• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2011.11a
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• pp.282-285
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• 2011

클라우드 컴퓨팅에 있어서 이질적 컴퓨팅 자원들을 소프트웨어에 의해 논리적 방법으로 제어할 수 있도록 하는 가상화와 대용량 데이터의 분산병렬처리가 핵심적인 기술이다. 재난의 예방 및 대응을 위해 다양한 센서들이 개발되고 있으며, 재난관리 어플리케이션들은 센서들에 의해 획득된 대용량의 데이터를 상호 관련성에 따라 신속하게 처리할 것이 요구된다. 이 논문에서는 클라우드 컴퓨팅을 이용한 재난관리시스템 구축을 위해 다양한 이질적 센서들을 가상화하여 센서 클라우드 환경을 구성하는 방안을 제시한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.452-454
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• 2008

지능형 서비스 로봇 분야의 발전은 최근 들어 빠른 속도로 급성장하고 있으며 다양한 환경에서 상황인지를 수행하고, 지능로봇으로서의 역할을 수행 할 수 있는 로봇 개발 연구가 활발히 진행되고 있다. 따라서 본 논문에서는 MSRDS를 활용한 3차원(3D) 가상공간에서 다중센서융합(MSF) 지능로봇을 시뮬레이션 할 수 있는 환경과 개발 방법을 제안한다. 또한 시뮬레이션 환경에서 다중센서융합을 적용한 지능로봇 개발방법을 연구하고 실험한다. 본 연구에 목적은 다양한 실제 환경에 로봇이 지능적으로 대처할 수 있도록 다중센서를 융합하고 시뮬레이션 로봇에 적용하여 지능로봇을 개발 할 수 있는 3 차원 시뮬레이션 시스템 환경을 개발하는 것이다. 유비쿼터스 시대에 가상공간이 아닌 현실세계에 적응할 수 있는 실제 지능로봇 개발에 큰 도움이 될 수 있을 것으로 기대한다.

• The Magazine of the IEIE
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• v.33 no.3 s.262
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• pp.28-35
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• 2006

소프트웨어 로봇들은 시뮬레이트된 센서와 실행기들을 가지고 가상 환경 안에서 자율적으로 동작하는 지능형 가상 에이전트로 볼 수 있다. 지능형 가상 에이전트 연구용 테스트베드들은 에이전트들의 성능 평가를 위해 표준화된 작업들을 구현할 수 있고, 환경이나 실험 에이전트들을 제어할 수 있는 도구들이다. 본 논문에서는 RoboCup 축구 시뮬레이션시스템, Gamebots 시스템, USARSim 시스템 등과 같은 지능형 가상 에이전트와 멀티 에이전트시스템 연구를 위한 대표적인 테스트베드들을 간략히 소개한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2001.11b
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• pp.205-208
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• 2001

최근 스포츠 중계를 중심으로 가상광고가 큰 주목을 받고 있다. 가상광고는 현실에 존재하지 않는 광고를 실영상 내에 삽입하여 마치 실제로 존재하는 물체처럼 보여주는 기술이다. 본 논문에서는 한 대의 카메라로 촬영한 영상으로부터 실시간으로 특징점 추출 및 추적을 행하여, 카메라 Projection 행렬을 복원하고, 이를 이용하여 범용적인 크로마키(chroma-key) 기법으로 영상합성 함으로써 센서와 같은 부가장비가 필요없는 영상기반의 가상광고 시스템을 구현하였다. 일반 PC상에서 알고리즘의 유효성과 실시간 동작성을 확인하였다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2009.04a
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• pp.277-278
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• 2009

발전된 센서 기술과 상황인지에 대한 여러 연구들을 기반으로 하여 현실 세계의 상황정보를 통합, 관리 및 활용을 위한 동기화 현실을 구축하고자 한다. 동기화 현실이란 기존의 가상현실과는 달리 실세계의 상황이 실시간으로 반영되는 가상 세계를 말한다. 동기화 현실의 구축을 위해 동적인 상황과 정적인 상황을 분류하여 가상세계에 적용시키고 분류된 상황은 각각 DSMS와 DBMS로 관리된다. 이런 정보는 OpenSimulator를 이용해서 가상세계에 반영이 되고 웹을 통한 OpenAPI를 통해 활용된다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.6
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• pp.549-559
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• 2015

In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments.

• Journal of Digital Contents Society
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• v.14 no.2
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• pp.161-169
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• 2013

Experiments and practices are critical instructional activities for teaching and learning natural sciences. However, by learning the experimental procedures in advance with the help of Virtual Experiments, natural science majors may address danger of handling chemicals before carrying out experiments in the laboratories. Virtual Experiments, a mobile learning app, provides learners with interactions between the learners and the contents by using the sensor built-in Android-platform smart phones. With the app, learners may handle the chemicals and experiment apparatuses, verify the reactions and assembly of the chemicals and instruments in advance. This paper describes the design and development of the Virtual Experiments in hope to promote the integration of mobile learning apps in order to better engage learners in the laboratories.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.7B
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• pp.886-891
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• 2011

Multicast has been a key routing service for efficient data dissemination in underwater acoustic sensor networks. In sensor networks, there are several multicast routing protocol which reflects sensor network nature. However, existing routing scheme was not targeted at underwater acoustic sensor networks which is hard to provide battery continually. Therefore, a specialized routing algorithm is essential for acoustic sensor networks. In this paper, we propose angle aided multicast routing algorithm for decreasing routing computation complexity, including virtual Euclidean Steiner point. Simulation results show better performance than exist routing Position Based Multicast, Geographic Multicast Routing. such as low computation capability and limited power consumption.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.12
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• pp.491-498
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• 2019

Digital twin is a technology that virtualizes physical objects of the real world on a computer. It is used by collecting sensor data through IoT, and using the collected data to connect physical objects and virtual objects in both directions. It has an advantage of minimizing risk by tuning an operation of virtual model through simulation and responding to varying environment by exploiting experiments in advance. Recently, artificial intelligence and machine learning technologies have been attracting attention, so that tendency to virtualize a behavior of physical objects, observe virtual models, and apply various scenarios is increasing. In particular, recognition of each robot's motion is needed to build digital twin for co-robot which is a heart of industry 4.0 factory automation. Compared with modeling based research for recognizing motion of co-robot, there are few attempts to predict motion based on sensor data. Therefore, in this paper, an experimental environment for collecting current and inertia data in co-robot to detect the motion of the robot is built, and a motion prediction model based on the collected sensor data is proposed. The proposed method classifies the co-robot's motion commands into 9 types based on joint position and uses current and inertial sensor values to predict them by accumulated learning. The data used for accumulating learning is the sensor values that are collected when the co-robot operates with margin in input parameters of the motion commands. Through this, the model is constructed to predict not only the nine movements along the same path but also the movements along the similar path. As a result of learning using SVM, the accuracy, precision, and recall factors of the model were evaluated as 97% on average.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.228-236
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• 2008

Recently augmented reality technology has been researched to view the virtual shape of buildings before construction or cultural heritages under recovery. Those researches used special devices or markers that are not applicable in long distanced outdoor environment. Also the server had to compute a lot of transformations for the location changes of virtual objects. This paper proposed a mobile augmented reality system that uses GPS and accelerometer sensors in order to compute the virtual object's locations without using markers. The server determines the position and orientation by comparing the GPS data obtained from the client with the predefined 3D object informations in the server. If the server sends the virtual object informations such as the position, orientation and matching information, then the client matches the virtual object on the screen of mobile camera phone. In addition, the client computes the transformations of location change detected by the accelerometer derived from the user's movement without additional connection to the server.