• 제목/요약/키워드: Swarm Robot

검색결과 97건 처리시간 0.022초

군집 로봇의 침입자 포위를 위한 비동기 행동 제어 알고리즘 (Asynchronous Behavior Control Algorithm of the Swarm Robot for Surrounding Intruders)

  • 김종선;주영훈
    • 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.

Firefly Algorithm을 이용한 군집 이동 로봇의 경로 계획 (Path Planning of Swarm Mobile Robots Using Firefly Algorithm)

  • 김휴찬;김제석;지용관;박장현
    • 제어로봇시스템학회논문지
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    • 제19권5호
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    • pp.435-441
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    • 2013
  • A swarm robot system consists of with multiple mobile robots, each of which is called an agent. Each agent interacts with others and cooperates for a given task and a given environment. For the swarm robotic system, the loss of the entire work capability by malfunction or damage to a single robot is relatively small and replacement and repair of the robot is less costly. So, it is suitable to perform more complex tasks. The essential component for a swarm robotic system is an inter-robot collaboration strategy for teamwork. Recently, the swarm intelligence theory is applied to robotic system domain as a new framework of collective robotic system design. In this paper, FA (Firefly Algorithm) which is based on firefly's reaction to the lights of other fireflies and their social behavior is employed to optimize the group behavior of multiple robots. The main application of the firefly algorithm is performed on path planning of swarm mobile robots and its effectiveness is verified by simulations under various conditions.

PSO를 이용한 휴머노이드 로봇의 최적자세 생성 (Posture Optimization for a Humanoid Robot using Particle Swarm Optimization)

  • 윤재훈;당 반 치엔;트란 트렁 틴;김종욱
    • 한국지능시스템학회논문지
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    • 제24권4호
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    • pp.450-456
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    • 2014
  • 휴머노이드 로봇은 인간-로봇 상호작용에 가장 효과적인 로봇 플랫폼이지만 20개 이상의 관절로 구성되어 있을 만큼 복잡한 구조여서 전통적인 역기구학적 방법으로 안정되면서도 정교한 자세를 생성하기가 어렵다. 본 논문에서는 고속 연산최적화 기법인 Particle Swarm Optimization 기법을 사용해서 앞쪽 지면에 놓인 물체를 단측지지 상태로 상체를 굽혀서 왼팔이나 오른팔로 집는 고난도의 자세를 생성하고, 이를 상용 휴머노이드 로봇 플랫폼에 적용하여 검증함으로써 제안 된 방법의 적용 가능성을 확인한다.

스프링 댐퍼 임피던스 특성을 이용한 네트워크 기반의 군집 로봇의 경로 제어 기법 (Path Control Method of Networked Swarm Robot Systems using Spring Damper Impedance Features)

  • 김성욱;김동성
    • 제어로봇시스템학회논문지
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    • 제16권1호
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    • pp.61-68
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    • 2010
  • This paper proposes networked swarm robotic systems with group based control scheme using spring damper impendence feature. The proposed algorithm is applied to keep system arrangement in unexpected situations based on the spring-damper impedance and fuzzy logic. Using the proposed scheme, each robot overcome collision problems efficiently. The structure of UBSR (UMPC Based Swarm Robot) system consists of user level, cognitive level, and executive level. This structure is designed to easily meet the different configuration requirements for other levels. Simulation results show an availability of the proposed method.

네트워크 연결성 유지를 위한 군집 로봇의 행동 제어 알고리즘 (Behavior Control Algorithm of Swarm Robots to Maintain Network Connectivity)

  • 김종선;정준영;지상훈;주영훈
    • 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.

군집 로봇의 포메이션 이동 제어 (Formation Motion Control for Swarm Robots)

  • 라병호;김성호;주영훈
    • 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.

PSO를 이용한 인공면역계 기반 자율분산로봇시스템의 군 제어 (Swarm Control of Distributed Autonomous Robot System based on Artificial Immune System using PSO)

  • 김준엽;고광은;박승민;심귀보
    • 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.

컬러 인식에 기반을 둔 스웜 로봇의 자기 조직화 연구 (Self-Organization of Swarm Robots Based on Color Recognition)

  • 정하민;황영기;김동헌
    • 한국지능시스템학회논문지
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    • 제20권3호
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    • pp.413-421
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    • 2010
  • 본 논문에서는 로봇 축구용 카메라를 사용하는 기존 경로계획의 제한적인 사항을 극복하기 위해서 컬러 인식법에 의한 경로계획방법을 제시한다. 제안된 연구에서는 움직이는 목표물이 스웜로봇과 멀리 있어도 로봇의 직선 시야를 기반으로 동료 로봇을 따라가며, 움직이는 목표물을 추적 할 수 있다. 제안된 포텐셜 필드는 동료 로봇과의 충돌과 장애물과의 충돌을 피하면서 스웜 로봇들이 움직이는 목표물을 향하여 이동하게 한다. 결국, 스웜 로봇들 사이의 시각적 도움에 의해 최종 목표물에 모든 스웜 로봇들이 도달하게 된다. 제안된 방법은 움직이는 파티클, 즉 점 로봇이 아닌 논홀로노믹 제한이 있는 유니 사이클 로봇들을 대상으로 자기 조직화 방법을 제시하기 때문에 실제 하드웨어 적용시 유용하다.

Automatic Mutual Localization of Swarm Robot Using a Particle Filter

  • Lee, Yang-Weon
    • Journal of information and communication convergence engineering
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    • 제10권4호
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    • pp.390-395
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    • 2012
  • This paper describes an implementation of automatic mutual localization of swarm robots using a particle filter. Each robot determines the location of the other robots using wireless sensors. The measured data will be used for determination of the movement method of the robot itself. It also affects the other robots' self-arrangement into formations such as circles and lines. We discuss the problem of a circle formation enclosing a target that moves. This method is the solution for enclosing an invader in a circle formation based on mutual localization of the multi-robot without infrastructure. We use trilateration, which does require knowing the value of the coordinates of the reference points. Therefore, specifying the enclosure point based on the number of robots and their relative positions in the coordinate system. A particle filter is used to improve the accuracy of the robot's location. The particle filter is operates better for mutual location of robots than any other estimation algorithms. Through the experiments, we show that the proposed scheme is stable and works well in real environments.

지역적 통신과 인공면역계에 기반한 군집 로봇의 협조 전략과 군 행동 (Group Behavior and Cooperative Strategies of Swarm Robot Based on Local Communication and Artificial Immune System)

  • 심귀보;이동욱
    • 한국지능시스템학회논문지
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    • 제16권1호
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    • pp.72-78
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    • 2006
  • 군집 로봇시스템에서 협조 행동을 위기 위해서는 로봇의 센싱과 통신 기능은 필수적이다. 일반적으로 대역적 통신 시스템에서는 로봇의 대수가 증가하면 통신 자원의 제한과 정보의 범람이 발생한다. 따라서 이 경우 지역적 통신방법이 유리하다. 따라서 본 논문에서는 지역적 통신에 의한 정보의 전파 해석을 통하여 최적의 통신 반경을 결정하는 방법을 제안하고, 이를 이용하여 인공면역계에 기반한 군집 로봇시스템의 협조 전략과 군 행동 알고리즘을 제안한다.