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The perception of what artificial intelligence was capable of began to change when chess grand master and world champion Garry Kasparov lost to Deep Blue, IBM's chess-playing program, in 1997. Significantly more complex, requiring even more strategic thinking, and featuring an intricate interweaving of tactical and strategical components, it posed an even greater challenge to artificial intelligence. With a number of possible moves per turn an order of magnitude greater than chess, any algorithm trying to evaluate all possible future moves was expected to fail. Led by Hiroaki Kitano and Manuela Veloso, the ambitious goal set that year was to have by 2050 a team of humanoid robots able to play a game of football against the world champion team according to FIFA rules, and win.


RoboCup: 10 Years of Achievements and Future Challenges

AI Magazine

Will we see autonomous humanoid robots that play (and win) soccer against the human soccer world champion in the year 2050? There are serious research questions that have to be tackled behind the scenes of a soccer game: perception, decision making, action selection, hardware design, materials, energy, and more. RoboCup is also about the nature of intelligence, and playing soccer acts as a performance measure of systems that contain artificial intelligence -- in much the same way chess has been used over the last century. This article outlines the current situation following 10 years of research with reference to the results of the 2006 World Championship in Bremen, Germany, and discusses future challenges.


RoboCup 2004 Competitions and Symposium: A Small Kick for Robots, a Giant Score for Science

AI Magazine

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.


Toward RoboCup without Color Labeling

AI Magazine

To overcome these limitations, we propose an algorithm, called the CONTRACTING CURVE DENSITY (CCD) algorithm, for fitting parametric curves to image data. The method neither assumes object-specific color distributions, or specific edge profiles, nor does it need threshold parameters. To separate adjacent regions, we use local criteria that are based on local image statistics. We apply the method to the problem of localizing the ball and show that the CCD algorithm reliably localizes the ball even in the presence of heavily changing illumination, strong clutter, specularity, partial occlusion, and texture.


RoboCup-2000: The Fourth Robotic Soccer World Championships

AI Magazine

The Fourth Robotic Soccer World Championships (RoboCup-2000) was held from 27 August to 3 September 2000 at the Melbourne Exhibition Center in Melbourne, Australia. RoboCup-2000 showed dramatic improvement over past years in each of the existing robotic soccer leagues (legged, small size, mid size, and simulation) and introduced RoboCup Jr. competitions and RoboCup Rescue and Humanoid demonstration events. The RoboCup Workshop, held in conjunction with the championships, provided a forum for the exchange of ideas and experiences among the different leagues. This article summarizes the advances seen at RoboCup-2000, including reports from the championship teams and overviews of all the RoboCup events.


RoboCup Rescue: A Grand Challenge for Multiagent and Intelligent Systems

AI Magazine

The intention of the RoboCup Rescue project is to promote research and development in this socially significant domain at various levels, involving multiagent teamwork coordination, physical agents for search and rescue, information infrastructures, personal digital assistants, a standard simulator and decision-support systems, evaluation benchmarks for rescue strategies, and robotic systems that are all integrated into a comprehensive system in the future. Although the rescue domain is intuitively appealing as a large-scale multiagent and intelligent system domain, analysis has not yet revealed its domain characteristics. The first research evaluation meeting will be held at RoboCup-2001, in conjunction with the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI-2001), as part of the RoboCup Rescue Simulation League and RoboCup/AAAI Rescue Robot Competition. In this article, we present a detailed analysis of the task domain and elucidate characteristics necessary for multiagent and intelligent systems for this domain.


Trying to Understand RoboCup

AI Magazine

As the English striker Gary Lineker famously said, "Football is a very simple game. We take the giant set of log data produced by the simulator tournaments from 1997 to 1999 and feed it to a data-munching program that produces statistics on important game features. Plus, because the data muncher can work in real time, we can also release it as a proxy server for RoboCup. This proxy server gives all RoboCup developers instant access to statistics while a game is in progress and is a promising step toward an important goal: understanding RoboCup.


Overview of RoboCup-98

AI Magazine

The Robot World Cup Soccer Games and Conferences (RoboCup) are a series of competitions and events designed to promote the full integration of AI and robotics research. Following the first RoboCup, held in Nagoya, Japan, in 1997, RoboCup-98 was held in Paris from 2-9 July, overlapping with the real World Cup soccer competition. RoboCup-98 included competitions in three leagues: (1) the simulation league, (2) the real robot small-size league, and (3) the real robot middle-size league. Champion teams were cmunited-98 in both the simulation and the real robot small-size leagues and cs-freiburg (Freiburg, Germany) in the real robot middle-size league.


Vision, Strategy, and Localization Using the Sony Robots at RoboCup-98

AI Magazine

Sony has provided a robot platform for research and development in physical agents, namely, fully autonomous legged robots. In this article, we describe our work using Sony's legged robots to participate at the RoboCup-98 legged robot demonstration and competition. Robotic soccer represents a challenging environment for research in systems with multiple robots that need to achieve concrete objectives, particularly in the presence of an adversary. We introduce the RoboCup context and briefly present Sony's legged robot.


RoboCup: A Challenge Problem for AI

AI Magazine

The Robot World-Cup Soccer (RoboCup) is an attempt to foster AI and intelligent robotics research by providing a standard problem where a wide range of technologies can be integrated and examined. A robot team must actually perform a soccer game, incorporating various technologies, including design principles of autonomous agents, multiagent collaboration, strategy acquisition, real-time reasoning, robotics, and sensor fusion. RoboCup is a task for a team of multiple fast-moving robots under a dynamic environment. Although RoboCup's final target is a world cup with real robots, RoboCup offers a software platform for research on the software aspects of RoboCup.