• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.69-75
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• 2019

Remotely Piloted Aircraft (RPA) controls as a type of unmanned aerial vehicle (drone) is growing rapidly and its flight controller stick disposition is required standardization. We should standardize RPA drone flight control disposition because the flight pilot of RPA is hard to be trained so the flight controller stick differences impairs safety and wastes time and effort of flight controller industry. So this study researches the on-going standardization of RPA drone flight control disposition in Korea and foreign countries. Also this paper analyzes and researches of expert about RPA drone flight controller function and application of flight control mode. I accomplished expert research about standardization plan of unmanned flight control mode and confirm the necessity. Nowadays mode1 and 2 are mostly used in Korea so I carried out preference investigation for two modes. There were 4 preferences choices of RPA drone control mode necessity (importance) and recommendation of standardization modes. They answered that necessity of standardization is important considering pilot training, flight safety and positive development of drone industry. The result of standardization mode preference is that they prefer mode 2 (drone maker 86%, training facilities and research facilities 58%, government bureau 60%). Overall preference result shows that mode 1 24%, mode 1&2 16%, mode 2 60%. So they preferred mode 2 by 60%. The differences between two modes are the direction of throttle and pitch. Direction of throttle and pitch operate opposite way. They prefer mode 2 because mode 2 has similarities of manned flight control mode. Significance of this study is that it showed the necessity of standardization and flight control preference in a quantitative way. It will help drone standardization in related industries and development direction near future.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1081-1087
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• 2015

Recently, the researches of aerial drones are actively executed in various areas, the researches of surface drones and underwater drones are also executed in marine areas. In case of surface drones, they essentially utilize acoustic information by the sonar and consequently have the local information in the obstacle avoidance as the sonar has the limitations due to the beam width and detection range. In order to overcome this, more global method that utilizes optical images by the camera is required. Related to this, the aerial drone with the camera is desirable as the obstacle detection of the surface drone with the camera is impossible in case of the existence of clutters. However, the dynamic-floating aerial drone is not desirable for the long-term operation as its power consumption is high. To solve this problem, a collaborative obstacle avoidance method based on the acoustic information by the sonar of the surface drone and the optical image by the camera of the static-floating aerial drone is proposed. To verify the performance of the proposed method, the collaborative obstacle avoidances of a MSD(Micro Surface Drone) with an OAS(Obstacle Avoidance Sonar) and a BMAD(Balloon-based Micro Aerial Drone) with a camera are executed. The test results show the possibility of real applications and the need for additional studies.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.132-137
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• 2017

Drone is currently used for wide application areas in our real life. Also it performs more important functions. We propose a method of drone operation system for the prevention of industrial disaster. In normal operation of drone system the drone monitors the industrial sites according to the planned flight path with acquiring the monitored images and send the image information to the server. The server analyzes and compares the images to DB information by calculating the similarity based on the threshold. Then the system decides whether the industrial sites has problems or not. If the abnormal condition is occurred, the drone change the flight path to abnormal flight path and keep monitoring the industrial sites with measuring the air status by sensors and sends all information to server system on the ground. If the emergency case is occurred, drone approaches the closest position of accident points and acquiring the all information and send them to server and 119 center.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.205-210
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• 2022

Drones, which have rapidly grown along with the 4th industrial revolution, spread over industries and also widely used for military purposes. In recent wars in Europe, drones are being evaluated as a game changer on the battlefield, and their importance for military use is being highlighted. The Republic of Korea Army also planned drone-bot systems including various drones suitable for echelons and missions of the military as future defense forces. The keyword of these drone-bot systems is autonomy by artificial intelligence. In addition, common use of operating platforms is required for the rapid development of various types of drones. In this paper, we propose software framework that applies diverse artificial intelligence technologies such as multi-agent system, cognitive architecture and knowledge-based context reasoning for mission autonomy and common use of military drones.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.93-104
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• 2023

Recently, the technology of drones is developing remarkably. The role of military drones is so great that they can cause serious damage to the enemy's important strategic assets without any damage to our allies in all battlefield environments (land, sea, air). However, the battleship combat management system currently operated by the Korean Navy is vulnerable to defense because there is no customized defense system against drones. As drones continue to develop, they are bound to pose a major threat to navy in the future. This paper proposes a way for the warfare software of naval combat management system sets a combat mode suitable for anti-drone battle, evaluates the threat priority in order to preemptively respond to drone threats and eliminate drone threats through automatic allocation of self-ship-mounted weapons and sensors, and through a test of the improved warfare software in a simulated environment, it was proved that the time to respond to the drone was improved by 62%.

• Journal of Platform Technology
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• v.10 no.4
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• pp.56-61
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• 2022

Various convergence technologies discovered through the 4th industrial revolution are permeating the industry. Drones are being used in industries such as construction, transportation, and national defense based on convergence technology. Quart-copter drone control is being used in a wide range of fields from the visual field of operation with the naked eye to the remote field of view using GCS. If we classify those who operate industrial drones, there are general pilots who directly use drones, instructors who train drone pilots, and mechanics who check the status of drones and use them for a long time. Depending on the shape of the screen of the drone GCS, a user's quick response or key data can be acquired. Accordingly, in this study, GUI characteristics were analyzed for the mission planner GCS and a screen composition method according to the user was proposed.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.3
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• pp.271-278
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• 2020

KEPCO Research Institute developed a GIS-based autopilot drone inspection system for electric power facilities and since its pilot application in 2017, it has been successfully used to detect defects in power transmission lines. This paper presents how to operate this system in the field of power line inspection. Power transmission lines are located in a wide variety of environments such as plains, mountains, river crossings, sea crossings, and industrial areas. Among these, some transmission lines are difficult for human workers to access because of their geographies and some should be checked more often due to their severe contamination. Considering these field conditions, we classified drone operation in two categories to increase its effectiveness and efficiency - patrol surveillance and detailed inspection tasks. This paper describes the detailed procedures of the two tasks above and their field application experiences. In addition, this paper newly proposes how to construct public drone roads by using the information of KEPCO's power transmission lines.

• Journal of Platform Technology
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• v.9 no.3
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• pp.78-83
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• 2021

The new industry drone research is increasing through convergence between 4th industrial revolution technology. In particular, the government indicates the D.N.A platform as a countermeasure of 4th industrial revolution. So, the research topics are remarkable which are using D.N.A platform. On the other hand, the drone for industrial and research has spatial factor based on sequential because, they performance scenario-based mission through control operation. When the drone flights as a control operation, they have necessity apply multi-dimensional methods to improve the security level. So, this study researched a scenario based drone platform to improve the security level. As a result, the space classified as a ground control system, drone, drone data server and designed the application method based on scenario security technology.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.126-134
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• 2023

Drones are emerging as a new security threat, and the world is working to reduce them. Detection and identification are the most difficult and important parts of the anti-drone systems. Existing detection and identification methods each have their strengths and weaknesses, so complementary operations are required. Detection and identification performance in anti-drone systems can be improved through the use of artificial intelligence. This is because artificial intelligence can quickly analyze differences smaller than humans. There are three ways to utilize artificial intelligence. Through reinforcement learning-based physical control, noise and blur generated when the optical camera tracks the drone may be reduced, and tracking stability may be improved. The latest NeRF algorithm can be used to solve the problem of lack of enemy drone data. It is necessary to build a data network to utilize artificial intelligence. Through this, data can be efficiently collected and managed. In addition, model performance can be improved by regularly generating artificial intelligence learning data.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.137-146
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• 2024

drones are used in a variety of fields, including business, leisure, lifesaving, and war. Various research using drones is being conducted in the military. In particular, the use of drones in 『Manned-Unmanned Complex combat performance plan』, powered by various unmanned vehicles deployed in the Army TIGER system, is expected to be a major factor realizing the Army's future combat performance that minimizes damage to ally combat troops while causing maximum damage to the enemy. As the deployment of various systems progresses, combat performance methods utilizing each system are evolving, but there is a lack of research to identify and resolve limitations in the perspective of unmanned vehicle operators. Based on the Ukrainian military's FPV drone combat case, we would like to make suggestions from the operator's perspective on overcoming perspective limitations through the introduction of FPV and the designation of military drone frequency.