• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.309-313
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• 2002

This paper presents an artificial intelligent model for a soccer robot. We classified soccer robot as artificial intelligent model into three elemental groups including instinct intuition and reason. Instinct is responsible for keeping the ball, walking or rushing toward the ball. This is very simple fundamental action without regard to associates and enemies. Intuition contributes to the faster/slower moving and simple basic turning to get near to the ball and to make a goal noticing associates and enemies. Reason is the most intelligent part, the law of reason is not simple relatively with instinct and intuition. We shall expect to design the best law of reason for a soccer robot some time. We also compared nerve system and muscles of human being model with controller and motors of a physical soccer robot model individually. We had designed several algorithms and made programs to investigate effects and control soccer robot.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.1169-1170
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• 2008

The paper is represented active robot soccer system using humanoid. many robot we implement the control method of several robot and the algorithm of robot soccer system.

• 대한임베디드공학회논문지
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• 제4권1호
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• pp.9-15
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• 2009

In this paper, a network based robot soccer system is proposed. The system consists of robots, an image processing sub-system, a game server, and client systems. Embedded technique is applied to the hardware and software for controlling the robots and image processing. In this robot soccer system, a gamer can see and control robots in a remote site through Internet. During the game, the game server gives geometrical information on robots such as positions and orientations. We demonstrated the game in public and obtained optimistic results even though some technical problemssuch as communication delay and precise control for the robots should be improved.

• 한국정밀공학회지
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• 제19권9호
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• pp.133-141
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• 2002

In this paper, we propose a hierarchical motion controller with stand-alone vision system to enhance the flexibility of the robot soccer system. In addition, we simplified the model of dynamic environments of the robot using petri-net and simple state diagram. Based on the proposed model, we designed the robot soccer system with velocity and position controller that includes 4-level hierarchically structured controller. Some experimental results using the stand-alone vision system from host system show improvement of the controller performance by reducing processing time of vision algorithm.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.434-438
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• 1996

In this paper we present the multi-agent robot system and the vision system developed for participating in micro robot soccer tournament. The multi-agent robot system consists of micro robot, a vision system, a host computer and a communication module. Micro robot are equipped with two mini DC motors witf encoders and gearboxes, a R/F receiver, a CPU and infrared sensors for obstacle detection. A vision system is used to recognize the position of the ball and opponent robots, position and orientation of our robots. The vision system is composed of a color CCD camera and a vision processing unit(AISI vision computer). The vision algorithm is based on morphological method. And it takes about 90 msec to detect ball and 3-our robots and 3-opponent robots with reasonable accuracy

• International Journal of Control, Automation, and Systems
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• 제1권2호
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• pp.236-242
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• 2003

This paper presents a cooperation strategy between a human operator and autonomous robots for an interactive robot soccer game, The interactive robot soccer game has been developed to allow humans to join into the game dynamically and reinforce entertainment characteristics. In order to make these games more interesting, a cooperation strategy between humans and autonomous robots on a team is very important. Strategies can be pre-programmed or learned by robots themselves with learning or evolving algorithms. Since the robot soccer system is hard to model and its environment changes dynamically, it is very difficult to pre-program cooperation strategies between robot agents. Q-learning - one of the most representative reinforcement learning methods - is shown to be effective for solving problems dynamically without explicit knowledge of the system. Therefore, in our research, a Q-learning based learning method has been utilized. Prior to utilizing Q-teaming, state variables describing the game situation and actions' sets of robots have been defined. After the learning process, the human operator could play the game more easily. To evaluate the usefulness of the proposed strategy, some simulations and games have been carried out.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.149.4-149
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• 2001

In this paper, the multiple micro robot soccer playing system is introduced at first. Learning and evolving in artificial agents is a difficult problem, but on the other hand a challenging task. In our laboratory, this soccer studies mainly centered on single agent learning problem. The construction of such experimental system has involved lots of kinds of challenges such as robot designing, vision processing, motion controlling. At last we will give some results showing that the proposed approach is feasible to guide the design of common agents system.

• International Journal of Control, Automation, and Systems
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• 제1권2호
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• pp.243-251
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• 2003

In this paper, a new model for mobile soccer robot, a type of linear system, is presented. A controller, consisting of two loops the one of which is the inner state feedback loop designed for stability and plant be well conditioned and the outer loop is a well-known PI controller designed for tracking the reference input, is suggested. Because the plant, the soccer robot, is parameter dependent, it requires the controller to be insensitive to the parameter variation. To achieve this objective, the pole-sensitivity as a pole-variation with respect to the parameter variation is defined and design algorithms for state-feedback controllers are suggested, consisting of two matrices one of which is for general pole-placement and other for parameter insensitive. This paper shows that the PI controller is equivalent to the state feedback and the cost function for reference tracking is equivalent to the LQ cost. By using these properties, we suggest a tuning procedure for the PI controller. We that the control algorithm in this paper, based on the linear system theory, is well work by simulation, and the LPD system modeling and control are more easy treatment for soccer robot.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.608-611
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• 1997

The soccer robot system consists of multi agents, with highly coordinated operation and movements so as to fulfill specific objectives, even under adverse situation. The coordination of the multi-agents is associated with a lot of supplementary work in advance. The associated issues are the position correction, prevention of communication congestion, local information sensing in addition to the need for imitating the human-like decision making. A control structure for soccer robot is designed and several behaviors and actions for a soccer robot are proposed. Variable zone defense as a basic strategy and several special strategies for fouls are applied to SOTY2 team.

• 전자공학회논문지CI
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• 제40권4호
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• pp.193-205
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• 2003

지능 제어, 통신, 컴퓨터 및 센서 기술, 영상 처리, 메카트로닉스 등과 같은 다양한 분야에서 로봇 축구 시스템에 대한 연구가 진행되고 있다. 그중 전략 연구는 대부분 공격 전략 연구에 치중하고 있으며, 점차 지능적인 공격 전략을 구현하는 방향으로 흘러가고 있다. 이에 따라 과거의 단순한 수비 전략으로는 완전한 수비가 불가능하게 되었다. 따라서, 지능적인 공격을 효율적으로 수비할 수 있는 수비 전략이 필요하며, 효율적인 수비를 위하여 공격자 로봇의 의도 추출이 필요하다. 본 논문에서는, 퍼지 최대 최소 신경망을 이용한 축구 로봇의 공격 의도 추출기를 설계하였다. 첫째로 축구 로봇 시스템에서의 의도를 정의하고 의도 추출에 대하여 설명한다. 다음으로 설계한 퍼지 최대 최소 신경망을 이용하여 설계한 축구 로봇의 의도 추출기에 대하여 설명한다. 퍼지 최대 최소 신경망은 패턴분류 방법 중의 하나로 온라인 적용, 짧은 학습 시간, 소프트 결정(soft decision) 등의 많은 장점을 갖고 있다. 따라서, 다이나믹한 환경을 가진 축구 로봇 시스템의 의도 추출에 적합하다. 이 의도 추출기는 상대 팀 로봇이 공격시 어떠한 상황에서 어떠한 행동을 할 것인가를 미리 알아내어 수비 시 이용할 수 있도록 하며, 학습을 통하여 의도 추출을 함으로써 상대 팀 경기를 보고 팀의 전략을 파악하는 전략 분석기로도 사용이 가능하다. 자체 제작한 3대3 로봇 축구 시뮬레이터를 이용하여 시뮬레이션을 하였으며, 학습을 함에 따라서 의도 추출률이 증가함을 확인할 수 있었다.