• 로봇학회논문지
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• 제17권2호
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• pp.142-151
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• 2022

With the advent of the 4th industrial revolution, autonomous driving technology is being commercialized in various industries. However, research on autonomous driving so far has focused on platforms with wheel-type platform. Research on a tracked platform is at a relatively inadequate step. Since the tracked platform has a different driving and steering method from the wheel-type platform, the existing research cannot be applied as it is. Therefore, a path-tracking algorithm suitable for a tracked platform is required. In this paper, we studied a path-tracking algorithm for a tracked platform based on a GPS sensor. The existing Pure Pursuit algorithm was applied in consideration of the characteristics of the tracked platform. And to compensate for "Cutting Corner", which is a disadvantage of the existing Pure Pursuit algorithm, an algorithm that changes the LAD according to the curvature of the path was developed. In the existing pure pursuit algorithm that used a tracked platform to drive a path including a right-angle turn, the RMS path error in the straight section was 0.1034 m and the RMS error in the turning section was measured to be 0.2787 m. On the other hand, in the variable LAD algorithm, the RMS path error in the straight section was 0.0987 m, and the RMS path error in the turning section was measured to be 0.1396 m. In the turning section, the RMS path error was reduced by 48.8971%. The validity of the algorithm was verified by measuring the path error by tracking the path using a tracked robot platform.

• 한국항만학회지
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• 제14권3호
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• pp.303-312
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• 2000

In this paper, we describe an image processing algorithm which is able to recognize the road lane. This algorithm performs to recognize the interrelation between AGV and the other vehicle. We experimented on AGV driving test with color CCD camera which is setup on the top of vehicle and acquires the digital signal. This paper is composed of two parts. One is image preprocessing part to measure the condition of the condition of the lane and vehicle. This finds the information of lines using RGB ratio cutting algorithm, the edge detection and Hough transform. The other obtains the situation of other vehicles using the image processing and viewport. At first, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, if vehicle knows the driving conditions which are lane angle, distance error and real position of other vehicles, we should calculate the reference steering angle.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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• pp.3-6
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• 2007

전 세계적으로 차량의 급속한 증가로 인해 지능형교통시스템에 대한 연구가 활발히 진행 되고있다. 그중 차량의 자율주행에 관한 연구가 한 분야를 차지한다. 그리고 차량의 자율주행은 경로 인식이 기본적인 요소이다. 기존의 경로인식은 3축 자계 센서로 자석마커의 3차원의 데이터를 분석하여 인식하였다. 그러나 본 논문에서는 Magnetic Wire와 자기거리계를 이용하여 측면 이탈거리를 계측하여 주행하는 시스템을 제안한다. 그리고 기존 자율주행 차량의 시스템과 비교하고 제안하는 시스템이 저사양의 하드웨어와 간단한 알고리즘으로 자율주행이 가능함을 실험을 통해 검증하고자 한다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.446-449
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• 2004

In the former researches〔2〕〔5〕 for the unmanned bicycle system, we do only focus on stabilizing it by using the lateral motion of mass which plays important role in driving a bicycle system. In this papers, we suggest an algorithm for deriving steering angle and speed for a given desired tracking path. As you may see in this paper, load mass balance system plays important role in stabilization and it is also discussed. We propose a control algorithm for the autonomous self stabilization of unmanned bicycle by using nonlinear compensation-like control based on the Lyapunov stability theory We then propose a tracking control strategy by moving the center of load mass left and right respectively. From the computer simulation results, we can show the effectiveness of the proposed control strategy.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술대회 논문집 전문대학교육위원
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• pp.38-41
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• 2003

An Autonomous Mobile Robot(AMR) performs duty by sensing a recognized situation and controlling suitably. The existing algorithm has some advantages that it is possible to express the obstacle exactly and the robot is sensitive to the change of environment. However, this algorithm needs to control repeatedly according to the modelling and working environment that requires a great quantity of calculations. In this paper, We supplement shortcoming and designed direction algorithm of AMR using fuzzy controller. Fuzzy controller does not derive special quality spinning expression for system, and uses rules by value expressed by language. It is used extensively to non-linear, plant which mathematical modelling is difficult etc... Fuzzy control algorithm of AMR that is used by this research applies obstacle position, distance of obstacle, Progress direction of robot, speed of robot, Perception area of sensor, etc... by fuzzy control and decide steering angle of robot.

• 한국해양공학회지
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• 제20권6호
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• pp.7-17
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• 2006

Depth and heading control of an AUV are considered to follow the predetermined depth and heading angle. The proposed control algorithm is designed. based on a sliding mode control using estimated hydrodynamic coefficients. The hydrodynamic coefficients are estimated with conventional nonlinear observer techniques, such as sliding mode observer and extended Kalman filter. By using the estimated coefficients, a sliding mode controller is constructed for the combined diving and steering maneuver. The simulation results of the proposed control system are compared with those of control system with true coefficients. This paper demonstrates the proposed control system, discusses the mechanisms that make the system stable and follows the desired depth and heading angle, accurately, in the presence of parameter uncertainty.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.180.1-180
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• 2001

In the autonomous vehicle, the reference lane is continually detected by machine vision system. And then the vehicle is steered to follow the reference yaw rates which are generated by the deviations of lateral distance and the yaw angle between the vehicle and the reference lane. To cope with the steering delay and the side-slip of vehicle, PI controller is introduced for the yaw rate feedback. And it is tuned by the simulation that the vehicle is modeled as 2 DOF verified by the results of the actual vehicle test. The lateral control algorithm by the yaw rate feedback has good performances of lane tracking and passenger comfort.

• Journal of Mechanical Science and Technology
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• 제16권3호
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• pp.338-343
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• 2002

In the autonomous vehicle, the reference lane is continually detected by machine vision system. And then the vehicle is steered to follow the reference yaw rates which are generated by the deviations of lateral distance and the yaw angle between a vehicle and the reference lane. To cope with the steering delay and the side-slip of vehicle, PI controller is introduced by yaw rate feedback and tuned from the simulation where the vehicle is modeled as 2 DOF and 79 DOF and verified by the results of an actual vehicle test. The lateral control algorithm by yaw rate feedback has good performances of lane tracking and passenger comfort.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2004년도 추계학술대회 논문집
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• pp.180-185
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• 2004

This paper shows how can be controlled the rubber tired TRAM by electromagnetic field with a specific pattern as autonomous driving system. The system is composed with drive elements. steering elements. navigational devices. transmitter/receivers and sensor means for sensing the position relative to the magnetic markers. There are difficulties in sensing track conditions. curvatures. slops etc. forward compared to that of the control system optically. The sensing track conditions previously is important for running stability and riding comfort. This paper shows how can achieve track condition in advance by means of electromagnetic pattern originally.

• 제어로봇시스템학회논문지
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• 제12권9호
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• pp.850-855
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• 2006

This is concerned with the development and design of automatic maneuvering system using Differential Global Positioning System(DGPS). To achievement of autonomous maneuvering controller for giant ship, first, we investigated automatic maneuvering controller using DGPS in motor car. The sensors are configured with DGPS and digital compass. We calculated velocity and steering angle of motor car based on sensor signal. To design the controller, we derived the bicycle model and developed critically damped controller. The critically damped controller can be tracing previously appointed position in the fastest time. We are used a laptop computer to realize and the control algorithm is programmed by visual basic software. The obtained experimental results from developed system show unmanned motor car is good tracing planed positions. Hence, the system is looking forward to use the autonomous maneuvering control fur giant ship.