• 전기학회논문지
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• 제67권12호
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• pp.1729-1734
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• 2018

Recently, interest in environmentally friendly transportation systems has been increasing, and study on railway systems has been aggressively conducted. Therefore, lots of studies have been done in railway advanced countries to improve performance of PWM converter. The research on the PWM converter for railway vehicle was mainly carried out on the converter mounted on railway vehicle such as the high-speed railway and metropolitan railway. In also, a lot of study has been carried out to improve converter performance installed in the ground. The high-capacity transform used in this paper converted from AC 22.9kV to AC 590V. The converter changed from AC 590V to DC 950V. In general, in the case of rectifier, the DC power supply system has a negative impact on inverter control characteristics because it can not avoid the pulsating component. In this study, it was performed current control for high-capacity converter using Matlab Simulink. The PWM converter is normally performed through the voltage and current at starting mode, powering mode, and braking mode. In the light-load test and the on-line test, we have studied for the PWM converter characteristics. Using this research, we have founded that the converter has excellent performance.

• 제어로봇시스템학회논문지
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• 제15권12호
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• pp.1246-1253
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• 2009

To be high efficient for a navigation of unmanned ground vehicle, it must be able to distinguish between safe and hazardous regions in its immediate environment. We present an advanced method using laser range finder for building global 2D digital maps that include environment information. Laser range finder is used for mapping of obstacles and driving environment in the 2D laser plane. Rotary encoders are used for localization of UGV. The main contributions of this research are the development of an algorithm for global 2D map building and it will turn a UGV navigation based on map matching into a possibility. In this paper, a map building algorithm will be introduced and an assessment of algorithm reliability is judged at an each environment.

• 대한임베디드공학회논문지
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• 제12권2호
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• pp.113-120
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• 2017

In this paper, we present a night-time vehicle detection method using CNN (Convolutional Neural Network) classification. The camera based night-time vehicle detection plays an important role on various advanced driver assistance systems (ADAS) such as automatic head-lamp control system. The method consists mainly of thresholding, labeling and classification steps. The classification step is implemented by existing CIFAR-10 model CNN. Through the simulations tested on real road video, we show that CNN classification is a good alternative for night-time vehicle detection.

• International Journal of Automotive Technology
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• 제7권4호
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• pp.509-517
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• 2006

In the mid 1990s, the combination of vehicles and communication was expected to bolster the stagnant car industry by offering a flood of new revenues. In-vehicle computing systems provide safety and control systems needed to operate the vehicle as well as infotainment, edutainment, entertainment, and mobile commerce services in a safe and responsible manner. Since 1980 the word "telematics" has meant the blending of telecommunications and informatics. Lately, telematics has been used more and more to mean "automotive telematics" which use informatics and telecommunications to enhance the functionality of motor vehicles such as wireless data applications, intelligent cruise control, and GPS in vehicles. This definition identifies telecommunications transferring information as the key enabling technology to provide these advanced services. In this paper, a possible framework for future telematics, which called an Intelligent Vehicle Network(IVN), is proposed. The paper also introduces and compares a number of existing technologies and the terms of their capabilities to support a suite of services. The paper additionally the paper suggests and analyzes possible directions for future telematics from current telematics techniques.

• 제어로봇시스템학회논문지
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• 제18권2호
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• pp.81-86
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• 2012

Reconnaissance robots can reduce the danger of hazardous places by providing information before human personnel take action. For the usage, robot platform should be small and light. However, this fact leads to a scaling issue with terrain that landscape poses a huge obstacle for the vehicle. The problem can be solved by the inspiration of nature. This paper presents design of the locomotive mechanism inspired by Pill bugs. The mechanism was designed by the principles of a pill bug's locomotion and experiments were conducted to validate the mechanism.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.330-335
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• 1993

This paper presents an efficient solution for a class of forbidden state problems by introducing a cyclic timed controlled marked graphs (TCMG's), a special class of timed controlled Petri nets (TCPN's) as a model of a class of discrete event systems (DES's). The state feedback control is synthesized, which is maximally permissive while guaranteeing the forbidden states will be avoided. The practical applications or tire theoretical results for an automated guided vehicle (ACV) coordination problem in a flexible manufacturing facility is illustrated.

• 제어로봇시스템학회논문지
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• 제19권2호
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• pp.158-163
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• 2013

The fusion of the GPS (Global Positioning System) and DR (Dead Reckoning) is widely used for position and latitude estimation of vehicles such as a mobile robot, aerial vehicle and marine vehicle. Among the many types of aerial vehicles, grater focus is given on the quad-rotor and accuracy of the position information is becoming more important. In order to exactly estimate the position information, we propose the fusion method of GPS and Gyroscope sensor using the DEKF (Dual Extended Kalman Filter). The DEKF has an advantage of simultaneously estimating state value and a parameter of dynamical system. It can also be used even if state value is not available. In order to analyze the performance of DEKF, the computer simulation for estimating the position, the velocity and the angle in a circle trajectory of quad-rotor was done. As it can be seen from the simulation results using own proposed DEKF instead of EKF on own fusion method in the navigation of a quad-rotor gave better performance values.

• 제어로봇시스템학회논문지
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• 제10권5호
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• pp.442-449
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• 2004

As underwater robotic vehicles (URVs) become attractive for more sophisticated underwater tasks, the demand of high performance in terms of accuracy and dexterity has been increased. An autonomous underwater robotic vehicle, ODIN (Omni-Directional Intelligent Navigator) was designed and built at the Autonomous Systems Laboratory of the University of Hawaii in 1991. Since 1991, various studies were conducted on ODIN and have contributed to the advancement in underwater robotics. Its refurbished model ODIN II was based on VxWorks in VMEbus. Recently, ODIN was born again as a PC based system, ODIN III with unique features such as new vehicle system software architecture with an objective-oriented concept, a graphical user interface, and an independent and modular structure using a Dynamic Linking Library (DLL) based on the Windows operating system. ODIN III software architecture offers an ideal environment where various studies for advanced URV technology can be conducted. This paper describes software architecture of ODIN III and presents initial experimental results of fine motion control on ODIN III.

• 제어로봇시스템학회논문지
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• 제21권8호
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• pp.766-772
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• 2015

This paper proposes an object detection method based on motion estimation using background subtraction in the fisheye images obtained through omni-directional camera mounted on the vehicle. Recently, most of the vehicles installed with rear camera as a standard option, as well as various camera systems for safety. However, differently from the conventional object detection using the image obtained from the camera, the embedded system installed in the vehicle is difficult to apply a complicated algorithm because of its inherent low processing performance. In general, the embedded system needs system-dependent algorithm because it has lower processing performance than the computer. In this paper, the location of object is estimated from the information of object's motion obtained by applying a background subtraction method which compares the previous frames with the current ones. The real-time detection performance of the proposed method for object detection is verified experimentally on embedded board by comparing the proposed algorithm with the object detection based on LKOF (Lucas-Kanade optical flow).

• 한국산업융합학회 논문집
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• 제22권5호
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• pp.575-582
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• 2019

Advanced driving assist system can support safety of driver and passengers which may require vehicle dynamics states as well as road geometry. It is essential to have in real-time estimation of related variables and parameters. Among the road geometry parameters, road slope angle which can not be measured is essential parameter in pose estimation, adaptive cruise control and others on sag road. In this paper, Kalman filter based method for the estimation of the vehicle dynamics and road slope angle using a nonlinear vehicle model is proposed. It uses a combination of Kalman filter as Cascade Extended Kalman Filter. CEKF uses measured vehicle states such as yaw rate, longitudinal/lateral acceleration and velocity. Unknown vehicle parameters such as center of gravity and inertia are obtained by 2 D.O.F lateral model and experimentally. Simulation and Experimental tests conducted with commercialized vehicle dynamics model and real-car.