• Journal of the Korean Society for Precision Engineering
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• v.14 no.9
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• pp.68-79
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• 1997

A six DOF fine manipulator based on magnetic levitation is developed. Since most of magnetic levitation system are inherently unstable, a proposed magnetically levitated fine manipulator is implemented by use of an antagonistic structure to increase stability. From mathematical modeling and experiment, the equations of motion are derived. In addition, a six DOF sensing system is implemented by use of three 2-axis PSD sensors. A model reference-$H_{\infty}$ controller is applied to the system for the position control, In application of the fine manipulator, a wafer probing system is proposed to identify nonfunctional circuts. The probing system requires compliance to avoid destruction of DUT(device under test). A feedfor- ward-PD controllers are presented by the terms of the position accuracy, the settling time and the force accuracy.y.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1468-1471
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• 2005

This Paper is to find out a solution for the full-coverage algorithm requiring the real-time processing such as mobile home service robots and vacuum cleaner robots. Previous methods are used by adopting based grid approach method. They used lots of sensors, a high speed CPU, expensive ranger sensors and huge memory. Besides, most full-coverage algorithms should have a map before obstacle avoidance. However, if a robot able to recognize the tangent vector of obstacles, it is able to bring the same result with less sensors and simplified hardware. Therefore, this study suggests a topological based approach and a local obstacle voidance method using a few of PSD sensors and ultra sonic sensors. The simulation results are presented to prove its applicability.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.186-193
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• 2008

We propose a novel real-time obstacle avoidance method for rescue robots. This method, named the ELA(Emergency Level Around), permits the detection of unknown obstacles and avoids collisions while simultaneously steering the mobile robot toward safe position. In the ELA, we consider two sensor modules, PSD(Position Sensitive Detector) infrared sensors taking charge of obstacle detection in short distance and LMS(Laser Measurement System) in long distance respectively. Hence if a robot recognizes an obstacle ahead by PSD infrared sensors first, and judges impossibility to overcome the obstacle based on driving mode decision process, the order of priority is transferred to LMS which collects data of radial distance centered on the robot to avoid the confronted obstacle. After gathering radial information, the ELA algorithm estimates emergency level around a robot and generates a polar histogram based on the emergency level to judge where the optimal free space is. Finally, steering angle is determined to guarantee rotation to randomly direction as well as robot width for safe avoidance. Simulation results from wandering in closed local area which includes various obstacles and different conditions demonstrate the power of the ELA.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.372-374
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• 2009

In this research, an obstacle avoidance method is proposed. The common usage of a robot is indoor and the obstacles to the indoor robot is studied. The accurate detection of direction after overcoming the obstacles is necessary for performance of autonomous navigation and mission project. The sensors such as Laser, Ultrasound, PSD can be used to measure the obstacles. In this research, a PSD sensor is used to detect obstacles. It detects the height and width of obstacles located on the floor. Before measuring the obstacles, a calibration of the sensor was done and it produced a better accuracy. We have plotted an error graph using data obtained from the repeated experiments. The graph is fitted to a polynomial curve. The polynomial equation is used for the robot navigation. And in this research, a model of the error of the direction of the robot after overcoming obstacles was obtained also. The prototype of the obstacle and the error of the direction after overcoming the obstacles are modelled using a neural networks. The input of the neural network composed with the height of the obstacles, the speed of robot, the direction of wheels and the error of the direction. To implement the suggested algorithm, we set up a robot which is operated by a notebook computer. Experiment showed the suggested algorithm performed well.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.2
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• pp.209-218
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• 2019

This study proposes a new approach to Control the Orientation and position based on obstacle avoidance technology by multi sensors fusion and autonomous travelling control of mobile robot system for implimentation of Smart FA. The important focus is to control mobile robot based on by the multiple sensor module for autonomous travelling and obstacle avoidance of proposed mobile robot system, and the multiple sensor module is consit with sonar sensors, psd sensors, color recognition sensors, and position recognition sensors. Especially, it is proposed two points for the real time implementation of autonomous travelling control of mobile robot in limited manufacturing environments. One is on the development of the travelling trajectory control algorithm which obtain accurate and fast in considering any constraints. such as uncertain nonlinear dynamic effects. The other is on the real time implementation of obstacle avoidance and autonomous travelling control of mobile robot based on multiple sensors. The reliability of this study has been illustrated by the computer simulation and experiments for autonomous travelling control and obstacle avoidance.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.675-679
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• 2005

This paper deals with the problem of gust load alleviation in active control for the case that aeroelasticity takes place due to interaction between wing structure and aerodynamics on wing when aircraft meets gust during flight. Aeroservoelasticity model includes wing structure modeled in FEM, unsteady aerodynamics in minimum state approximate method, and models of actuator and sensors in state space. Based on this augmented model, digitally redesigned gust load alleviation system is designed in sampled-data control technique. From numerical simulation, this digital control system is effective to gust load on aircraft wing, which is shown in transient responses and PSD analysis to random gust inputs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.7
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• pp.551-562
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• 2013

Current CCTV systems, which require continuous monitoring of the screens, have the limitation to detect and respond to the crime scenes in timely manner. Therefore, in recent years, the request for more intlligent surveillance system, with a ubiquitous sensor network, is increasing in order to behave more humanly fashions. Such systems require cllective data processing of the environments based on various sensors. In this article, we suggests a new paradigm based surveillance system which integrates PSD and dual PIR sensors. The proposed system evlves from a existing indoor intrusion detection system which can only identify the intrusion event to a better inteligent system with context awareness. We have conducted the various simulations in order to prove the effectiveness of the proposed system.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.463-468
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• 2010

An obstacle avoidance method for a mobile robot is proposed in this paper. Our research was focused on the obstacles that can be found indoors since a robot is usually used within a building. It is necessary that the robot maintain the desired direction after successfully avoiding the obstacles to achieve a good autonomous navigation performance for the specified project mission. Sensors such as laser, ultrasound, and PSD (Position Sensitive Detector) can be used to detect and analyze the obstacles. A PSD sensor was used to detect and measure the height and width of the obstacles on the floor. The PSD sensor was carefully calibrated before measuring the obstacles to achieve better accuracy. Data obtained from the repeated experiments were used to plot an error graph which was fitted to a polynomial curve. The polynomial equation was used to navigate the robot. We also obtained a direction-error model of the robot after avoiding the obstacles. The prototypes for the obstacle and direction-error were modeled using a neural network whose inputs are the obstacle height, robot speed, direction of the wheels, and the error in direction. A mobile robot operated by a notebook computer was setup and the proposed algorithm was used to navigate the robot and avoid the obstacles. The results showed that our algorithm performed very well during the experiments.

• Journal of Sensor Science and Technology
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• v.11 no.2
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• pp.67-76
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• 2002

We have presented a 2-dimensional fluxgate sensor with ferrite core, excitation, and pick-up coil. This fluxgate sensor system consists of a sensing element, driving circuits for excitation coil and signal processing for detecting second harmonic frequency component which is proportional to the DC magnetic to be measured. The sensor core is excited by a square waveform of voltage through the excitation coil of 80 turns. The second harmonic output of pick-up coil(x and y axis: 100 turns) is measured by FFT spectrum analyzer. This result is compared with output of PSD(phase sensitive detector) unit for detecting the second harmonic component. The measured maximum sensitivity is about 1580 V/T at driving frequency of 1.5 kHz and excitation current of 2 App. The nonlinearity of this system is measured about 2.3%(PSD) and about 1%(second harmonics of the pick-up). The angle error of the system is ${\pm}2$ %/FS.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.468-471
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• 2003

The A＊ algorithm is usually used in game programming, mainly because it is fast in finding a optimal path to goal. In this paper. This algorithm was utilized for path finding, HIMM(Histogramic In-Motion Mapping) method is used in map-building. Map is updated continuously with range data sampled by PSD sensors From the map, A＊ algorithm finds a optimal path and sends subsequently the most suitable point to the Eyebot. A＊ algorithm has been tested on the Eyebot in various unknown maps of unknown and proved to work well. It could escape the local minimum, also.