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 Asada, Minoru


TRACKIES: RoboCup-97 Middle-Size League World Cochampion

AI Magazine

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.


RoboCup-97: The First Robot World Cup Soccer Games and Conferences

AI Magazine

RoboCup-97, The First Robot World Cup Soccer Games and Conferences, was held at the Fifteenth International Joint Conference on Artificial Intelligence. There were two leagues: (1) real robot and (2) simulation. Ten teams participated in the real-robot league and 29 teams in the simulation league. Over 150 researchers attended the technical workshop. The world champions are CMUNITED (Carnegie Mellon University) for the small-size league, DREAMTEAM (University of Southern California) and TRACKIES (Osaka University, Japan) for the middle-size league, and AT-HUMBOLDT (Humboldt University) for the simulation league. The Scientific Challenge Award was given to Sean Luke (University of Maryland) for his genetic programming- based simulation team LUKE, and the Engineering Challenge Awards were given to UTTORI UNITED (Utsunomiya University, Toyo University, and Riken, Japan) and RMIT (Royal Melbourne Institute of Technology, Australia) for designing novel omnidirectional driving mechanisms. Over 5000 spectators and 70 international media covered the competition worldwide. RoboCup-98, the Second Robot World Cup Soccer, was held in conjunction with the Third International Conference on Multiagent Systems in Paris, France, in July 1998.


TRACKIES: RoboCup-97 Middle-Size League World Cochampion

AI Magazine

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.


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.


RoboCup: A Challenge Problem for AI

AI Magazine

Although RoboCup's primary objective is a Although RoboCup's final target is a world For the Although it is obvious that building a robot robot (physical robot and software agent) to to play a soccer game is an immense challenge, play a soccer game reasonably well, a wide readers might wonder why we propose range of technologies need to be integrated, RoboCup. It is our intention to use RoboCup and numbers of technical breakthroughs as a vehicle to revitalize AI research by offering must be accomplished. When the accomplishment intelligent robotics, and sensor fusion. of such a goal has significant social The first RoboCup, RoboCup-97, will be held impact, it is considered a grand-challenge during the Fifteenth International Joint Conference project (Kitano et al. 1993). Building a robot on Artificial Intelligence (IJCAI-97) in to play a soccer game itself does not generate Nagoya, Japan, as part of IJCAI-97's special significant social and economic impact, but Accessibility Complete Incomplete and architectures can be evaluated. Computer Sensor Readings Symbolic Nonsymbolic chess is a typical example of the standard Control Central Distributed problem. Various search algorithms were evaluated and developed using this domain. With the recent accomplishment by the Deep Blue team, which beat Kasparov, a human grand Table 1. A major reason for the success of computer chess as a standard problem is that the evaluation of the accomplishment will certainly be considered the progress was clearly defined.