in Omniscient Spaces, the features of the environments embed themselves in every entity, allowing robots to easily identify and manipulate unknown objects. To achieve this end, we propose a new paradigm of the interaction through Radio Frequency Identification (RFID). The aim of this paper is to learn about RFID and investigate how it works in object manipulation. Specifically, as an innovative trial for autonomous, real-time manipulation, a likely mobile robot equipped with an RFID system is developed. Details on the experiments are described together with some preliminary results.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.119-125
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• 2008

This paper presents the polygon-based Q-leaning and Cascade Support Vector Machine algorithm for object search with multiple robots. We organized an experimental environment with ten mobile robots, twenty five obstacles, and an object, and then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning and dodecagon-based Q-learning and Cascade SVM to enhance the fusion model with DBAM and ABAM process.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.669-686
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• 1997

In this research, an object-oriented Petri net model for representing a flexible process plan is proposed, which is hierarchically multi-faceted for supporting planning, scheduling, and shop floor control functions. The multi-faceted process plan model consists of the following: a) an object model which represents on object-oriented data model, b) a static model which represents a process flow model with process alternatives, and c) a dynamic model which represents a process activity model with resources alternatives, of a flexible process plan. Petri nets allow the static and the dynamic process plan models to be represented in a unified formalism with an ease of model transformation. The multi-faceted process plan model suggested in this paper, is illustrated with a prismatic port in comprehensive detail.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1929-1930
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• 2006

Human like robot arm posture for grasping by considering the shape of the target object is quite a challenge in the field of robotics. In this paper, an optimized grasp posture with respect to the shape of the object considering the wrist joint angle and elbow elevation angle, in order to verify that the grasp posture is human like has been proposed. Given a target object, the candidates for grasp are computed by the method described in this paper. For each candidate, the closed loop inverse kinematics has been solved for the corresponding hand position and orientation. From the obtained joint angles through inverse kinematics, the elbow elevation angle has been computed and compared with the elbow elevation angle obtained through human movement data by the characteristic equation. After considering all the candidates, the hand position and orientation with minimum wrist joint and difference in elbow elevation angles has been utilized as the optimized grasp posture. Simulation results are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2010-2014
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• 2005

Object detection and parameter estimation in point cloud data is a relevant subject to robotics, reverse engineering, computer vision, and sport mechanics. In this paper a software is presented for fully-automatic object detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting. The newly developed algorithms for orthogonal distance fitting (ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. Curvature analysis of the local quadric surfaces fitted to small patches of point cloud provides the necessary seed information for automatic model selection, point segmentation, and model fitting. The performance of the software on a variety of point cloud data will be demonstrated live.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1524-1529
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• 2005

Particle filter is a kind of conditional density propagation model. Its similar characteristics to both selection and mutation operator of evolutionary strategy (ES) due to its Bayesian inference rule structure, shows better performance than any other tracking algorithms. When a new object is entering the region of interest, particle filter sets which have been swarming around the existing objects have to move and track the new one instantaneously. Moreover, there is another problem that it could not track multiple objects well if they were moving away from each other after having been overlapped. To resolve reinitialization problem, we use competitive-AVQ algorithm of neural network. And we regard interfarme difference (IFD) of background images as potential field and give priority to the particles according to this IFD to track multiple objects independently. In this paper, we showed that the possibility of real-time object tracking as intelligent interfaces by simulating the deformable contour particle filters.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.71-75
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• 1999

In this paper, we present the 3DOF force-reflecting interface which allows to acquire force of object within a virtual environment. This system is composed of device, virtual environment model, and force-reflecting rendering algorithm. We design a 3 DOF force-reflecting device using the parallel linkage, torque shared by wire, and the controller of system applied by impedance control algorithm. The force-reflecting behaviour implemented as a function position is equivalent to controlling the mechanical impedance felt by the user. Especially how force should be supplied to user, we know using a God-Object algorithm. As we experiment a system implemented by the interface of 3D virtual object and 3DOF force-reflecting interface, we can feel a contact, non-contact of 3D virtual object surface and sensing of push button model.