• Journal of Mechanical Science and Technology
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• 제18권11호
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• pp.1916-1922
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• 2004

A robust position control with the bound function of neural network structure is proposed for uncertain robot manipulators. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, and etc. Therefore, uncertainties are often nonlinear and time-varying. The neural network structure presents the bound function and does not need the concave property of the bound function. The robust approach is to solve this problem as uncertainties are included in a model and the controller can achieve the desired properties in spite of the imperfect modeling. Simulation is performed to validate this law for four-axis SCARA type robot manipulator.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 추계학술대회(한국공작기계학회)
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• pp.117-121
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• 2001

This paper presents a new approach to the calibration of a SCARA robot orientation with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. Thin prism distortion arises from imperfection in lens design and manufacturing as well as camera assembly. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.

• 한국정밀공학회지
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• 제16권7호
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• pp.66-72
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• 1999

Robot calibration is very important to improve the accuracy of robot manipulators. However, the calibration procedure is very time consuming and laborious work for users. In this paper, we propose a method of relative error compensation to make the calibration procedure easier. The method is completed by a Pi-Sigma network architecture which has sufficient capability to approximate the relative relationship between the accuracy compensations and robot configurations while maintaining an efficient network learning ability. By experiment of 4-DOF SCARA robot, KIRO-3, it is shown that both the error of joint angles and the positioning error of end effector are drop to 15$\%$. These results are similar to those of other calibration methods, but the number of measurement is remarkably decreased by the suggested compensation method.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.1114-1119
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• 1995

This paper presents the development of estimation model and control method based on the new computer vision. This proposed control method is accomplished using a sequential estimation scheme that permits placement of the rigid body in each of the two-dimensional image planes of monitoring cameras. Estimation model with six parameters is developed based on a model that generalizes known 4-axis scara robot kinematics to accommodate unknown relative camera position and orientation, etc. Based on the estimated parameters,depending on each camers the joint angle of robot is estimated by the iteration method. The method is tested experimentally in two ways, the estimation model test and a three-dimensional rigid body placement task. Three results show that control scheme used is precise and robust. This feature can open the door to a range of application of multi-axis robot such as assembly and welding.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.1052-1057
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• 1993

A scara type Direct Drive Arm(DDA) with two degrees-of-freedom is designed and implemented. The direct drive motor is used to furnish large torque to reduce the modeling error by the gear and chains. To control the DDA, a multiprocessor control structure with multirate dynamic control algorithm is designed. In the control algorithm, the dynamics of system is used to calculate the nominal control torque and the feedback controls are calculated with a parallel processing algorithm for each joint. The laboratory experiments on Hong-Ik DDA by dynamic control algorithm are presented and compared to that of PID control algorithm. This result shows that the proposed controller guarantees small trajectory error and stability. With this research, Hong-Ik DDA is expected to be utilized as A basic tool for robotics and control engineering.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.445-449
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• 1993

The role of a robot becomes more important as factory automation is widely spread in the manufacturing industry. An off-line program system has been required for uninterruption of production lines because it can save cost and time spent in adjusting a robot to a new workcell. The objective of this paper is to develop our own OLP system for a SCARA type FARA robot with four axes. Three-dimensional graphic results are presented for the case when the robot is simulated using the computed torque method with a PD controller and the continuous path trajectory planning.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.428-433
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• 1994

This investigates the feasibility of applying fuzzy ogic controllers to the motion tracking control of a direct drive robot manipulator to deal with highly nonlinear and time-varying dynamics associated with robot motion. A fuzzy logic controller with narrow shape of membership functions near zero and wide shape far away zero is analyzed. Simulation and experimental studies have been conducted for a 2 degree of freedom direct drive SCARA robot to evaluate control performances, Fuzzy logic controllers have shown control performances that are often better, or at least, as good as those of conventional PID controllers. Furthermore, the control performance of fuzzy logic controllers can be improved by selecting membership functions of narrow shapes near zero and wide shapes far away zero.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.40-43
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• 1996

An off-line programming, OLP, system is widely used in automation fines. To help an on-line robot system to carry out desirable tasks planned by the off-line simulation, an approach to the real-time communication is presented. The OLP system developed consists of a software, a host computer(PC), a SCARA robot body, four servo drivers, and four independent joint controllers. This study focuses on the software where real-time communication is included. The software, can be used in teaching, trajectory planning, real-time running, and performance evaluation. The evaluation of different control algorithms is one of the merits of the software. The software can give servo commands for task running. A comparison of generated and corresponding actual trajectories provides the evaluation of task performance. The safety, of the OLP system is ensured by alarming malfuntions of the system. The OLP system developed can reduce the teaching time and increase the user's convenience.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.65-68
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• 1996

Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. The TMS32OC31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the, network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time, control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.410-414
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• 1996

A visual servoing algorithm is proposed for a robot with a camera in hand. Specifically, novel image features are suggested by employing a viewing model of perspective projection to estimate relative pitching and yawing angles between the object and the camera. To compensate dynamic characteristics of the robot, desired feature trajectories for the learning of visually guided line-of-sight robot motion are obtained by measuring features by the camera in hand not in the entire workspace, but on a single linear path along which the robot moves under the control of a, commercially provided function of linear motion. And then, control actions of the camera are approximately found by fuzzy-neural networks to follow such desired feature trajectories. To show the validity of proposed algorithm, some experimental results are illustrated, where a four axis SCARA robot with a B/W CCD camera is used.