1. RoboCup: The Robot World Cup Initiative
Based on Wikipedia and presentations by
Mariya Miteva, Kevin Lam, Paul Marlow

2. What is RoboCup? RoboCup is an international robotics competition
The official goal of the project
By mid-21st century, a team of fully autonomous humanoid robot soccer players shall win the soccer game, complying with the official rule of the FIFA, against the winner of the most recent World Cup.
Sample Game Video

3. The Different Competitions
RoboCup Soccer
Small size
Middle size
Four-legged
Humanoid
Simulation
RoboCup Rescue
RoboCup Junior
Soccer Challenge
Dance Challenge
Rescue Challenge
Genereal

4. Examples of RoboCup Leagues
four-legged
small size
middle size
simulation

5. 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.
AI research should be focused on solving real life problems, but often face social or economic constraints.
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.

6. 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.

7. 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.

8. 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

9. 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

10. 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

11. RoboCup Simulator Server Monitor clients Player clients (i.e. agents!)
Coach clients

12. Sample Team Strategy

13. Design and Control A combination of many specialized components
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 final goal of building a successful Humanoid Soccer Player currently appears to be unfeasible

14. 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,
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

15. Learning
Because of the dynamic and uncertain 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.

16. Learning Robots first learn skills in one to one competitions.
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.
It’s 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.

17. Current Champions 2008 (Germany)
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)