RoboCup is an international initiative with the main goals of fostering research and education in artificial intelligence and robotics, as well as of promoting science and technology to world citizens. The idea behind RoboCup is to provide a standard problem for which a wide range of technologies can be integrated and examined, as well as being used for project-oriented education, and to organize annual events open to the general public, at which different solutions to the problem are compared. The eighth annual RoboCup -- RoboCup 2004 -- was held in Lisbon, Portugal, from 27 June to 5 July. In this article, a general description of RoboCup 2004 is presented, including summaries concerning teams, participants, distribution into leagues, main research advances, as well as detailed descriptions for each league.

RoboCup is an international initiative with the main goals of fostering research and education in artificial intelligence and robotics, as well as of promoting science and technology to world citizens. The idea behind RoboCup is to provide a standard problem for which a wide range of technologies can be integrated and examined, as well as being used for project-oriented education, and to organize annual events open to the general public, at which different solutions to the problem are compared. The eighth annual RoboCup -- RoboCup 2004 -- was held in Lisbon, Portugal, from 27 June to 5 July. In this article, a general description of RoboCup 2004 is presented, including summaries concerning teams, participants, distribution into leagues, main research advances, as well as detailed descriptions for each league.

This article describes a milestone in our research efforts toward the real robot competition in RoboCup. We participated in the middle-size league at RoboCup-97, held in conjunction with the Fifteenth International Joint Conference on Artificial Intelligence in Nagoya, Japan. The most significant features of our team, TRACKIES, are the application of a reinforcement learning method enhanced for real robot applications and the use of an omnidirectional vision system for our goalie that can capture a 360-degree view at any instant in time. The method and the system used are shown with competition results.

This article describes a milestone in our research efforts toward the real robot competition in RoboCup. We participated in the middle-size league at RoboCup-97, held in conjunction with the Fifteenth International Joint Conference on Artificial Intelligence in Nagoya, Japan. The most significant features of our team, TRACKIES, are the application of a reinforcement learning method enhanced for real robot applications and the use of an omnidirectional vision system for our goalie that can capture a 360-degree view at any instant in time. The method and the system used are shown with competition results.