• Journal of the Korea Society for Simulation
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• v.33 no.3
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• pp.37-50
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• 2024

In indoor disaster scenarios such as fires or gas leak, prompt rescue operations are essential to minimize expected casualties. This paper proposes a simulation model that applies the concept of Manned-Unmanned Teaming (MUM-T) for effective search and rescue in indoor fires. To this end, we first identify appropriate agents to model search and rescue operations. The proposed agent-based simulation consists of a fire and map model, an occupant model, a drone model for occupants searching, a rescuer model for searching and rescuing occupants, and a control center model that assigns missions to drones and rescuers. The agent models identified according to the MUM-T concept interact with other agents during the fire response simulation. Simulation experiments were conducted for search and rescue operations in three scenarios, one consisting of only rescuers and two with mixed rescuers and drones for MUM-T. The simulation results indicated that a drone applied to MUM-T could replace an average of four rescuers. The simulation method proposed in this study is expected to improve the efficiency of search and rescue operations in indoor disaster situations and minimizing the loss of life.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.117-118
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• 2018

드론의 활용은 점점 더 다양해지며 소규모지역에 대한 정밀 지도제작방법으로 자리매김하고 있다. 그러나, 결과물의 요구정확도의 예측이 불가능하므로 종종 촬영계획을 수정하여 재촬영할 경우가 종종있다. 촬영지역의 면적, 기준점 수 및 배치, 촬영고도 및 중복도에 대한 다양한 정확도 분석이 이루어진다면 사전 시뮬레이션을 통하여 원하는 정확도의 결과물을 얻을 수 있다. 본 연구에서는 드론측량 시 정확도에 영향을 주는 다양한 요소들을 추출하고 정확도 분석을 위한 테스트필드를 설계하고자 한다.

• Electronics and Telecommunications Trends
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• v.35 no.4
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• pp.81-90
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• 2020

The use of machine learning technologies such as deep and reinforcement learning has proliferated in various domains with the advancement of deep neural network studies. To make the learning successful, both big data acquisition and fast processing are required. However, for some physical world applications such as autonomous drone flight, it is difficult to achieve efficient learning because learning with a premature A.I. is dangerous, cost-ineffective, and time-consuming. To solve these problems, simulation-based approaches can be considered. In this study, we analyze recent trends in drone simulation technologies and compare their features. Subsequently, we introduce Octopus, which is a highly precise and scalable drone simulator being developed by ETRI.

• Annual Conference of KIPS
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• 2016.10a
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• pp.728-730
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• 2016

드론 기반의 항공촬영 기법을 영화제작에 적용토록 하기 위해 드론 기반의 스토리보드 제작 시스템을 제안한다. 제작 시스템은 항공촬영 수행 전, 비행 시뮬레이션을 수행하여, 다양한 스토리보드 세트를 수집한다. 감독은 스토리보드 세트 중 가장 적합한 스토리보드를 선택한다. 선택된 스토리보드에는 촬영 영상정보와 함께, 드론 제어정보들이 포함된다. 드론의 제어정보를 실제 촬영에서 사용하여, 정밀한 항공촬영을 지원할 수 있다.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.12
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• pp.277-286
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• 2019

The Unmanned Aerial Vehicle (UAV) is one of the most precious inventions of Internet of things (IOT). UAV faces the necessity to charge battery or replace battery from the charging stations during or between services. We propose scheduling algorithms for drone power charging (SADPC). The basic idea of algorithm is considering both a deadline (for increasing deadline miss ratio) and a charging time (for decreasing waiting time) to decide priority on charging station among drones. Our simulation results show that our power charging algorithm for drones are efficient in terms of the deadline miss ratio as well as the waiting time in general in compare to other conventional algorithms (EDF or SJF). Also, we can choose proper algorithms for battery charge scheduling and charge ready battery allocation according to system parameters and user requirements based on our simulation.

• Smart Media Journal
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• v.8 no.4
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• pp.38-45
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• 2019

When there is a spray flow such as from a pesticide nozzle, winds affect the droplet flow of a rotary-wing drone accompanied by a strong wake, with a severe oscillation. Especially, during forwarding flights or when winds come from the side, compare to a simple hovering flight as the droplet is in the effect of aerodynamic drag force, the effect of spraying region becomes even larger. For this reason, the spraying of pesticides using drones may cause a greater risk of scattering or a difference in droplet dispersion between locations, resulting in a decrease in efficiency. Therefore, through proper numerical modeling and its applied simulation, an indication tool is required applicable for the various flight and atmospheric conditions. In this research, we completed both experiment and numerical analysis for the strong downwash from the rotor and flight velocity of the drone by comparing the probability density function of droplet distribution to build a spraying system that can improve the efficiency when spraying droplets in the pesticide spray drone.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.531-536
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• 2024

Control drones, which are recently classified as smart agricultural machines in the agricultural field, are striving to build smart control and automatic control systems by combining hardware and software in order to shorten working hours and increase the effectiveness of control in the aging era of rural areas. In this paper, the characteristics of the nozzle dedicated to the control drone were analyzed as a basic study for the establishment of management control and automatic control systems. In order to consider various variables such as the type of various drone models, controller, wind, flight speed, flight altitude, weather conditions, and UAV pesticide types, related studies are needed to be able to present the drug spraying criteria in consideration of the characteristics and versatility of the nozzle. Therefore, to enable the consideration of various variables, flow analysis (CFD) simulation was conducted based on the self-designed nozzle, and the theoretical and experimental values of the droplet distribution were compared and analyzed through water reduction experiments. In the future, we intend to calculate accurate scattering in consideration of various variables according to drone operation and use it in management control and automatic control systems.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.12
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• pp.975-985
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• 2018

The drones have been developed for military purposes and are now used in many fields such as logistics, communications, agriculture, disaster, defense and media. As the range of use of drones increases, cases of abuse of drones are increasing. It is necessary to develop anti-drone technology to detect the position of unwanted drones using the physical phenomena that occur when the drones fly. In this paper, we estimate the DOA(direction of arrival) of the drone by using the acoustic signal generated when the drone is flying. In addition, the dynamics model of the drones was applied to the unscented kalman filter to improve the microphone array detection performance and reduce the error of the position estimation. Through simulation, the drone detection performance was predicted and verified through experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.943-948
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• 2022

Drones have been widely used in various fields due to the rapid development of done-related technologies, which causes various problems. The schemes which can track target drones by using signal transmitted by target drones have been investigated as a key technology for anti-drone systems to solve these problems. In this paper, we investigate an illegal drone tracking system based on swarming flight that consists of multiple small drones in order to resolve the limitations of a conventional system that consists of a single drone. In addition, we also propose a scheme with which we can adaptively adjust the separation distance between small drones in a swarm according to channel situations. We analyzed the performance of the proposed scheme in terms of success ratio and the number of movements. The proposed scheme can improve the success ratio and the number of movements by 170% and 63% respectively, compared to the conventional scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2371-2379
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• 2017

For the drone that is active in a wide search area, the time to grasp the target in the field of applications such as searching for emergency patients, monitoring of natural disasters requiring prompt warning and response, that is, the speediness of target detection is very important. In the actual operation of drone, the time for target detection is highly related to collaboration between drones and search algorithm to efficiently search the navigation area. In this research, we will provide a search method with cooperation of drone based on target existence probability to solve the problem of quickness in drone target search. In particular, the proposed method increases the probability of finding a target and shorten the search time by transmitting high-altitude drone search results to a low-altitude drone after searching first and performing more precise search. We verify the performance of the proposed method through several simulations.