• Journal of Institute of Control, Robotics and Systems
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• v.7 no.11
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• pp.933-938
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• 2001

In this paper, we describe a method for the mobile robot using images of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using the a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot`s position. Since the equations are based on the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot. The Kalman filter scheme is applied to this method. Effectiveness of the proposed method is demonstrated by the simulation.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.63-72
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• 1997

The design and implementation of a drive wheel position, orientation, and velocity feedback control algorithm for a differential-drive mobile robot is described here. A new concept, the most significant error, is introduced as the control design objective. Drive wheel position, orientation, and velocity feedback control directly minimize the most siginificant error by coordinating the motion of the two drive wheels. The drive wheel position, orientation, and velocity feedback control algorithm is analyzed and experiments are conducted to evaluate its performance. The experimental results are shown that drive wheel position, orientation and velocity feedback control algorithm yields substantially smaller position and orientation errors than those of conventional methods.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.235-241
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• 2007

This paper proposes a self-calibration method of robots those are used in industrial assembly lines. The proposed method is a position compensation using laser sensor and vision camera. Because the laser sensor is cross type laser sensor which can scan a horizontal and vertical line, it is efficient way to detect a feature of vehicle and winding shape of vehicle's body. For position compensation of 3-Dimensional axis, we applied block interpolation method. For selecting feature point, pattern matching method is used and 3-D position is selected by Euclidean distance mapping between 462 feature values and evaluated feature point. In order to evaluate the proposed algorithm, experiments are performed in real industrial vehicle assembly line. In results, robot's working point can be displayed 3-D points. These points are used to diagnosis error of position and reselecting working point.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1036-1041
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• 1993

The tip of the flexible robot arm has to be controlled by the active control reducing vibration because it has residual vibration after getting to desired position. This paper presents an end-point position control of a 1-link flexible robot arm having tip mass by the PID control algorithm. The system is composed of a flexible arm with tip mass, dc servomotor and ballscrew mechanism under translational motion. The feedback signal composed of the tip displacement measured by laser sensor, estimated velocity and acceleration is used to control the base motion. Theoretical results are obtained by applying the Laplace transform and the numerical inversion method to the governing equations. After the flexible robot arm reaches to. the desired position, the residual vibration is controlled by the PID algorithm. This paper gives the simulation and experimental results of end-point responses according to changing tip-mass and arm length. And this algorithm shows good effects of reducing the residual vibration. Approximately, theoretical response is in good agreement with experimental one.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.2
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• pp.76-83
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• 1996

We have developed the unconventional robot arm which is composed of the two main parts, one is a ball screw and the other is a robot arm. The dynamic systems of the robot arm and ball screw are unstable systems coupled with each other. The ball screw mechanism is unstable system but controllable system. The robot arm's dynamics is quasi stable system when ball screw's angular position is zero, else, unstable system. Our system has the duality between stability and controllability at the view point of control. This duality causes difficulty to control of the robot arm using normal control law. We have investigated the location of the characteristic roots of the dynamic equation. And we have found out that the best condition for the control of the arm is quasi stable state. In this paper, we have proposed multiple control laws which are consist of three components to guarantee the stability and controllability simultaneously. The computer simulations were carried out based on VSC about the angular position control of the robot arm, and it is confirmed that the good performances could be obtained by using new controller.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.933-940
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• 2022

In this paper, the algorithm was developed to recognize hand 3D position through 2D image sensor and implemented a system to remotely control the 6 d.o.f. robot arm by using it. The system consists of a camera that acquires hand position in 2D, a computer that controls robot arm that performs movement by hand position recognition. The image sensor recognizes the specific color of the glove putting on operator's hand and outputs the recognized range and position by including the color area of the glove as a shape of rectangle. We recognize the velocity vector of end effector and control the robot arm by the output data of the position and size of the detected rectangle. Through the several experiments using developed 6 axis robot, it was confirmed that the 6 d.o.f. robot arm remote control was successfully performed.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2384-2386
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• 2003

This paper presents an image processing method to recognize object's position from images for robot control applications. The Sobel Mask and the Dialated Gradient Mask algorithms are used to extract and refine the edge of the object. The inside of the extracted edge is filled with '1's for calculation of the center of mass to identify object's position. We propose a heuristic method which averages the positions of the objects in 10 frames to reject noises, and discuss the application of the proposed method to robot control.

• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.309-315
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• 2020

This study shows a control strategy that acquires both precision and manipulation sensitivity of remote center motion with manual traction for a surgical assistant robot. Remote center motion is an essential function of a laparoscopic surgical robot. The robot has to keep the position of the insertion port in a three-dimensional space, and general laparoscopic surgery needs 4-DoF (degree-of-freedom) motions such as pan, tilt, spin, and forward/backward. The proposed robot consists of a 6-axis collaborative robot and a 2-DoF end-effector. A 6-axis collaborative robot performs the cone-shaped trajectory with pan and tilt motion of an end-effector maintaining the position of remote center. An end-effector deals with the remaining 2-DoF movement. The most intuitive way a surgeon manipulates a robot is through direct teaching. Since the accuracy of maintaining the remote center position is important, direct teaching is implemented based on position control in this study. A force/torque sensor which is attached to between robot and end-effector estimates the surgeon's intention and generates the command of motion. The predefined remote center position and the pan and tilt angles generated from direct teaching are input as a command for position control. The command generation algorithm determines the direct teaching sensitivity. Required torque for direct teaching and accuracy of remote center motion are analyzed by experiments of panning and tilting motion.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.613-620
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• 2013

A new remote control algorithm for a mobile robot is proposed, where a remote controller consists of a camera and inertial sensors. Initially the relative position and orientation of a robot is estimated by capturing four circle landmarks on the plate of the robot. When the remote controller moves to point to the destination, the camera pointing trajectory is estimated using an inertial navigation algorithm. The destination is transmitted wirelessly to the robot and then the robot is controlled to move to the destination. A quick movement of the remote controller is possible since the destination is estimated using inertial sensors. Also unlike the vision only control, the robot can be out of camera's range of view.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.375-382
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• 2016

This paper realizes control of the motion of a swimming robot fish in order to implement an underwater robot fish aquarium. And it implements positional control of a two-axis trajectory path of the robot fish in the aquarium. The performance of the robot was verified though certified field tests. It provided excellent performance in driving force, durability, and water resistance in experimental results. It can control robot motion, that is, it recognizes an object by using an optical flow object-detecting algorithm, which uses a video camera rather than image-detecting sensors inside the robot fish. It is possible to find the robot's position and control the motion of the robot fish using a radio frequency (RF) modem controlled via personal computer. This paper proposes realization of robot fish motion-tracking control using the optical flow object-detecting algorithm. It was verified via performance tests of lead-lag action control of robot fish in the aquarium.