• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2475-2478
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• 2002

This paper consider's the problem of exploring an unfamiliar environment in search of recognizable objects of visual landmarks. In order to extract and recognize them automatically, a feature map is constructed which records the set of features continually during a learning phase. The map contains photometric geometric, and metric information of each feature. Meanwhile, the localization algorithm can determine the position of the robot by extracting features and matching in the map. These procedures are implemented and tested using an AMR, and preliminary results are presented in this paper.

• International Journal of Control, Automation, and Systems
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• 제6권1호
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• pp.62-75
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• 2008

Vision-based simultaneous localization and map building using a single camera, while compelling in theory, have not until recently been considered extensive in the practical realm of the real world. In this paper, we propose a simple framework for the monocular SLAM of an indoor mobile robot using natural line features. Our focus in this paper is on presenting a novel approach for modeling the landmark before integration in monocular SLAM. We also discuss data association improvement in a particle filter approach by using the feature management scheme. In addition, we take constraints between features in the environment into account for reducing estimated errors and thereby improve performance. Our experimental results demonstrate the feasibility of the proposed SLAM algorithm in real-time.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1767-1768
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• 2007

This paper represents a map building system of Embedded Linux mobile robot. We propose a localization method which uses multiple sensors such as indoor GPS and encoder sensor for simultaneous map building system. In this paper we proposed a multiple sensor system for SLAM. For this, we developed a sensor based navigation algorithm and grid based map building algorithm under the Embedded Linux O.S. We proved this system's validity through field test

• Journal of the Korean Data and Information Science Society
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• 제22권6호
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• pp.1029-1040
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• 2011

본 연구에서는 실제 환경에 적용 가능한 지능형 자율 이동 방법을 개발하기 위해 위치정보를 사용하지 않고 지도 작성이 가능한 지능형 이동 알고리즘을 제안한다. 제안한 알고리즘은 온라인으로 동작하면서 위치 정보를 사용하지 않고 지도 작성이 가능 할 뿐 아니라 현실 세계에 적용 가능하기 위해 많은 계산량을 요구하지도 않는다. 이는 이동 로봇의 실세계 주행과 같은 대용량의 이미지 처리가 필요한 경우에는 매우 유용하게 사용될 수 있다. 토이 자료와 대용량 자료에 대해 제안한 알고리즘을 적용한 결과 기존의 방법에 비해 적은 메모리와 새로운 입력에 대해 고유공간을 새로 계산하지 않아도 되어 로봇의 현실세계의 주행에도 문제가 없는 것으로 판단되었다.

• 드라이브 ㆍ 컨트롤
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• 제19권4호
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• pp.97-103
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• 2022

Low fertility rates and increased life expectancy further exacerbate the process of an aging society. This is also reflected in the gradual increase in the proportion of vulnerable groups in the social population. The demand for improved mobility among vulnerable groups such as the elderly or the disabled has greatly driven the growth of the electric-assisted mobility device market. However, such mobile devices generally require a certain operating capability, which limits the range of vulnerable groups who can use the device and increases the cost of learning. Therefore, autonomous driving technology needs to be introduced to make mobility easier for a wider range of vulnerable groups to meet their needs of work and leisure in different environments. This study uses mini PC Odyssey, Velodyne Lidar VLP-16, electronic device and Linux-based ROS program to realize the functions of working environment recognition, simultaneous localization, map generation and navigation of electric powered mobile devices for vulnerable groups. This autonomous driving mobility device is expected to be of great help to the vulnerable who lack the immediate response in dangerous situations.

• 전자공학회논문지SC
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• 제47권3호
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• pp.5-12
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• 2010

천장의 반복 무늬를 이용하여 로봇의 방향과 위치를 계산하는 새로운 알고리즘을 제안하였다. 방향 계산을 위해서 천장 영상으로부터 검출한 직선과 로봇의 현재 방향 간의 상대 각도를 계산한 후, 천장무늬에 포함된 여러 기준 직선의 방향들에 상기 상대각도를 더하여 로봇의 절대방향 후보 집합을 구성한다. 로봇 방향은 이 절대방향 후보 집합 중, 이전의 로봇 방향과 가장 가까운 방향으로 결정한다. 로봇의 위치도, 영상에서의 격자점의 화소 위치를 이용하여 로봇의 격자점과 로봇 간의 상대위치를 계산 한 후, 이전 로봇 주변의 격자점들에 상기 상대위치 벡터를 더하여 절대 위치 후보 집합을 구성하며, 이들 중 이전 로봇의 위치와 가장 가까운 위치를 현재 로봇 위치로 결정한다. 제안한 알고리즘을 이용하여 구한 위치 및 방향의 정확성을 검증하기 위한 실험을 수행하였다.

• 제어로봇시스템학회논문지
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• 제17권2호
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• pp.164-170
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• 2011

This paper proposes a novel monocular vision-based SLAM (Simultaneous Localization and Mapping) method using both position and orientation information of ceiling lamps. Conventional approaches used corner or line features as landmarks in their SLAM algorithms, but these methods were often unable to achieve stable navigation due to a lack of reliable visual features on the ceiling. Since lamp features are usually placed some distances from each other in indoor environments, they can be robustly detected and used as reliable landmarks. We used both the position and orientation of a lamp feature to accurately estimate the robot pose. Its orientation is obtained by calculating the principal axis from the pixel distribution of the lamp area. Both corner and lamp features are used as landmarks in the EKF (Extended Kalman Filter) to increase the stability of the SLAM process. Experimental results show that the proposed scheme works successfully in various indoor environments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.343-345
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• 2007

This paper proposes an inertial navigation system(INS) with which a biped robot can determine his position, velocity, posture, etc. The proposed system provides the information of robots independently without using any outer signals. The defect of the algorithm is the en'or accumulation as the robot increases the mobile range. However, in this application the problem is not so critical because the working space is small and operation period of the robots is relatively short. With the proposed INS system biped robots obtain enhanced intelligence to execute their tasks. The structure and theoretical backgrounds are utilized to design the INS system. The method for application of INS system to biped robots has been illustrated.

• 제어로봇시스템학회논문지
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• 제17권3호
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• pp.277-282
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• 2011

This paper describes a sensor fusion-based semantic map building which can improve the capabilities of a mobile robot in various domains including localization, path-planning and mapping. To build a semantic map, various environmental information, such as doors and cliff areas, should be extracted autonomously. Therefore, we propose a method to detect doors, cliff areas and robust visual features using a laser scanner and a vision sensor. The GHT (General Hough Transform) based recognition of door handles and the geometrical features of a door are used to detect doors. To detect the cliff area and robust visual features, the tilting laser scanner and SIFT features are used, respectively. The proposed method was verified by various experiments and showed that the robot could build a semantic map autonomously in various indoor environments.

• 제어로봇시스템학회논문지
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• 제18권5호
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• pp.419-425
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• 2012

This paper presents an approach to implement the behaviors of multi-robots responding to user's input characters. The robots are appropriately displaced to express any input characters. Using our method, any user can easily and friendly control multirobots. The responses of the robots to the user's input are intuitive. We utilize the centroidal Voronoi algorithm and the continuoustime Lloyd algorithm, which have popularly been used for the optimal sensing coverage problems. Collision protection is considered to be applied for real robots. LED sensors are used to identify positions of multi-robots. Our approach is evaluated through experiments with five mobile robots. When a user draw alphabets, the robots are deployed correspondingly. By checking position errors, the feasibility of our method is validated.