• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.4
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• pp.266-273
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• 2019

The efficiency and effectiveness of mission performance can be greatly changed according to the operating conditions such as the number of manned aircraft, flight altitude, and so on, in performing search and reconnaissance missions using a large number of small reconnaissance unmanned aerial vehicles. However, it is not easy to determine which operating conditions are most reasonable. Therefore, in this study, we developed an unmanned airplane flight simulation that can detect and identify the target while avoiding collision according to autonomous flight, suggesting a way to derive operating conditions when operating a large number of unmanned aerial vehicles.

• 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.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.117-129
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• 2024

This paper introduces collective navigation through a narrow gap using a curriculum-based deep reinforcement learning algorithm for a swarm of unmanned aerial vehicles (UAVs). Collective navigation in complex environments is essential for various applications such as search and rescue, environment monitoring and military tasks operations. Conventional methods, which are easily interpretable from an engineering perspective, divide the navigation tasks into mapping, planning, and control; however, they struggle with increased latency and unmodeled environmental factors. Recently, learning-based methods have addressed these problems by employing the end-to-end framework with neural networks. Nonetheless, most existing learning-based approaches face challenges in complex scenarios particularly for navigating through a narrow gap or when a leader or informed UAV is unavailable. Our approach uses the information of a certain number of nearest neighboring UAVs and incorporates a task-specific curriculum to reduce learning time and train a robust model. The effectiveness of the proposed algorithm is verified through an ablation study and quantitative metrics. Simulation results demonstrate that our approach outperforms existing methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.2 no.1
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• pp.25-33
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• 2007

Crowd behaviors on cyber underwater environment are often produced in entertainment contents, such as films and games. It is easy for us to come in contact with the scenes appearing a lot of characters as digital films and animation works are increased gradually, owing to developing of computer graphics. Though the processing a scene of crowd and the behavior system of crowd, related to the processing techniques of crowd behavior in cyber space, have been implemented so far, the research for developing the natural crowd behavior simulator can not be still satisfying. In this paper, we designed a realistic and efficient Fish Schooling Behavior Simulator for the contents production of cyber underwater environment, which showed each type of fish behavior in cyber underwater smartly, and which generated the animating the behavior automatically, reducing the time and cost.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.355-362
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• 2009

In this paper, we present a framework for managing group behaviors in multi-agent swarm systems. The framework explores the benefits by dynamic associations with the proposed artificial potential functions to realize complex swarming behaviors. A key development is the introduction of a set of flocking by dynamic association (DA) algorithms that effectively deal with a host of swarming issues such as cooperation for fast migration to a target, flexible and agile formation, and inter-agent collision avoidance. In particular, the DA algorithms employ a so-called systematic singular association (SSA) rule for fast migration to a target and compact formation through inter-agent interaction. The resulting algorithms enjoy two important interrelated benefits. First, the SSA rule greatly reduces time-consuming for migration and satisfies low possibility that agents may be lost. Secondly, the SSA is advantageous for practical implementations, since it considers for agents even the case that a target is blocked by obstacles. Extensive simulation presents to illustrate the viability and effectiveness of the proposed framework.

• 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 Korea Game Society
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• v.13 no.6
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• pp.27-34
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• 2013

This paper analyzes the behaviour of a prey to avoid the pursuit of a predator at predator-prey relationship to be appeared in the collective behavior of animals. One of the methods to avoid the pursuit of a predator is to rotate quickly when a predator arrives near to it. At that moment, a critical distance and a rotating angular are very important for the prey in order to survive from the pursuit, where the critical distance is the distance between the predator and the prey just before rotation. In order to analyze the critical distance and the rotating angular, this paper introduces the energy for a predator which it has at starting point of the chase and consumes during the chase. Through simulations, we can know that the rotating angle for a prey to survive from the pursuit is increased when the critical distance is shorter and when the ratio of predator's mass and prey's mass is also decreased. The results of simulations are the similar phenomenon in nature and therefore it means that the method to analyze in this paper is correct.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4A
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• pp.259-270
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• 2005

This paper proposes a mathematical model to analyze call-and packet-level performance of the TD-CDMA/TDD system which could serve a flexible radio resource management against multi-type heterogeneous and asymmetrical traffic conditions. On call-level analysis, the mathematical model based on queueing theory performs multi-dimensional operations using random vectors or matrices to consider multiple types of traffic and also deal with asymmetrical up- and down-direction transmissions separately. Employing the mathematical model, we obtain rail blocking probability for each type of traffic and also the optimum switching-point with the smallest call flocking probability. And on packet-level analysis, employing a non-prioritized queueing scheme between circuit and packet calls, we solve 2-dimensional random vector problem composed of the queue length for packets and the number of circuit calls being served. Finally, packet-level performance is analyzed in terms of the packet loss probability and the buffer size required under mixed-traffic conditions of multiple types of circuit and packet calls.

• Journal of the Korean Society of Costume
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• v.60 no.10
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• pp.100-117
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• 2010

This thesis has three main purposes: first, will show kinds, patterns, types, expression techniques of modern korean women's trimmings by every ten years. Second, it is to trace the effect of each decade on women's Hanbok trimming designs. Third, it will point out factors. that caused the change of modern Korean women's Hanbok trimming design patterns. Henceforth, there comes the result of the research and analysis. Trimming design patterns of modern women's Hanbok can be divided into three categories temporally: The first period of from 1910s to the first half of 1950s saw that design patterns did not changed much from traditional ones. It is because there were many catastrophes such as the invasion of Japanese Empire and Korean War. The compound design had expressed people's wish to earn many sons and babies at the end of Joseon Dynasty. But it turned to wishing luck for individuals affected by individualism and liberalism imported from the west. Realistic designs are the most frequently used and the least lines made up patterns. The second period of from the latter half of 1950s to 1970s saw that women wore their Jeogories and Chimas as suits. Screen printing technique enabled for various design patterns to come out. And the development of textile industry introduced various expression techniques such as making lace, meshing, flocking, burn-out etc cetera. The third period of 1980s saw that Hanbok became a kind of luxurious clothe as people's living standard rose. Hanbok again came into the spotlight, Hanbok designers came forward and their individualities are respected. The characteristic expression technique of grey-dying and geometric design patterns are more frequently used for the simple and modern beauty.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1435-1440
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• 2021

With the advent of the low interest rate era, many investors are flocking to the stock market. In the past stock market, people invested in stocks labor-intensively through company analysis and their own investment techniques. However, in recent years, stock investment using artificial intelligence and data has been widely used. The success rate of stock prediction through artificial intelligence is currently not high, so various artificial intelligence models are trying to increase the stock prediction rate. In this study, we will look at various artificial intelligence models and examine the pros and cons and prediction rates between each model. This study investigated as stock prediction programs using artificial intelligence artificial neural network (ANN), deep learning or hierarchical learning (DNN), k-nearest neighbor algorithm(k-NN), convolutional neural network (CNN), recurrent neural network (RNN), and LSTMs.