• Journal of The Korean Association of Information Education
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• v.12 no.1
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• pp.57-63
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• 2008

This study uses the identification which is one of the critical components of psychological mechanism and enables replacing one's own self because of the needs of self-expression(disclosure) and creation. The study aims to improve educational effects using the realistic by increasing sense of the virtual reality and the attention. After the computer-based contents were developed and converted to be applied into robot, and then the contents were combined the student's photo and the avatar using automatic loading. Finally each one of the contents was applied to the students. The results of the investigation indicated that there were significant effects of the contents based on identification. In other words, the contents effect on student's attention, but not their academic achievement. The study could find the effect of the identification's application using the educational robot. We suggested that improving technical ability of the augmented virtuality as a face-detection and sensitive interaction may lead to the specific suggestions for educational effects for further research.

• Journal of Sensor Science and Technology
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• v.14 no.4
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• pp.278-285
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• 2005

This paper describes techniques of camera calibration and artificial landmarks detection for the automatic charging of a mobile robot, equipped with a fish-eye camera in the direction of its operation for movement or surveillance purposes. For its identification from the surrounding environments, three landmarks employed with infrared LEDs, were installed at the charging station. When the robot reaches a certain point, a signal is sent to the LEDs for activation, which allows the robot to easily detect the landmarks using its vision camera. To eliminate the effects of the outside light interference during the process, a difference image was generated by comparing the two images taken when the LEDs are on and off respectively. A fish-eye lens was used for the vision camera of the robot but the wide-angle lens resulted in a significant image distortion. The radial lens distortion was corrected after linear perspective projection transformation based on the pin-hole model. In the experiment, the designed system showed sensing accuracy of ${\pm}10$ mm in position and ${\pm}1^{\circ}$ in orientation at the distance of 550 mm.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.259-266
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• 2015

This study presents new scheme for various walking pattern of biped robot under the limitted enviroments. We show that the neural network is significantly more attractive intelligent controller design than previous traditional forms of control systems. A multilayer backpropagation neural network identification is simulated to obtain a learning control solution of biped robot. Once the neural network has learned, the other neural network control is designed for various trajectory tracking control with same learning-base. The main advantage of our scheme is that we do not require any knowledge about the system dynamic and nonlinear characteristic, and can therefore treat the robot as a black box. It is also shown that the neural network is a powerful control theory for various trajectory tracking control of biped robot with same learning-vase. That is, we do net change the control parameter for various trajectory tracking control. Simulation and experimental result show that the neural network is practically feasible and realizable for iterative learning control of biped robot.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.4
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• pp.427-433
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• 2019

This paper propose a fuzzy inference model for map building and navigation for a mobile robot with an active camera, which is intelligently navigating to the goal location in unknown environments using sensor fusion, based on situational command using an active camera sensor. Active cameras provide a mobile robot with the capability to estimate and track feature images over a hallway field of view. In this paper, instead of using "physical sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data. Command fusion method is used to govern the robot navigation. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a command fusion technique is introduced, where the sensory data of active camera sensor for navigation experiments are fused into the identification process. Navigation performance improves on that achieved using fuzzy inference alone and shows significant advantages over command fusion techniques. Experimental evidences are provided, demonstrating that the proposed method can be reliably used over a wide range of relative positions between the active camera and the feature images.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.296-303
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• 2011

This paper describes a game called the "robot hopscotch game" which uses mobile robots. In this game, a mobile robot moves on a board which consists of a number of square cells. This is similar to the usual hopscotch game in which a human player hops through a course on the ground. In the robot hopscotch game, each cell has a visual light communication unit. The unit sends identification signal and the robot which moves over the cell receives the signal for location recognition. In the game, a human player or a human operator competes with a robot or other human player on how accurately and fast they move to a goal location passing through the given way point cells. People played the game at the RoboWorld 2008 which was held at COEX Seoul, on 16th to 20th of October 2008. The replies to the questionnaire to the users show that users have interests on the game and expect further expansion of robot use though they are not in favor of the robot's outlook and they feel inconvenience on manipulation of the robot.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.728-734
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• 1999

An on-line system identification scheme of unknown system is proposed based on a Laguerre models representation. The unknown parameters are detemined using recursive least-square identification. The proposed method have the advantage that an unknown system can be modelled without structural knowledge and assumption about the true model order and time delay. Therefore, the proposed method can make the design procedure very when compared to widely-used conventional method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.61-64
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS32OC50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator. In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters are determined by the pole-placement method. Performance of self-tuning adaptive controller is illustrated by the simulation and experiment for a SCARA robot.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.4
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• pp.213-221
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• 2017

Utilizing the existing polishing robot prevents unrestricted change of direction, driving, and identification of driving pathway. To overcome this barrier, driving mechaism has been designed with Omniwheels with encoders and RSSI method of beacon system has been utilized to identify the driving path by position recognition. Due to the wheel characteristics, the Omniwheel mobile robot generates greater slip than the conventional mobile robot, which reduces its driving accuracy. Therefore, to improve the driving accuracy, the localization is conducted through the fusion of encoder and RSSI of beacon data to compensate for the errors caused by Dead Reckoning and inaccuracy of sensors. Finally, the localization accuracies of the proposed and conventional indoor localization method are compared to show effectiveness of the proposed driving control for a polishing robot.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.451-456
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• 2005

In this paper, we propose the navigation control method for intelligent robot using messy genetic algorithm. The fuzzy controller design for navigation of the intelligent robot was dependant on expert's knowledge. But, the parameters of the fuzzy logic controller obtained from expert's control action may not be outimal. In this paper, to solve the above problem, we propose the identification method to automatically tune the number of fuzzy rule and parameters of memberships of fuzzy controller using mGA. Finally, to show and evaluate the generality and feasibility of the proposed method, we provides some simulations for wall following navigation of intelligent robot.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.304-313
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• 2005

The robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robot need to recognize his position and direction for intelligent performance in an unknown environment. And the mobile robots may navigate by means of a number of monitoring systems such as the sonar-sensing system or the visual-sensing system. Notice that in the conventional fusion schemes, the measurement is dependent on the current data sets only. Therefore, more of sensors are required to measure a certain physical parameter or to improve the accuracy of the measurement. However, in this research, instead of adding more sensors to the system, the temporal sequence of the data sets are stored and utilized for the accurate measurement. As a general approach of sensor fusion, a UT -Based Sensor Fusion(UTSF) scheme using Unscented Transformation(UT) is proposed for either joint or disjoint data structure and applied to the landmark identification for mobile robot navigation. Theoretical basis is illustrated by examples and the effectiveness is proved through the simulations and experiments. The newly proposed, UT-Based UTSF scheme is applied to the navigation of a mobile robot in an unstructured environment as well as structured environment, and its performance is verified by the computer simulation and the experiment.