CSFRIEBURG 1998

1. CSFRIEBURG 1998 Team Analysis for Middle Size League in RoboCup Jaisudha Purushothaman

2. Why Robocup? • Alan Mackworth (1993) proposed soccer as a test bed for AI and Robotics research. • Landmark Project and Standard Problem • American Space Project Apollo ULTIMATE GOAL: By 2050, develop a team of fully autonomous humanoid robots that can win against the human world champion team in soccer

3. Research Areas Covered • 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

4. Soccer Rules! • Simulation League • Small Size League • Middle Size League --Size and color of 3X3 ping pong tables --Up to 5 robots per team --Futsal-4 ball --Size of base of robot upto 50 cm --No global vision --Colored Goals --Walls surrrounding field

5. The Team 2nd place at RoboCup German Open2002, Paderborn, April 2002 World champion at RoboCup 2001, Seattle, August 2001 Champion at RoboCup German Open2001, Paderborn, June 2001 World champion at RoboCup 2000, Melbourne, September 2000 German champion at VISIONRoboCup'99, Stuttgart, October 1999 3rd place at RoboCup'99, Stockholm, August 1999 German champion at VISIONRoboCup'98, Stuttgart, October 1998 World champion at RoboCup'98, Paris, July 1998

6. Team Players • Pioneer 1 Robot developed by Kurt Kolenidge & manufactured by ActivMedia • Video Camera to Cognachrome Vision system manufactured by Newton Lab • PLS200 Laser Range Finders manufactured by SICK AG – 1800 field of view and .50 angular resolution • Toshiba Notebook Libretto 70CT running Linux • Wavelan Radio Ethernet

7. Ball Handling Mechanism

8. Player Architecture

9. Team Architecture

10. Self Localization

11. Perception Module

12. Global World Model

13. Basic Skills • Goalkeeper • Head mounted to right • Always watches the ball • Moves to point where it expects to intercept the ball • Field Player • Approach-Postion • Go-to-Position • Observe-Ball • Search-Ball • Move-Ball • Shoot-Ball

14. Action Selection (Decision Tree)

15. Roles and Areas of Competence

16. Path Planning Module World Model Graph Building A* Search Path Test Path Introspection

17. Path Planning Example

18. Other Techniques & Issues of Interest • UttoriUnited and RMIT omni directional driving mechanisms • Principles of Minimal Control (Ullanta) • Vision Guided Behavior Acquisition (Osaka) • Dynamic Role Changing (CMUnited) • Explicit World Model alternative : Action Based Sensor Space Categorization for Robot Learning. • Osaka and its Improvements over the years • CSFreiburg’s Improvements till 2001

19. Robocup Applications • Robocup Rescue • The Future University – Hakodate • Education and Edutainment • Rocco – Live Commentator • The Licentiate Thesis of Johan Kummeneje, Stockholm University

20. My Perfect Team CSFreiburg with: • Training to Shoot by Offline Learning • A Defense Strategy ( Ball Intercept already inbuilt) • Dynamic Role Change between Forwarder and Defender Issues : • What if there is No Communication allowed? • What if the same teams play against each other?

21. 1998 Final Goal (T-Team)

22. 2001 Final Goal (Trackies)

23. Papers • Robocup: Robot World Cup by Kitano, Asada, Noda and Matsubara • What we learned from Robocup-97 and Robocup-98 by Asada,Suzuki,Veloso and Kitano • The CS Freiburg Team Playing Robotic Soccer in an Explicit World Model by J-S. Gutmann, W. Hatzack, I. Herrmann, B. Nebel,F.Rittinger, A. Topor, and T. Weigel • Fast, Accurate, and Robust Self-Localization in Polygonal Environments by J.-S. Gutmann, T. Weigel, B. Nebel. • The CS Freiburg Robotic Soccer Team: Reliable Self-Localization, Multirobot Sensor Integration, and Basic Soccer Skills by J.-S. Gutmann, W. Hatzack,I. Herrmann,B. Nebel,F. Rittinger, A. Topor,T. Weigel, and B. Welsch. • CS Freiburg 2001 by T. Weigel, A. Kleiner, F. Diesch, M. Dietl, J.-S. Gutmann, B. Nebel, P. Stiegeler and B. Szerbakowski • CS Freiburg Doing the Right Thing in a Group by Weigel et al.

24. More Papers • Osaka University “Trackies 2002” by Takahashi, Hikiti, Katoh, Chaladhorn, Edazawa and Asada • An overview of Robocup Physical Challenge: Phase I by Asada • Robocup Rescue: A grand Challenge for Multi-Agent Systems by Kitano • Vision Guided Behavior Acquisition of a Mobile Robot by Multi-Layered Reinforcement Learning by Takahashi and Asada • Priniciples of Minimal Control of a Comprehensive Team Behavior by Brian Werger • Osaka University Trackies 2003 by Takahashi et al. • Strategy Classification in Multi-Agent Environment Applying Reinforcement Learning to Soccer Agents by Asada et al • Vision based Robot Learning Towards Robocup: Osaka University Trackies by Takahashi et al • Reasonable Performance in Less Learning Time by Real Robot Based on Incremental State Space Segmentation by Takahashi, Asada and Hosoda 1996

25. Papers, Links and Books • Cooperative Team Play Based on Communication by K. Yokota, K. Ozaki, N.Watanabe,A. Matsumoto, D. Koyama, T. Ishikawa, K. Kawabata, H. Kaetsu and H. Asama. Journal: Artificial Intelligence ,July 1999, Vol.110 no.2 ,Special Issue : RoboCup The First Step by Kitano guest editor Book: Robotics by Marvin Minsky Websites: www.cs-freiburg.de www.robocup.org www.csl.sony.co.jp/person/kitano/RoboCup/RoboCup-old.html So Finally Question Time Now !

26. Semifinal 2001 goal (Stuttgart)

27. 99 Preliminaries (RMIT)

28. 00 Quarter Final (CMU)

29. Tricking the Goalie (CE)

30. The Visibility Graph Method GOAL START

31. The Visibility Graph Method (cont’d) GOAL START

32. GOAL START The Visibility Graph Method (cont’d)

33. GOAL START The Visibility Graph Method (cont’d)

34. The Visibility Graph Method (cont’d) We can find the shortest path using Dijkstra’s Algorithm GOAL Path START