• 제목/요약/키워드: Embedded swarm system

검색결과 4건 처리시간 0.019초

임베디드 군집 시스템의 상호작용 기반 간접적 군집 구성 제어 (Indirect Configuration Control of Embedded Swarm System Based on Human-Swarm Interaction)

  • 변희정
    • 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.

실시간 탄도 궤적 목표물 추적을 위한 GPU 기반 병렬적 입자군집최적화 기법 (Parallelized Particle Swarm Optimization with GPU for Real-Time Ballistic Target Tracking)

  • 한윤호;이헌철;권혁훈;최원석;정보라
    • 대한임베디드공학회논문지
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    • 제17권6호
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    • pp.355-365
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    • 2022
  • This paper addresses the problem of real-time tracking a high-speed ballistic target. Particle filters can be considered to overcome the nonlinearity in motion and measurement models in the ballistic target. However, it is difficult to apply particle filters to real-time systems because particle filters generally require much computation time. This paper proposes an accelerated particle filter using graphics processing unit (GPU) for real-time ballistic target tracking. The real-time performance of the proposed method was tested and analyzed on a widely-used embedded system. The comparison results with the conventional particle filter on CPU (central processing unit) showed that the proposed method improved the real-time performance by reducing computation time significantly.

충돌 회피가 보장된 분산화된 군집 UGV의 모델 예측 포메이션 제어 (Distributed Model Predictive Formation Control of UGV Swarm Guaranteeing Collision Avoidance)

  • 박성창;이승목
    • 대한임베디드공학회논문지
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    • 제17권2호
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    • pp.115-121
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    • 2022
  • This paper proposes a distributed model predictive formation control algorithm for a group of unmanned ground vehicles (UGVs) with guaranteeing collision avoidance between UGVs. Generally, the model predictive control based formation control has a disadvantage in that it takes a long time to compute control inputs when considering collision avoidance between UGVs. In this paper, in order to overcome this problem, the formation control algorithm is implemented in a distributed manner so that it could be individually controlled. Also, a collision-avoidance method considering real-time is proposed. The proposed formation control algorithm is implemented based on robot operating system (ROS), open source-based middleware. Through the various simulation tests, it is confirmed that the formation control of five UGVs is successfully performed while avoiding collisions between UGVs.

다각형 기반의 Q-Learning과 Cascade SVM을 이용한 군집로봇의 목표물 추적 알고리즘 (Object Tracking Algorithm of Swarm Robot System for using Polygon Based Q-Learning and Cascade SVM)

  • 서상욱;양현창;심귀보
    • 대한임베디드공학회논문지
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    • 제3권2호
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    • pp.119-125
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    • 2008
  • This paper presents the polygon-based Q-leaning and Cascade Support Vector Machine algorithm for object search with multiple robots. We organized an experimental environment with ten mobile robots, twenty five obstacles, and an object, and then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning and dodecagon-based Q-learning and Cascade SVM to enhance the fusion model with DBAM and ABAM process.

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