• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.479-482
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• 2005

본 연구는 알루미늄 단조 라인의 가열로 컨베이어에 적용된 6관절 이송용 로봇에 Machine Vision System을 구축 한 것으로 이송용 로봇이 작업 대상물을 적재하기 위한 위치정보를 획득하고 재처리하여 로봇 컨트롤러에 제공하는 비주얼가이던스 기법을 연구하여 이를 적용하였다. 적용된 Machine Vision System이 실제 구동에 있어서 안정함을 확인하였다. Machine Vision System에 적용된 CCD 센서로는 Sony사의 XC-HR50이 적용되었으며 Frame Grabber는 Matrox Meter II 카드가 적용되었다. Machine Vision System 제어기로는 범용PC(2.4Ghz, Windows 2000)를 사용하였으며 제어Software는 Microsoft 사의 Visual Basic 6.0 version을 사용하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.887-889
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• 2022

화재로 발생하는 산업시설의 인명·재산 피해를 줄이고 기존 소방 설비의 단점을 보완하는 소방 로봇을 제안한다. 소방 로봇은 무인 시스템으로 설계되었으며 6개의 핵심 기능인 화재 감지, 화재 진압, 현장 이동, 화재 알림, 소방서 신고, 현장 모니터링으로 구성된다. 로봇의 구성은 구동부, 제어부, 소화부로 이루어져 있으며, 각 구성 중 일부를 선정하고 테스트 통하여 화재 진압에 유효함을 증명하였다.

• Journal of the KSME
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• v.44 no.6
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• pp.48-52
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• 2004

과거 10여 년 간 Electro-Active Polymer(EAP) 분야는 큰 변형을 낼 수 있는 지능재료들이 출현함에 따라 인공근육을 만들 수 있는 가능성으로 인해 많은 관심이 모아지고 있다. EAP는 외부의 자극에 따라 큰 변위를 생성할 뿐만 아니라 근육과 같이 탄력성이 있는, 다른 재료기술들이 낼 수 없는 특성과 성능을 가지고 있다. EAP가 갖는 생체근육과 같은 작동을 할 수 있는 가능성은 곧 공상과학의 꿈을 이루고자하는 희망을 갖게 하며 인류의 문명발전에 크게 기여할 것이다. EAP는 차세대 마이크로 로봇, 오락산업 또는 초소형 비행체의 구동과 같은 인공근육 작동기의 응용분야를 창출하고 있다. EAP 작동기의 응용성은 폭넓으며 새로운 기술혁신의 기대를 불러 일으키고 있다. (중략)

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.6
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• pp.1497-1508
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• 1993

Real-time mobile robot controllers usually have been designed focused on control theory without paying attention to the importance of system integration. This paper demonstrates that autonomous mobile robots require a real-time controller with a wide range of capabilities in addition to control theory. An architectural frame work supporting these capabilities has been designed in actual hardware environments. Individual modules such as a path planner, a path tracking controller, position estimators, wheel controllers and other cruical elements have been successfully integrated into the control system using this frame work. The overall performance of the system was investigated via a series of tracking experiments with a prototype mobile robot named LCAR deveoped in the laboratory. The context of the research involves the architecture, its implementation and experimental results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.8
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• pp.1638-1644
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• 2002

A novel locomotion using the pneumatic impulsive actuator was proposed for robotic colonoscope. This locomotion showed good moving performance in the environment of rigid pipe, however, the displacement per one impact(step displacement) is greatly reduced due to the low stiffness and high damping characteristics of the colon. Therefore, the modeling technique based on spring and damping system is studied to predict the step displacement and some parametric studies are carried out to investigate main parameters that influence the step displacement of locomotion. Based on simulation result, a new locomotion to control the resistance force is suggested and fabricated. Through the experiment on the colon, the usefulness of modeling technique is confirmed and successful improvement of moving characteristics is achieved.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.1
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• pp.9-16
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• 2004

In this paper, we propose a robust controller for robot manipulators with parametric uncertainties using feature-based visual servo control system. In order to improve trajectory error of the robot manipulators due to the parameter variation, integral action is included in the dynamic control of part in inner subroutine of the control system. This integral action also reduces feature error in the steady state. The stability analysis of the closed-loop system is shown by the Lyapunov method. The effectiveness of the proposed method is shown by simulation and experimental results on the 5 link robot manipulator with two degree of freedom.

• Journal of Advanced Navigation Technology
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• v.16 no.4
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• pp.586-592
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• 2012

One approach of the control of a nonlinear system that has gained some success employs a fuzzy structure in cooperation with a neural network(ANFIS). The traditional ANFIS can only model and control the process in single-dimensional output nature in spite of multi-dimensional input. The membership function parameters are tuned using a combination of least squares estimation and back-propagation algorithm. In the case of a mobile robot, we need to drive left and right wheel respectively. In this paper, we proposed the control system architecture for a mobile robotic system that employs the 2-input 2-output ANFIS controller for trajectory tracking. Simulation results and preliminary evaluation show that the proposed architecture is a feasible one for mobile robotic systems.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.3
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• pp.6-12
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• 2011

Electric vehicles and robots are real-time distributed control systems composed of multiple drive subsystems using micro controller units. Each control subsystem should be modular, compact, power saving, interoperable and fault tolerable in order to be incorporated into the networked real-time distributed control system. Under the networked real-time distributed control the synchronization problem can be occurred to the position and orientation tracking control due to the load variance, mismatch and time delay between the multiple drive subsystems. This paper suggests two types of position synchronization control of the single link manipulators. One of them is composed of cross controller, Kalman filter and disturbance observer, and the other uses the generation of target trajectories to minimize the gradient vector of the scalar function which is composed of the sum of square errors between the reference input vector and the output vectors. The availability of the proposed control schemes is shown through the control experiments.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.3 s.174
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• pp.653-660
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• 2000

The automatization by industrial robot of today is merely rely on to the simple position repeating works, but requirements of research and development to the force control which would adapt positively to various restriction or contacting works to environment. In this paper, a learning control algorithm using, neural networks is proposed for the position and force control by a direct-drive robot. The proposed controller is the feedback controller to which the learning function of neural network is added on to and has a character of improving controller's efficiency by learning. The effectiveness of the proposed algorithm is demonstrated by the experiment on the hybrid position and force control of a parallelogram link robot with a force sensor.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.2
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• pp.125-130
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• 2001

This paper presents an indirect field-oriented (IFO) induction motor position servo drives which uses the model following adaptive controller with the artificial neural network(ANN)-based rotor resistance estimator. The model reference adaptive system(MRAS)-based 2-layer ANN estimates the rotor resistance on-line and a linear model-following position controller is designed by using the estimated the rotor resistance value. At the end, a fuzzy logic system(FLS) is added to make the position controller robust to the external disturbances and the parameter variations. The simulation results show the effectiveness of the proposed method.