• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.318-325
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• 2024

The rapid advancement of drone technology has led to the emergence of drone swarms, a game-changing concept in modern warfare. This study explores the military applications, countermeasures, and strategic implications of drone swarms. By examining the current trends in drone swarm development and deployment, this research highlights the potential of this technology to revolutionize the battlefield. The study also investigates the challenges and vulnerabilities associated with drone swarms, emphasizing the need for effective countermeasures. Through an analysis of multi-sensor fusion, directed energy weapons, and artificial intelligence, this research proposes comprehensive strategies to counter the threats posed by drone swarms. Furthermore, the study delves into the ethical and legal issues surrounding the use of autonomous drone swarms, underscoring the necessity for international norms and regulations. The findings of this research contribute to the understanding of the transformative impact of drone swarms on military strategy and national security, while providing valuable insights for policymakers, military strategists, and researchers in the field.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.179-185
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• 2017

Communication technologies hold a significant place in the swarm flight of drones for surveillance, inspection of disasters and calamities, entertainment performances, and drone collaborations. A GCS(ground control station) for the control of drone swarms needs its devoted communication method to control a large number of drones at the same time. General drone controllers control drones by connecting transmitters and drones in 1:1. When such an old communication method is employed to control many drones simultaneously, problems can emerge with the control of many transmitter modules connected to a GCS and frequency interference among them. This study implemented a transmitter controller to control many drones simultaneously with a communication chip of 2.4GHz ISM band and a Cortex M4-based board. It also designed a GCS to control many transmitter controllers via a network. The hierarchical method made it possible to control many more drones. In addition, the problem with frequency interference was resolved by implementing a time- and frequency-sharing method, controlling many drones simultaneously, and adding the frequency hopping feature. If PPM and S.BUS protocol features are added to it, it will be compatible with more diverse transmitters and drones.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.8
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• pp.1080-1088
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• 2018

General methods of controlling a drone are divided into manual control and automatic control, which means a drone moves along the route. In case of manual control, a man should be able to figure out the location and status of a drone and have a controller to control it remotely. When people control a drone, they collect information about the location and position of a drone with the eyes and have its internal information such as the battery voltage and atmospheric pressure delivered through telemetry. They make a decision about the movement of a drone based on the gathered information and control it with a radio device. The automatic control method of a drone finding its route itself is not much different from manual control by man. The information about the position of a drone is collected with the gyro and accelerator sensor, and the internal information is delivered to the CPU digitally. The location information of a drone is collected with GPS, atmospheric pressure sensors, camera sensors, and ultrasound sensors. This paper presents an investigation into drone control by a remote computer. Instead of using the automatic control function of a drone, this approach involves a computer observing a drone, determining its movement based on the observation results, and controlling it with a radio device. The computer with a Depth camera collects information, makes a decision, and controls a drone in a similar way to human beings, which makes it applicable to various fields. Its usability is enhanced further since it can control common commercial drones instead of specially manufactured drones for swarm flight. It can also be used to prevent drones clashing each other, control access to a drone, and control drones with no permit.

• Journal of the Korean Society of Visualization
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• v.17 no.3
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• pp.32-38
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• 2019

The dynamic stability of swarms is crucial in preventing collisions in clustered flights and safely moving along a defined path. Although there have been many simulation studies on dynamic stability, there have not been many experimental studies using real clusters due to the difficulty in implementation. In this study, we constructed a particle-lattice structure simulating bird flocks or drone swarms, and conducted experiments within turbulent flow. We identified a criterion that describes dynamically stable particle-lattice structures. The stability increased as this newly defined spatial index increased.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.12
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• pp.971-980
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• 2021

Recently popularized drone technologies have revealed that low-cost small unmanned aerial vehicles(UAVs) can be a significant threat to prevailing power by operating in group or in swarms. Researchers in many countries have tried to utilize integrated swarm unmanned aerial system(SUAS) in the battlefield. Agency for Defense Development also identified four core technologies in developing SUAS: swarm control, swarm network, swarm information, and swarm collaboration, and the authors started researches on swarm control and network technologies in order to be able to operate vehicle platforms as the first stage. This paper introduces design and integration of SUAS consisting of small fixed-wing UAVs, swarm control and network algorithms, a ground control system, and a launcher, with which swarm control and network technologies have been verified by flight tests. 19 fixed-wing UAVs succeeded in swarm flight in the final flight test for the first time as a domestic research.