• 한국항공우주학회지
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• 제49권12호
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• pp.971-980
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• 2021

최근 드론 기술의 대중화와 함께 저비용의 소형 무인기를 다수 또는 군집으로 운용함으로써 상당한 군사적 효용성을 얻을 수 있음이 알려지면서, 군집무인체계의 전장 활용을 위한 연구가 활발히 진행되고 있다. 국방과학연구소에서는 이와 관련한 주요기술로 군집제어, 군집통신, 군집정보, 군집협업 기술을 식별하였으며, 1단계로써 대상 무인체를 운용하는 데 필요한 군집제어와 군집통신 기술에 대한 연구를 수행하였다. 본 논문에서는 소형 고정익 무인기 기반의 군집무인기시스템을 설계 및 제작하고, 군집제어 및 군집통신 기술을 비행시험으로 검증한 과정을 소개한다. 최종비행시험에서 무인기 19대가 군집비행을 수행함으로써 국내 최초로 군사적으로 활용도가 높은 고정익 무인기 약 20대 규모의 군집 비행시험에 성공하였다.

• 대한임베디드공학회논문지
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• 제14권1호
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• pp.19-24
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• 2019

Embedded swarm systems consist of a large number of robots that use local control laws based on spatial information nearby environment and adjacent robots. In this paper, we propose a new scheme for indirect swarm configuration in swarm interaction system to adapt the swarm operation according to the desired goal. Also, we provide a method for the operator to observe the state of the swarm, which results in providing appropriate input to the swarm. We analyze the stability properties of the proposed swarm system and show the simulation results.

• 제어로봇시스템학회논문지
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• 제18권9호
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• pp.812-818
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• 2012

In this paper, we propose an asynchronous behavior control algorithm of the swarm robot for surrounding intruders when detected an intruder in a surveillance environment. The proposed method is divided into three parts: First, we proposed the method for the modeling of a state of the swarm robot. Second, we proposed an asynchronous behavior control algorithm for the surrounding an intruder by the swarm robot. Third, we proposed a control method for the collision avoidance with the swarm robot. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.

• 제어로봇시스템학회논문지
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• 제19권12호
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• pp.1132-1137
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• 2013

In swarm robot systems, it is vital to maintain network connectivity to ensure cooperative behavior between robots. This paper deals with the behavior control algorithm of the swarm robots for maintaining network connectivity. To do this, we divide swarm robots into search-robots, base-robots, and relay-robots. Using these robots, we propose behavior control algorithm to maintain network connectivity. The behavior control algorithms to maintain network connectivity are proposed for the local path planning using virtual force and global path planning using the Delaunay triangulation, respectively. Finally, we demonstrate the effectiveness and applicability of the proposed method through some simulations.

• 전기학회논문지
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• 제60권11호
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• pp.2147-2151
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• 2011

In this paper, we propose the formation control algorithm for swarm robots. The proposed algorithm uses the artificial potential field(APF) to plan the global path of swarm robots and to control the formation movement. The navigation function generates a global APF for a leader robot to reach a given destination and an avoidance function generates a local APF for follow robots to avoid obstacles. Finally, some simulations show the validity of the proposed method.

• 제어로봇시스템학회논문지
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• 제18권5호
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• pp.465-470
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• 2012

This paper proposes a distributed autonomous control method of swarm robot behavior strategy based on artificial immune system and an optimization strategy for artificial immune system. The behavior strategies of swarm robot in the system are depend on the task distribution in environment and we have to consider the dynamics of the system environment. In this paper, the behavior strategies divided into dispersion and aggregation. For applying to artificial immune system, an individual of swarm is regarded as a B-cell, each task distribution in environment as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. The executing process of proposed method is as follows: When the environmental condition changes, the agent selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other agent using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. In order to decide more accurately select the behavior strategy, the optimized parameter learning procedure that is represented by stimulus function of antigen to antibody in artificial immune system is required. In this paper, particle swarm optimization algorithm is applied to this learning procedure. The proposed method shows more adaptive and robustness results than the existing system at the viewpoint that the swarm robots learning and adaptation degree associated with the changing of tasks.

• International Journal of Control, Automation, and Systems
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• 제1권3호
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• pp.301-307
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• 2003

A control system design based on coupled nonlinear oscillators (CNOs) for a self- organized swarm system is presented. In this scheme, agents self-organize to flock and arrange group formations through attractive and repulsive forces among themselves using CNOs. Virtual agents are also used to create richer group formation patterns. The objective of the swarm control in this paper is to follow a moving target with a final group formation in the shortest possible time despite some obstacles. The simulation results have shown that the proposed scheme can effectively construct a self-organized multi-agent swarm system capable of group formation and group immigration despite the emergence of obstacles.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.421-426
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• 2005

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes particle swarm optimization algorithm based optimal learning fuzzy-neural network (PSOA-FNN). The proposed learning scheme is the fuzzy-neural network structure which can handle linguistic knowledge as tuning membership function of fuzzy logic by particle swarm optimization algorithm. The learning algorithm of the PSOA-FNN is composed of two phases. The first phase is to find the initial membership functions of the fuzzy neural network model. In the second phase, particle swarm optimization algorithm is used for tuning of membership functions of the proposed model.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.493-495
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• 2005

This paper proposes a swarm-based fuzzy system modeling technique for coke oven combustion control diagnosis. The coke plant produces coke for the blast furnace plant in steel making process by charging coal into oven and supplying gas to carbonize it. A conventional mathematical model for coke oven combustion control has been used to control the amount of gas input, but it does not work well because of highly nonlinear feature of coke plant. To solve this problem, swarm-based fuzzy system modeling technique is suggested to construct a diagnosis model of coke oven combustion control. Based on the measured input-output data pairs, the fuzzy rules are generated and the parameters are tuned by the PSO(Particle Swarm Optimizer) to increase the accuracy of the fuzzy system is operated. This system computes the proper amount of gas input taking the operation conditions of coke oven into account, and compares the computed result with the supplied gas input.

• 제어로봇시스템학회논문지
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• 제18권5호
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• pp.433-438
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• 2012

In this paper, a operation network system equipped with onboard wireless communication systems and ground-based mission control systems is proposed for swarm flight of small UAVs. This operating system can be divided into two networks, UAV communication network and ground control system. The UAV communication network is intend to exchange the informations of navigation, mission and flight status with minimum time delay. The ground control system consisted of mission control systems and UDP network. Proposed operation network system can make a swarm flight of various UAVs, execute complex missions decentralizing mission to several UAVs and cooperte several missions. Finally, PILS environments are developed based on the total operating system.