• International Journal of Automotive Technology
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• 제3권2호
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• pp.71-78
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• 2002

A new control method far vision-based autonomous vehicle is proposed to determine navigation direction by analyzing lane information from a camera and to navigate a vehicle. In this paper, characteristic featured data points are extracted from lane images using a lane recognition algorithm. Then the vehicle is controlled using new Levenberg-Marquardt neural network algorithm. To verify the usefulness of the algorithm, another algorithm, which utilizes the geometric relation of a camera and vehicle, is introduced. The second one involves transformation from an image coordinate to a vehicle coordinate, then steering is determined from Ackermann angle. The steering scheme using Ackermann angle is heavily depends on the correct geometric data of a vehicle and a camera. Meanwhile, the proposed neural network algorithm does not need geometric relations and it depends on the driving style of human driver. The proposed method is superior than other referenced neural network algorithms such as conjugate gradient method or gradient decent one in autonomous lateral control .

• 대한기계학회논문집A
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• 제38권5호
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• pp.551-557
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• 2014

본 논문은 작업 시 농업용 트랙터의 운전지원을 위한 강인한 횡방향 제어기를 제안하고자 한다. 자동차와 달리 트랙터의 조향 방식은 유압실린더를 이용함으로써 상대적으로 큰 시간지연을 가지고 있으며 작업 시 지면 환경도 일반 도로와는 다르다. 조향 액추에이터 모델을 포함하는 기구학적 트랙터 모델을 기반으로 동적 표면 제어라는 비선형 제어기법을 적용하여 조향 액추에이터의 시간지연 및 노면 경사의 변화에 강인한 횡방향 제어기를 설계한다. 마지막으로 상용 트랙터 시뮬레이터를 이용하여 마찰 계수가 일정한 주어진 노면 상태에서 조향 액추에이터의 시간 지연 변경이나 오르막 또는 내리막과 같은 지형 조건 변화에 대한 횡방향 제어기의 성능 및 강인성을 검증한다.

• 한국전자통신학회논문지
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• 제16권4호
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• pp.699-708
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• 2021

본 논문에서는 2개의 비전 센서와 딥 러닝을 이용한 자율주행 차량의 속도제어 알고리즘을 제시하였다. 비전 센서 A로부터 제공되는 도로 속도 표지판 영상에 딥 러닝 프로그램인 텐서플로우를 이용하여 속도 표지를 인식한 후, 자동차가 인식된 속도를 따르도록 하는 자동차 속도 제어 알고리즘을 제시하였다. 동시에 비전 센서 B부터 전송되는 도로 영상을 실시간으로 분석하여 차선을 검출하고 조향 각을 계산하며 PWM 제어를 통해 전륜 차축을 제어, 차량이 차선을 추적하도록 하는 조향 각 제어 알고리즘을 개발하였다. 제안된 조향 각 및 속도 제어 알고리즘의 유효성을 검증하기 위해서 파이썬 언어, 라즈베리 파이 및 Open CV를 기반으로 하는 자동차 시작품을 제작하였다. 또한, 시험 제작한 트랙에서 조향 및 속도 제어에 관한 시나리오를 검증함으로써 정확성을 확인할 수 있었다.

• 드라이브 ㆍ 컨트롤
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• 제17권4호
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• pp.113-124
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• 2020

Most of the work of construction equipment and agricultural machinery is done in off-road conditions. Autonomous driving required in these conditions uses GPS sensors, and PID controllers to control their speed and position. The hydrostatic steering, which is composed of a PSU, hydraulic hoses, and cylinders, rather than a mechanical coupling is used in these equipments. The PSU plays a key role in hydrostatic steering. Precise control of the position under various conditions requires detailed behavioral analysis of the basic components and operation. Two Gerotor PSU is now a commonly used safer option. The components of the PSU can be divided into mechanical and hydraulic actuating elements by its behavior. Since the system is combined by mechanical and hydraulic elements, the modelings are performed using Amesim, which is one of the most effective for the multi-domain dynamic system analysis. To confirm the validity of the model, input torque and pressures are checked with varying steering speed. The opening and the steering speed of normal and newly designed control valve set is investigated with the effect of centering spring force and friction. Finally, simulation results with fully detailed model with two gerotors are analyzed and compared with simple model.

• 제어로봇시스템학회논문지
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• 제7권10호
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• pp.827-836
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• 2001

The PID controller has been widely applied to the most control systems because of its simple structure and east designing. One of the important points to design the PID control system is to tune the approximate control parameters for the given target system. To find the PID parameters using Ziegler Nichols(ZN) method needs a lot of experience and experiments to ensure the optimal performance. In this paper, CMIA(Cell Mediated Immune Algorithm) controller is proposed to drive the autonomous guided vehicle (AGV) more effectively. The proposed controller is based on specific immune responses of the biological immune system which is the cell mediated immunity. To verify the performance of the proposed CMIA controller, some experiments for the control of steering and speed of that AGV are performed. The tracking error of the AGV is mainly investigated for this purpose. As a result, the capability of realization and reliableness are proved by comparing the response characteristics of the proposed CMIA controllers with those of the conventional PID and NNPID(Neural Network PID) controller.

• 한국정밀공학회지
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• 제25권10호
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• pp.58-66
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• 2008

In the development of intelligent vehicles, path tracking of unmanned vehicle is a basis of autonomous driving and automatic navigation. It is very important to find the exact position of a vehicle for the path tracking, and it is possible to get the position information from GPS. However the information of GPS is not the current position but the past position because a vehicle is moving and GPS has a time delay. In this paper, therefore, the moving distance of a vehicle is estimated using a direction sensor and a velocity sensor to compensate the position error of GPS. In the steering control, optimal fuzzy rules for the path tracking can be found through the simulation of Simulink. Real driving experiments show the fuzzy rules are good for the steering control and the position error of GPS is well compensated by the proposed estimation method.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제9권6호
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• pp.674-682
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• 2003

선박 자율운항시스템(autonomous navigation system)이란 선박운항에 있어 항해계획을 수립하고 현재의 선박운항 상태를 파악하여 주변 상황변화를 예측하고 대처하는 항해 전문가의 능력을 전산화한 것이다. 선박 자율운항시스템은 항해, 충돌회피, 선체유지, 자료융합, 운동제어 그리고 이를 통합하는 아키텍처로 구성되어 있다. 운동제어시스템은 선박의 유체학적 특성을 고려하여 해도 상에 원하는 위치로 선박을 이동하기 위해서 추진 및 조타장치를 제어하는 시스템으로 자율운항제어시스템에 필수적인 구성 시스템 중에 하나이다. 본 논문은 운영플랫폼인 가상세계시스템을 기반으로 운영되는 선박자율운항시스템과 운동제어시스템의 연동과 구현에 관한 연구이다. 운동제어시스템은 충돌회피시스템으로부터 상위 레벨의 고수준제어 요구치를 전달받아 조타 및 추진치로 변환하고 조타장치와 추진장치를 제어하는 시스템이다. 본 논문에서 선박 운동 특성을 수학적으로 모방하는 Oldenburger의 제어 이론에 기반하여 선박운동제어기를 개발하고 성능검정을 위해 선박시뮬레이터에서 다양한 시나리오를 바탕으로 시뮬레이션 한다.

• Journal of Biosystems Engineering
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• 제26권1호
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• pp.29-38
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• 2001

A navigation system was developed for autonomous guidance of a combine. It consisted of a DGPS, a machine vision system, a gyro sensor and an ultrasonic sensor. For an autonomous operation of the combine, target points were determined at first. Secondly, heading angle and offset were calculated by comparing current positions obtained from the DGPS with the target points. Thirdly, the fuzzy controller decided steering angle by the fuzzy inference that took 3 inputs of heading angle, offset and distance to the bank around the rice field. Finally, the hydraulic system was actuated for the combine steering. In the case of the misbehavior of the DGPS, the machine vision system found the desired travel path. In this way, the combine traveled straight paths to the traget point and then turned to the next target point. The gyro sensor was used to check the turning angle. The autonomous combine traveled within 31.11cm deviation(RMS) on the straight paths and harvested up to 96% of the whole rice field. The field experiments proved a possibility of autonomous harvesting. Improvement of the DGPS accuracy should be studied further by compensation variations of combines attitude due to unevenness of the rice field.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.91.1-91
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• 2001

The subject of this paper is vision system analysis of the autonomous vehicle. But, autonomous vehicle is one of the difficult topics from the point of view of several constrains on mobility, speed of vehicle and lack of environment information. Therefore, we are application of the vision system so that autonomous vehicle. Vision system of autonomous vehicle is likely to eyes of human. This paper can be divided into 2 parts. First, acceleration system and brake control system for longitudinal motion control. Second vision system of real time lane detection is for lateral motion control. This part deals lane detection method and image processing method. Finally, this paper focus on the integration of tole-operating vehicle and autonomous ...

• Agricultural and Biosystems Engineering
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• 제4권1호
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• pp.22-27
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• 2003

An autonomous tractor requires not only automatic steering (automatic guidance) but also automated control of tractor functions and implement operations. Examples of tractor functions include engine throttle, transmission speed, and 3-point hitch position. Implement operations include tillage, planting, and cultivating. This article provides an overview of a map-based methodology used for the implementation of autonomous field operations of agricultural tractors. The procedure for developing autonomous field operation maps were presented, and several important issues in the implementation of map-based autonomous operations were discussed. These issues included combining field operation maps, position offset, and real-time sensing and update of field operation maps.