• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.99-107
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• 2014

In this paper, a landmark based localization system using a Kinect sensor is proposed and evaluated with the implemented system for precise and autonomous navigation of low cost robots. The proposed localization method finds the positions of landmark on the image plane and the depth value using color and depth images. The coordinates transforms are defined using the depth value. Using coordinate transformation, the position in the image plane is transformed to the position in the body frame. The ranges between the landmarks and the Kinect sensor are the norm of the landmark positions in body frame. The Kinect sensor position is computed using the tri-lateral whose inputs are the ranges and the known landmark positions. In addition, a new matching method using the pin hole model is proposed to reduce the mismatch between depth and color images. Furthermore, a height error compensation method using the relationship between the body frame and real world coordinates is proposed to reduce the effect of wrong leveling. The error analysis are also given to find out the effect of focal length, principal point and depth value to the range. The experiments using 2D bar code with the implemented system show that the position with less than 3cm error is obtained in enclosed space($3,500mm{\times}3,000mm{\times}2,500mm$).

• The Journal of Korea Robotics Society
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• v.5 no.3
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• pp.186-196
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• 2010

In this paper, we present a global localization and position error compensation method in a known indoor environment using magnet hall sensors. In previous our researches, it was possible to compensate the pose errors of $x_e$, $y_e$, ${\theta}_e$ correctly on the surface of indoor environment with magnets sets by regularly arrange the magnets sets of identical pattern. To improve the proposed method, new strategy that can realize the global localization by changing arrangement of magnet pole is presented in this paper. Total six patterns of the magnets set form the unique landmarks. Therefore, the virtual map can be built by using the six landmarks randomly. The robots search a pattern of magnets set by rotating, and obtain the current global pose information by comparing the measured neighboring patterns with the map information that is saved in advance. We provide experimental results to show the effectiveness of the proposed method for a differential drive wheeled mobile robot.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.55-61
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• 2009

This paper proposes a position estimation of a mobile robot based on USN(Ubiquitous Sensor Network) and encoder, and development of tele-operation system using Internet. USN used in experiments is based on ZigBee protocol and has location estimation engine which uses RSSI signal to estimate distance between nodes. By distortion the estimated distance using RSSI is not correct, compensation method is needed. We obtained fuzzy model to calculate more accurate distance between nodes and use encoder which is built in robot to estimate accurate position of robot. Based on proposed position estimation method, tele-operation system was developed. We show by experiment that proposed method is more appropriate for estimation of position and remote navigation of mobile robot through Internet.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.185-191
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• 2008

In this paper, experimental studies of a neural network (NN) control technique for non-model based position control of the x-y table robot are presented. Decentralized neural networks are used to control each axis of the x-y table robot separately. For an each neural network compensator, an inverse control technique is used. The neural network control technique called the reference compensation technique (RCT) is conceptually different from the existing neural controllers in that the NN controller compensates for uncertainties in the dynamical system by modifying desired trajectories. The back-propagation learning algorithm is developed in a real time DSP board for on-line learning. Practical real time position control experiments are conducted on the x-y table robot. Experimental results of using neural networks show more excellent position tracking than that of when PD controllers are used only.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1866-1870
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• 2005

Typical small desktop robots have limied application due to their intrinsic feaures like friction, backlash, etc. However, a newly developed small gantry desktop robot needs smaller footprint and shows better performance in position accuracy, velocity, and acceleration. In order to achieve such results, synchronization control of two axes, position compensation methods in plane are suggested.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.386-388
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• 1996

This paper presents the learning controller for robot manipulators to track the desired trajectory exactly. The learning controller, based on the Lyapunov theory, consists of a fixed PD action and a repetitive action for the purpose of feedforward compensation which is adjusted utilizing a linear combination of the velocity and position errors. The learning controller Is often used In case of the desired trajectories are periodic tasks, and has advantage that it periodically converges to zero even if we don't know the exact dynamic parameters. In this paper, we show that the position and velocity errors of robot manipulators converge to zero sa time goes infinite for the input is periodic function and show a good trajectory tracking performance In the cartesian space.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.238-247
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• 2014

The milking robot system is very important to detect correctly the teats position in the moving condition of cow. Also, the robot manipulator must control tracking the teat cup to the detected teat position. The presented milking robot is designed using the one point laser sensor for teat position detection. The teats of cow are detected by the laser scanning unit and the manipulator has the function of 3 axes moving control unit. The presented teat detection method and the electrical driving manipulator have the advantages of a simple, low cost and very quiet. The designed manipulator is realized by the totally electrical motor and servo poison control algorithm with velocity PID compensation. The presented robot is realized using the teat detection unit, 4 teat cups, 3 axes robot arm, 6 servo motors and automatic milking control line. The designed robot is experimented in the cow farm and is satisfied with the designed performance specification for milking robot manipulator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.863-870
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• 2015

A Compensation Algorithm for The Position of the User Hands based on the Moving Mean-Shift ($CAPUH_{MMS}$) in Human Robot Interface (HRI) System running the Kinect sensor is proposed in order to improve the performance of the gesture recognition is proposed in this paper. The average error improvement ratio of the trajectories ($AEIR_{TJ}$) in left-right movements of hands for the $CAPUH_{MMS}$ is compared with other compensation algorithms such as the Compensation Algorithm based on the Compensation Algorithm based on the Kalman Filter ($CA_{KF}$) and the Compensation Algorithm based on Least-Squares Method ($CA_{LSM}$) by the developed realtime performance simulator. As a result, the $AEIR_{TJ}$ in up-down movements of hands of the $CAPUH_{MMS}$ is measured as 19.35%, it is higher value compared with that of the $CA_{KF}$ and the $CA_{LSM}$ as 13.88% and 16.68%, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1796-1799
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• 1997

This thersis presents precise position control emthods of a 3-PRPS in-parallel manipulator for industrial applications such as assembly of highly integrated semiconductors and microsurgery. Since real-time ontrol is one of the most important issues required for industrial application, the experimental hardware is set up with a VME based DSP controller. In the 3-PRPS parallel mainpulator, structurally existing frictiion at three horizontal links considerably degrades the precise position control. In order to compensate the friction of the horizontal links in the joint space, a disturbance compensation usign disturbance and velocity observers has been proposed and investigated. We analyzed the decision method of eigenvalues of the disturbance observer and the effects of the control resulted form tehsystem model errors. Through a series of simulations and experiments, we see that the methods is capable of compensating variations of the robot parameters such as inertia and damping as well as the joint friction. Experiments show that the disturbance compensation method usign disturbance and velocity observer is very effective to compensate the friction. Compared with conventional PID position control, it decreased position errors ina circular motion by approximately 70%.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1820-1823
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• 1997

For the Cartesian space position controlled robot, it is required to have the accurate mapping from the Cartesian space to the joint space in order to command the desired joint trajectories correctly. since the actual mapping from Cartesian space to joint space is obtained at the joint coordinate not at the actuator coordinate, uncertainty in Jacobian can be present. In this paper, two feasible neural network schemes are proposed to compensate for the kinematic Jacobian uncertainties. Uncertainties in Jacobian can be compensated by identifying either actuator Jacobian off-line or the inverse of that in on-line fashion. the case study of the stenciling robot is examined.