• 한국정밀공학회지
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• 제20권11호
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• pp.171-179
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• 2003

This paper presents a rehabilitation exercise system which utilizes a 6 DOF robot as a motion generator. This system was proposed for a stroke patient or a patient who has hemiplegia. A master-slave system was designed to exercise either paralysis or abnormal limb by using normal limb motion. The study on the human body was applied to calculate the motion range of elbows and shoulders. In addition, a force-torque sensor was applied to the slave robot to estimate the rehabilitation extent of the patient. Therefore, the stability of the rehabilitation robot could be improved. By using the rehabilitation robot. the patients could exercise by themselves without assistance. In conclusion, the proposed system was verified by computer simulations and system experiment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.302-305
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• 1996

This paper presents a visual servoing combined by Neural Network with optimal structure and predictive control for robotic manipulators to tracking or grasping of the moving object. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we want to predict the updated position of the object. The Kalman filter is used to estimate the motion parameters, namely the state vector of the moving object in successive image frames, and using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. The validity and effectiveness of the proposed control scheme and predictive control of moving object will be verified by computer simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1269-1271
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• 1996

This paper presents a visual servoing combined by evolutionary algorithms and neural network for a robotic manipulators to control position and orientation of the end-effector. Using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we generate the control input to agree the target image, to realize the visual servoing. The validity and effectiveness of the proposed control scheme will be verified by computer simulations.

• 한국정밀공학회지
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• 제16권8호
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• pp.186-192
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• 1999

This paper introduces a study of a method for the forward kinematic analysis, which finds the 6 DOF motions and velocities from the given six cylinder lengths in the Stewart platform. From the viewpoints of kinematics, the solution for the inverse kinematic is easily found by using the vectors of the links which are composed of the joint coordinates in base and plate frames, to act contrary to the serial manipulator, but forward kinematic is difficult because of the nonlinearity and complexity of the Stewart platform dynamic equation with the multi-solutions. Hence we, first in this study, introduce the linear estimator using the Luenberger's observer, and the estimator using the nonlinear measured model for the forward kinematic solutions. But it is difficult to find the parameter of the design for the estimation gain or to select the estimation gain and the constant steady state error exists. So this study suggests the estimator with the estimation gain to be learned by the neural network with the structure of multi-perceptron and the learning method using back propagation and shows the estimation performance using the simulation.

• 전자공학회논문지SC
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• 제42권1호
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• pp.1-11
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• 2005

본 연구에서는 다양한 재료의 시트(Sheet)를 각각 절단하여 적층하는 방법으로 기존 적층조형법과는 다른 쾌속 임의형상제작 시스템인 CAFL/sup VM/(Computer Aided Fabrication of Lamination for Various Material)을 제안한다. 이러한 조형 방법은 가공 속도를 빠르게 하며 복잡한 후처리 과정을윽 대폭 줄일 수 있고, 여러 가지 재료가 사용 가능한 장점을 지니고 있다. 이러한 목적으로 개발된 2자유도의 X-Y테이블 형태의 CAFL/sup VM/은 레이저빔으로 시트(Sheet)를 절단, 적층하여 조형물을 완성하는 새로운 고속적층 시스템으로 가능성을 검증하였다. 하지만 2자유도 시스템은 X-Y 평면을 이동하는 작업공간에 수직으로 레이저 가공이 이루어지는 방법으로, 조형된 사물의 표면에 계단 형상이 나타나는 표면정밀도상의 문제점을 드러낸다. 이러한 문제점을 해결하고자 2자유도에 3자유도를 추가한 5자유도 시스템을 제안하여 레이저의 경사절단이 가능하게 함으로서 조형된 사물의 표면 정밀도를 높이고, 일정한 패턴의 모양을 갖는 조형물 가공의 경우 여러 시트(Sheet)가 적층되는 부분을 한번에 가공할 수 있도록 하여 보다 빠르고 정밀한 5자유도 매니퓰레이터 CAFL/sup VM/ 시스템을 설계한다. 즉, 정속경로제어와 경사각절단제어를 구현하고 그 외에 수반된 자동화 CAFL/sup VM/ 시스템을 구현하는 것이 본 논문의 목적이다.

• Journal of Biosystems Engineering
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• 제33권3호
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• pp.186-195
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• 2008

In this paper, a prototype tele-operative system with a mobile base was developed in order to automate cultivation of house melon. A man-machine interactive hybrid decision-making system via tele-operative task interface was proposed to overcome limitations of computer image recognition. Identifying house melon including position data from the field image was critical to automate cultivation. And it was not simple especially when melon is covered partly by leaves and stems. The developed system was composed of 5 major modules: (a) main remote monitoring and task control module, (b) wireless remote image acquisition and data transmission module, (c) three-wheel mobile base mounted with a 4 dof articulated type robot manipulator (d) exchangeable modular type end tools, and (e) melon storage module. The system was operated through the graphic user interface using touch screen monitor and wireless data communication among operator, computer, and machine. Once task was selected from the task control and monitoring module, the analog signal of the color image of the field was captured and transmitted to the host computer using R.F. module by wireless. A sequence of algorithms to identify location and size of a melon was performed based on the local image processing. Laboratory experiment showed the developed prototype system showed the practical feasibility of automating various cultivating tasks of house melon.