• 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.

• 전자공학회논문지 IE
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• v.46 no.4
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• pp.73-77
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• 2009

This paper presents the trajectory tracking control for mobile robot. The designed controller consists of kinematic and dynamic controller. Kinematic controller has two gains and it reduces the trial time for gain setting as compared convectional controller with three gains. Dynamic controller includes the compensation of friction and disturbance. It can improve the performance of the trajectory tracking under the various environment. Simulation results shows that the proposed controller has a stable performance.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.6
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• pp.466-472
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• 2003

This paper describes a tracking control for the mobile robot based on fuzzy systems. Since the mobile robot has the nonholonomic constraints, these constraints should be considered to design a tracking controller for the mobile robot. One of the well-known tracking controllers for the mobile robot is the back-stepping controller. The conventional back-stepping controller includes the dynamics and kinematics of the mobile robot. The conventional back-stepping controller is affected by the derived velocity reference by a kinematic controller. To improve the performance of the conventional back-stepping controller, this paper uses the fuzzy systems known as the nonlinear controller. The new velocity reference for the back-stepping controller is derived through the fuzzy inference. Fuzzy rules are selected for gains of the kinematic controller. The produced velocity reference has properly considered the varying reference trajectories. Simulation results show that the proposed controller is more robust than the conventional back-stepping controller.

• Journal of the Ergonomics Society of Korea
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• v.18 no.3
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• pp.141-152
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• 1999

In this paper, We performed the human body dynamic modelling for the realistic animation based on the dynamical behavior of human body, and designed controller for the effective control of complicate human dynamic model. The human body was simplified as a rigid body which consists of 18 actuated degrees of freedom for the real time computation. Complex human kinematic mechanism was regarded as a composition of 6 serial kinematic chains : left arm, right arm, support leg, free leg, body, and head. Based on the this kinematic analysis, dynamic model of human body was determined using Newton-Euler formulation recursively. The balance controller was designed in order to control the nonlinear dynamics model of human body. The effectiveness of designed controller was examined by the graphical simulation of human walking motion. The simulation results were compared with the model base control results. And it was demonstrated that, the balance controller showed better performance in mimicking the dynamic motion of human walking.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.399-399
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• 2000

In this paper, path generation using the sensor platform is proposed. The sensor platform is composed two electric motors which make panning and tilting motions. An algorithm fur a real path form and an obstacle length is realized using a scanning algorithm to rotating the sensors on the sensor platform. An ARV (Autonomous Robot Vehicle) is able to recognize the given path by adapting this algorithm. In order for the ARV to navigate the path flexibly, a kinematic model needed to be constructed. The kinematic model of the ARV was reformed around its body center through a relative velocity relationship to controllability, which derives from the nonholonomic characteristics. The optimal controller that is based on tile kinematic model is operated purposefully to track a reference vehicle's path. The path generation algorithm is composed of two parks. On e part is the generating path pattern, and the other is used to avoid an obstacle. The optimal controller is used for tracking the reference path which is generated by recognizing the path pattern. Results of simulation show that this algorithm for an ARV is sufficient for path generation by small number of sensors and for low cost controller.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1287-1296
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• 2014

This paper is about control of Automated Guided Vehicle for path following using fuzzy logic controller. The Automated Guided Vehicle is a tricycle wheeled mobile robot with three wheels, two fixed passive wheels and one steering driving wheel. First, kinematic and dynamic modeling for Automated Guided Vehicle is presented. Second, a controller that integrates two control loops, kinematic control loop and dynamic control loop, is designed for Automated Guided Vehicle to follow an unknown path. The kinematic control loop based on Fuzzy logic framework and the dynamic control loop based on two PID controllers are proposed. Simulation and experimental results are presented to show the effectiveness of the proposed controllers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.201-204
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• 2008

The mobile robot is known as a nonlinear system with constraints. The general tracking controller for the mobile platform has been divided into the kinematic and the dynamic controller. The reason of dividing controller is the constraints. We can get some information through some numerical experiments. When the reference linear and angular velocity were given, the stability of mobile robot without the kinematic controller depend on the start point of reference cart. Therefore this paper composed of two controller for solving tracking problem. The main controller is the dynamic controller which used generally such as the PID controller. And this paper adopts the auxiliary controller in order to compensate the difference of initial point between the reference cart and a mobile robot. Finally, the numerical experiment is performed in order to show the validity of our method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.361-362
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• 2011

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.313-318
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• 2001

A haptic hand controller operated by the user's hand can receive information on position and orientation of the hand and display force and moment generated in the virtual environment to the hand. This paper presents a design method for KU-HHC, 6 DOF Korea University-haptic hand controller, which allows separation of workspace from linkage mechanism in consideration of the efficient user operation. First, the 3 DOF mechanism in which all the actuators are mounted on the fixed base is developed by combining a 5-bar linkage and gimbal mechanism. Then, the 6 DOF HHC is designed by connecting the two 3 DOF devices through a handle. This paper presents the forward and inverse kinematics for this device and Jacobian analysis. Improvement of the kinematic characteristics using performance index is also discussed. The hand controller KU-HHC based on this design concept and kinematic analysis was manufactured and shows excellent performance.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.5
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• pp.308-316
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• 2003

This paper describes a tracking control for the mobile robot based on fuzzy systems. The conventional back-stepping controller includes the dynamics and kinematics of the mobile robot, which is affected by the derived velocity reference by a kinematic controller. To improve the performance of conventional back-stepping controller, this paper uses the fuzzy systems known as the nonlinear controller. In this paper, the new velocity reference for the back-stepping controller is derived through the fuzzy inference. Fuzzy rules are selected for gains of the kinematic controller. The produced velocity reference has properly considered the varying reference trajectories. And simulation results show that the proposed controller is more robust than the conventional back-stepping controller.