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@InProceedings{HUMANOIDS13-menashe,
  author = {Jacob Menashe and Katie Genter and Samuel Barrett and Peter Stone},
  title = {{UT} {A}ustin {V}illa 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.
  },
}