• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.431-431
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• 2000

The modeling of 5-bar linkage robot manipulator dynamics by means of a mathematical and neural architecture is presented. Such a model is applicable to the design of a feedforward controller or adjustment of controller parameters. The inverse model consists of two parts: a mathematical part and a compensation part. In the mathematical part, the subsystems of a 5-bar linkage robot manipulator are constructed by applying Kawato's Feedback-Error-Learning method, and trained by given training data. In the compensation part, MLP backpropagation algorithm is used to compensate the unmodeled dynamics. The forward model is realized from the inverse model using the inverse of inertia matrix and the compensation torque is decoupled in the input torque of the forward model. This scheme can use tile mathematical knowledge of the robot manipulator and analogize the robot characteristics. It is shown that the model is reasonable to be used for design and initial gain tuning of a controller.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.4
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• pp.386-394
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• 2011

This paper is concerned with the application of the vision control scheme for robot's point placement task in discontinuous trajectory caused by obstacle. The proposed vision control scheme consists of four models, which are the robot's kinematic model, vision system model, 6-parameters estimation model, and robot's joint angles estimation model. For this study, the discontinuous trajectory by obstacle is divided into two obstacle regions. Each obstacle region consists of 3 cases, according to the variation of number of cameras that can not acquire the vision data. Then, the effects of number of cameras on the proposed robot's vision control scheme are investigated in each obstacle region. Finally, the practicality of the proposed robot's vision control scheme is demonstrated experimentally by performing the robot's point placement task in discontinuous trajectory by obstacle.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.5-8
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• 1999

The main stream of researches on the mobile robot is planning motions of the mobile robot under nonholonomic constraints while only considering kinematic model of a mobile robot. These researches, however, assume that there is some kind of dynamic controller which can produce perfectly the same velocity that is necessary for the kinematic controller. Moreover, there are little results about the problem of integrating the nonholonomic kinematic controller and the dynamic controller for a mobile robot. Also the literature on the robustness of the controller in the presence of uncertainties or external disturbances in the dynamical model of a mobile robot is very few. Thus, in this paper, the robust adaptive controller which can achieve velocity tracking while considering not only kinematic model but also dynamic model of the mobile robot is proposed. The stability of the dynamic system will be shown through the Lyapunov method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.1
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• pp.41-48
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• 2014

This paper analyzes the Monte Carlo localization (MCL) method, which estimates the pose of an indoor mobile robot. A mobile robot must know where it is to navigate in an indoor environment. The MCL technique is one of the most influential and popular techniques for estimation of robot position and orientation using a particle filter. For the analysis, we perform experiments in an indoor environment with a differential drive robot and ultrasonic range sensor system. The analysis uses MATLAB for implementation of the MCL and investigates the effects of the control parameters on the MCL performance. The control parameters are the uncertainty of the motion model of the mobile robot and the noise level of the measurement model of the range sensor.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2016-2021
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• 2003

This paper deals with a control technique of eliminating the transient vibration with respect to a waist axis of an articulated robot. This control technique is based on a model-based control in order to establish the damping effect on the driven mechanical part. The control model is composed of reduced-order electrical and mechanical parts related to the velocity control loop. The parameters of the control model can be obtained from design data or experimental data. This model estimates a load speed converted to the motor shaft. The difference between the estimated load speed and the motor speed is calculated dynamically, and it is added to the velocity command to suppress the transient vibration. This control method is applied to an articulated robot regarded as a time-invariant system. The effectiveness of the model-based control integrated into the position control loop is verified by simulations. Simulations show satisfactory control results to reduce the transient vibration at the end-effector.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.565-570
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• 2008

Recently, the intelligent service robot is applied for the purpose of guiding the building or providing information to the visitors of the public institution. The intelligent robot which is on development has a sensor to recognize its location at the bottom of it. Four wheels which are arranged in the form of a lozenge support the weight of the components and structures of the robot. The operating environment of this robot is restricted at the uneven place because the driving part and internal structure is designed in one united body. The impact from the ground is transferred to the internal equipments and structures of the robot. This continuous impact can cause the unusual state of the precise components and weaken the connection between each structural part. In this paper, a suspension system which can be applied to the intelligent robot is designed. The dynamic model of the robot is created, and the driving characteristics of the actual robot and the robot with suspension are compared. The road condition which the robot can operate is expanded by the application of the suspension system. Additionally, the suspension system is optimized to reduce the impact to the robot components.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.548-551
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• 1997

Performance of force tracking impedance control of robot manipulators is degraded by the uncertainties in the robot and environment dynamic model. The purpose of this paper is to improve the controller robustness by applying neural network. Neural networks are designed to learn the uncertainties in robot and environment model for compensating the uncertainties. The proposed scheme is verified through the simulation of 20DOF robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.101-106
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• 2005

In this paper, we propose a behavior decision model for a robot, which is based on artificial emotion, various motivations and dynamic personality. Our goal is making a robot which can express its emotion human-like way. To achieve this goal, we applied several emotion and personality theories in psychology. Especially, we introduced the concept of dynamic personality model for a robot. Drawing on this concept, we could make a behavior decision model so that the emotion expression of the robot has adaptability to various environments through interactions between human and the robot.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.503-512
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• 2014

People would like to be socially engaged not only with humans but also with robots. One of the most common ways in the robotic field to enhance human robot interaction is to use emotion and integrate emotional concepts into robots. Many researchers have been focusing on developing a robot's emotional expressions. However, it is first necessary to establish the psychological background of a robot's emotion generation model in order to implement the whole process of a robot's emotional behavior. Therefore, this article suggests a robot's motivational emotion model with value effectiveness from a Higgins' motivation definition, regulatory focus theory, and Circumplex model. For the test, a game with the best-two-out-of-three rule is introduced. Each step of the game was evaluated by the proposed model. As the results imply, the proposed model generated psychologically appropriate emotions for a robot in the given situation. The empirical survey remains for future work to prove that this research improves social human robot interaction.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.142-149
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• 2022

This study attempts to analyze the economic impact of the service robot industry using Input-Output analysis, which is conducted based on Demand-driven model, the Leontief price model, the Backward and Forward Linkage Effects, and the Exogenous Methods. In a Demand-driven model analysis, we can conclude that the service robot industry contains characteristics of both the manufacturing industry and the service industry, which causes a positive impact on the overall industry by compensating for the weaknesses of the two industries. The Leontief price analysis indicates when wages in the service robot industry increase, prices related to robot manufacturing also increase. Also, when profits in the service robot industry increase, prices related to service provision increase, too. The Backward and Forward Linkage Effects analysis shows that the service robot industry is highly sensitive to the current economic condition and has a great influence on the service industry. The service robot industry can highlight the aspect of service characteristics when the manufacturing industry is in recession and vice versa. In addition, the service robot industry can be regarded as a value-adding and domestic economy promoting industry which utilizes knowledge of information and communication technologies. It is important to foster the service robot industry in South Korea, which is in economic recession to provide an opportunity to stimulate the growth of both service and robot industries.