• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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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.

• Proceedings of the IEEK Conference
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• 2008.06a
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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.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.1
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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.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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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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• v.1 no.2
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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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• 2001.10a
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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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• v.1 no.2
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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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• 1997.10a
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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.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.4
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• pp.193-205
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• 2003

There has been so many research activities about robot soccer system in the many research fields, for example, intelligent control, communication, computer technology, sensor technology, image processing, mechatronics. Especially researchers research strategy for attacking in the field of strategy, and develop intelligent strategy. Then, soccer robots cannot defense completely and efficiently by using simple defense strategy. Therefore, intention extraction of attacker is needed for efficient defense. In this thesis, intention extractor of soccer robots is designed and developed based on FMMNN(Fuzzy Min-Max Neural networks ). First, intention for soccer robot system is defined, and intention extraction for soccer robot system is explained.. Next, FMMNN based intention extractor for soccer robot system is determined. FMMNN is one of the pattern classification method and have several advantages: on-line adaptation, short training time, soft decision. Therefore, FMMNN is suitable for soccer robot system having dynamic environment. Observer extracts attack intention of opponents by using this intention exactor, and this intention extractor is also used for analyzing strategy of opponent team. The capability of developed intention extractor is verified by simulation of 3 vs. 3 robot succor simulator. It was confirmed that the rates of intention extraction each experiment increase.