• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.198-201
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• 2021

무인 항공기(UAV, Unmanned Aerial Vehicles)는 높은 기동성을 가지며 설치 비용이 저렴하다는 이점이 있어 홍수, 지진 등의 재난 재해 감시 시스템에 이용되고 있다. 재난 재해 감시 시스템에서 UAV는 지상에 위치한 사물인터넷(IoT, Internet of Things) 기기로부터 데이터를 수집하는 임무를 수행하기 위해 계획된 항로를 따라 비행한다. 이때 UAV가 정상 경로로 비행하기 위해서는 실시간으로 GPS 위치 확인이 가능해야 한다. 만일 UAV가 계산한 현재 위치의 GPS 정보가 잘못될 경우 비행경로에 대한 통제권을 상실하여 임무 수행을 완료하지 못하는 결과가 초래될 수 있다는 취약점이 존재한다. 이러한 취약점으로 인해 UAV는 공격자가 악의적으로 거짓 GPS 위치 신호를 전송하는GPS 스푸핑(Spoofing) 공격에 쉽게 노출된다. 본 논문에서는 신뢰할 수 있는 시스템을 구축하기 위해 지상에 위치한 기기가 송신하는 신호의 세기와 GPS 정보를 이용하여 UAV에 GPS 스푸핑 공격 여부를 탐지하고 공격당한 UAV가 경로를 이탈하지 않도록 대응하기 위해 연합학습(Federated Learning)을 이용하는 방안을 제안한다.

• Journal of Technology Innovation
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• v.27 no.4
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• pp.85-110
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• 2019

This study examines the social problem-solving R&D policies from the perspective of 'Mission-oriented innovation policy'. To this end, we analyzed the 'second science and technology-based social problem solving plan' in terms of civil society's participation, securing the government's dynamic capabilities, and government's risk investments. The plan introduces an institutional framework for civic participation for social problem-solving innovation, strengthening R&D program coordination and integration, and new innovation ecosystem formation. However, there is a need for a concrete program to overcome a path dependency of existing activities. Otherwise new institutions are likely to be formalized. In addition, in order to derive risk investment, it is necessary to integrate innovation policy with social policy fields such as community care and climate change. It is necessary to establish an policy process that combines the agenda of social policy beyond with R & D policy, and to forms a platform for problem solving, integrates various technologies, industries and resources.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.5
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• pp.667-673
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• 2019

We present an orienteering problem with unknown stochastic reward(OPUSR) model for persistent monitoring tasks with unknown event probabilities at each point of interest. Prior studies on orienteering problem for persistent monitoring task assume that rewards and event probabilities are known as a prior. In this paper, we propose a stochastic reward model with unknown event statistics and a path re-planning algorithm based on Bayesian reward inference. Experiments demonstrate the efficiency of our method.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.190-192
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• 2006

게임의 장르가 다양해지고 대규모의 온라인 게임이 가능해 징에 따라 게임 환경과 더불어 게임 안에 등장하는 캐릭터의 수도 많아지고 있다. 게이머에 의해 움직이는 캐릭터 외에도 여러 종류의 다양한 NPC(Non-Player Character)들이 각각 맡은 임무를 띠고 각기 움직이게 된다. 본 논문에서는 NPC들의 자연스러운 이동을 위해 제안된 일반화 가시성그래프를 이용하여 계획된 경로의 효과적인 구현을 위한 조타행동(steering behaviors)과 경로 이동 중에 만나는 다른 캐릭터에 대한 NPC들의 조타행동을 정의하고 구현하여 이동에 따른 효율을 실험해 본다.

• Journal of the Korea Society for Simulation
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• v.31 no.3
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• pp.1-10
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• 2022

Defense fields widely operate unmanned systems to lower vulnerability and enhance combat effectiveness. In the navy, swarm unmanned surface vehicles(USVs) form a cluster within communication range, share situational awareness information among the USVs, and cooperate with them to conduct military missions. This paper proposes an interface system, i.e., Interface Adapter System(IAS), to achieve inter-USV and intra-USV interoperability. We focus on the mission planning subsystem(MPS) for interoperability, which is the core subsystem of the USV to decide courses of action such as automatic path generation and weapon assignments. The central role of the proposed system is to exchange interface data between MPSs and other subsystems in real-time. To this end, we analyzed the operational requirements of the MPS and identified interface messages. Then we developed the IAS using the distributed real-time middleware. As experiments, we conducted several integration tests at swarm USVs simulation environment and measured delay time and loss ratio of interface messages. We expect that the proposed IAS successfully provides bridge roles between the mission planning system and other subsystems.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.6
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• pp.711-717
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• 2014

Global path planning for autonomous driving of unmanned ground vehicle is essential. When setting global path planning, its accuracy and effectiveness is increased if useful information such as terrain type of driving route has been reflected on global path planning. As a method to reflect the terrain type, there is a method to perform global path planning by applying the weight to each terrain type. At this time, how to assign appropriate weights corresponding to the terrain type is more important than anything. In this paper, we proposed a method to determine the weight for terrain type that may affect the results of global path planning. Moreover, we presented effective operation method and design results(GUI) to check the possibility of the use of the proposed method.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.4
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• pp.424-434
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• 2012

This paper presents a path planning algorithm of the unmanned aerial vehicle for the neutralization of the enemy firepower. The long range firepower of the ememy is usually located at the rear side of the mountain which is difficult to bomb. The path planner not only consider the differential constraints of the Unmanned Aerial Vehicle (UAV) but also consider the final approaching angle constraint. This problem is easily solved by incorporating the analytical upper bounded continuous curvature path smoothing algorithm into the Rapidly Exploring Random Tree (RRT) planner. The proposed algorithm can build a feasible path satisfying the kinematic constraints of the UAV on the fly. In addition, the curvatures of the path are continuous over the whole path. Simulation results show that the proposed algorithm can generate a feasible path of the UAV for the bombing mission regardless of the posture of the tunnel.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.11
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• pp.763-770
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• 2022

In an environment where multiple drones are operated, collisions can occur when path points overlap, and collision avoidance in preparation for this is essential. When multiple drones perform multiple tasks, it is not appropriate to use a method to generate a collision-avoiding path in the path planning phase because the path of the drone is complex and there are too many collision prediction points. In this paper, we generate a path through a commonly used path generation algorithm and propose a collision avoidance method using speed profile optimization from that path segment. The safe distance between drones was considered at the expected point of collision between paths of drones, and it was designed to assign a speed profile to the path segment. The optimization problem was defined by setting the distance between drones as variables in the flight time equation. We constructed the constraints through linearize and convexification, and compared the computation time of SQP and convex optimization method in multiple drone operating environments. Finally, we confirmed whether the results of performing convex optimization in the 20 drone operating environments were suitable for the multiple drone operating system proposed in this study.

• Current Industrial and Technological Trends in Aerospace
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• v.7 no.1
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• pp.141-152
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• 2009

The simultaneous operation of multiple UAV's makes it possible for us to raise the mission accomplishment and cost efficiency. For this we need an easily scalable control algorithm, and swarm intelligence having the characteristics such as flexibility, robustness, decentralized control and self-organization comes into the spotlight as a practical substitute. In this paper the features of swarm intelligence are described, and various research results are introduced which show that the application of swarm intelligence to the control of multiple UAV's enables the missions of surveillance, path planning, target tracking and attack to be accomplished efficiently by simulations and tests.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.1-12
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• 2003

In this paper, we Introduce the Unreal Tournament (UT) game and the Gamebots system. The former it a well-known 3D first-person action game and the latter is an intelligent agent research testbed based on UT And then we explain the design and implementation of KGBot, which is an intelligent non-player character deploying effectively within the 3D virtual environment provided by UT and the Gamebots system. KGBot is a bot client within the Gamebots System. KGBot accomplishes its own task to find out and dominate several domination points pro-located on the complex surface map of 3D virtual environment KGBot adopts UM-PRS as its control engine, which is a general BDI agent architecture. KGBot contains a hierarchical knowledge base representing its complex behaviors in multiple layers. In this paper, we explain details of KGBot's Intelligent behaviors, tuck af locating the hidden domination points by exploring the unknown world effectively. constructing a path map by collecting the waypoints and paths distributed over the world, and finding an optimal path to certain destination based on this path graph. Finally we analyze the performance of KGBot exploring strategy and control engine through some experiments on different 3D maps.