• 한국ITS학회 논문지
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• 제15권4호
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• pp.81-90
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• 2016

자율주행 차량은 변화하는 도로환경에 스스로 대응 가능하여야 하여, 인간 운전자 수준의 도로환경 인지성능을 확보하여야 한다. 자율주행 차량의 센서 중 영상센서는 주행방향 결정 및 차로이탈 방지 등 조향제어 수행을 위하여 차선인식 기능을 수행한다. 현재 제시된 영상센서의 차선인식 성능기준은 ADAS(Advanced Driver Assistance System)과 관련된 '운전자 보조' 관점의 성능기준으로서, 자율주행 차량의 '주체적 인지'를 위한 성능조건과 상이할 것으로 판단된다. 본 연구에서는 자율주행 시 차선인식이 비정상적으로 지속되어, 직선구간에서 곡선구간으로 진입하는 차량이 조향실패에 따라 차로를 이탈하는 상황을 가정하였다. 차량 이동궤적을 기반하여 차로이탈 상황을 모형화하고, 차로이탈 허용 수준에 따른 자율주행 차량 영상센서 성능수준을 제시하였다. 분석 결과 승용차 조건에서 차선인식 기능이 1초 이상 연속적인 오작동을 일으킨다면 차로이탈에 의한 위험한 상황에 놓일 수 있으며, 자율주행 차량을 위하여 현재 ADAS 영상센서 성능평가 방법에서의 차로이탈조건보다 심각한 차로이탈상황을 고려한 영상센서 성능평가 방안이 필요할 것으로 판단된다.

• 제어로봇시스템학회논문지
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• 제20권2호
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• pp.132-137
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• 2014

In this paper, An LQR controller is proposed for way-point tracking of AUV (Autonomous Underwater Vehicle). The LQR controller aims at tracking a series of way-points which operator registers arbitrarily in advance. It consists of a depth controller and a steering controller and AUV's surge speed is assumed varying to consider the dynamic environment of the underwater. In order to show the performance, a conventional state feedback controller is compared with the proposed controller by the simulation using Matlab/Simulink. The parameters of AUV developed by the author's laboratory are used. In the simulation, we verify that the LQR controller can track all the way-points within 1 m error range under the varying surge speed, which proves the robustness of the LQR controller.

• Journal of Biosystems Engineering
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• 제21권4호
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• pp.422-428
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• 1996

This study was conducted to developed to develop a simple battery-powered autonomous vehicle for greenhouse works. A steering method using speed difference of two independent driving motors was adopted. DC motor driving circuit, speed control circuit and controller using one-chip microcomputer were constructed. The inputs of controller are rolling of the vehicle and current speed of driving motors. Using these signals, automatic guidance system along furrow was developed. A computer simulation program by the kenematic analysis was developed to find out optimal control algorithm. The results of this study are as follows. 1. Automatic guidance system along the furrow that adopted two independent driving motors and rolling of vehicle was developed. 2. The results of simulation showed that PID control was adequate to automatic guidance system along furrow. 3. Two commercial 12V battery serially connected were able to drive the vehicle on the soil ground for five hours in continuous operation and for four hours in intermittent operation without recharging the battery. 4. The speed range was 0-0.7m/s and the rolling of vehicle could be controlled within $pm5^{\circ}$ range. 5. From a series of tests, developed vehicle was found to be a useful tool for greenhouse works.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2000년도 춘계학술대회논문집
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• pp.56-63
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• 2000

Abstract - In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2000년도 추계학술대회논문집
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• pp.207-217
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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 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 angle, distance error and real position of other vehicles, we should calculate the reference steering angle.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 1999년도 춘계종합학술대회
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• pp.340-347
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• 1999

최근 산업화로 인하여 물류 자동화에 많은 관심이 집중되고 있다. 지금까지는 컨베이어 벨트가 물류 자동화에 있어서 가장 많이 사용되었지만 이 시스템은 공간을 많이 차지하고, 비용이 많이 든다는 단점을 가지고 있다. 본 논문은 퍼지를 이용한 새로운 자율 주행 제어 알고리즘을 소개한다. 이 이동로봇은 바닥 위에 설치된 선을 따라가도록 되어있다. 그리고 3개의 근접센서로부터 정보가 입력된다. 이러한 획득된 정보를 자율 주행을 위하여 퍼지로 제어하였다. 그러므로 현존하는 시스템과는 달리, 열악한 환경 조건하에서도 높은 신뢰성을 보증하고, 라인의 유지 보수를 낮은 비용으로 쉽게 설치할 수 있다. 이 자율이동로봇의 이용은 공장이나 병원 내의 물류자동화를 실현시키고, 사무실 내에서 서류배달 등의 여러분야에 응용되어 질 수 있다.

• 제어로봇시스템학회논문지
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• 제21권3호
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• pp.179-186
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• 2015

In this paper, a novel lateral control system is proposed for the purpose of improving lane keeping performance which is independent from GPS signals. Lane keeping is a key function for the realization of unmanned driving systems. In order to obtain this objective, a vision sensor based real-time lane detection scheme is developed. Furthermore, we employ a data fusion along with a real-time steering angle of the test vehicle to improve its lane keeping performance. The fused direction data can be obtained by an IMU sensor and vision sensor. The performance of the proposed system was verified by computer simulations along with field tests using MOHAVE, a commercial vehicle from Kia Motors of Korea.

• 한국정밀공학회지
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• 제26권6호
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• pp.74-80
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• 2009

Path tracking of unmanned vehicle is a basis of autonomous driving and navigation. For the path tracking, it is very important to find the exact position of a vehicle. GPS is used to get the position of vehicle and a direction sensor and a velocity sensor is used to compensate the position error of GPS. To detect path lines in a road image, the bird's eye view transform is employed, which makes it easy to design a lateral control algorithm simply than from the perspective view of image. Because the driving speed of vehicle should be decreased at a curved lane and crossroads, so we suggest the speed control algorithm used GPS and image data. The control algorithm is simulated and experimented from the basis of expert driver's knowledge data. In the experiments, the results show that bird's eye view transform are good for the steering control and a speed control algorithm also shows a stability in real driving.

• 한국항공우주학회지
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• 제37권12호
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• pp.1217-1224
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• 2009

고정익 항공기가 3차원의 복잡한 경로를 추종하기 위해 필요한 비교적 간단하며 효과적인 유도 제어 방법을 제시한다. 소개되는 방법은 비선형 경로 추종 유도 기법을 외부 루프로 사용한다. 외부 루프는 원하는 경로와 함께 항공기의 현재 위치와 속도를 바탕으로 비행 경로를 변화하기 위한 가속도 명령을 생성한다. 가속도 명령은 중력과 벡터적으로 결합되어 Specific Force Acceleration을 만든다. 이렇게 생성된 Specific Force Acceleration은 내부 루프를 위한 명령으로 쓰이는데, 이는 항공기가 가속도 자체보다는 Specific Force Acceleration을 더 직접적으로 제어할 수 있기 때문이다. 나아가 배면 비행이나 Slow Roll, Knife-Edge 등과 같은 옆미끄럼짐 기동을 하기 위해 필요한 롤 자세 제어 기법도 제시한다. 마지막으로 표준이 되는 여러 가지 곡예비행 경로들에 대한 시뮬레이션을 수행함으로써 제시된 기법의 성능을 검증한다.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권4호
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• pp.201-212
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• 2000

In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. When the immune algorithm is applied to the PID controller, there exists the cast that the plant is damaged due to the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.