• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1283-1289
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• 2016

In this paper, we propose a new localization system using ceiling outlines. We acquire the entire ceiling image by using fisheye lens camera, and extract the lines by binarization and segmentation. The optical flow algorithm is then applied to identify the ceiling region from the segmented regions. Finally we obtain the position and orientation of the robot by the center position and momentum of ceiling region. Since we use the fully detected outlines, the accuracy and reliability of the localization system is improved. The experimental result are finally presented to show the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.625-630
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• 1987

Technology associated with power plant control system has been heavily rely on foreign technology. The main reason is that the system has tomaintain stringent reliability and stability. Localization of this system can be started from localization of modules necessary for maintenance and repair in hydraulic and thermal power plant. Gradually and eventually system engineering capability can be built up to design and develop nuclear power plant control system through technology accumulation. Methods are presented to achieve this goal.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.12
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• pp.2308-2312
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• 2008

As power plant facilities are being deteriorated, their safety is getting more important, and more routine surveillance is being required. For this purpose, this paper presents an indoor localization system for field robot system which performs the surveillance of power plant facilities instead of human workers from the viewpoint of the workers' safety and work efficiency.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.367-371
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• 2015

In this paper, a novel localization method for a monocular camera is proposed by using a feature-based probabilistic map. The localization of a camera is generally estimated from 3D-to-2D correspondences between a 3D map and an image plane through the PnP algorithm. In the computer vision communities, an accurate 3D map is generated by optimization using a large number of image dataset for camera pose estimation. In robotics communities, a camera pose is estimated by probabilistic approaches with lack of feature. Thus, it needs an extra system because the camera system cannot estimate a full state of the robot pose. Therefore, we propose an accurate localization method for a monocular camera using a probabilistic approach in the case of an insufficient image dataset without any extra system. In our system, features from a probabilistic map are projected into an image plane using linear approximation. By minimizing Mahalanobis distance between the projected features from the probabilistic map and extracted features from a query image, the accurate pose of the monocular camera is estimated from an initial pose obtained by the PnP algorithm. The proposed algorithm is demonstrated through simulations in a 3D space.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1083-1097
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• 2018

This paper presents a novel range-free localization algorithm based on quantum particle swarm optimization. The proposed algorithm is capable of estimating the distance between two non-neighboring sensors for multi-hop heterogeneous wireless sensor networks where all nodes' communication ranges are different. Firstly, we construct a new cumulative distribution function of expected hop progress for sensor nodes with different transmission capability. Then, the distance between any two nodes can be computed accurately and effectively by deriving the mathematical expectation of cumulative distribution function. Finally, quantum particle swarm optimization algorithm is used to improve the positioning accuracy. Simulation results show that the proposed algorithm is superior in the localization accuracy and efficiency when used in random and uniform placement of nodes for heterogeneous wireless sensor networks.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.955-961
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• 2006

The global ultrasonic system for the self-localization of a mobile robot consists of several ultrasonic transmitters fixed at some reference positions in the global coordinates of robot environment. By activating the ultrasonic transmitters, the mobile robot is able to get the distance to the ultrasonic transmitters and compute its own position in the global coordinate. Due to the limitation on the ultrasonic signal strength and beam width as well as the environmental obstacles however, the ultrasonic signals from some generator may not be transmitted to the robot. Thus, instead of activating the all ultrasonic transmitters, it is necessary to select some ultrasonic generators to activate based on the current robot position. In this paper, we propose a selective activation algorithm for self-localization with the global ultrasonic system. The selective activation algorithm gets the meaningful ultrasonic data at every sampling instants, which results in the faster and more accurate response of the self-localization than the conventional sequential activation. Through the self-localization and path following control, we verify the effectiveness of the proposed selective activation algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.597-598
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• 2009

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.111-112
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• 2007

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.33-34
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• 2010

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.9
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• pp.866-871
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• 2010

Gait analysis is essential for leg diagnosis and rehabilitation for the patients, the handicapped and the elderly. The use of 3D motion capture device for gait analysis is very common for gait analysis. However, this device has several shortcomings including limited workspace, visibility and high price. Instead, we developed gait estimation system using gyroscopes. This system provides gait information including the number of gaits, stride and walking distance. With four gyroscope (one for each leg's thigh and calf) outputs, the proposed gait modeling estimates the movements of the hip, the knees and the feet. Complete pedestrian localization is implemented with gait information and the heading angle estimated from the rate gyro and the magnetic compass measurements. The developed system is very useful for diagnosis and the rehabilitation of the pedestrian at the hospital. It is also useful for indoor localization of the pedestrians.