• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.648-651
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• 1997

This paper proposes methods for the cooperative control of multiple mobile robots and constructs a robotic soccer system in which the cooperation will be implemented as a pass play of two robots. To play a soccer game, elementary actions such as shooting and moving have been designed, and Q-learning, which is one of the popular methods for reinforcement learning, is used to determine what actions to take. Through simulation, learning is successful in case of deliberate initial arrangements of ball and robots, thereby cooperative work can be accomplished.

• 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.

• 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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• 1997.10a
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• pp.819-824
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• 1997

This paper presents a cell-based motion control strategy for soccer playing mobile robots. In the central robot motion planner, the planar ground is divided into rectangular cells with variable sizes and motion indices to which direction the mobile robot should move. At every time the multiple objects-the goal gate, ball, and robots-detected, integer values of motion indices are assigned to the cells occupied by mobile robots. Once the indices being calculated, the most desirable state-action pair is chosen from the state and action sets to achieve successful soccer game strategy. The proposed strategy is computationally simple enough to be used for fast robotic soccer system.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.507-510
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• 1996

In this paper we present the multi-agent robot 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. Mcro robot are equipped with two mini DC motors with 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. Host computer is a Pentium PC, and it receives information from the vision system, generates commands for each robot using a robot management algorithm and transmits commands to the robots by the R/F communication module. And in order to achieve a given mission in micro robot soccer game, cooperative behaviors by robots are essential. Cooperative work between individual agents is achieved by the command of host computer.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1073-1078
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• 2012

This paper deals with the trajectory planning of multi agent robots using complex potential theory for robot soccer. The complex potential theory is introduced, then the circle theorem is used to avoid obstacles, and the vortex pair is used to make precise kicking direction of robot. Various situations of robot soccer are simulated and the effect of vortex strength and the speed of robots are discussed and the better way to avoid obstacles and to kick the precise direction is found. The feasibilities of complex potential theory to apply for the multi agent robots are successful.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.11
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• pp.906-916
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• 2003

A multi-robot control algorithm using Petri-Net is proposed for 5vs5 robot soccer. The dynamic environment of robot soccer is modeled by defining the place and transition of each robot and converting it into Petri-Net diagram. Once all the places and transitions of robots are represented by the Petri-Net model, their actions can be chosen according to the roles of robots and position of the ball in soccer game, e.g., offensive, defensive and goalie robot. The proposed modeling method is implemented for soccer robot system. The efficiency and applicability of the proposed multiple-robot control algorithm using Petri-Net are demonstrated through 5vs5 Middle League SimuroSot soccer game.

• 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

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.1
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• pp.156-161
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• 2009

This paper proposes a new method about performance improvement of soccer robots system by the revision of lens distortion most commonly occurred in camera and the revision of position and angle error in robot patch for the realization of robot position. Among the lens distortions, we revise geometrical distortion and apply it to soccer robots system for realtime environment. Patch used in the recognition and the distinction for coordination and direction of robot occurs a position and angle error according to the figure of it. In this paper, we suggest the method of reduction for position and angle error of robot by improved patch and verify its propriety through the experiment.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.612-616
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• 1997

In this paper, two kinds of controller are proposed for a soccer robot system.. One for Supervisor and defense mode, and the other for attack mode. Robot soccer game has very dynamic characteristics. Furthermore, there exist competitions between agents. The soccer-playing robot should take an appropriate action according to its surroundings. Initially, an attack mode controller using a vector field concept is designed, then a supervisor and a defense mode controller are designed with a Petri-net. The efficiency and applicability of the proposed controllers are demonstrated through a real robot soccer game(MiroSot 97).