• 제목/요약/키워드: Robocup

검색결과 4건 처리시간 0.02초

Development of a Synthetic Multi-Agent System;The KMITL Cadence 2003 Robotic Soccer Simulation Team, Intelligent and AI Based Control

  • Chitipalungsri, Thunyawat;Jirawatsiwaporn, Chawit;Tangchupong, Thanapon;Kittitornkun, Surin
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.879-884
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    • 2004
  • This paper describes the development of a synthetic multi-agent called KMITL Cadence 2003. KMITL Cadence 2003 is a robotic soccer simulation team consisting of eleven autonomous software agents. Each agent operates in a physical soccer simulation model called Robocup Soccer Server which provides fully distributed and real-time multi-agent system environment. All teammates have to cooperate to achieve the common goal of winning the game. The simulation models many aspects of the football field such as noise in ball movements, noisy sensors, unreliable communication channel between teammates and actuators, limited physical abilities and restricted communication. This paper addresses the algorithm to develop the soccer agents to perform basic actions which are scoring, passing ball and blocking the opponents effectively. The result of this development is satisfactory because the successful scoring attempts is increased from 11.1% to 33.3%, successful passing ball attempts is increased from 22.08% to 63.64%, and also, successful intercepting attempts is increased from 88% to 97.73%.

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Multi-agent System based on Blackboard System for Soccer Robot Implementation

  • Sanornoi, Nitiwat;Phurahong, Boonchana;Sooraksa, Pitikhate
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.2023-2028
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    • 2004
  • This paper reveals the utilization of the multi-gent system that based on the Blackboard system basis as the controller of Soccer Robot. This system is a portion of developing the Soccer Robot team for Robocup 2004 Competition. In this development, the intelligent control system was initiated by the combination of parallel and distributed blackboard structures with the principle design that generated from human body structures, which consists of the combination of two main systems, the organs system and the brain system. The system is designed using the control system theory based on Blackboard basis. Modification of the initial structures to corroborate the Soccer Robot and the structure's constituents are clarified accordingly. To demonstrate the idea, ITE-old team is given as a case study.

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Power System and Drive-Train for Omni-Directional Autonomous Mobile Robots with Multiple Energy Storage Units

  • Ghaderi, Ahmad;Nassiraei, Amir A.F;Sanada, Atsushi;Ishii, Kazuo;Godler, Ivan
    • Journal of Power Electronics
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    • 제8권4호
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    • pp.291-300
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    • 2008
  • In this paper power system and drive-train for omni-directional autonomous mobile robots with multiple energy storage units are presented. Because in proposed system, which is implemented in soccer robots, the ability of power flow control from of multiple separated energy storage units and speed control for each motor are combined, these robots can be derived by more than one power source. This capability, allow robot to diversify its energy source by employing hybrid power sources. In this research Lithium ion polymer batteries have been used for main and auxiliary energy storage units because of their high power and energy densities. And to protect them against deep discharge, over current and short circuit, a protection circuit was designed. The other parts of our robot power system are DC-DC converters and kicker circuit. The simulation and experimental results show proposed scheme and extracted equations are valid and energy management and speed control can be achieved properly using this method. The filed experiments show robot mobility functions to perform the requested motion is enough and it has a high maneuverability in the field.

퍼지 추론 기반의 멀티에이전트 강화학습 모델 (Multi-Agent Reinforcement Learning Model based on Fuzzy Inference)

  • 이봉근;정재두;류근호
    • 한국콘텐츠학회논문지
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    • 제9권10호
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    • pp.51-58
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    • 2009
  • 강화학습은 최적의 행동정책을 구하는 최적화 문제로 주어진 환경과의 상호작용을 통해 받는 보상 값을 최대화하는 것이 목표이다. 특히 단일 에이전트에 비해 상태공간과 행동공간이 매우 커지는 다중 에이전트 시스템인 경우 효과적인 강화학습을 위해서는 적절한 행동 선택 전략이 마련되어야 한다. 본 논문에서는 멀티에이전트의 효과적인 행동 선택과 학습의 수렴속도를 개선하기 위하여 퍼지 추론 기반의 멀티에이전트 강화학습 모델을 제안하였다. 멀티 에이전트 강화학습의 대표적인 환경인 로보컵 Keepaway를 테스트 베드로 삼아 다양한 비교 실험을 전개하여 에이전트의 효율적인 행동 선택 전략을 확인하였다. 제안된 퍼지 추론 기반의 멀티에이전트 강화학습모델은 다양한 지능형 멀티 에이전트의 학습에서 행동 선택의 효율성 평가와 로봇축구 시스템의 전략 및 전술에 적용이 가능하다.