• IEIE Transactions on Smart Processing and Computing
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• v.2 no.5
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• pp.317-321
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• 2013

This paper proposes a detection algorithm for view reversal in a stereoscopic video using a disparity map and motion vector field. We obtain the disparity map of a stereo image was obtained using a specific stereo matching algorithm and classify the image into the foreground and background. Next, the motion vector field of the image on a block basis was produced using a full search algorithm. Finally, the stereo image was considered to be reversed when the foreground moved toward the background and the covered region was in the foreground. The proposed algorithm achieved a good detection rate when the background was covered sufficiently by its moving foreground.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.11
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• pp.1770-1781
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• 1989

Two robots working in a common workspace may collide with each other. In this paper, a collision-free motion planning algorithm using view time concept is proposed to detect and avoid collision before robot motion. Collision may occur not only at the robot end effector but also at robot links. To detect and avoid potential collisions, the trajectory of the first robot is sampled periodically at every view time and the region in Cartesian space swept by the first robot is viewed as an obstacle during a single sampling period. The forbidden region in the joint constraint map (JCM). The JCM's are obtained in this way at every view time. An algorithm is established for collision-free motion planning of the two robot system from the sequence of JCM's and it is verified by simulations.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1039-1043
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• 2005

Despite the many significant advances made in robot architecture, the basic approaches are deliberative and reactive methods. They are quite different in recognizing outer environment and inner operating mechanism. For this reason, they have almost opposite characteristics. Later, researchers integrate these two approaches into hybrid architecture. In such architecture, Reactive module also called low-level motion control module have advantage in real-time reacting and sensing outer environment; Deliberative module also called high-level task planning module is good at planning task using world knowledge, reasoning and intelligent computing. This paper presents a framework of the integrated planning and control for mobile robot navigation. Unlike the existing hybrid architecture, it learns topological map from the world map by using MST (Minimum Spanning Tree)-based SOFM (Self-Organizing Feature Map) algorithm. High-level planning module plans simple tasks to low-level control module and low-level control module feedbacks the environment information to high-level planning module. This method allows for a tight integration between high-level and low-level modules, which provide real-time performance and strong adaptability and reactivity to outer environment and its unforeseen changes. This proposed framework is verified by simulation.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.323-326
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• 2006

The operation planning of multi-AUV is considered as a very difficult task. This paper proposes the qualitative method about the operation plan of multi-agents. In order to achieve this goal, it applies an extension collision map method as a tool to avoide collision between multi AUVs. This tool has been developed for the purpose of collision forecasting and collision avoidance for the multi - agents system in a land where a control is much easier. This paper analyzes the avoidance value of maximum path of AUV in order to apply this to a water environment where a tidal, a wave and disturbances are common. And it suggests the method that the maximum path avoidance can be applied to the collision avoidance on the extension collision map. Finally, the result proves that multi AUVs effectively navigates to the goal point, avoiding the collision by the suggested method.

• ETRI Journal
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• v.37 no.6
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• pp.1220-1230
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• 2015

An autonomous valet parking (AVP) system is designed to locate a vacant parking space and park the vehicle in which it resides on behalf of the driver, once the driver has left the vehicle. In addition, the AVP is able to direct the vehicle to a location desired by the driver when requested. In this paper, for an AVP system, we introduce technology to recognize a parking space using image sensors. The proposed technology is mainly divided into three parts. First, spatial analysis is carried out using a height map that is based on dense motion stereo. Second, modelling of road markings is conducted using a probability map with a new salient-line feature extractor. Finally, parking space recognition is based on a Bayesian classifier. The experimental results show an execution time of up to 10 ms and a recognition rate of over 99%. Also, the performance and properties of the proposed technology were evaluated with a variety of data. Our algorithms, which are part of the proposed technology, are expected to apply to various research areas regarding autonomous vehicles, such as map generation, road marking recognition, localization, and environment recognition.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.69-75
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• 2012

This paper presents a novel de-interlacing algorithm that can make up motion compensation errors by using maximum a posteriori (MAP) estimator. First, a proper registration is performed between a current field and its adjacent fields, and the progressive frame corresponding to the current field is found via MAP estimator based on the computed registration information. Here, in order to obtain a stable solution, well-known bilateral total variation (BTV)-based regularization is employed. Next, so-called feathering artifacts are detected on a block basis effectively. So, edge-directional interpolation is applied to the pixels where feathering artifact may happen, instead of the above-mentioned temporal de-interlacing. Experimental results show that the PSNR of the proposed algorithm is on average 4dB higher than that of previous studies and provides the better subjective quality than the previous works.

• Journal of the Chungcheong Mathematical Society
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• v.22 no.4
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• pp.771-776
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• 2009

Let (H, g) denote the upper half plane in $R^2$ with the Riemannian metric g := ($(dx)^2$ + $(dy)^2$)$/y^2$. First of all we get a necessary and sufficient condition for a diffeomorphism $\phi$ of (H, g) to be a harmonic map. And, we obtain the fact that if a diffeomorphism $\phi$ of (H, g) is a harmonic function, then the following facts are equivalent: (1) $\phi$ is a harmonic map; (2) $\phi$ is an affine transformation; (3) $\phi$ is an isometry (motion).

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.468-471
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• 2003

The A＊ algorithm is usually used in game programming, mainly because it is fast in finding a optimal path to goal. In this paper. This algorithm was utilized for path finding, HIMM(Histogramic In-Motion Mapping) method is used in map-building. Map is updated continuously with range data sampled by PSD sensors From the map, A＊ algorithm finds a optimal path and sends subsequently the most suitable point to the Eyebot. A＊ algorithm has been tested on the Eyebot in various unknown maps of unknown and proved to work well. It could escape the local minimum, also.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.51-57
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• 2021

In this paper, we propose a new framework that calculates the user's hand motions using a Leap Motion device, and uses this to practice and analyze arm muscles as well as juggling motions. The proposed method can map the movement of the ball in a virtual environment according to the user's hand motions in real time, and analyze the amount of exercise by visualizing the relaxation and contraction of the muscles. The proposed framework consists of three main parts : 1) It tracks the user's hand position with the Leap Motion device. 2) As with juggling, the action pattern of the user throwing the ball is defined as an event. 3) We propose a parabola-based particle method to map the movement of a juggling shape to a ball based on the user's hand position. As a result, using the our framework, it is possible to play a juggling game in real-time.

• The Journal of Korea Robotics Society
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• v.7 no.4
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• pp.252-258
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• 2012

This paper describes hierarchical semantic map building using the classified area information in home environments. The hierarchical semantic map consists of a grid, CAIG (Classified Area Information in Grid), and topological map. The grid and CAIG maps are used for navigation and motion selection, respectively. The topological map provides the intuitive information on the environment, which can be used for the communication between robots and users. The proposed semantic map building algorithm can greatly improve the capabilities of a mobile robot in various domains, including localization, path-planning and HRI (Human-Robot Interaction). In the home environment, a door can be used to divide an area into various sections, such as a room, a kitchen, and so on. Therefore, we used not only the grid map of the home environment, but also the door information as a main clue to classify the area and to build the hierarchical semantic map. The proposed method was verified through various experiments and it was found that the algorithm guarantees autonomous map building in the home environment.