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To adapt the segway RMP, a dynamically balancing robot base, to build robots capable of playing soccer autonomously.

Focuses on the electro‐mechanical mechanisms required to make the Segway RMP autonomous, sensitive, and able to control a football.

Finds that turning a Segway RMP into a soccer‐playing robot requires a combined approach to the mechanics, electronics and software control.

Although software algorithms necessary for autonomous operation and infrastructure supplying logging and debugging facilities have been developed, the scenario of humans and robots playing soccer together has yet to be addressed.

Turning the model into a soccer playing robot demonstrates the technique of combining mechanics, electronics and software control.

Shows how the model as a base platform can be developed into a fully functional, autonomous, soccer‐playing robot.

The purpose of this paper is to design and implement a team of middle size soccer robots to conform RoboCup middle‐size league.

First, according to the rules of RoboCup, a middle size soccer robot was designed. The proposed autonomous soccer robot consists of the mechanical platform, motion control module, omni‐directional vision module, front vision module, image processing and recognition module, investigated target object positioning and real coordinate reconstruction, robot path planning, competition strategies, and obstacle avoidance. This soccer robot equips the laptop computer system and interface circuits to make decisions.

In fact, the omni‐directional vision sensor of the vision system deals with the image processing and positioning for obstacle avoidance and target tracking. The boundary‐following algorithm is applied to find the important features of the field. The sensor data fusion method is utilized in the control system parameters, self‐localization, and world modeling. A vision‐based self‐localization, and the conventional odometry systems are fused for robust self‐localization. The localization algorithm includes filtering, sharing, and integration of the data for different types of objects recognized in the environment.

This paper presents results of research work in the field of autonomous robot‐middle size soccer robot supported by IAU‐Khorasgan Branch (Isfahan).

The purpose of this paper is to design intelligent robots operating in such dynamic environments like the RoboCup Middle-Size League (MSL). In the RoboCup MSL, two teams of five autonomous robots play on an 18- × 12-m field. Equipped with sensors and on-board computers, each robot should be able to perceive the environment, make decision and control itself to play the soccer game autonomously.

This paper presents the design of our soccer robots, participating in RoboCup MSL. The mechanical platform, electrical architecture and software framework are discussed separately. The mechanical platform is designed modularly, so easy maintainability is achieved; the electronic architecture is built on industrial standards using PC-based control technique, which results in high robustness and reliability during the intensive and fierce MSL games; the software is developed upon the open-source Robot Operating System (ROS); thus, the advantages of ROS such as modularity, portability and expansibility are inherited.

Based on this paper and the open-source hardware and software, the MSL robots can be re-developed easily to participate in the RoboCup MSL. The robots can also be used in other research and education fields, especially for multi-robot systems and distributed artificial intelligence. Furthermore, the main designing ideas proposed in the paper, i.e. using a modular mechanical structure, an industrial electronic system and ROS-based software, provide a common solution for designing general intelligent robots.

The methodology of the intelligent robot design for highly competitive and dynamic RoboCup MSL environments is proposed.

In a soccer robot game, the environment is highly competitive and dynamic. In order to work in the dynamically changing environment, the decision‐making system of a soccer robot system should have the features of flexibility and real‐time adaptation. The purpose of this paper is to focus on the middle‐size soccer robot league (MSL) and present new hierarchical hybrid fuzzy methods for decision making and action selection of an MSL robot.

In this paper, new hierarchical hybrid fuzzy methods for decision making and action selection of a robot in MSL are presented. First, the behaviors of an agent are introduced, implemented and classified in two layers, the low‐level behaviors and the high‐level behaviors. In the second layer, a two‐phase mechanism for decision making is introduced. In phase one, some useful methods are implemented which check the robot's situation for performing required behaviors. In the next phase, the team strategy, team formation, robot's role and the robot's positioning system are introduced. A fuzzy logical approach is employed to recognize the team strategy and furthermore to tell the player the best position to move.

This methodology was implemented on the ADRO RoboCup Team and ADRO team performance 2008 was compared with its previous version 2007. The results showed the success of this methodology; the team performance in coordination and collaboration highly improved; in fact, the players switched their strategic area smoothly as the team strategy changed in a reasonable manner, the robots carried out the high‐level behaviors much more efficiently and the final results were enhanced significantly.

This paper is a result of the authors' original research work in the field of autonomous robot‐middle size soccer robot, supported by Islamic Azad University – Khorasgan Branch, Isfahan, Iran.

The purpose of the present paper is to propose a full model‐based method for distance‐mapping calibration for the non‐SVP (non‐single viewpoint) catadioptric camera of the soccer robot. The method should be easy to operate, efficient, accurate, and scalable to fit larger field sizes.

The distance‐mapping model was first constructed based on the imaging principle. The authors then calibrated the internal parameters using the mirror boundary and used the mirror center to choose the correct pose from two possible solutions. The authors then proposed a three‐point method based on a unique solution case of the non‐SVP P3P (perspective‐three‐point) problem to solve the external parameters. Lastly, they built the distance mapping by back‐projection.

The simulation experimental results have shown that the authors' method is very accurate even when there is severe misalignment between the mirror and the camera and that all calibration operations, except the calibration of a standard camera, can be completed in 1 min. The result of the comparison with the traditional calibration method shows that the authors' method is superior to the traditional method in terms of accuracy and efficiency.

The proposed calibration method is scalable to larger fields because it only uses the boundary of the mirror and three feature points on the field, and does not need additional calibration objects. Additionally, an automatic calibration method that can be used during the game can be easily developed based on this method. Moreover, the proposed mirror‐pose‐selection method and a unique solution to the non‐SVP P3P problem are especially useful for a non‐SVP catadioptric camera.

The purpose of this paper is to design and implement a team of kid size humanoid soccer robots conforming to RoboCup Humanoid league.

The project is described in two main parts: hardware and software. The hardware section consists of the mechanical structure and the driver circuit board enabling each robot to walk, fast walk, autonomously get up, kick and dribble when it catches the ball. The software is developed as a robot application which consists of motion controller, autonomous motion robot, self localization based on vision system, AI, trajectory planning and network.

This year, the authors' developments for the humanoid robot include: the design and construction of our new humanoid robots structure and implementation of a new recurrent hybrid neural network for walking control. The control system consists of two neural network controllers, two standard PD controllers and a robot walking planar. The proposed neural network controller has three layers, which are input, hidden, and output layers.

This paper presents results of research work in the field of autonomous robot‐middle size soccer robot, supported by IAU‐ Isfahan Branch (Khorasgan).

For intelligent robots in a multi‐agent system communication is essential for cooperative behavior. Here we describe the explicit communication between individual robots acting as team members of a RoboCup team playing soccer. The robots are based on the EyeBot platform. An overview of communication systems being published and a discussion of their advantages and drawbacks is followed by an introduction into multi‐agent systems and the problems we faced applying them to the task of playing soccer. Then we describe the wireless communication network in detail including the EyeBot platform, message structures, self‐configuration and error recovery. The communication allows transmission of messages between individuals, broadcasts and communication with a remote computer workstation. The communication system is a layer beneath the multi‐robot console, which is the user interface, and above the EyeBot hardware.

Since the advent of Honda’s ASIMO and Sony’s AIBO, robot fever has broken out in the general public of Japan. However no significant business has yet materialized, except in the pet robot business in the toy industry. On the other hand serious basic research for humanoid robots is going on which may have an impact on the future of robotics. This report describes the current status of Japanese humanoid fever and its reality.