• Proceedings of the Korean Society of Computer Information Conference
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• 2008.06a
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• pp.257-262
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• 2008

컴퓨팅 기술의 발전에 따라 선박의 안전항해를 지원하기 위해 Radar, GPS 등 다양한 장비들이 계량, 개발되고 있으며 그들은 선박 항해에 필요한 많은 정보를 제공하고 있다. 하지만 여전히 선박 충돌사고는 끊이지 않고 있으며, 선박 대형화에 힘입어 그 피해도 커지고 있는 실정이다. 이러한 선박 충돌사고는 앞에서 언급한 선박 항해 안전 장비의 성능제약을 받는 야간이나, 해상 환경 악화 시 두드러지게 발생하고 있으며, 특히 제한적인 상황에서 인간의 눈에만 의지해서 항해를 하고 있기 때문이기도 하다. 그래서 이러한 상황에서 Vision기술을 사용하여 카메라를 활용 상대선박을 자동으로 식별하는 시스템을 제안하고자 한다. 이는 선박들이 법적으로 야간이나 각종 장비들이 제한을 받는 상황에서 근처의 다른 선박에게 상황을 전달하기 위해서 등화(불빛)와 형상물을 사용해야한다는 점에서 착안하였다. 제안 시스템을 실제 해상 환경에서 실험하기에 제한점이 많아 프로토타입을 구현하여 실험실 환경에서 실험하고 사용자 평가를 실시하였다. 즉, LED를 가상 등화로 하여 선박에 설치된 것과 동일한 색상과 동일한 위치에 배치하고 이를 카메라를 활용하여 인식 실험을 하였으며 약 90%의 인식률을 보였다. 그리고 이러한 실험화면을 활용하여 항해업무 종사자 15명을 대상으로 사용자 평가를 실시하였으며 대부분의 사람들이 제안된 체계가 해상에서 유용하다고 답변하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1044-1050
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• 2014

Robots used for pipe inspection have been studied for a long time and many mobile mechanisms have been proposed to achieve inspection tasks within pipelines. Localization is an important factor for an inpipe robot to perform successful autonomous operation. However, sensors such as GPS and beacons cannot be used because of the unique characteristics of inpipe conditions. In this paper, an inpipe localization algorithm based on elbow detection is presented. By processing the projected marker images of laser pointers and the attitude and heading data from an IMU, the odometer module of the robot determines whether the robot is within a straight pipe or an elbow and minimizes the integration error in the orientation. In addition, an off-line positioning algorithm has been performed with forward and backward estimation and Procrustes analysis. The experimental environment has consisted of several straight pipes and elbows, and a map of the pipeline has been constructed as the result.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.29-35
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• 2019

This paper proposes a UAV equipped with an automatic control system for educational purposes such as navigation flight or autonomous flight. The proposed UAV is capable of automatic navigation flight and it is possible to control more precisely and delicately than existing UAV which is directly controlled. And it has the advantage that it is possible to fly in a place out of sight. In addition, the user may arbitrarily change the route or route information to use it as an educational purpose for achieving the special purpose. It also allows you to check flight status by shooting a video during flight. For this purpose, it is designed to check the image in real time using 5.8GHz video transmitter and receiver. The flight information is recorded separately and used as data to judge the normal flight after the flight. The result of the paper can be flighted along the coordinates specified using GPS information. Since it can receive real-time video, it is expected to be used for various education purposes such as reconnaissance of polluted area, achievement of special purpose, and so on.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.237-238
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• 2019

현시대에 자율주행 기술이 자동차를 단순 이동수단에서 이동성을 확보한 생활공간으로 자동차의 근본적인 개념을 변화시켜 새로운 산업 패러다임적 가치뿐 아니라, 사회 경제적 변혁을 예고하고 있다. 이미 전 세계적인 기업들은 자율주행 시스템을 구축하고 개발하여 실제 생활에서 활용도 하고 있다. 그럼에도 불구하고 상용화를 하기 위해선 아직 법/제도의 부재, 안정성, 가격 등 여러부분에서 문제점들을 극복해야한다. 본 과제인 라인트레이서와 GPS를 활용한 자율주행시스템이 목적지를 지정하면 자율적으로 길이나 도로를 따라 이동하면서 장애물을 피해가게 만들어 안정성을 확보하고 이동하는 시간에 개인 여가 시간이나 생산적인 활동을 할수 있게 만들어 삶의 질 개선에 기여할 것이다. 이러한 기술들을 적극 활용하여 목적지를 설정하면 자율주행 하는 자동차로 설정하였고, 장애물 감지와 현재 방향 감지를 추가하였다. 장애물 감지와 방향 그리고 위치를 수신받기 위해 5개의 센서를 활용하였고 한번에 구동을 시키기 위해 센서 쉴드를 활용하여 기능을 확장 시켰다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.3
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• pp.480-488
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• 2019

In this paper, we propose an obstacle avoidance system for an unmanned ship to navigate safely in dynamic environments. Also, in this paper, one-dimensional low-cost lidar sensor is used, and a servo motor is used to implement the lidar sensor in a two-dimensional space. The distance and direction of an obstacle are measured through the two-dimensional lidar sensor. The unmanned ship is controlled by the application at a Tablet PC. The user inputs the coordinates of the destination in Google maps. Then the position of the unmanned ship is compared with the position of the destination through GPS and a geomagnetic sensor. If the unmanned ship finds obstacles while moving to its destination, it avoids obstacles through a fuzzy control-based algorithm. The paper shows that the experimental results can effectively construct an obstacle avoidance system for an unmanned ship with a low-cost LiDAR sensor using fuzzy control.

• Journal of Drive and Control
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• v.17 no.4
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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.

• The Journal of Korea Robotics Society
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• v.16 no.4
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• pp.306-312
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• 2021

This paper describes localization of autonomous underwater vehicles(AUV), which can be used when some navigation sensor data are an outlier. In that situation, localization through existing navigation algorithms causes problems in long-range localization. Even if an outlier sensor data occurs once, problems of localization will continue. Also, if outlier sensor data is related to azimuth (direction of AUV), it causes bigger problems. Therefore, a parallel localization module, in which different algorithms are performed in a normal and abnormal situation should be designed. Before designing a parallel localization module, it is necessary to study an effective method in the abnormal situation. So, we propose a localization method through machine learning. For this method, a learning model consists of only Fully-Connected and trains through randomly contaminated real sea data. The ground truth of training is displacement between subsequent GPS data. As a result, average error in localization through the learning model is 0.4 times smaller than the average error in localization through the existing navigation algorithm. Through this result, we conclude that it is suitable for a component of the parallel localization module.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.352-354
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• 2022

Position measurement using a camera has been studied for a long time. This is being studied for distance recognition or object recognition in autonomous vehicles, and it is being studied in the field of indoor navigation, which is a limited space where GPS is difficult to apply. In general, in a method of measuring the distance using a camera, the distance is measured using a distance between the cameras using two stereo cameras and a value measured through a captured image or photo. In this paper, we propose a method of measuring the distance of an object using a single camera. The proposed method measures the distance by using the distance between cameras, such as a stereo camera, and the value measured by the photographed picture through the gap of the photographing time and the distance between photographing.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.9
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• pp.495-504
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• 2017

An amphibious scrubbing/suction dredging machine with cylindrical rotating brush, housing, and turbidity barrier was newly-developed to remove both sediments with about 10 cm thickness and periphyton attached on various structures in urban water-circulating systems through the scrubbing, suction, and dredging processes. Based on the field application and long-term monitoring, the increase in both suspended solids (SS) and turbidity of water during the scrubbing, suction, and dredging processes was negligible (p>0.05). In some cases, the turbidity of water initially increased, however, the turbidity was stabilized within 20 minutes from the start of dredging processes. The concentration changes in TN and TP of water were not statistically different (p>0.05) before and after the scrubbing, suction, and dredging processes, indicating that benthic nutrients released from sediments were not significantly diffused, and were not supposed to cause significant water pollution. Also, water treatment facilities along with an amphibious scrubbing/suction dredging machine could be more effective since the removal of contaminant loadings through the scrubbing, suction, and dredging processes was much greater than that through simple coagulation/precipitation processes. Finally, GPS-based realtime tracking and operation program have been developed and applied in various urban water-circulating systems, and development of driver cooperative autonomous driving system is in progress to eliminate the need for manual driving of an amphibious scrubbing/suction dredging machine.

• Journal of Korean Society of Transportation
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• v.35 no.2
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• pp.116-128
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• 2017

Traffic accidents can be defined as a physical collision event of vehicles occurred instantaneously when drivers do not perceive the surrounding vehicles and roadway environments properly. Therefore, detecting the high potential events that cause traffic accidents with monitoring the interactions among the surroundings continuously by driver is the prerequisite for prevention the traffic accidents. For the analysis, basic data were collected to analyze interactions using a test vehicle which is equipped the GPS(Global Positioning System)-IMU(Inertial Measurement Unit), camera, radar and RiDAR. From the collected data, highway geometric information and the surrounding traffic situation were analyzed and then safety evaluation algorithm for driving vehicle was developed. In order to detect a dangerous event of interaction with surrounding vehicles, locations and speed data of surrounding vehicles acquired from the radar sensor were used. Using the collected data, the tangent and curve section were divided and the driving safety evaluation algorithm which is considered the highway geometric characteristic were developed. This study also proposed an algorithm that can assess the possibility of collision against surrounding vehicles considering the characteristics of geometric road structure. The methodology proposed in this study is expected to be utilized in the fields of autonomous vehicles in the future since this methodology can assess the driving safety using collectible data from vehicle's sensors.