• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.6
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• pp.565-573
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• 2008

The behavior-based decentralized approach is considered for multi-UAV formation flight. It is assumed that each UAV has its own mission of flying to a specified region, while the distances between UAVs should be maintained. These two requirements may conflict with each other. To design the controller, coupled dynamics approach is applied to multi-UAVs with an assumption that each UAV can communicate with each other to share the state-information. Control gain matrices are optimized to acquire better performances of formation flying. To validate the proposed control approach, numerical simulation is performed for the waypoint-passing mission of multi-UAVs.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.12
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• pp.981-988
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• 2021

This paper presents a decentralized guidance algorithm for swarm flight of fixed-wing UAVs (Unmanned Aerial Vehicles). Considering swarm flight missions, we assume four representative swarm tasks: gathering, loitering, waypoint/path following, and individual task. Those tasks require several distinct maneuvers such as path following, flocking, and collision avoidance. In order to deal with the required maneuvers, this paper proposes an integrated guidance algorithm based on vector field, augmented Cucker-Smale model, and potential field methods. Integrated guidance command is synthesized with heuristic weights designed for each guidance method. The proposed algorithm is verified through flight tests using up to 19 small fixed-wing UAVs.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.5
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• pp.448-454
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• 2008

This paper deals with a behavior based decentralized control strategy for UAV swarming utilizing the artificial potential functions and the sliding mode control technique. Individual interactions for swarming behavior are modeled using the artificial potential functions. The motion of individual UAV is directed toward the negative gradient of the combined potential. For tracking the reference trajectory of UAV swarming, a swarming center is considered as the object of control. The sliding-mode control technique is adopted to make the proposed swarm control strategy robust with respect to the system uncertainties and the varying mission environment. Numerical simulation is performed to verify the performance of the proposed controller.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.10
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• pp.859-867
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• 2015

This study proposes a robust formation flight control technique of multiple unmanned aerial vehicles(UAVs) using behavior-based decentralized approach. The behavior-based decentralized method has various advantages because it utilizes information of neighboring UAVs only instead of information of whole UAVs in the formation maneuvering. The controllers in this paper are divided into two methods: first one is based on position and velocity of neighboring UAVs, and the other one is based on position of neighboring UAVs and passivity technique. The proposed controllers assure uniformly ultimate boundedness of closed-loops system under time varying bounded disturbances. Numerical simulations are performed to validate the effectiveness of the proposed method.

• 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.

• Journal of Digital Convergence
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• v.15 no.8
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• pp.195-202
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• 2017

Unmanned Aerial Vehicles (UAV) have mostly been used for military purposes but with the progress in ICT and reduced manufacturing costs, they are increasingly used for various private services. UAVs are expected to carry out autonomous flying in the future. In order to carry out complex tasks, swarm flights are essential. Although the swarm flights has been researched a lot due to its different network and infrastructure from the existing UAV system, There are still not enough study on security threats and requirements for the secure swarm flights. In this paper, to solve these problems, UAV autonomous flight technology is defined based on US Army Corps of Engineers (USACE) and Air Force Research Laboratory (AFRL), and swarm flights and security threat about it are classified. And then we defined and compared security requirements according to security threats of each swarm flights so as to contribute to the development of secure UAC swarm flights in the future.

• 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.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.443-449
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• 2017

Swarm of low-cost UAVs for search mission has benefit in the sense of rapid search compared to use of single high-end UAV. As the number of UAVs forming swarm increases, not only the time for the mission planning increases, but also the system to operate UAVs has excessive burden. This paper addresses a decentralized area search algorithm adequate for multiple UAVs which takes advantages of flexibility, robustness, and simplicity. To down the cost, it is assumed that each UAV has limited ability: close-communication, basic calculation, and limited memory. In close-communication, heath conditions and search information are shared. And collision avoidance and consensus of next search direction are then done. To increase weight on un-searched area and to provide overlapped search, the score function is introduced. Performance and operational characteristics of the proposed search algorithm and mission planning logic are verified via numerical simulations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.6
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• pp.385-391
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• 2022

This paper presents to develop a path planning algorithm combining gradient descent-based path planning (GBPP) and particle swarm optimization (PSO) for considering prohibited flight areas, terrain information, and characteristics of fixed-wing unmmaned aerial vehicle (UAV) in 3D space. Path can be generated fast using GBPP, but it is often happened that an unsafe path can be generated by converging to a local minimum depending on the initial path. Bio-inspired swarm intelligence algorithms, such as Genetic algorithm (GA) and PSO, can avoid the local minima problem by sampling several paths. However, if the number of optimal variable increases due to an increase in the number of UAVs and waypoints, it requires heavy computation time and efforts due to increasing the number of particles accordingly. To solve the disadvantages of the two algorithms, hierarchical path planning algorithm associated with hierarchical particle swarm optimization (HPSO) is developed by defining the initial path, which is the input of GBPP, as two variables including particles variables. Feasibility of the proposed algorithm is verified by software-in-the-loop simulation (SILS) of flight control computer (FCC) for UAVs.