• IEIE Transactions on Smart Processing and Computing
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• 제2권5호
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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.

• 대한전자공학회논문지
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• 제26권11호
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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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• 제어로봇시스템학회 2005년도 ICCAS
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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.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2006년 창립20주년기념 정기학술대회 및 국제워크샵
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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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• 제37권6호
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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.

• 대한전자공학회논문지SP
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• 제49권2호
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• pp.69-75
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• 2012

본 논문은 MAP (maximum a posterior) 예측기에 기반하여 움직임 보상 예측 오차를 보정해주는 방식의 순차주사화 (de-interlacing) 알고리즘을 제안한다. 먼저, 현재 필드와 인접한 필드 간의 적절한 정합 (registration)을 수행 한 후, 계산된 정합 정보에 기반한 MAP 예측기를 통해 현재 필드에 대응하는 순차 주사 (progressive) 프레임을 찾아낸다. 안정적인 결과를 얻기 위하여 잘 알려진 BTV (bilateral total variation) 기반의 평활화 (regularization) 과정이 추가된다. 한편, 잘못된 정합 정보로 인한 소위 깃털 현상 (feathering artifact)을 억제하기 위하여 블록 단위로 깃털 현상 발생 여부를 판단하여 발생되었다고 판단된 블록 영역에 대해서는 앞서 설명한 MAP기반 순차주사화 대신 에지 방향성에 기반한 공간적 순차주사화를 적용한다. 실험 결과에 따르면, 제안된 기법은 종래 기법들에 비하여 평균 약 4dB의 PSNR 성능 개선을 보이고 있으며, 우수한 주관적 화질을 보여주고 있다.

• 충청수학회지
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• 제22권4호
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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).

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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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.

• 한국컴퓨터정보학회논문지
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• 제26권11호
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• pp.51-57
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• 2021

본 논문에서는 립모션 디바이스를 이용하여 사용자의 손 움직임을 계산하고, 이로부터 저글링 동작뿐만 아니라 이것을 활용하여 팔 근육을 연습 및 분석할 수 있는 새로운 프레임워크를 제안한다. 제안하는 방법은 실시간으로 사용자의 손동작에 맞춰 가상환경에서 공의 움직임을 매핑 할 수 있고, 근육의 이완과 수축을 시각화하여 운동량을 분석할 수 있다. 제안하는 프레임워크는 크게 세 부분으로 구성된다 : 1) 립모션 디바이스를 이용하여 사용자의 손 위치를 추적한다. 2) 저글링을 하듯이, 사용자가 공을 던지는 행동 패턴을 이벤트로 정의한다. 3) 사용자의 손 위치를 기준으로 저글링 형태의 움직임을 공에 매핑하기 위한 포물선 기반 입자 기법을 제안한다. 결과적으로 본 논문의 프레임워크를 이용하면 실시간 저글링 게임을 할 수 있다.

• 로봇학회논문지
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• 제7권4호
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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.