1. 2011 NSF REU Research Proposal This research is supported by NSF Grant No. CNS 1005212. Opinions, findings, conclusions, or recommendations expressed in this presentation are those of the author(s) and do not necessarily reflect the views of NSF.

2. 2011 NSF REU Research Proposal This research is supported by NSF Grant No. CNS 1005212. Opinions, findings, conclusions, or recommendations expressed in this presentation are those of the author(s) and do not necessarily reflect the views of NSF.

3. Nao Robot Soccer David Kari, Jesse Kawell Dr. Mohan Sridharan NSF REU 2011

4. UT Austin Villa Naos across Texas

5. The Goal ”The stated goal of the Robocup initiative is to develop a team of robots that is better than the best human soccer team by the year 2050.” -Peter Stone et al.

6. RoboCup is Significant RoboCup provides... An excellent testbed for developing robot software A fun, visual presentation of robotics Multi-agent interaction Human-robot interaction

7. Related Work The Essence of Soccer, Can Robots Play Too?  Peter Stone, Michael Quinlan, and Todd Hester TT-UT Austin Villa 2009: Naos Across Texas  Todd Hester, Michael Quinlan, Peter Stone, and Mohan Sridharan Half Field O ff ense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study  Shivaram Kalyanakrishnan, Yaxin Liu, and Peter Stone

8. Statement of Objectives Multiagent Collaboration on the Nao Platform  Intelligent passing/scoring  Aggressive off-ball offense →high possession %  On-ball pass/shoot balance Project Goal  Score as quickly and efficiently as possible Intermediate Goal  Implement basic plays for offense

9. Triangle Play

10. Simulation Strategies are Successful Half Field O ff ense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study -Shivaram Kalyanakrishnan, Yaxin Liu, and Peter Stone

11. Project Prerequisites Accurate and timely passing Accurate self-localization Localization of enemies

12. Current Status 1) Downloaded code, simulator, and compiler on individual PC's 2) Connected to robots R2, D2, C3, and PO 3) Tuned walking parameters to increase speed of walk (min freq=15) 4) Created data logs based on the visual data returned from the robot

13. Color Maps: Do you see what I see?

14. Challenges Hardware Issues  R2 fully functioning  D2 ceased normal functioning  C3 just returned!  PO arrived last week from upgrades Robots intermittently lose functionality Understanding scope of software

15. Anticipated Research Outcomes Robots learn how to collaborate more effectively Given the current set of hardware specifications and constraints the software maximizes team performance

16. Current Progress

17. Image Citations http://www.google.com/imgres?imgurl=http://cdn.wn.com/ph/img/60/95/d97bb6d82345a1fc314dd7b0b145- grande.jpg&imgrefurl=http://article.wn.com/view/2010/06/22/World_Cup_2010_Spains_Iker_Casillas_Sergi_Busquets_Focused_ O/&usg=__VYny1oF0A4hTR47n6Dk__ggyhV0=&h=311&w=468&sz=48&hl=en&start=0&zoom=1&tbnid=aCcIUL03oPl8uM:&tbn h=158&tbnw=200&ei=rb_3Tf3DF4fpgQeL8uD9Cw&prev=/search%3Fq%3Dworld%2Bcup%2Bsoccer%2Bgoalie%26um%3D1% 26hl%3Den%26biw%3D1366%26bih%3D658%26tbm%3Disch&um=1&itbs=1&iact=hc&vpx=866&vpy=103&dur=3391&hovh=18 3&hovw=276&tx=166&ty=108&page=1&ndsp=18&ved=1t:429,r:4,s:0&biw=1366&bih=658 http://www.google.com/imgres?imgurl=http://static.startblatt.at/files/blogentry/image/84276/resize400/TU_Wien_austrian_kangar oos.jpg&imgrefurl=http://www.startblatt.net/blogs/at.wien-6-mariahilf/austrian-kangaroos-wiens-erstes-humanoides- roboterfussballteam&usg=__HlIBTIc31H3YHGyFHD72xozwmW0=&h=325&w=400&sz=81&hl=en&start=218&zoom=1&tbnid=q5 G2r9QYt_1_2M:&tbnh=154&tbnw=187&ei=xMP3TbXoH4PrgQfUq7D_Cw&prev=/search%3Fq%3DRoboCup%2BNaos%26um% 3D1%26hl%3Den%26biw%3D1366%26bih%3D658%26tbm%3Disch&um=1&itbs=1&iact=hc&vpx=613&vpy=218&dur=1899&ho vh=202&hovw=249&tx=122&ty=142&page=13&ndsp=20&ved=1t:429,r:9,s:218&biw=1366&bih=658 http://www.google.com/imgres?imgurl=http://light.ece.illinois.edu/img/nsf.jpg&imgrefurl=http://light.ece.illinois.edu/sponsors.html &usg=__2FuXUagVJSSjxaOpQq4ytEUFjpI=&h=900&w=900&sz=115&hl=en&start=157&zoom=1&tbnid=pD_7ra4MKJ3YAM:&tb nh=127&tbnw=124&ei=- cX3TfGmCIjMgQf5j4DlCw&prev=/search%3Fq%3DNational%2BScience%2BFoundation%2Blogo%26um%3D1%26hl%3Den% 26biw%3D1366%26bih%3D621%26tbs%3Disz:l%26tbm%3Disch&um=1&itbs=1&iact=hc&vpx=371&vpy=305&dur=1736&hovh= 225&hovw=225&tx=150&ty=137&page=8&ndsp=24&ved=1t:429,r:10,s:157&biw=1366&bih=621 http://www.google.com/imgres?imgurl=http://regmedia.co.uk/2010/09/14/aldebaran_nao.jpg&imgrefurl=http://naoforge.net/naopr essblog/author/zelig/page/26/&usg=__1UKDx6mesxhuqxUOpK8GZrVqYL8=&h=873&w=580&sz=42&hl=en&start=0&zoom=1&t bnid=L_WhNl0- T5OdbM:&tbnh=147&tbnw=97&ei=xMP3TbXoH4PrgQfUq7D_Cw&prev=/search%3Fq%3DRoboCup%2BNaos%26um%3D1%2 6hl%3Den%26biw%3D1366%26bih%3D658%26tbm%3Disch&um=1&itbs=1&iact=hc&vpx=1144&vpy=150&dur=238&hovh=276 &hovw=183&tx=145&ty=155&page=1&ndsp=21&ved=1t:429,r:20,s:0&biw=1366&bih=658

18. Image Citations (continued) http://www.google.com/imgres?imgurl=http://www.openlocksmith.com/houston_locksmith/texas- map.gif&imgrefurl=http://www.openlocksmith.com/texas.html&usg=__gY1iACXdUAyQ3T1wA3K3- TvM5Es=&h=284&w=300&sz=8&hl=en&start=0&zoom=1&tbnid=8qBGOged_LtOvM:&tbnh=160&tbnw=169&ei=bXT7TeK9J86Ut wfy89S6Dg&prev=/search%3Fq%3DTexas%2Bmap%2Bwith%2BLubbock%2Band%2BAustin%26um%3D1%26hl%3Den%26au thuser%3D0%26biw%3D1366%26bih%3D658%26tbm%3Disch&um=1&itbs=1&iact=hc&vpx=682&vpy=86&dur=1054&hovh=21 8&hovw=231&tx=107&ty=99&page=1&ndsp=18&ved=1t:429,r:3,s:0&biw=1366&bih=658

19. Related Work The Essence of Soccer, Can Robots Play Too?  Peter Stone, Michael Quinlan, and Todd Hester TT-UT Austin Villa 2009: Naos Across Texas  Todd Hester, Michael Quinlan, Peter Stone, and Mohan Sridharan Half Field O ff ense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study  Shivaram Kalyanakrishnan, Yaxin Liu, and Peter Stone