• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.109.3-109
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• 2002

1. Introduction 2. Vision system 3. Effect of brightness variations 4. Color classifier using multi-layer neural network 5. Experimental result of color classifier 6. Applications for robot soccer system 7. Conclusion

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.661-663
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• 1999

본 논문에서는 새로운 경로 계획 방법으로 중심 이등에 의한 경로 알고리즘을 제안한다. 제안된 알고리즘을 사용하여 곡률 반경을 이용한 경로 계획의 문제점인 각도오차가 커질수록 우회하는 현상을 보다 효율적으로 해결함을 시뮬레이션을 통하여 보인다. 또한 제안된 경로 알고리즘에 칼만 필터를 이용한 예측기를 적용시켜 로봇이 공을 추정하는데 발생할 수 있는 잡음에 강인함을 보이며 신뢰성 있는 결과를 확인한다.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.722-730
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• 2008

This paper proposes two novel algorithms enabling mobile robots to cooperate with each other in a reliability-based system and a time-critical system. In the reliability-based cooperative system, the concepts of a mobile ad hoc network (MANET) and an object entropy are adopted in order to coordinate a specific task. A logical robot group is created based on the exchange of request and reply messages in a robot communication group whose organization depends on transmission range. In the time-critical cooperative system, relational entropy is used to define the relationship between mobile robots. A group leader is selected based on optimizing power consumption. The proposed algorithm has been verified based on the computer-based simulation and soccer robot experiment. The performance metrics are defined. The metrics include the number of messages needed to make a logical robot group and to obtain the relationship of robots and the power consumption to select a group leader. They are verified by simulation and experiment.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.190-194
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• 1998

In this paper, we introduce the micro robot soccer playing system as a standard test bench for the study on the multiple agent system. Our method is based on following viewpoints. They are (1) any complex behavior such as cooperation among agents must be completed by sequential basic actions of concerned agents. (2) those basic actions can be well defined, but (3) how to organize those actions in current time point so as to result in a new stale beneficial to the end aim ought to be achieved by a kind of self-learning self-organization strategy.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.19-22
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• 2002

분류자 시스템은 유전자 알고리즘(Genetic Algorithm : GA)을 이용하여 새로운 규칙 집합을 발견하는 시스템이다 또 로봇 축구 시뮬레이션 게임(SimuroSot)은 시간에 따라 상태가 변화하는 동적인 시스템이다 본 논문에서는 GBML(Genetic Based Machine Learning)의 한 갈래이자 미시간 접근 방법을 기반으로 하는 Zeroth Level Classifier System(ZCS)을 SimuroSot에 적용하여 게임 전략을 구성하는 새로운 규칙의 발견과 학습에 의한 축구 로봇의 행동전략 알고리즘을 제안하고, 시뮬레이션을 통하여 본 전략의 유용성을 확인한다

• Journal of Power Electronics
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• v.8 no.4
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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.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.828-831
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• 1997

One of the most important design factor for the image tracker is the speed of the data processing which allows real-time operation of the system and provides reasonably accurate performance at the same time. Use of powerful DSP alone does not guarantee to meet such requirement. In this paper, a simple efficient algorithm for real-time multi-target image tracking is suggested. The suggested method is based on a recursive centroiding technique and color table look-up. This method has been successfully implemented in a image processing system for Micro-Robot Soccer Tournament(MIROSOT). This tracker can track positions of a ball, 3 enemies, and 3 agents at the same time. The experimental results show that the processing time for each frame of image is less than 7ms, which is well within the 60Hz sampling interval for real-time operation.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.303-304
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• 2009

본 논문에서는 로봇축구에 관심을 가지고 있는 프로그래밍 초보자가 웹 환경에서 인터프리터 기반의 학습기능을 통해 쉽게 제어 언어에 대한 이해도를 높이고 프로그래밍을 학습할수 있는 시스템을 제안하고 설계한다. 개발시 사용한 실버라이트[1]는 웹에서의 닷넷 기반 미디어 경험과 리치 인터렉티브(Interactive) 어플리케이션을 실행하기 위한 차세대 크로스브라우저이다. 본 논문에서는 로봇축구와 관련된 기본기능, 시스템 구조, 구현 시 구축한 웹기반 시뮬레이션 및 사용자 학습 Interpreter 시스템에 대해 설명한다. 결론에서는 구현한 전체 시스템 평가 및 연구방향에 대해 논하였다.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.51-58
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• 2009

Reinforcement learning is a sub area of machine learning concerned with how an agent ought to take actions in an environment so as to maximize some notion of long-term reward. In the case of multi-agent, especially, which state space and action space gets very enormous in compared to single agent, so it needs to take most effective measure available select the action strategy for effective reinforcement learning. This paper proposes a multi-agent reinforcement learning model based on fuzzy inference system in order to improve learning collect speed and select an effective action in multi-agent. This paper verifies an effective action select strategy through evaluation tests based on Robocup Keepaway which is one of useful test-beds for multi-agent. Our proposed model can apply to evaluate efficiency of the various intelligent multi-agents and also can apply to strategy and tactics of robot soccer system.