• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1881_1882
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• 2009

Simple quadratic potential functions for unicycle robot path planning are presented, where proposed algorithm for path planning has the different environment for each robot based on LOS(Line Of Sight) between a target and an obstacle, unlike a conventional path planning. In doing so, the proposed algorithm assumes that each swarm robot equips its own vision instead of a ceiling camera. In particular, this paper presents that each robot follows its different local leader. As a result proposed algorithm reduces local minimum problems by the help of each local leader.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.40-47
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• 2010

This paper presents a simultaneous localization and mapping (SLAM) of an indoor hallway environment using Rao-Blackwellized particle filter (RBPF) along with a line segment as a landmark. Based on the fact that fluent line features can be extracted around the ceiling and side walls of hallway using vision sensor, a horizontal line segment is extracted from an edge image using Hough transform and is also tracked continuously by an optical flow method. A successive observation of a line segment gives initial state of the line in 3D space. For data association, registered feature and observed feature are matched in image space through a degree of overlap, an orientation of line, and a distance between two lines. Experiments show that a compact environmental map can be constructed with small number of horizontal line features in real-time.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.2
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• pp.89-95
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• 2017

In this paper, we suggest the method for a mobile robot to move safely from an initial position to a goal position in the wide environment like a building. There is a problem using odometry encoder sensor to estimate the position of a mobile robot in the wide environment like a building. Because of the phenomenon of wheel's slipping, a encoder sensor has the accumulated error of a sensor measurement as time. Therefore the error must be compensated with using other sensor. A vision sensor is used to compensate the position of a mobile robot as using the regularly attached light's panel on a building's ceiling. The method to create global path planning for a mobile robot model a building's map as a graph data type. Consequently, we can apply floyd's shortest path algorithm to find the path planning. The effectiveness of the method is verified through simulations and experiments.

• 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.

• Korean Institute of Interior Design Journal
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• v.21 no.4
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• pp.12-20
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• 2012

The aim of this study is to review phenomenological characteristics in Steven Holl's architecture through his design of St. Ignatius Chapel at Seattle University. To obtain this purpose, an analytical frame based on Holl's theory of phenomenological architecture is suggested to have a systematic study for St. Ignatius chapel. This chapel can be a good example of phenomenological architecture in that it is based on the concept of 'A Gathering of Different Lights' related to phenomenology and considered perception including multi sensory (as well as vision) as primary factors from site and program interpretation to spatial configuration. Unprecedented exterior of St. Ignatius chapel reflected on characteristics and function of rooms to magnify user's spatial experiences through inducing natural light and spatial effect. Holl used various openings and screen for natural light with colors to invoke religious inspiration. He also try to give spatial depth and multi foci for experiencing space through various ceiling forms. These phenomenological features originated in client's strong will as well as appropriateness of the function of facility's religious experiences through building to the purpose of phenomenological architecture.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.359-365
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• 2008

As housing supply ratio has become over 100%, the strategic vision of government's policies has been changed from new construction to maintenance and regeneration of old architectural-structures. This fact has brought a light on the reconstruction and remodeling industries and a need for retrofit and rehabilitation techniques of existing foundation. Various methods of foundation for architectural-structures do exist. Among them, micropiling technologies are increasingly applied in foundation rehabilitation and seismic retrofitting projects. Micropiling techniques provide environmental-friendly methods for minimizing disturbance to adjacent structures, ground, and the environment. The installation is possible in restrictive area and general ground conditions. The fact that the installation procedures cause minimal vibration and noise and require very low ceiling height makes the micropiling methods to be commonly used for underpin existing structures. Specialized drilling equipment is often required to install the micropiles for existing basement facilities. This paper presents a case study in which micropiles were constructed to support a superstructure for vertical extension of existing elevator core and provide accessibility to underground parking lot. It is intended to become useful reference for the similar remodeling project.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.353-361
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• 2011

A precise embedded ultrasonic localization system is developed for autonomous mobile robots in indoor environments, which is essential for autonomous navigation of mobile robots with various tasks. Although ultrasonic sensors are more cost-effective than other sensors such as LRF (Laser Range Finder) and vision, they suffer inaccuracy and directional ambiguity. First, we apply the matched filter to measure the distance precisely. For resolving the computational complexity of the matched filter for embedded systems, we propose a new matched filter algorithm with fast computation in three points of view. Second, we propose an accurate ultrasonic localization system which consists of three ultrasonic receivers on the mobile robot and two or more transmitters on the ceiling. Last, we add an extended Kalman filter to estimate position and orientation. Various simulations and experimental results show the effectiveness of the proposed system.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.32-40
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• 2008

Since vision-based surveillance system uses a conventional camera which has a narrow field of view, it is difficult to apply it into the environment whose the ceiling is low and the monitoring area is wide. To overcome this problem, the method of increasing the number of camera causes the increase of the cost and the difficulties of camera set-up For these problems, we propose a new surveillance system based on multiple fisheye cameras which have 180 degree field of view. The proposed method handles occlusions using the homography relation between the multiple fisheye cameras. In the experiment, four fisheye cameras were set up within the area of $17{\times}14m$ at height of 2.5 m and five people wandered and crossed with one another within this area. The detection rates of the proposed system was 83.0% while that of a single camera was 46.1%.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.1
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• pp.111-116
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• 2019

The fire detectors used in the engine rooms of ships offer only a slow response to emergencies because smoke or heat must reach detectors installed on ceilings, but the air flow in engine rooms can be very fluid depending on the use of equipment. In order to overcome these disadvantages, much research on video-based fire detection has been conducted in recent years. Video-based fire detection is effective for initial detection of fire because it is not affected by air flow and transmission speed is fast. In this paper, experiments were performed using images of smoke from a smoke generator in an engine room. Data generated using LBP and GLCM operators that extract the textural features of smoke was classified using SVM, which is a machine learning classifier. Even if smoke did not rise to the ceiling, where detectors were installed, smoke detection was confirmed using the image-based technique.