Peter Stone's Selected Publications

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UT Austin Villa 2013: Advances in Vision, Kinematics, and Strategy

Jacob Menashe, Katie Genter, Samuel Barrett, and Peter Stone. UT Austin Villa 2013: Advances in Vision, Kinematics, and Strategy. In The Eighth Workshop on Humanoid Soccer Robots at Humanoids 2013, October 2013.

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Abstract

In RoboCup, although the fields are standardized and color coded, the area outside the fields often contains many objects of various colors. Sometimes objects off the field may look very similar to balls, robots, or other objects normally found on the soccer field. Robots must detect all of these objects, and then differentiate between the true positives and false positives. This paper presents a new method using Gaussian fitness scores to differentiate between true positives and false positives for balls, robots, and penalty crosses. We also present some other improvements in our code base following our 2012 championship, such as our usage of a virtual base for forward kinematics calculations, our ability to flexibly transition player roles given dynamic numbers of teammates, and our ability to quickly integrate new kicks of varying speeds into our strategy. With these improvements, our UT Austin Villa team finished third in the Standard Platform League at RoboCup 2013.

BibTeX Entry

@InProceedings{HUMANOIDS13-menashe,
  author = {Jacob Menashe and Katie Genter and Samuel Barrett and Peter Stone},
  title = {UT Austin Villa 2013: Advances in Vision, Kinematics, and Strategy},
  booktitle = {The Eighth Workshop on Humanoid Soccer Robots at Humanoids 2013},
  location = {Atlanta, GA},
  month = {October},
  year = {2013},
  abstract = {
   In RoboCup, although the fields are standardized
  and color coded, the area outside the fields often contains many
  objects of various colors. Sometimes objects off the field may
  look very similar to balls, robots, or other objects normally
  found on the soccer field. Robots must detect all of these objects,
  and then differentiate between the true positives and false
  positives. This paper presents a new method using Gaussian
  fitness scores to differentiate between true positives and false
  positives for balls, robots, and penalty crosses. We also present
  some other improvements in our code base following our 2012
  championship, such as our usage of a virtual base for forward
  kinematics calculations, our ability to flexibly transition player
  roles given dynamic numbers of teammates, and our ability to
  quickly integrate new kicks of varying speeds into our strategy.
  With these improvements, our UT Austin Villa team finished
  third in the Standard Platform League at RoboCup 2013.
  },
}

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