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RoboCup: The Robot World Cup Initiative

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Title: RoboCup: The Robot World Cup Initiative


1
RoboCupThe Robot World Cup Initiative
  • By Mariya Miteva

2
What is RoboCup?
  • Soccer world cup for robots
  • An attempt to foster AI and intelligent robotics
    research by providing a standard problem where
    wide range of technologies can be integrated and
    examined
  • The ultimate goal is a team of fully autonomous
    humanoid robots that can win against the human
    world soccer champion team to be developed by
    2050!
  • Sample Game Video

3
The Different Competitions
  • RoboCup Soccer
  • Small size
  • Middle size
  • Four-legged
  • Humanoid
  • Simulation
  • RoboCup Rescue
  • RoboCup Junior

4
RoboCup as a Standard AI Problem
  • Standard problems are the driving force of AI
    research. For example, research on chess lead to
    the discovery of powerful search algorithms.
  • After Deep Blue defeated Garry Kasparov in chess,
    AI needs a new challenge.
  • AI research groups should be focused on solving
    real life problems, but often face social or
    economic constraints.
  • A realistic, but affordable for many research
    groups problem is necessary.
  • RoboCup is designed to meet the need of handling
    real world complexity, though in a limited
    environment, while maintaining an affordable
    problem size and research cost..

5
Why is soccer a good option?
  • Soccer challenges
  • dynamic environment
  • real-time decision making and action
  • high level of uncertainty and incomplete
    information
  • sensor-acquired information
  • distributed control and cooperation
  • Areas of research include real-time sensor
    fusion, reactive behavior, strategy acquisition,
    learning, real-time planning, multi-agent
    systems, context recognition, vision, strategic
    decision making, motor control, intelligent robot
    control, etc.

6
Rules
  • There are real robot, special skill, and
    simulation competitions, each having different
    rules usually controlled by human referees.
  • In real robot competitions attributes of the
    environment such as the size of the field and the
    goal, the colors of the field, balls and robots,
    the maximum number of robots in a team, etc. are
    predetermined and differ from league to league.
  • Most physical fouls are considered unintentional
    and ignored.

7
More Rules
  • In simulation RoboCup a Soccer Server provides
    the virtual environment and controls the
    communication between the virtual robots and
    their control programs.
  • Robots do not know their exact position, but only
    their position relative to landmarks
  • Simulation allows development of advanced
    coordination systems without the physical
    constraints of real robots

8
Research Issues
  • The goal of the competitions is to stimulate
    research and advancement in both designing and
    programming robots.
  • The major areas of interest according to the
    article are
  • Collaboration in a multi-agent environment
  • Design and control
  • Vision and sensor fusion
  • Learning

9
Collaboration
  • Each team has
  • common goal (to win the game) , incompatible
    with the goal of the opponent team, and several
    subgoals (scoring)
  • team-wide strategies to fulfill the common goal
    and local and global tactics to achieve subgoals
  • Complications
  • Dynamic environment
  • Locally limited perception
  • Different roles of team players
  • Limited communication among players
  • Trade-off between communication cost and accuracy
    of the global plan
  • Final goal - promising local plans at each agent
    and coordination of these local plans

10
Sample Team Strategy
11
Design and Control
  • Existing robots have been designed to perform
    mostly single behavior actions
  • A RoboCup player needs to perform multiple
    subtasks( shooting, passing, heading, throwing,
    etc.) and meanwhile avoid opponents
  • Two approaches in building a RoboCup player
  • A combination of many specialized components
  • One or two multitasking components
  • The first approach is easier to design, while the
    second is easier to build
  • The second approach is preferable since a RoboCup
    robot should be compact and quick
  • The final goal of building a successful Humanoid
    Soccer Player currently appears to be unfeasible

12
Vision and Sensor Fusion
  • Computer Vision researchers have been seeking for
    3D reconstruction of 2D visual information
  • 3D reconstruction is too time-consuming for a
    RoboCup player to react in real time, so a
    simpler, faster and reliable vision system needs
    to be developed
  • Other sensors (sonar, touch and force) need to be
    incorporated to provide further information,
    which can not be acquired by vision
  • A method of sensor fusion/integration is
    necessary
  • Robot Vision Video
  • Robot Vision Video 2

13
Learning
  • Because of the dynamic and uncertainty of the
    RoboCup environment, programming robot behaviors
    for all possible situations is impossible.
  • Reinforcement learning is promising in RoboCup,
    since it allows acquisition of advanced behaviors
    with little prior knowledge.
  • Almost all existing reinforcement learning has
    been used in computer simulation, but not in
    physical applications.

14
Learning
  • Robots first learn skills in one to one
    competitions, which are still complex because of
    the motion of the opponent.
  • To simplify the process, task decomposition is
    implemented
  • two skills are independently acquired and then
    coordinated through learning
  • Later on, many-to-many competitions are
    considered.
  • Its hard to find a simple method for learning
    collective behavior
  • Pattern finding methods or coordination by
    imitation are used
  • The most difficult task is integration of
    the learning methods in a physical environment.

15
Current Champions (Osaka 2005)
  • Soccer
  • Small Sized Fu-Fighters (German)
  • Middle Sized EIGEN Keio Univ (Japan)
  • 4 Legged German Team (German)
  • Humanoid 2-on-2 Team Osaka (Japan)
  • 2D Simulation Brainstormers 2D (Germany)
  • 3D Simulation Aria (Iran)
  • Rescue
  • Simulation Impossibles (Iran)
  • Robot Toin Pelican (Japan)
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