@COMMENT This file was generated by bib2html.pl version 0.90
@COMMENT written by Patrick Riley
@COMMENT This file came from Peter Stone's publication pages at
@COMMENT http://www.cs.utexas.edu/~pstone/papers
@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.
},
}