• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.575-578
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• 1995

In general, the control of robot manipulator is classified into position control and force control. Position controllers give adequate performance when a manipulator is following a trajectory through space and end-effector has no contact with environment. However for most tasks performed by robot manipulator in industry, contact is made between the end-effector and manipulator's environment, so position control may not suffice. The objective of this study is to control both position of a manipulator and the contact forces generated at the hand by using a conceptually simple control law. Position and force control problem is decoupled into subtasts via taskspace formulation and inverse dynamics. Then, the position controllers are designed for the task space variable which represent tangent motion and the forte controllers are designed for the lash space variables which represent normal force.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.608-611
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• 2000

We introduce Adaptive Fuzzy Impedance Controller for position and force control when robot contact with environment. Because Robot and environment was always effected by nonlinear conditions, it need to deal with parameter’s uncertainty. For solving this problem, it induced Fuzzy System in Impedance Control so fuzzy system is impedance’s stiffness gain. We apply adaptive fuzzy impedance controller in One-Link Robot System, it shows the good performance on desired position control and force control about contacting with arbitrarily environment.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.341-345
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• 1986

In the course of robot control system building, there are problems in the position control loop of 3rd axis of robot manipulator. The problems are summerized as two: one is uncontrollability of position and the other is oscillation. And these problems are analyzed through experiment, and it is known that the cause of problems in torsional vibration of 3rd axis. So that these two problems are solved by noise immunity enhancement and lowering of PI controller gain.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1589-1592
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• 1997

Among the prerequisite abilities (perception of environment, path planning and position estimation) of an autonomous mobile robot, position estimation has been seldom studied by mobile robot researchers. In most cases, conventional positioin estimation has been performed by placing landmarks or giving the entrire environmental information in advance. Unlikely to the conventional ones, the study addresses a new method that the robot itself can select distinctive features in the environment and save them as landmarks without any a priori knowledge, which can maximize the autonomous behavior of the robot. First, an orjentaion probaility model is applied to construct a lcoal map of robot's surrounding. The feature of the object in the map is then extracted and the map is saved as landmark. Also, presented is the position estimation method that utilizes the correspondence between landmarks and current local map. In dong this, the uncertainty of the robot's current positioin is estimated in order to select the corresponding landmark stored in the previous steps. The usefulness of all these approaches are illustrated with the results porduced by a real robot equipped with ultrasonic sensors.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.1
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• pp.21-29
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• 2003

It is very important to reduce the computational time in estimating the parameters of vision control algorithm for robot's position control in real time. Unfortunately, the batch estimation commonly used requires too murk computational time because it is iteration method. So, the batch estimation has difficulty for robot's position control in real time. On the other hand, the Extended Kalman Filtering(EKF) has many advantages to calculate the parameters of vision system in that it is a simple and efficient recursive procedures. Thus, this study is to develop the EKF algorithm for the robot's vision control in real time. The vision system model used in this study involves six parameters to account for the inner(orientation, focal length etc) and outer (the relative location between robot and camera) parameters of camera. Then, EKF has been first applied to estimate these parameters, and then with these estimated parameters, also to estimate the robot's joint angles used for robot's operation. finally, the practicality of vision control scheme based on the EKF has been experimentally verified by performing the robot's position control.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.297-298
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• 2009

• Journal of the Korean Society of Industry Convergence
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• v.20 no.2
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• pp.89-95
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• 2017

In this paper, we suggest the method for a mobile robot to move safely from an initial position to a goal position in the wide environment like a building. There is a problem using odometry encoder sensor to estimate the position of a mobile robot in the wide environment like a building. Because of the phenomenon of wheel's slipping, a encoder sensor has the accumulated error of a sensor measurement as time. Therefore the error must be compensated with using other sensor. A vision sensor is used to compensate the position of a mobile robot as using the regularly attached light's panel on a building's ceiling. The method to create global path planning for a mobile robot model a building's map as a graph data type. Consequently, we can apply floyd's shortest path algorithm to find the path planning. The effectiveness of the method is verified through simulations and experiments.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.708-713
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• 2004

This research develops a sensorless hydraulic servo system of Parallel-Typed robot for harbour construction. Purpose of the robot is to mechanize the construction, which is accomplished through a joystick's operating by a stoneworker (or diver). The robot is attached on the end of an excavator as its attachment or transported by a crane to reach the desired place. The embedded compact controller is installed on the robot body and controlled by wireless telecommunication. For underwater work, it is necessary to waterproof the robot and its sensors. Especially, a sensor waterproof is a main drawback for the underwater robot. This leads us to develop a hydraulic robot position controller using an observer which gives the position information without any position sensor. We design a neural network to identify the displacement change according to the command voltage to servo valve. To verify the sensorless controller, this paper presents the performance of the sensorless control for which the position is given by the observer comparing with that of the sensor control for which the position is measured by LVDT sensors.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.647-652
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• 2000

This paper presents a study on the position tracking control of robot system on the uncertain elastic base. The elastic base is modeled as a virtual robot which has passive joints and the control strategy is using approximate Jacobian operators. Jacobian operators represent the overall robot system including base movement. However, because we don't know the base movement we can't estimate the jacobian operators directly. The control algorithm is proposed which uses only Jacobian operators of a real robot as approximate Jacobian operators. The measured errors from external sensor are compensated by approximate Jacobian operators. The simulation results of a single-axis robot system show that the control strategy can be used for position tracking.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.916-919
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• 1996

An real-time active beacon localization system for mobile robots is developed and implemented. This system permits the estimation of robot positions when detecting light sources by PSD(Position Sensitive Detector) sensor which are placed sparsely over the robot's work space as beacons(or landmarks). An LSE(Least Square Estimation) method is introduced to calibrate the internal parameters of a model for the beacon and robot position. The proposed system has two operational modes of position estimation. One is the initial position calculation by the detection of two or more light sources positions of which are known. The other is the continuous position compensation that calculates the position and heading of the robot using the IEKF(Iterated Extended Kalman Filter) applied to the beacon and dead-reckoning data. Practical experiments show that the estimated position obtained by this system is precise enough to be useful for the navigation of robots.