• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.959-962
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• 2003

In this paper, a decentralized adaptive controller is proposed to control robot manipulators which are governed by highly nonlinear dynamic equations. The controller is computationally efficient since it does not require mathematical model or parameter values of robot manipulators. The stability of the manipulators with the controller is proved by Lyapunov theory. The results of computer simulations show that the robot manipulator system is stable, and has excellent trajectory tracking performance.

• Journal of Drive and Control
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• v.17 no.4
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• pp.170-175
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• 2020

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.8
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• pp.32-38
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• 1998

In this paper, we design a robust controller for trajectory control of n-link robot manipulators with bounded parametric uncertainties. The proposed control scheme with integral control improves tracking error due to limit of the robust feedback gains and use of continuous control input for chattering rejection. The integral of the tracking error is augmented to the error system equation and the stability of the closed-loop system is achieved. The performance of the proposed method is demonstrated by simulation on a 2-link manipulator.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.43-44
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• 2018

본 논문에서는 로봇 매니퓰레이터의 순방향 기구학 학습에 있어서 로봇의 비용적인 측면으로 인하여 실재 로봇 매니퓰레이터를 교보재로 사용하여 실습을 하기에 제한되는 환경과 교재만으로 학습하는 제한된 환경에서 학생들이 이해하는 것 뿐만 아니라 검증이나 실험을 하기가 어려운 점을 개선하기 위해서 증강현실 기반의 시뮬레이터를 제안한다 로봇 기구학에서는 주로 교재를 사용하는데 실재로 존재하는 모델보다 회전 관절(revolute joint)과 병진 관절(prismatic joint) 모형의 조합으로 모델링한다 관절의 모형을 일종의 증강현실의 마커로 사용하여 교재에서 제안하는 모델에 더해서 개인이 조합한 모델 또한 실습이 가능하도록 하는 증강현실 시뮬레이터를 제안한다.

• ICROS
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• v.13 no.2
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• pp.27-33
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• 2007

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.1
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• pp.1-9
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• 2000

In this paper, we design a robust output feedback controller for robot manipulators with bounded parametric uncertainties using high-gain observer. The proposed control scheme with integral action improves tracking error due to limit of the robust feedback gains. High-gain observer is used to solve the noise problem with the joint velocity measurement. This controller avoids the limitation on the variation of unknown parameters and guarantees the uniformly ultimate boundedness of the closed-loop system. The performance of the proposed method is demonstrated by simulation on a 2-link manipulator.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.1
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• pp.60-68
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• 1999

This paper deals with the tracking control problem of industrial robotic manipulators with unknown or changing dynamics. The proposed method makes use of multiple moodels and switching mechanism by fuzzy inference of the manipulator in an indirect adaptive controller architecture. The models used for the indmtification of the manipliator are identical, except for the initial estimates of the unknown inertial pararmeters of the manipulator and its load. The torque input that is applied to the joint actuators is determined at every instant by the identification model that best approximates the robot dynamics. Simulation results are also included to dermnstrate the improvement in the tracking perfermance when the proposed method is used.s used.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.210-213
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• 1999

In this paper, we propose a new neural network for the control of a robot manipulator The proposed neural network structure is that all of network outputs feed bark into hidden units and output units from feedback units The feedback units are only to memorize the previous activations of the hidden units and output units and can be considered to function as one-step time delays. The proposed neural network works standard back-propagation Loaming algorithm. The simulation and experiment results showed the effectiveness of using the modified neural network structure in the control of the robot manipulator.

• ICROS
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• v.10 no.4
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• pp.13-18
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• 2004

로봇(Robot)이란 단어는 1921년에 최초로 연극이름에서 사용되었고. 체코언어인 robota(강제노동)와 robotik (노동자)의 합성어이다. 이러한 로봇은 현대 사회에서 보통 산업용 로봇을 뜻한다. 곧, 공장에서 하기 힘든 반복적인 일들을 인간을 대신하여 작업하는 기계들을 가르켜 로봇이라고 하였다. 그런데 최근에 와서 컴퓨터와 각종 기계, 전자 산업이 발전하면서 로봇이라는 의미가 공장안의 매니퓰레이터에서 점차 지능적이고 인간 생활환경에서 적응하고 인간과 친근할 수 있는 지능형 로봇으로 바뀌어 가고 있다. 대표적으로 휴머노이드(Humanoid)라는 인간과 닮은 2족 보행로봇을 예로 들 수 있다. (중략)

• Journal of IKEEE
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• v.27 no.4
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• pp.610-616
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• 2023

In this paper, we implement an unmanned delivery robot system with Robot Operating System(ROS)-based mobile manipulator, and introduce the technologies employed for the system implementation. The robot consists of a mobile robot capable of autonomous navigation inside the building using an elevator and a Selective Compliance Assembly Robot Arm(SCARA)-Type manipulator equipped with a vacuum pump. The robot can determines the position and orientation for picking up a package through image segmentation and corner detection using the camera on the manipulator. The proposed system has a user interface implemented to check the delivery status and determine the real-time location of the robot through a web server linked to the application and ROS, and recognizes the shipment and address at the delivery station through You Only Look Once(YOLO) and Optical Character Recognition(OCR). The effectiveness of the system is validated through delivery experiments conducted within a 4-story building.