• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.476-480
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• 2012

In this paper, artificial potential field(APF) is applied to formation control for the leader-following swarm robot. Furthermore, APF is constructed by applying the electrical field model. Moreover, to model the obstacle effectively, each obstacle has different form due to the electrical field equation. The proposed method is formed as two sub-objective: path planning for the leader-robot and following-robots following the leader-robot. Finally, simulation example is given to prove the validity of proposed method.

• ICROS
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• v.19 no.2
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• pp.26-33
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• 2013

과학 기술의 발달로 다수의 로봇이나 비행체 등을 운영하게 되면서 하나의 시스템을 운용할 때는 나타나지 않던 새로운 동역학적 특성들이 나타나게 되었다. 생물 및 생태학에서는 이미 오래전부터 이러한 군집 현상과 그 현상의 이면에 있는 목적 등이 연구의 대상이 되었고 그것에서 새로운 교훈을 얻고자 하였다. 서로 상호 작용을 하는 다수의 부시스템로 구성된 다개체 시스템의 출현으로 인해 그것의 공학적 분석을 위해 새로운 시스템 이론적 해석과 그에 따른 제어 문제들이 주목을 받고 있다. 다개체 시스템이 특정한 목적을 달성하기 위하여 개별 부시스템이 달성해야 할 세부 제어 문제 정의 및 제어 알고리즘에 대한 연구가 활발히 주목을 받고 있다. 본 기고에서는 자연과 공학에 나타나는 다개체 시스템이 보이는 군집 현상의 사례들과 주요 연구 문제를 소개한다.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1833_1834
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• 2009

본 논문에서는 이동 로봇의 군집 제어를 위해 선도-추종 로봇 방법에 기반한 적응 군집 제어 방법을 제안한다. 제안된 제어 방법 에서는 선도 로봇의 선형 속도와 각 속도를 추정하기 위해 투영 법칙에 기반한 적응 기법을 이용하며, 또한 백스테핑 제어 기법을 이용하여 이동 로봇의 제어 입력인 토크를 구한다. 마지막으로, 컴퓨터 모의실험을 통해 본 논문에서 제안한 제어기의 성능을 검증하고자 한다.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.1
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• pp.9-16
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• 2023

Robots are expected to expand their scope of application to the military field and take on important missions such as surveillance and enemy detection in the coming future warfare. Swarm robots can perform tasks that are difficult or time-consuming for a single robot to be performed more efficiently due to the advantage of having multiple robots. Swarm robots require mutual recognition and collaboration. So they send and receive vast amounts of data, making it increasingly difficult to verify SW. Hardware-in-the-loop simulation used to increase the reliability of mission verification enables SW verification of complex swarm robots, but the amount of verification data exchanged between the HILS device and the simulator increases exponentially according to the number of systems to be verified. So communication overload may occur. In this paper, we propose a digital twin-based communication optimization technique to solve the communication overload problem that occurs in mission verification of swarm robots. Under the proposed Digital Twin based Multi HILS Framework, Network DT can efficiently allocate network resources to each robot according to the mission scenario through the Network Controller algorithm, and can satisfy all sensor generation rates required by individual robots participating in the group. In addition, as a result of an experiment on packet loss rate, it was possible to reduce the packet loss rate from 15.7% to 0.2%.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.527-530
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• 2010

효과적으로 군집 로봇을 제어하기 위해 리더 로봇을 선정하여 특별한 역할을 부여하는 방법이 보편적으로 사용되고 있다. 본 논문에서는 효과적인 지형 탐사를 위해 군집 로봇 그룹의 리더를 관리하는 방법을 제안한다. 그룹에 리더가 없는 경우와 리더를 선정한 경우로 나누어 2차원 지형을 탐사하는 실험을 수행하였다. 지형을 탐사하는 과정에서 리더 로봇이 동작 불능 상태가 되는 경우가 발생할 수도 있는데, 이때에는 그룹의 리더를 교체하는 방법을 사용하였다. 그룹의 리더를 관리하는 방법을 시뮬레이션 환경에 적용하여 실험한 결과, 리더가 없는 경우보다 지형 탐사 성공률이 훨씬 높아지는 것을 알 수 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2554-2561
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• 2015

In this paper, we strengthen the advantages of a simple PID controller as a study on the formation control of mobile robots and propose an adaptive PID controller with robust performance at the dynamics characteristics of following robot. Simulation studies show that the adaptive PID controller has better keeping constant distance and angle such as tracking performance of following robot for the formation control than a conventional PID controller. This is the proposed adaptive PID controller to change the gains is found to represent the best performance. This is able to verify that the performance of the proposed adaptive PID controller is excellent.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.246-247
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• 2008

본 논문에서는 군집간 제어를 위한 이동용 로봇제작과 로봇의 좌표인식, 방향을 찾기 위하여 GPS(Global Positioning System)수신 모듈과 Bluetooth송 수신기를 사용하였다. 실험에 쓰인 모든 이동용 로봇에 GPS수신기와 Bluetooth 송 수신기를 장착하고, GPS 수신기로부터 받은 blaster-이동로봇의 위치좌표를 Bluetooth통신 영역 내에 있는 모든 이동로봇에게 보내면 각 Slave-이동로봇은 Master이동로봇으로부터 받은 위치 좌표를 이용하여 blaster-이동로봇을 중심으로 상대적인 위치, 거리 유지, 진행방향을 계산한다. Master-이동로봇과 Slave-이동로봇 간의 실시간 통신과 일정거리를 유지함으로써 군집간 제어를 할 수 있다.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.712-717
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• 2008

In swarm robot systems, each robot must act by itself according to the its states and environments, and if necessary, must cooperate with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, reinforcement learning method with SVM based on structural risk minimization and distributed genetic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. By distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning that basis of SVM is adopted in this paper.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.660-666
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• 2011

In this paper, we proposed a Particle Swarm Optimization(PSO) to search the optimal link lengths for legged walking robot. In order to apply the PSO algorithm for the proposed, its walking robot kinematic analysis is needed. A crab robot based on four-bar linkage mechanism and Jansen mechanism is implemented in H/W. For the performance index of PSO, the stride length of the legged walking robot is defined, based on the propose kinematic analysis. Comparative simulation results present to illustrate the viability and effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.279-284
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• 2009

In swarm robot systems, each robot must behaves by itself according to the its states and environments, and if necessary, must cooperates with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, reinforcement learning method using many SVM based on structural risk minimization and distributed genetic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. By distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning that basis of Cascade SVM is adopted in this paper.