• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.335-338
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• 2020

주로 맵 빌딩 테스트는 불안정한 환경이 아닌 안정된 환경을 조성한 후에 이루어진다. 본 논문에서는 인위적인 안정된 환경이 아닌 불안정한 환경에서 맵 빌딩을 테스트한다. 맵 빌딩 테스트를 위하여 터틀봇3 버거를 사용한다. 터틀봇3의 라이더 센서를 이용하여 맵 빌딩을 진행한다. 터틀봇3는 라즈베리파이로 제어되며 맵 빌딩과 터틀봇3 제어를 위해서는 ROS를 사용한다. 터틀봇3는 우분투와 ROS가 설치된 컴퓨터와 네트워크 통신을 하며 맵 빌딩을 한다. 불안정한 환경에서 맵빌딩이 동작 및 오동작하는 모습을 확인하였으며, 향후 이를 보완하기 위한 방향을 제시한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1057-1059
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• 2011

본 논문은 홈/빌딩네트워크 환경에서 에너지 절감을 위한 효율적인 관리방법을 제안한다. 보다 상세하게는 먼저 가정(home)이나 빌딩(building) 등의 건물에서 사용되는 에너지의 정보를 수집하여 이들에 관한 통합 자원 관계맵을 구축한다. 구축된 자원 관계맵을 기반으로 실제 에너지 사용량과 금액을 계산하여 알려줄 뿐만 아니라 에너지의 예측 사용량과 금액을 계산하여 사용자에게 알려준다. 이와 더불어 사용량이 많을 경우 각 자원별 뿐만 아니라 지역, 사용량, 타입, 특성과 같은 다양한 그룹별로 에너지 절감 방안을 제시함으로써 사용자가 실제로 에너지를 효과적으로 절감할 수 있도록 하는 자원관계맵 기반의 에너지 절감방안을 제안한다.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.256-262
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• 2004

A key component of an autonomous mobile robot is to localize itself and build a map of the environment simultaneously. In this paper, we propose a vision-based localization and mapping algorithm of mobile robot using fisheye lens. To acquire high-level features with scale invariance, a camera with fisheye lens facing toward to ceiling is attached to the robot. These features are used in mP building and localization. As a preprocessing, input image from fisheye lens is calibrated to remove radial distortion and then labeling and convex hull techniques are used to segment ceiling and wall region for the calibrated image. At the initial map building process, features we calculated for each segmented region and stored in map database. Features are continuously calculated for sequential input images and matched to the map. n some features are not matched, those features are added to the map. This map matching and updating process is continued until map building process is finished, Localization is used in map building process and searching the location of the robot on the map. The calculated features at the position of the robot are matched to the existing map to estimate the real position of the robot, and map building database is updated at the same time. By the proposed method, the elapsed time for map building is within 2 minutes for 50㎡ region, the positioning accuracy is ±13cm and the error about the positioning angle of the robot is ±3 degree for localization.

• Journal of IKEEE
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• v.9 no.1 s.16
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• pp.7-18
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• 2005

A key component of an autonomous mobile robot is to localize itself accurately and build a map of the environment simultaneously. In this paper, we propose a vision-based mobile robot localization and mapping algorithm using scale-invariant features. A camera with fisheye lens facing toward to ceiling is attached to the robot to acquire high-level features with scale invariance. These features are used in map building and localization process. As pre-processing, input images from fisheye lens are calibrated to remove radial distortion then labeling and convex hull techniques are used to segment ceiling region from wall region. At initial map building process, features are calculated for segmented regions and stored in map database. Features are continuously calculated from sequential input images and matched against existing map until map building process is finished. If features are not matched, they are added to the existing map. Localization is done simultaneously with feature matching at map building process. Localization. is performed when features are matched with existing map and map building database is updated at same time. The proposed method can perform a map building in 2 minutes on $50m^2$ area. The positioning accuracy is ${\pm}13cm$, the average error on robot angle with the positioning is ${\pm}3$ degree.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.938-941
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• 2007

The most of humonoid robot which is utility for the existing industry use a magnetic sensor and infrared sensor and route in their courses consist of guidance or the optical tape. It is impossible to establish courses in the room that is the working environment of the humonoid robot. So It has need of the development of the flexible humonoid robot. In this paper, we describe the map building method combined with ultrasonic sensors and infrared sensor additionally.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.2075-2076
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• 2008

복잡 다기능화 사회를 효율적으로 운영하기 위한 각종 관련 산업이 발전하면서 초초고층빌딩의 건설이 확대될 예정이다. 일반적으로 1,000 ft를 넘는 빌딩을 '초초고층 빌딩'이라 하며, 고부가가치 시설인 초초고층빌딩 전기설비의 국내 기술수준은 기본설계 자료 외국 의존, 기본 성능보증을 위한 여건 미흡, 초초고층빌딩 건설 관련 전기설비시공 경험의 부족 등으로 인하여 선진국의 의존도가 높다. 따라서, 초초고층 빌딩 전기설비 성능 중심의 시공기술 개발 등이 절실하게 필요하다. 본 연구에서는 국내 외 초초고층 빌딩의 전기설비 성능 중심 기준 현황, 시공기술의 로드맵 작성을 위한 기술동향 및 환경을 조사, 분석하였으며, 또한 전기설비공사 성능 중심 로드맵 작성 및 요소기술을 도출하였다. 향후 국내의 성능관련 법규 및 기준을 마련할 필요성이 있으며, 기법 개발과 더불어 실용 시스템에 구축하는 연구가 필요할 것으로 사료된다.

• Archives of design research
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• v.18 no.2 s.60
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• pp.155-164
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• 2005

Home-service robots need to have sufficient spatial information about the surroundings for interacting with human intelligently and performing services efficiently. It is very important to investigate the efficient interaction style that supports map building task through human-robot collaboration. We first analyzed map building task with a cleaning robot and drew 4 design factors and tentative solutions, including map building procedure (task-preferred procedure/space- preferred procedure), LCD display installation (robot/robot+remote control), navigation method (push type/pull type), feedback modality(GUI/GUI+TTS). The design factors and tentative solutions were defined as independent variables and levels. This research investigated how those variables affect to the human task performance and behavior in map building tast. 8 kinds of experiment prototypes were built and usability test among 16 house wives was conducted for acquiring empirical data. As the experiment result, in terms of map building procedure, space-preferred procedure indicated better task performance than task-proffered procedure as we expected. For the LCD display installation factor, remote control with LCD display indicated higher task performance and subjective satisfaction. In robot navigation method, it was very difficult to find a significant difference between push type and pull type which contrary to our expectation. In fact, push type indicated higher subjective satisfaction. Also in feedback modality, we have acquired negative feedback an additional TTS operation guidance. It seems that robot's autonomy before achieving spatial information is rudiment condition which means users are just interacting with a mobile appliance. Thus they prefer remote-control-based interaction style in robot map building process as they used in traditional appliance control.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1475-1478
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• 2004

This paper describes map building for the path planning to avoid obstacles with vision sensor and ultrasonic sensor. We get the 2 dimensional information from the processed images of CCD sensor and 1 dimensional range information from ultrasonic sensor. I proposed a way to generate the map which contains these two kinds of information in the program. And we made the biped robot which have 20 DOF with these sensors and get good experimental result to prove the validity of the proposed method.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.2
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• pp.351-358
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• 2008

This paper introduces a map building algorithm which can collect environmental information using ultrasonic sensors. And also this paper discusses a traveling algorithm using environmental information which leads to the map building algorithm. In order to accomplish the proposed traveling algorithm, this paper additionally discusses a path revision algorithm. For verifying the proposed algorithms, several experiments are executed using a mobile robot physically designed in this paper. The conclusion is that the proposed algorithm is very effective and is applicable to mobile robots especially requiring a low-cost environmental information.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.1
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• pp.192-199
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• 2008

In order for a mobile robot to move under unknown or uncertain environment. it is very important to collect environmental information. This paper suggests a traveling algorithm which leads to the map building algorithm and the $A^*$ algorithm under the assumption that environmental information should already be collected. In order to apply the proposed traveling algorithm to a real mobile robot. this paper additionally discusses a path amendment algorithm. For the purpose of verifying the proposed algorithms, several simulations are executed based on a UI host program-based simulation interface and an experiment is executed using a mobile robot under a real unknown environment.