• Journal of the Korean Society of Industry Convergence
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• v.23 no.4_1
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• pp.549-558
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• 2020

We describe a new approach to real-time implementation of track record and trajectory control of robotic manipulator with eight joints based on monitoring simulator. Trajectory generator uses the kinematic equations of the arm to convert the task description into a series of set points for each of the joint control loops, while the joint controllers, with simple algorithms for just one joint can move at a fast sampling rate, guaranteeing a smooth motion. The proposed control scheme is robust, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate parameter information, nor values of manipulator parameters and payload. Reliability of the proposed technology is veriefied by monitoring simulation and experimental of robot manipulator for the smart factory with eight degrees of freedom.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.10
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• pp.3186-3198
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• 1996

When a robot is to have contact with its enviornment, such as a medi-care robot, it would be advantageous for the robot to have a high compliance. For this reason, a robot having not only a flexible link but also an actuator with compliance, is desirable. This paper is concerned with the position and vibration control of 1 degree of freedom flexible robot using a pneumatic artificial muscle actuator. The dynamics of the manipulator assumed to be and Euler-Bernoulli beam are derived on the basis of the linear mathematical modle. Although this pneumatic artifical muscle actuator has many merits for the compliance robot, it is difficult to make an effective control scheme of this system because of ths nonlinearity and uncertainty on the dynamics of the actuator. By designing a controller using .mu.-synthesis, robust performance against measurement noise, various modeling uncertainties on the dynamics of the servo valve, actuator and mainpulator, is achieved. The effectiveness of the proposed control method is illustrated through simulations and experiments.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.56-62
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• 2021

MSRDS(Microsoft Robotics Developer Studio) provides the ability to simulate these technologies. SPL(Simple Programming Language) of MSRDS provides many functions for sensor programming to control autonomous robots. Sensor programming in SPL can be implemented in two types of schemes: procedure sensor notification and while-loop schemes. We considered the three programming schemes to control the robot movement after studying the advantages and disadvantages of the sensor notification procedure and the while-loop scheme. We also created simulation environments to evaluate the performance of the three considered schemes when applied to four different mazes. The simulation environment consisted of a maze and a robot with the most powerful sensor, i.e., the LRF(Laser Range Finder) sensor. We measured the required travel time and robot actions (number of turns and number of collisions) needed to escape the maze and compared the performance outcomes of the three considered schemes in the four different mazes.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.755-762
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• 2004

In this research, EOG(Electrooculogram) signal was analyzed to predict the subject's intention using a fuzzy classifier. The fuzzy classifier is built automatically using the EOG data and evolutionary algorithms. An assistant robot manipulator in redundant configuration has been developed, which operates according to the EOG signal classification results. For automatic fuzzy model construction without any experts' knowledge, an evolutionary algorithm with the new representation scheme, design of adequate fitness function and evolutionary operators, is proposed. The proposed evolutionary algorithm can optimize the number of fuzzy rules, the number of fuzzy membership functions, parameter values for the each membership functions, and parameter values for the consequent parts. It is shown that the fuzzy classifier built by the proposed algorithm can classify the EOG data efficiently. Intelligent motion planner that consists of several neural networks are used for control of robot manipulator based upon EOG classification results.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.58-62
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• 1988

Recently many adaptive control schemes for the industrial robot manipulator have been developed. Especially, learning control utilizing the repetitive motion of robot and based on iterative signal synthesis attracts much interests. However, since most of these approaches excludes the boundness of the input torque supplied to the manipulator, its effectiveness may be limited and also the full dynamic capacity of the robot manipulator can not be utilized. To overcome the above-mentioned difficulties and meet the desired performance, we propose an approach which yields the effective learning control schemes in this paper. In this study, some stability conditions derived from applying the Lyapunov theory to the discrete linear time-varying dynamic system are established and also an optimization scheme considering the bounded input torque is introduced. These results are simulated on a digital computer using a three-joint revolute manipulator to show their effectiveness.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.41-44
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• 1988

This paper represents the study of an effective self-tuning PID control for a robot manipulator to track a reference trajectory in spite of the presence of nonlinearities and parameters uncertainties in robot dynamic models. In this control scheme, an error model of the manipulator is established, for the first time, by difference between joint reference trajectory and tracked trajectory. It's model Parameters are estimated by the recursive least-square identification algorithm, and classical controller parameters are determined by pole placement method. A computer simulation study was conducted to demonstrate performance of the proposed self-tuning PID control in joint-based coordinates for a robot with payload.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.327-339
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• 2003

In this paper, a self-organizing fuzzy controller(SOFC) for the industrial robot manipulator with a actuator located at the base is studied A fuzzy login composed of linguistic conditional statements is employed by defining the relations of input-output variable of the controller, In the synthesis of a FLC, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult SOFC is proposed for a hierarchical control structure consisting of basic level and high level that modify control rules. The proposed SOFC scheme is simple in structure, fast in computations and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for robot with low joints.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.5
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• pp.485-497
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• 2014

This paper presents the robot vision control schemes based on the Newton-Raphson (N-R) and the Extended Kalman Filter (EKF) methods for the tracking of moving targets. The vision system model used in this study involves the six camera parameters. The difference is that refers to the uncertainty of the camera's orientation and focal length, and refers to the unknown relative position between the camera and the robot. Both N-R and EKF methods are employed towards the estimation of the six camera parameters. Based on the these six parameters estimated using three cameras, the robot's joint angles are computed with respect to the moving targets, using both N-R and EKF methods. The two robot vision control schemes are tested by tracking the moving target experimentally. Given the experimental results, the two robot control schemes are compared in order to evaluate their strengths and weaknesses.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.511-516
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• 2000

In order to not only perform as a extreme model under the severe operating condition but also acquire more diverse and advanced control capability utilizing high compliance, active vibration control of a flexible 2-link robot manipulator are investigated. Multi variable-structured frequency shaped optimal sliding mode is proposed for the flexible robot manipulator like control system, whose control variables, an angular motion of joint and vibration of flexible link, have to be controlled simultaneously by one control torque at a driving joint. The control system is divided into two subsystems, a control input related subsystem and an added subsystem. The proposed sliding mode, composed of multi control variables, makes optimized relation between subsystems and a individual control input, thus, the sliding mode controller can compensate whole dynamics of each subsystems simultaneously. And the possibility and effectiveness are verified by vibration control of a manipulator having two flexible links. Simulation and experiment results show that the proposed control scheme achieves the purpose effectively.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.4
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• pp.340-346
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• 2008

An unmanned surveillance robot consists of a machine gun, a laser receiver, a thermal imager, a color CCD camera, and a laser illuminator. It has two axis control systems for elevation and azimuth. Because the current robot system is mounded at a fixed post to take care of surveillance tasks, it is necessary to modify such a surveillance robot to be installed on an UGV (Unmanned Ground Vehicle) system in order to watch blind areas. Thus, it is required to have a stabilization system to compensate the disturbance from the UGV. In this paper, a simulation based design scheme has been adopted to develop a mobile surveillance robot. The 3D CAD geometry model has first been produced by using Pro-Engineer. The required pan and tilt motor capacities have been analyzed using ADAMS inverse dynamics analysis. A target tracking and stabilization control algorithm of the mobile surveillance robot has been developed in order to compensate the motion of the vehicle which will experience the rough terrain. To test the performance of the stabilization control system of the robot, ADAMS/simulink co-simulations has been carried out.