• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.744-748
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• 2007

In this paper, a new localization method of indoor mobile robot using multi IR(infrared) range sensors is proposed. Each IR range sensor detects the edge of obstacles and wall using the acquired range data. The environment map is built by the merging process of the detected edge data of each sensor. The performance of proposed system is verified by the comparison of the real environment and the detected map in experiments.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.713-716
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• 1991

This paper describes a methodology of mobile robot navigation which is designed to carry heavy payloads at high speeds to be used in FMS(Flexible Manufacturing System) without human control. Intelligent control scheme using fuzzy logic is applied to the navigation control. It analyzes sensor readings from multi-sensor system, which is composed of ultrasonic sensors, infrared sensors and odometer, for environment learning, planning, landmark detecting and system control. And it is implemented on a physical robot, AGV(Autonomous Guided Vehicle) which is a two-wheeled, indoor robot. An on-board control software is composed of two subsystems, i.e., AGV control subsystem and Sensor control subsystem. The results show that the navigation of the AGV is robust and flexible, and a real-time control is possible.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.505-508
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• 2004

Korea Aerospace Research Institute (KARI) has a plan to launch COMS for consistent monitoring of the Korean Peninsula. Korea Geostationary Ocean Color Imager (GOCI) is one of the main payloads of COMS which will provide a monitoring of ocean-colour around the Korean Peninsula from geostationary platforms. Ocean color observation from geostationary platform is required to achieve the proper spatial and temporal resolution for coastal observation mission. In this paper the characteristics of GOCI and LEO sensors are discussed. GOCI will provide the measurement data of 6 visible channels and 2 near-infrared channels (400nm ~ 900nm). The integration time and aperture diameter required to achieve the SNR specification of KGOCI are analyzed.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2019-2023
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• 2005

In this paper, an autonomous omni directional cleaning robot which recognizes an obstacle and a battery charger is introduced. It utilizes a robot vision, ultra sonic sensors, and infrared sensors information along with appropriate algorithm. Three omni-directional wheels make the robot move any direction, enabling a faster maneuvering than a simple track typed robot. The robot system transfers command and image data through Blue-tooth wireless modules to be operated in a remote place. The robot vision associated with sensor data makes the robot proceed in an autonomous behavior. An autonomous battery charger searching is implemented by using a map-building which results in overcoming the error due to the slip on the wheels, and camera and sensor information.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.104.3-104
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• 2001

This paper develops a control approach to generic formation tasks of multiple mobile robots with inaccurate sensor information. Inaccurate sensor information means that all the robots have only local sensors which cannot accurately measure absolute distances and directions of objects. The control logic is developed considering generic situations in order to adapt to increasing number of robots which participate in the formation. Petri nets are used for modeling and design of the control logic, which can visualize the control models and make it easy to check the states of each robot. Physically homogenous mobile robots are designed and built to evaluate the developed logic. Each robot is equipped with eighteen infrared sensors and a UHF transceiver module. The developed control ...

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.495-500
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• 2002

Recently, a service robot industry outstands as an up and coming industry of the next generation. Specially, there are so many research in self-steering movement(SSM). In order to implement SSM, robot must effectively recognize all around, detect objects and make a surrounding map with sensors. So, many robots have a sonar and a infrared sensor, etc. But, in these sensors, We only know informations about between the robot and the object as well as resolution faculty is of inferior quality. In this paper, we will introduce new algorithm that recognizes objects around robot and makes a two dimension surrounding map with a omni-direction vision camera and two stereo vision cameras.

• Journal of Welding and Joining
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• v.23 no.4
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• pp.53-58
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• 2005

We designed a weld monitoring system with UV and IR sensors using a embedded DSP controller for implementing a distribution system; running stand alone and communication with outside by industrial standard protocols. Also this system provided a USB port in order to be acquiring data in PC. The user interface program in PC visualized the IR and W data in time, frequency and state space. A correlation of IR and UV signals showed closely related to weld quality. A rapid change of geometry can be found through a moving average filter. And the average value of IR signal at an interval represented a welding width and depth. Through these results, we proposed a monitoring algorithm for a integer type DSP.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.117-124
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• 2006

In this paper, we develope the navigation system for patrol robots in indoor environment. The proposed system consists of PDA map modelling, a localization algorithm based on a global position sensor and an automatic charging station. For the practical use in security system, the PDA is used to build object map on the given indoor map. And the builded map is downloaded to the mobile robot and used in path planning. The global path planning is performed with a localization sensor and the downloaded map. As a main controller, we use PXA270 based hardware platform in which embedded linux 2.6 is developed. Data handling for various sensors and the localization algorithm are performed in the linux platform. Also, we implemented a local path planning algorithm for object avoidance with ultra sonar sensors. Finally, for the automatic charging, we use an infrared ray system and develop a docking algorithm. The navigation system is experimented with the two-wheeled mobile robot using North-Star localization system.

• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.25-30
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• 2017

In this paper, We proposed an effective demosaicking method for single chip RGB-NIR sensors to recover RGB and NIR images. As the method operates in the spatial frequency domain, the frequency domain characteristics of the sampled CFA data are investigated. Using the luminance signal in the frequency domain and the chrominance signals are processed separately with different filters. The simulated images using the real images are compared with other state-of-art methods. As a result, the proposed demosaicking method resulted an effective calculation by a single processing which the existing alternating projection method requires repeated calculation.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.112-119
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• 2000

A die-casting junction method is usually used to manufacture the tub of an IH(induction heating) jar. If there is a very small air bubble in the junction area, the thermal conductivity is deteriorated and local overheat occurs. Such problem brings serious inferiority of the IH jar. In this paper, we propose a new method to detect such defect with simply measured thermal data. Thermal distribution of preheated tubs is obtained by scanning with infrared thermal sensors and analyzed with the statistic pattern recognition method. By defining the characteristic feature as the temperature difference between sensors and using ellipsoid function as decision boundary, a supervised learning method of genetic algorithm is proposed to obtain the required parpameters. After applying the proposed method to experiment, we have proved that the rate of recognition is high even for a small number of data set.