• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.27-35
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• 2008

A navigation system is one of the important components of an unmanned ground vehicle (UGV). A GPS receiver collects data signals transmitted by (Earth orbiting) satellites. However, these data signals may contain many errors resulting misinformation and depending on one's position (environment), reception may be impossible. The proposed self-driven algorithm uses three low-cost GPS in order to minimize errors of existing inexpensive single GPS's driving algorithm. By using reliable final data, which is analyzed and combined from each of three GPS's received data signals, gathering a vehicle's steering performance information and its current pin-point position is improved even with error containing signals or from a place where signal gathering is impossible. The purpose of this thesis is to explain navigation system algorithm using multiple GPS and compass sensor and prove the algorithm through experiments.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1998.04a
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• pp.56-63
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• 1998

A fiber optic gyrocompass for ships was made in consideratino of cost, reliability and convenience. In order to reduce the cost a cheaper fiber sensor was used inthis system. The accuracy was increased by replacing a 180ppr-slit disk with a 1000ppr-encoder. The reliability was also increased by improving the signal processing electronics. This system was made as a heading angle display type for convenience. Although more inexpensive FOG than that of the previous system was used , the accuracy of this compass was increased about 0.5$^{\circ}$. Moreover, it has a very fast warm-up time of about 5minutes. Therefore, this compass can show the prospect of proactical use on ships if it is installed ona stabilizer against the dynamic motion such as rolling and pitching.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.239-244
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• 2010

This paper is to present map building of mobile robot using RFID (Radio Frequency Identification) technology and ultrasonic sensor. For mobile robot to perform map building, the mobile robot needs its localization and accurate driving in space. In this reason, firstly, kinematic modeling of mobile robot under non-holonomic constrains is introduced. Secondly, based on this modeling, a tracking controller is designed for tracking a given path based on backstepping method using Lyapunov function. The Lyapunov function is also introduced for proving the stability of the designed tracking controller. Thirdly, 2D map building is performed by RFID system, mobile robot system and ultrasonic sensors. The RFID mobile robot system is composed of DC motor, encoder, ultra sonic sensor, digital compass, RFID receiver and RFID antenna. Finally, the path tracking simulation results and map building experimental results are presented to show the effectiveness of the designed controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.814-819
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• 2010

This paper is presented to study the error minimization of angular velocity for AGV(autonomous ground vehicle). The error minimization of angular velocity is related to localization technique which is the most important technique for autonomous vehicle. Accelerometer, yaw gyro and electronic compass have been used to measure angular velocity. And methods for error minimization of angular velocity have been actively studied through probabilistic methods and sensor fusion for AGVs. However, those sensors still occure accumulated error by mathematical error, system characters of each sensor, and computational cost are increased greatly when several sensor are used to correct accumulated error. Therefore, this paper studies about error minimization of angular velocity that just uses encoder and gyro. To experiment, we use autonomous vehicle which is made by ourselves. In experimental result, we verified that the localization error of proposed method has even less than the localization errors which we just used encoder and gyro respectively.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.141-148
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• 2003

This paper presents a rotating ann test for assessment of an underwater hybrid navigation system for a semi-autonomous underwater vehicle. The navigation system consists of an inertial measurement unit (IMU), an ultra-short baseline (USBL) acoustic navigation sensor and a doppler velocity log (DVL) accompanying a magnetic compass. The errors of inertial measurement units increase with time due to the bias errors of gyros and accelerometers. A navigational system model is derived to include the error model of the USBL acoustic navigation sensor and the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 25 in the order. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors and correct the state equation when the measurements are available. The rotating ann tests are conducted in the Ocean Engineering Basin of KRISO, KORDI to generate circular motion in laboratory, where the USBL system was absent in the basin. The hybrid underwater navigation system shows good tracking performance against the circular planar motion. Additionally this paper checked the effects of the sampling ratio of the navigation system and the possibility of the dead reckoning with the DVL and the magnetic compass to estimate the position of the vehicle.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1057-1064
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• 2017

High sensitivity magnetic sensor having foreign metal detection capability is proposed utilizing giant magneto-impedance effect. Strip sensor showed the increasing output voltage when the external magnetic field was applied along with strip from strip grounding point, although the initial DC voltage varied depending on the pointing direction of strip sensor. Proposed sensor was able to eliminate more than half of background noise using active noise filter to achive high sensitivity, and it showed the capability to detect magnetized foreign metal object independent of ambient electro-magnetic noise and earth magnet. In case of ferrous sphere, the metal detection up to 0.8mm diameter was experimentally demonstrated at 5mm distance from strip sensor.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.2
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• pp.69-78
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• 2009

Localization is a very important technique for the mobile robot to navigate in outdoor environment. In this paper, the development of the sensor fusion algorithm for controlling mobile robots in outdoor environments is presented. The multi-sensorial dead-reckoning subsystem is established based on the optimal filtering by first fusing a heading angle reading data from a magnetic compass, a rate-gyro, and two encoders mounted on the robot wheels, thereby computing the dead-reckoned location. These data and the position data provided by a global sensing system are fused together by means of an extended Kalman filter. The proposed algorithm is proved by simulation studies of controlling a mobile robot controlled by a backstepping controller and a cascaded controller. Performances of each controller are compared.

• Journal of the Korean Society of Industry Convergence
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• v.4 no.3
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• pp.339-347
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• 2001

Automatic automobile has been studied as the alternative energy system and the production flow automation device recently. But this is dependent on the import production, and its position cannot be controlled free from the fixed path. It is difficult to control the automobile position because of the eccentricity of inertia monent, slip and roughness between wheel and road surface. This problems is solved for the controller to be feedbacked the data of the multi-sensor system consisting of the rotary encoder and electronic compass. The proportional Integrated controller in the modified Ziegler-Nichols method is made up with Hitachi 7034 microprocessor. To the real time control the mechanical, electrical and electronic hardware and software device is produced by myself. The RF data of automobile speed and position is supplied to the remote PC to be displayed the automobile condition. By the experinent of the forward, spin, point path planning, it is known for autombile.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.3
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• pp.126-135
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• 2008

The development of an unmanned vehicle basically requires the robust and reliable performance of major functions which include global localization, lane detection, obstacle avoidance, path planning, etc. The implementation of major functional subsystems are possible by integrating and fusing data acquired from various sensory systems such as GPS, vision, ultrasonic sensor, encoder, and electric compass. This paper focuses on implementing the functional subsystems, which are designed and developed by a graphical programming tool, NI LabVIEW, and also verifying the autonomous navigation and remote control of the unmanned vehicle.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.64.4-64
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• 2001

Localization is the key role in controlling the Mobile Robot. In this papers, a development of the sensor fusion algorithm for controling UTV(Unmanned Tracked Vehicle) is presented. The multi-sensocial dead-rocking subsystem is established based on the optimal filtering by first fusing heading angle reading from a magnetic compass, a rate-gyro and two encoders mouned on the robot wheels, thereby computing the deat-reckoned location. These data and the position data provoded by LBL system are fused together by means of an extended Kalman filter. This algorithm is proved by simulation studies.