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Design and Optimization of an Omnidirectional Humanoid Walk:A Winning Approach at the RoboCup 2011 3D Simulation Competition

Patrick MacAlpine, Samuel Barrett, Daniel Urieli, Victor Vu, and Peter Stone. Design and Optimization of an Omnidirectional Humanoid Walk:A Winning Approach at the RoboCup 2011 3D Simulation Competition. In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI), July 2012.
Accompanying videos at http://www.cs.utexas.edu/ AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/walk.html

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Abstract

This paper presents the design and learning architecture for an omnidirectional walk used by a humanoid robot soccer agent acting in the RoboCup3D simulation environment. The walk, which was originally designed for and tested on an actual Nao robot before being employed in the 2011 RoboCup 3Dsimulation competition, was the crucial component in the UT Austin Villa teamwinning the competition in 2011. To the best of our knowledge, this is the first time that robot behavior has been conceived and constructed on a real robot for the end purpose of being used in simulation. The walk is based on a double linear inverted pendulum model, and multiple sets of its parameters areoptimized via a novel framework. The framework optimizes parameters for different tasks in conjunction with one another, a little-understood problem with substantial practical significance. Detailed experiments show that the UT Austin Villa agent significantly outperforms all the other agents in the competition with the optimized walk being the key to its success.

BibTeX

@InProceedings{AAAI12-MacAlpine,
  author = {Patrick MacAlpine and Samuel Barrett and Daniel Urieli and Victor Vu and Peter Stone},
  title = {Design and Optimization of an Omnidirectional Humanoid Walk:
A Winning Approach at the {R}obo{C}up 2011 3{D} Simulation Competition},
  booktitle = {Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI)},
  location = {Toronto, Ontario, Canada},
  month = {July},
  year = {2012},
  abstract={
   This paper presents the design and learning architecture for an 
omnidirectional walk used by a humanoid robot soccer agent acting in the RoboCup
3D simulation environment.  The walk, which was originally designed for and 
tested on an actual Nao robot before being employed in the 2011 RoboCup 3D
simulation competition, was the crucial component in the UT Austin Villa team
winning the competition in 2011.  To the best of our knowledge, this is the 
first time that robot behavior has been conceived and constructed on a real 
robot for the end purpose of being used in simulation.  The walk is based on a 
double linear inverted pendulum model, and multiple sets of its parameters are
optimized via a novel framework. The framework optimizes parameters for 
different tasks in conjunction with one another, a little-understood problem 
with substantial practical significance.  Detailed experiments show that the UT 
Austin Villa agent significantly outperforms all the other agents in the 
competition with the optimized walk being the key to its success. 
  },
  wwwnote={Accompanying videos at <a href="http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/walk.html">http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2011/html/walk.html</a>},
}

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