UTCS Artificial Intelligence
courses
talks/events
demos
people
projects
publications
software/data
labs
areas
admin
The UT Austin Villa 2004 RoboCup Four-Legged Team: Coming of Age (2004)
Peter Stone
,
Kurt Dresner
, Peggy Fidelman,
Nicholas K. Jong
, Nate Kohl,
Gregory Kuhlmann
,
Mohan Sridharan
, and
Daniel Stronger
The UT Austin Villa Four-Legged Team for RoboCup 2004 was a second-time entry in the ongoing series of RoboCup legged league competitions. The team development began in mid-January of 2003 without any prior familiarity with the Aibos. After entering a fairly non-competitive team in RoboCup 2003, the team made several important advances. By the July 2004 competition place in Lisbon, Portugal, it was one of the top few teams. In this report, we describe both our development process and the technical details of its end result. In conjunction with our previous technical report this paper provides full documentation of the algorithms behind our approach with the goal of making them fully replicable.
View:
PDF
,
PS
,
HTML
Citation:
Technical Report UT-AI-TR-04-313, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory.
Bibtex:
@TechReport{Villa04-legged-tech, title={The UT Austin Villa 2004 RoboCup Four-Legged Team: Coming of Age}, author={Peter Stone and Kurt Dresner and Peggy Fidelman and Nicholas K. Jong and Nate Kohl and Gregory Kuhlmann and Mohan Sridharan and Daniel Stronger}, number={UT-AI-TR-04-313}, month={October}, institution={The University of Texas at Austin, Department of Computer Sciences, AI Laboratory}, url="http://www.cs.utexas.edu/users/ai-lab?Villa04-legged-tech", year={2004} }
People
Kurt Dresner
Ph.D. Alumni
kurt [at] dresner name
Nicholas Jong
Ph.D. Alumni
nickjong [at] me com
Gregory Kuhlmann
Ph.D. Alumni
kuhlmann [at] cs utexas edu
Mohan Sridharan
Ph.D. Alumni
mhnsrdhrn [at] gmail com
Peter Stone
Faculty
pstone [at] cs utexas edu
Daniel Stronger
Ph.D. Alumni
dan stronger [at] gmail com
Areas of Interest
Other Areas
Quadruped Robots
Real Robot Soccer
Labs
Learning Agents