• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.524-526
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• 2006

We proposes integrated information system, Service Robot Information System(SRIS), for mobile robot. The system has objectives that can heir efficient management and sharing as support information for mobile service robot like recognition, navigation, manipulation and modeling. This paper introduces the concert and architecture of SRIS. An Implementation is done by using ER based database and CAD modeling which is DXF format. The experimental shows the result of object and environment map matching by SLAM. This system is expected that can help reduce the cost and efforts of information management under multiple mobile robot environment.

• IEIE Transactions on Smart Processing and Computing
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• 제5권3호
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• pp.215-221
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• 2016

This paper describes an automatic vowel sequence reproduction system for a talking robot built to reproduce the human voice based on the working behavior of the human articulatory system. A sound analysis system is developed to record a sentence spoken by a human (mainly vowel sequences in the Japanese language) and to then analyze that sentence to give the correct command packet so the talking robot can repeat it. An algorithm based on a short-time energy method is developed to separate and count sound phonemes. A matching template using partial correlation coefficients (PARCOR) is applied to detect a voice in the talking robot's database similar to the spoken voice. Combining the sound separation and counting the result with the detection of vowels in human speech, the talking robot can reproduce a vowel sequence similar to the one spoken by the human. Two tests to verify the working behavior of the robot are performed. The results of the tests indicate that the robot can repeat a sequence of vowels spoken by a human with an average success rate of more than 60%.

• 로봇학회논문지
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• 제2권1호
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• pp.48-54
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• 2007

A network-based robot [1] is a robot that explores service servers in the network environment for analyzing sensor data and making decision. Since network-based robot architecture was proposed, it's possible to reduce costs of robots. We hope robots would be all around at home environment. Therefore, normal users who are not experts need to be able to control those robots by using easy commands. We developed a scripting language, named CCSLR, to help users and developers who control various robots in ubiquitous environment. We focused on how to design the common language for various robots and how to translate a CCSLR script into a sequence of low-level commands of the target robot. In this paper, we propose scripting methods, with three layers. The CCSLR system reads the profile information from the knowledge representation database. Users don't have to know all about kinematical and mechanical details of a robot. Then again, the CCSLR system will use the profile information to translate the script into separated executable library commands. The CCSLR system manages robot's changing state every time a robot executes a command.

• 한국지능시스템학회논문지
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• 제26권1호
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• pp.9-15
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• 2016

본 논문에서는 도서관의 도서 관리 효율을 높이기 위해 도서들이 제 위치를 정상적으로 배치되어 있음을 검증하는 시스템을 제안하고자 한다. 개방형 도서관에서 일반인들이 도서를 열람하고 난 후, 고의 혹은 실수로 인해 제자리에 도서를 꽂아 놓지 않는 경우가 발생한다. 이렇게 되면 소장되어 있는 도서임에도 불구하고 분실도서로 처리되어 다른 사람이 열람하지 못하게 된다. 이와 같은 문제를 해결하기 위해 로봇을 이용하여 서가의 영상을 획득하고, 획득한 영상으로부터 책의 분류정보를 읽어드려서 도서의 위치를 데이터베이스와 비교하여 검증한 다음, 잘못 비치된 도서를 사서에게 알려주는 시스템을 제안한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.61-63
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• 2005

Retreiving indoor scene reference image from database using visual information is important issue in Robot Navigation. Scene matching problem in navigation robot is not easy because input image that is taken in navigation process is affinly distorted. We represent probabilistic framework for the feature matching between features in input image and features in database reference images to guarantee robust scene matching efficiency. By reconstructing probabilistic scene matching framework we get a higher precision than the existing feaure-feature matching scheme. To construct probabilistic framework we represent each image as Gaussian Mixture Model using Expectation Maximization algorithm using SIFT(Scale Invariant Feature Transform).

• 제어로봇시스템학회논문지
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• 제14권5호
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• pp.483-488
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• 2008

An active omni-directional raging system using an omni-directional vision with structured light has many advantages compared to the conventional ranging systems: robustness against external illumination noise because of the laser structured light and computational efficiency because of one shot image containing $360^{\circ}$ environment information from the omni-directional vision. The omni-directional range data represents a local distance map at a certain position in the workspace. In this paper, we propose a matching algorithm for the local distance map with the given global map database, thereby to localize a mobile robot in the global workspace. Since the global map database consists of line segments representing edges of environment object in general, the matching algorithm is based on relative position and orientation of line segments in the local map and the global map. The effectiveness of the proposed omni-directional ranging system and the matching are verified through experiments.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.28-32
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• 2007

While various methods for sound source localization have been developed, most of them utilize on the time difference of arrival (TDOA) between microphones or the measured head related transfer functions (HRTF). In case of a real robot implementation, the former has a merit of light computation load to estimate the sound direction but can not consider the effect of platform on TDOAs, while the latter can, because characteristics of robot platform are included in HRTF. However, the latter needs large resources for the HRTF database of a specific robot platform. We propose the compensation method which has the light computation load while the effect of platform on TDOA can be taken into account. The proposed method is used with spherical head related transfer function (SHRTF) on the assumption that robot platform, for example a robot head, installed microphones can be modeled to a sphere. We verify that the proposed method decreases the estimation error caused by the robot platform through the simulation and experiment in real environment.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.517-519
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• 2004

This paper describes an approach to estimate a robot pose with an image. The algorithm of pose estimation with an image can be broken down into three stages : extracting scale-invariant features, matching these features and calculating affine invariant. In the first step, the robot mounted mono camera captures environment image. Then feature extraction is executed in a captured image. These extracted features are recorded in a database. In the matching stage, a Random Sample Consensus(RANSAC) method is employed to match these features. After matching these features, the robot pose is estimated with positions of features by calculating affine invariant. This algorithm is implemented and demonstrated by Matlab program.

• Journal of Welding and Joining
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• 제14권2호
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• pp.96-105
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• 1996

Robot systems are widely utilized in the shipbuilding industry to enhance the productivity by automating the welding process. In order to increase productivity, it is necessary to reduce the time used for robot teaching. In this work, the automatic teaching system is developed for the subassembly process in the shipbuilding industry. A alser/vision sensor is designed to detect the weld seam and the image of the fillet joint is processed using the arm method. Positions of weld seams defined in the CAD database are transformed into the robot coordinate, and the dynamic programming technique is applied to find the sub-optimum weld path. Experiments are carried out to verify the system performance. The results show that the proposed automatic teaching system performs successfully and can be applied to the robot system in the subassembly process.

• 융합신호처리학회논문지
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• 제5권4호
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• pp.256-262
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• 2004

로봇이 자율주행을 하는데 있어 중요한 요소는 로봇 스스로 위치를 추정하고 동시에 주위 환경에 대한 지도를 작성하는 것이다. 본 논문에서는 어안렌즈를 이용한 비전 기반 위치 추정 및 매핑 알고리즘을 제안한다. 로봇에 어안렌즈가 부착된 카메라를 천정을 바라볼 수 있도록 부착하여 스케일 불변 특징을 갖는 고급의 영상 특징을 구하고, 이 특징들을 맵 빌딩과 위치 추정에 이용하였다. 전처리 과정으로 어안렌즈를 통해 입력된 영상을 카메라 보정을 행하여 축방향 왜곡을 제거하고 레이블링과 컨벡스헐을 이용하여 보정된 영상에서 천정영역과 벽영역으로 분할한다. 최초 맵 빌딩시에는 분할된 영역에 대해 특징점을 구하고 맵 데이터베이스에 저장한다. 맵 빌딩이 종료될 때까지 연속하여 입력되는 영상에 대해 특징점들을 구하고 맵과 매칭되는 점들을 찾고 매칭되지 않은 점들에 대해서는 기존의 맵에 추가하는 과정을 반복한다. 위치 추정은 맵 빌딩 과정과 맵 상에서 로봇의 위치를 찾는데 이용된다. 로봇의 위치에서 구해진 특징점들은 로봇의 실제 위치를 추정하기 위해 기존의 맵과 매칭을 행하고 동시에 기존의 맵 데이터베이스는 갱신된다. 제안한 방법을 적용하면 50㎡의 영역에 대한 맵 빌딩 소요 시간은 2분 이내, 위치 추정시 위치 정확도는 ±13cm, 로봇의 자세에 대한 각도 오차는 ±3도이다.