• The Journal of the Convergence on Culture Technology
• /
• v.10 no.4
• /
• pp.425-430
• /
• 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 the Korea Institute of Military Science and Technology
• /
• v.25 no.4
• /
• pp.425-433
• /
• 2022

This paper studies the method of delivering munitions using both drones and UGVs that are developing along with the 4th Industrial Revolution. While drones are more mobile than UGVs, their loading capacity is small, and UGVs have relatively less mobility than drones, but their loading capacity is better. Therefore, by simultaneously operating these two delivery means, each other's shortcomings may be compensated. In addition, on actual battlefields, time constraints are an important factor in delivering munitions. Therefore, assuming an actual battlefield environment with a time limit, we establish delivery routes that minimize delivery time by operating both drones and UGVs with different capacities and speeds. If the delivery is not completed within the time limit, penalties are imposed. We devised the hybrid genetic algorithm to find solutions to the proposed model, and as results of the experiment, we showed the algorithm we presented solved the actual size problems in a short time.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.41 no.3
• /
• pp.75-96
• /
• 2016

This paper investigates the usefulness of drones in an urban delivery system. We define the vehicle and drone routing problem with time window (VDRPTW) and present a model that can describe a dual mode delivery system consisting of drones and vehicles in the metropolitan area. Drones are relatively free from traffic congestion but have limited flight range and capacity. Vehicles are not free from traffic congestion, and the complexity of urban road network reduces the efficiency of vehicles. Using drones and vehicles together can reduce inefficiency of the urban delivery system because of their complementary cooperation. In this paper, we assume that drones operate in a point-to-point manner between the depot and customers, and that customers in the need of fast delivery are willing to pay additional charges. For the experiment datasets, we use instances of Solomon (1987), which are well known in the Vehicle Routing Problem society. Moreover, to mirror the urban logistics demand trend, customers who want fast delivery are added to the Solomon's instances. We propose a hybrid evolutionary algorithm for solving VDRPTW. The experiment results provide different useful insights according to the geographical distributions of customers. In the instances where customers are randomly located and in instances where some customers are randomly located while others form some clusters, the dual mode delivery system displays lower total cost and higher customer satisfaction. In instances with clustered customers, the dual mode delivery system exhibits narrow competition for the total cost with the delivery system that uses only vehicles. In this case, using drones and vehicles together can reduce the level of dissatisfaction of customers who take their cargo over the time-window. From the view point of strategic flexibility, the dual mode delivery system appears to be more interesting. In meeting the objective of maximizing customer satisfaction, the use of drones and vehicles incurs less cost and requires fewer resources.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.23 no.4
• /
• pp.234-252
• /
• 2020

This paper is to verify the effectiveness of 'Hybrid Disaster Management Strategy' that integrates 'RTM(Real-time Monitoring) based On-line' and 'UAV based Off-line' system. For landslide prone area where sensors were installed, the conventional way of risk management so far has entirely relied on RTM data collected from the field through the instrumentation devices. But it's not enough due to the limitation of'Pin-point sensor'which tend to provide with only the localized information where sensors have stayed fixed. It lacks, therefore, the whole picture to be grasped. In this paper, utilizing 'Digital Photogrammetry Software Pix4D', the possibility of inference for the deformation of ungauged area has been reviewed. For this purpose, actual measurement data from RTM were compared with the estimated value from 3D point cloud outcome by UAV, and the consequent results has shown very accurate in terms of RMSE.

• Journal of the Korea Convergence Society
• /
• v.8 no.6
• /
• pp.219-226
• /
• 2017

As the UAV industry is getting matured, various types of UAVs have appeared in many application fields, including filming, reconnaissance, rescue, and etc. and it requires the quick hardware designs, particularly a battery pack, of the UAV. We developed the automatic battery pack design tool for the convenient battery pack configuration design of the hoverable type delivery UAV. With inputs, including current profile, voltage profile, various kinds of cell specifications, desired battery pack voltage, and etc. the automatic battery pack design tool calculates a pack having the minimum weight and the maximum capacity by combining either homogeneous cells or heterogeneous cells. Also, the tool could predict the capacity fading trend of the designed battery pack configuration.

• Geophysics and Geophysical Exploration
• /
• v.25 no.1
• /
• pp.26-37
• /
• 2022

Recently, multiple methods using small aircraft for geophysical exploration have been suggested as a result of the development of information and communication technology. In this study, we introduce the hybrid unmanned aircraft electromagnetic system of the Korea Institute of Geosciences and Mineral resources, which is under development. Additionally, data processing and interpretation methods are suggested via the analysis of datasets obtained using the system under development to verify the system. Because the system uses a three-component receiver hanging from a drone, the effects of rotation on the obtained data are significant and were therefore corrected using a rotation matrix. During the survey, the heights of the source and the receiver and their offsets vary in real time and the measured data are contaminated with noise. The noise makes it difficult to interpret the data using the conventional method. Therefore, we developed a recurrent neural network (RNN) model to enable rapid predictions of the apparent resistivity using magnetic field data. Field data noise is included in the training datasets of the RNN model to improve its performance on noise-contaminated field data. Compared with the results of the electrical resistivity survey, the trained RNN model predicted similar apparent resistivities for the test field dataset.