• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1645-1653
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• 2014

In general, RGB, NIR, and thermal images are used for obtaining geospatial data. Such multiband images are collected via devices mounted on satellites or manned flights, but do not always meet users' expectations, due to issues associated with temporal resolution, costs, spatial resolution, and effects of clouds. We believe high-resolution, multiband images can be obtained at desired time points and intervals, by developing a payload suitable for a low-altitude, auto-piloted UAV. To achieve this, this study first established a low-cost, high-resolution multiband image collection system through developing a sensor and a payload, and collected geo-referencing data, as well as RGB, NIR and thermal images by using the system. We were able to obtain a 0.181m horizontal deviation and 0.203m vertical deviation, after analyzing the positional accuracy of points based on ortho mosaic images using the collected RGB images. Since this meets the required level of spatial accuracy that allows production of maps at a scale of 1:1,000~5,000 and also remote sensing over small areas, we successfully validated that the payload was highly utilizable.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.4
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• pp.8-15
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• 2011

This paper proposes a real-time navigation algorithm which integrates the artificial potential field (APF) for an unmanned vehicle in the unknown environment. This approach uses repulsive potential function around the obstacles to force the vehicle away and an attractive potential function around the goal to attract the vehicle. In this research, laser range finder is used as range sensor. An obstacle detected by the sensor creates repulsive vector. Differential global positioning system (DGPS) and digital compass are used to measure the current vehicle position and orientation. The measured vehicle position is also used to create attractive vector. This paper proposes a new concept of potential field based navigation which controls unmanned vehicle's speed and steering. The magnitude of repulsive force based on the proposed algorithm is designed not to be over the magnitude of attractive force while the magnitude is increased linearly as being closer to obstacle. Consequently, the vehicle experiences a generalized force toward the negative gradient of the total potential. This force drives the vehicle downhill towards its goal configuration until the vehicle reaches minimum potential and it stops. The effectiveness of the proposed APF for unmanned vehicle is verified through simulation and experiment.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.6
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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.

• Journal of Ocean Engineering and Technology
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• v.30 no.5
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• pp.426-430
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• 2016

Recently, many unmanned surface vehicles (USVs) have been developed and researched for various fields such as the military, environment, and robotics. In order to perform purpose specific tasks, common autonomous navigation technologies are needed. Obstacle avoidance is important for safe autonomous navigation. This paper describes a vector field histogram+ (VFH+) based obstacle avoidance method that uses the monocular vision of an unmanned surface vehicle. After creating a polar histogram using VFH+, an open space without the histogram is selected in the moving direction. Instead of distance sensor data, monocular vision data are used for make the polar histogram, which includes obstacle information. An object on the water is recognized as an obstacle because this method is for USV. The results of a simulation with sea images showed that we can verify a change in the moving direction according to the position of objects.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.339-340
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• 2008

로봇의 현재 위지 추적은 무인 로봇 자동 항법시스템의 중요 기술로 센서 데이터로부터 로봇의 위치를 결정하고 환경맵을 구성하는 것이다. 기존 방법으로는 초음파, 레이저 등의 거리 측정 센서를 이용해 로봇의 전역 위치를 찾는 방법과 스테레오 비전을 통한 방법이 개발되었다. 거리 측정 센서만으로 로봇위치 추적 알고리즘은 계산량이 감소하고 비용이 적게 들지만 센서오차율 및 환경장애에 따른 오류가 크다. 이에 반해 스테레오 비전 시스템은 3차원 공간영역을 정확히 측정할 수 있지만 계산량이 많아 고사양의 시스템을 요구하고 알고리즘 구현에 어려움이 있다. 따라서 본 논문에서는 단일 카메라 영상과 PSD(position sensitive device) 센서를 사용하여 로봇의 현재 위치를 추적하고 환경맵을 구성하여 자율이동이 가능한 시스템을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.675-678
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• 2016

최근 무인항공기 (Unmanned Aerial Vehicel, UAV)는 장점인 빠른 이동속도와 장착된 카메라를 이용하여 넓은 지역을 감시하기 위해서 활용되고 있다. 하지만, 조종사가 UAV를 직접 조종하여 넓은 지역을 비행하기에는 많은 비용이 발생한다. UAV가 자율적으로 넓은 지역을 비행하는 방법이 요구된다. 이 논문은 웨이포인트를 기반으로 UAV를 비행시키기 위한 Ground Control Station (GCS)의 구조를 제안한다. 비행할 웨이포인트는 위성항법시스템(Global Positioning System, GPS) 기반으로 설정하고 제안한 구조를 기반으로 다양한 임무 수행을 위해 다수의 비행 알고리즘을 정의하여 UAV를 비행시킨다. 부가적으로, 웨이포인트 기반으로 UAV를 비행시키기 위한 사용자 인터페이스도 소개한다.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.05a
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• pp.198-203
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• 2004

This paper describes a real-time control architecture for DUSAUV (Dual Use Semi-Autonomous Underwater Vehicle), which has been developed at Korea Research Institute of Ships & Ocean Engineering (KRISO), KORDI, for being a test-bed oj development of technologies for underwater navigation and manipulator operation. DUSAUV has three built-in computers, seven thrusters for 6 degree of freedom motion control, one 4-function electric manipulator, one pan/tilt unit for camera, one ballasting motor, built-in power source, and various sensors such as IMU, DVL, sonar, and so on. A supervisor control system for GUI and manipulator operation is mounted on the surface vessel and communicates with vehicle through a fiber optic link. Furthermore, QNX, one of real-time operating system, is ported on the built-in control and navigation computers of vehicle for real-time control purpose, while MicroSoft OS product is ported on the supervisor system for GUI programming convenience. A hierarchical control architecture which consist of three layers (application layer, real-time layer, and physical layer) has been developed for efficient control system of above complex underwater robotic system. The experimental results with implementation of the layered control architecture for various motion control of DUSAUV in a basin of KRISO is also provided.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.4
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• pp.181-186
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• 2016

Recently, the surveillance system research has focused because Unmanned Aerial Vehicle(UAV) has the ability to monitor wide area. When the wide area are monitored, controlling UAVs repeatedly by pilots invokes the cost problem to operate UAVs. If monitoring path can be defined in advance, the cost problem can be solved by controlling UAVs autonomously based on the monitoring path. The traditional approach generates multiple motor primitives based on flied GPS locations. However, the monitoring points by UAVs are not considered by the generated motor primitives, the surveillance by UAVs is not performed properly. This paper proposes a motor primitive structure for surveillance UAVs to be flied autonomously. Motor primitives are generated automatically by setting surveillance points to denote surveillance targets accurately.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.1-9
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• 2020

Acritical function of a nation is to protect its people's lives and properties from natural disasters such as a drought. A drought affects many aspects of human life, including social, economic, and industrial activities. Approximately 75.7% of reservoirs in Korea are over 50 years old.Sedimentation over the years may have caused a situation where storage capacity of the reservoirs is no longer sufficient and compliant with the original reservoir specifications. This study analyzes storage capacities for ten aged reservoirs using the autonomous navigation USV. It compares these capacities with sediment estimated by conventional empirical equations. Comparisons were made to the original specifications for the reservoirs.Storage capacity of six reservoirs decreased in a range between 16.2%-55.3% and storage capacity of 4 reservoirs increased in a range between 1.5%-380.2%. This data was compared to data derived from estimating sediment by empirical equations. Yoon's equation(1982) appeared more accurate than Sur's equation(1988) in Uhlinzi and Yongpo reservoirs, and Sur's equation(1988), however, appeared more accurate than Yoon's equation in Daegok, Ugok2 and Ochi reservoirs. The significant ranges of sedimentation shown in this study suggest that it is worth continuously surveying reservoirs to ensure their efficient management and operation.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.584-591
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• 2014

This paper presents a novel aided navigation method for AUV (Autonomous Underwater Vehicles). The navigation system for AUV includes several sensors such as IMU (Inertial Measurement Unit), DVL (Doppler Velocity Log) and depth sensor. In general, the $13^{th}$ order INS error model, which includes depth error, velocity error, attitude error, and the accelerometer and gyroscope biases as state variables is used with measurements from DVL and depth sensors. However, the model may degrade the estimation performance of the heading state. Therefore, the $11^{th}$ INS error model is proposed. Its validity is verified by using a degree of observability and analyzing steady state error. The performance of the proposed model is shown by the computer simulation. The results show that the performance of the reduced $11^{th}$ order error model is better than that of the conventional $13^{th}$ order error model.