• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.171-176
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• 2019

Drones are highly utilized because they can efficiently acquire long-distance videos. In drone operation, the speed, which is the magnitude of the velocity, can be set, but the moving direction cannot be set, so accurate information about the drone's movement should be estimated. In this paper, we estimate the velocity of the drone moving at a constant speed and direction. In order to estimate the drone's velocity, the displacement of the target frame to minimize the sum of absolute difference (SAD) of the reference frame and the target frame is obtained. The ground truth of the drone's velocity is calculated using the position of a certain matching point over all frames. In the experiments, a video was obtained from the drone moving at a constant speed at a height of 150 meters. The root mean squared error (RMSE) of the estimated velocities in x and y directions and the RMSE of the speed were obtained showing the reliability of the proposed method.

• Annual Conference of KIPS
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• 2018.10a
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• pp.434-437
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• 2018

본 논문에서는 ROS (Robot Operating System)에 대해서 소개하고 ROS를 이용해 드론의 제어기와 필터를 구현해본다. 드론이 강인한 성능을 보이기 위해서는 기체의 상태에 대한 더 정확한 추정이 필요하다. 드론이 기체좌표계로 출력하는 각 축(x축, y축, z축)에 대한 선속도, 선가속도를 더 정확히 추정하기 위해 칼만 필터를 설계하며 칼만 필터를 통과한 상태 변수를 제어 입력으로 하는 PID(Proportional Integral Derivative) 제어기를 설계한다. 실험적인 부분에서는 제어기와 자율 주행 알고리즘을 접목시켜 드론이 자신의 상태를 추정하고 알고리즘을 순차적으로 진행하는 과정을 살펴본다. 마지막으로 알고리즘을 통해 드론의 임무 수행 여부를 살펴보고 정밀한 제어를 위한 추가적인 제어기 설계 방법과 연구 방향을 제시하고자 한다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.5
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• pp.827-834
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• 2022

Recently, marine surveys using unmanned ships are attracting attention, and research on small unmanned ships using sails is on the rise. Sail drones can be used for marine surveys, monitoring, and pollution management. Therefore, in this study, using the method of estimating the ship speed for twin sail drones, the optimal conditions for sailing are checked, and the performance to be considered in the initial design stage, such as the motion performance and resistance of the sail drone. Consequently, the twin sail drone had a speed lower than 2.0 m/s, and the stability satisfied the rule by DNV. In addition, the maximum speed at an angle of attack of 20° at TWA 100° was 1.69 m/s and that at an angle of attack of 25° at TWA 100° was 1.74 m/s.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.322-323
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• 2021

증강현실이나 자율 주행, 드론 등의 기술에서 현재 위치와 시점을 파악하기 위해서는 실시간 카메라 자세 추정이 필요하다. 이를 위해 가장 일반적인 방식인 연속적인 단안 영상으로부터 카메라 자세를 추정하는 방식은 두 영상의 정적 객체 간에 견고한 특징점 매칭이 이루어져야한다. 하지만 일반적인 영상들은 다양한 이동 객체가 존재하는 동적 환경이므로 정적 객체만의 매칭을 보장하기 어렵다는 문제가 있다. 본 논문은 이 같은 동적 환경 문제를 해결하기 위해, 신경망 기반의 객체 분할 기법으로 영상 속 객체를 추출하고, 객체별 특징점 매칭 및 자세 추정 결과로 정적 객체를 특정해 매칭하는 방법을 제안한다. 또한, 제안하는 정적 객체 특정 방식에 적합한 신경망 기반 특징점 추출 방법을 사용하면 동적 환경에 보다 강인한 카메라 자세 추정이 가능함을 실험을 통해 확인한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.103-111
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• 2021

The purpose of this study is to study a method for preventing collisions of multiple drones in controlled airspace. As a result of the study, it was proved that it is appropriate as a method to control drone collisions after setting accurate information on the ROI (Region of Interest) area estimated based on the expected drone path and time in the control system as a method to avoid drone collision. As a result of the empirical analysis, the diameter of the flight path of the operating drone should be selected to reduce the risk of collision, and the change in the departure time and operating speed of the operating drone did not act as an influencing factor in the collision. In addition, it has been demonstrated that providing flight priority is one of the appropriate methods as a countermeasure to avoid collisions. For collision avoidance methods, not only drone sensor-based collision avoidance, but also collision avoidance can be doubled by monitoring and predicting collisions in the control system and performing real-time control. This study is meaningful in that it provided an idea for a method for preventing collisions of multiple drones in controlled airspace and conducted practical tests. This helps to solve the problem of collisions that occur when multiple drones of different types are operating based on the control system. This study will contribute to the development of related industries by preventing accidents caused by drone collisions and providing a safe drone operation environment.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.237-250
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• 2022

In this study, we propose a method to estimate the biomass of invertebrate grazers from the videos with underwater drones by using a multi-object tracking model based on deep learning. In order to detect invertebrate grazers by classes, we used YOLOv5 (You Only Look Once version 5). For biomass estimation we used DeepSORT (Deep Simple Online and real-time tracking). The performance of each model was evaluated on a workstation with a GPU accelerator. YOLOv5 averaged 0.9 or more mean Average Precision (mAP), and we confirmed it shows about 59 fps at 4 k resolution when using YOLOv5s model and DeepSORT algorithm. Applying the proposed method in the field, there was a tendency to be overestimated by about 28%, but it was confirmed that the level of error was low compared to the biomass estimation using object detection model only. A follow-up study is needed to improve the accuracy for the cases where frame images go out of focus continuously or underwater drones turn rapidly. However,should these issues be improved, it can be utilized in the production of decision support data in the field of invertebrate grazers control and monitoring in the future.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.589-597
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• 2023

Floating debris in large quantities from land during heavy rainfall has adverse social, economic, and environmental impacts, but the monitoring system for the concentration area and amount is insufficient. In this study, we proposed an efficient monitoring method for floating debris entering the river during heavy rainfall in Daecheong Lake, the largest water supply source in the central region, and applied remote sensing techniques to estimate the standing-stock of floating debris. To investigate the status of floating debris in the upper of Daecheong Lake, we used a tracking buoy equipped with a low-orbit satellite communication terminal to identify the movement route and behavior characteristics, and used a drone to estimate the potential concentration area and standing-stock of floating debris. The location tracking buoys moved rapidly during the period when the cumulative rainfall for 3 days increased by more than 200 to 300 mm. In the case of Hotan Bridge, which showed the longest distance, it moved about 72.8 km for one day, and the maximum moving speed at this time was 5.71 km/h. As a result of calculating the standing-stock of floating debris using a drone after heavy rainfall, it was found to be 658.8 to 9,165.4 tons, with the largest amount occurring in the Seokhori area. In this study, we were able to identify the main concentrations of floating debris by using location-tracking buoys and drones. It is believed that remote sensing-based monitoring methods, which are more mobile and quicker than traditional monitoring methods, can contribute to reducing the cost of collecting and processing large amounts of floating debris that flows in during heavy rain periods in the future.