@InProceedings{LNAI13-BarrettCodeRelease, author = {Samuel Barrett and Katie Genter and Yuchen He and Todd Hester and Piyush Khandelwal and Jacob Menashe and Peter Stone}, title = {The 2012 {UT Austin Villa} Code Release}, booktitle = {{R}obo{C}up-2013: Robot Soccer World Cup {XVII}}, Publisher=“Springer Verlag”, address=“Berlin”, year = {2014}, series=“Lecture Notes in Artificial Intelligence”, abstract={ In 2012, UT Austin Villa claimed the Standard Platform League championships at both the US Open and the 2012 RoboCup competition held in Mexico City. This paper describes the code release associated with the team and discusses the key contributions of the release. This release will enable teams entering the Standard Platform League and researchers using the Naos to have a solid foundation from which to start their work as well as providing useful modules to existing researchers and RoboCup teams. We expect it to be of particular interest because it includes the architecture, logic modules, and debugging tools that led to the team's success in 2012. This architecture is designed to be flexible and robust while enabling easy testing and debugging of code. The vision code was designed for easy use in creating color tables and debugging problems. A custom localization simulator that is included permits fast testing of full team scenarios. Also included is the kick engine which runs through a number of static joint poses and adapts them to the current location of the ball. This code release will provide a solid foundation for new RoboCup teams and for researchers that use the Naos.}, url=“http://www.cs.utexas.edu/users/piyushk/papers/LNAI13-BarrettCodeRelease.pdf”, links=”<a href=http://www.cs.utexas.edu/~AustinVilla/?p=downloads/source_code_and_binaries>[Code]</a>” }

@incollection{LNAI13-Barrett, author = {Samuel Barrett and Katie Genter and Yuchen He and Todd Hester and Piyush Khandelwal and Jacob Menashe and Peter Stone}, title = {UT Austin Villa 2012: Standard Platform League World Champions}, booktitle= “RoboCup-2012: Robot Soccer World Cup {XVI}”, Editor={Xiaoping Chen and Peter Stone and Luis Enrique Sucar and Tijn Van der Zant}, Publisher=“Springer Verlag”, address=“Berlin”, year=“2013”, series=“Lecture Notes in Artificial Intelligence”, abstract= { In 2012, UT Austin Villa claimed Standard Platform League championships at both the US Open and RoboCup 2012 in Mexico City. This paper describes the key contributions that led to the team's victories. First, UT Austin Villa's code base was developed on a solid foundation with a flexible architecture that enables easy testing and debugging of code. Next, the vision code was updated this year to take advantage of the dual cameras and better processor of the new V4 Nao robots. To improve localization, a custom localization simulator allowed us to implement and test a full team solution to the challenge of both goals being the same color. The 2012 team made use of Northern Bites' port of B-Human's walk engine, combined with novel kicks from the walk. Finally, new behaviors and strategies take advantage of opportunities for the robot to take time to setup for a long kick, but kick very quickly when opponent robots are nearby. The combination of these contributions led to the team's victories in 2012.}, url=“http://www.cs.utexas.edu/users/piyushk/papers/LNAI13-Barrett.pdf”, links=”<a href=http://www.cs.utexas.edu/~AustinVilla/?p=downloads/source_code_and_binaries>[Code]</a>” }

@incollection{LNAI11-piyush, author = {Piyush Khandelwal and Peter Stone}, title = {A Low Cost Ground Truth Detection System Using the Kinect}, booktitle= ”{R}obo{C}up-2011: Robot Soccer World Cup {XV}”, Editor={Thomas Roefer and Norbert Michael Mayer and Jesus Savage and Uluc Saranli}, Publisher=“Springer Verlag”, address=“Berlin”, year=“2012”, series=“Lecture Notes in Artificial Intelligence”, abstract = {Ground truth detection systems can be a crucial step in evaluating and improving algorithms for self-localization on mobile robots. Selecting a ground truth system depends on its cost, as well as on the detail and accuracy of the information it provides. In this paper, we present a low cost, portable and real-time solution constructed using the Microsoft Kinect RGB-D Sensor. We use this system to find the location of robots and the orange ball in the Standard Platform League (SPL) environment in the RoboCup competition. This system is fairly easy to calibrate, and does not require any special identifiers on the robots. We also provide a detailed experimental analysis to measure the accuracy of the data provided by this system. Although presented for the SPL, this system can be adapted for use with any indoor structured environment where ground truth information is required.}, url=“http://www.cs.utexas.edu/users/piyushk/papers/LNAI11-piyush.pdf”, links=”<a href=http://www.ros.org/wiki/austinvilla>[Code]</a> <a href=http://www.cs.utexas.edu/users/piyushk/papers/LNAI11-piyush-poster.pdf>[Poster]</a>”, }