• Aerospace Engineering and Technology
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• v.13 no.1
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• pp.153-165
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• 2014

Multi-rotor UAVs are utilized in various fields because of the advantages such that a hovering capability such as helicopters, a simple structure and a relatively high thrust. Recently, AR.Drone manufactured by Parrot is easily operated by beginner due to its internal stabilization loop in the on-board computer and it can be easily applied on various researches for the multi-rotor UAVs by providing an SDK(Software Development Kit). Further this platform can be suitably used for application to swarm flight since it is low cost and relatively small. Therefore, in this paper, we introduce the development process of the controller for indoor swarm flight by using the AR.Drone.

• Aerospace Engineering and Technology
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• v.13 no.1
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• pp.166-173
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• 2014

Recently, small quadcopters have been widely used in various areas ranging from military to entertainment applications because interest in the quadcopter increases. Especially, the research on swarm flight which control quadcopters simultaneously without any collision can increase success probability of a important mission. In addition the swarm flight can be applied for demonstrating choreographed aerial maneuvers such as dancing and playing musical instruments. In this paper, we introduce multiple AR.Drone control system based on motion capture for indoor environment in which quadcopters can recognize current position each other and perform scenario based mission.

• Convergence Security Journal
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• v.23 no.3
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• pp.65-71
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• 2023

The importance of combat drones has been highlighted through the recent outbreak of the Russia-Ukraine war. The combat drones play a significant role as a a game changer that alters the conventional wisdom of traditional warfare. Many pundits expect the role of combat swarm drones would be more crucial in the future warfare. In this regard, this paper aims to analyze the development of artificial intelligence-enabled combat swarm drones. To transform the human-operated swarm drones into fully autonomous weaponry system our suggestions are as follows. Developments of (1) AI algorithms for optimized swarm drone operations, (2) decentralized command and control system, (3) inter-drones' mission analysis and allocation technology, (4) enhanced drone communication security and (5) set up of ethical guideline for the autonomous system. Specifically, we suggest the development of AI algorithms for drone collision avoidance and moving target attacks. Also, in order to adjust rapidly changing military environment, decentralized command and control system and mission analysis allocation technology are necessary. Lastly, cutting-edging secure communication technology and concrete ethical guidelines are essential for future AI-enabled combat swarm drones.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.3
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• pp.71-84
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• 2024

Artificial intelligence can be cited as a key linkage technology for expanding drones' application fields, and drones combined with artificial intelligence are expected to improve drones' operational capabilities based on algorithms that can solve complex tasks through learning. The purpose of this study is to analyze various latest research cases that apply deep reinforcement learning to drones to solve limitations for performing swarm flight and to propose a new research direction that applies them to multi-agent communication optimization technology. The process of the research is to investigate and analyze the methods for efficient operation of control and communication technologies required for swarm flight to be successful, and to apply algorithms that have the advantage of exchanging richer feedback between agents and having less learning than conventional methods when learning deep reinforcement learning algorithms. It is expected that the efficiency and performance of learning communication protocols optimized for swarm flight will be improved, which will increase the efficiency of mission performance when exploring or scouting large areas through swarm flight in the future.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.9
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• pp.752-761
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• 2014

With increasing of interest in quad-rotor which has excellent maneuverability recently, a various types of multi-rotor aircraft was developed and commercialized, and there are many kinds of leisure products to be easily operated. In these products, the AR.Drone manufactured by Parrot has an advantage that it is easily operated by user due to the its internal stabilization loop in the on-board computer. Thus it is possible to design the unmanned UAV system easily by using this AR.Drone and its inner loop for the stabilization. For this advantage, KARI(Korea Aerospace Research Institute) has been developing the indoor swarming flight system by using multiple AR.Drones. For this indoor swarming flight, it is necessary that not only the position controller for each AR.Drone, but also the collision avoidance algorithm. Therefore, in this paper, the collision avoidance controller is provided for the swarm flight by using these AR.Drones.

• 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 Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.425-430
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• 2024

This paper analyzes the characteristics of various types of unmanned aerial vehicles (drones) for military use and how each type can be utilized in military operations. The scope of the study focuses on the structural features, advantages and disadvantages, and military application cases of fixed-wing, rotary-wing, hybrid, and swarm drones. It also discusses the development direction of drone technology, changes in military strategy, opportunities, and challenges. The results show that each type of drone plays a crucial role in various military operations such as reconnaissance, surveillance, strike, logistics, search, and rescue. With advancements in artificial intelligence, autonomous flight, and swarm technologies, the range of drone applications is expected to expand further. However, ensuring the safety and ethics of drone operations and establishing international norms have emerged as major challenges.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.119-125
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• 2023

Through the Ukraine-Russia war, the military importance of drones is being reassessed, and North Korea has completed actual verification through a drone provocation towards South Korea at 2022. Furthermore, North Korea is actively integrating artificial intelligence (AI) technology into drones, highlighting the increasing threat posed by drones. In response, the Republic of Korea military has established Drone Operations Command(DOC) and implemented various drone defense systems. However, there is a concern that the efforts to enhance capabilities are disproportionately focused on striking systems, making it challenging to effectively counter swarm drone attacks. Particularly, Air Force bases located adjacent to urban areas face significant limitations in the use of traditional air defense weapons due to concerns about civilian casualties. Therefore, this study proposes a new passive air defense method that aims at disrupting the object detection capabilities of AI models to enhance the survivability of friendly aircraft against the threat posed by AI based swarm drones. Using laser-based adversarial examples, the study seeks to degrade the recognition accuracy of object recognition AI installed on enemy drones. Experimental results using synthetic images and precision-reduced models confirmed that the proposed method decreased the recognition accuracy of object recognition AI, which was initially approximately 95%, to around 0-15% after the application of the proposed method, thereby validating the effectiveness of the proposed method.

• 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.