utaustinvilla3d

UT Austin Villa RoboCup 3D simulation team base code release

About:

This release is based off the UT Austin Villa RoboCup 3D simulation league team.

Video of default demo behavior: (YouTube, mp4)

What it includes:

Omnidirectional walk engine based on a double inverted pendulum model
A skill description language for specifying parameterized skills/behaviors
Getup behaviors for all agent types
A couple basic skills for kicking one of which uses inverse kinematics
Sample demo dribble and kick behaviors for scoring a goal
World model and particle filter for localization
Kalman filter for tracking objects
All necessary parsing code for sending/receiving messages from/to the server
Code for drawing objects in the roboviz monitor
Communication system previously provided for use in drop-in player challenges
Example behaviors/tasks for optimizing a kick and forward walk
Example simple soccer behavior with basic formation and dynamic greedy role assignment
Support for running with fat proxy (https://github.com/magmaOffenburg/magmaFatProxy)
Support for Gazebo RoboCup 3D simulation plugin (https://bitbucket.org/osrf/robocup3ds)
Scripts and code for collecting game statistics

What is not included:

The UT Austin Villa team's complete set of skills such as long kicks and goalie dives
Optimized parameters for behaviors such as the UT Austin Villa team's fastest walks (slow and stable walk engine parameters are included, as well as optimized walk engine parameters for positioning/dribbling and approaching the ball to kick)
The UT Austin Villa team's high level strategy including formations and role assignment

Requirements:

simspark and rcssserver3d
Boost library
Threads library

Instructions for installing simspark and rcssserver3d: https://gitlab.com/robocup-sim/SimSpark/wikis/Installation-on-Linux

It's optional (recommended) to install the roboviz monitor: https://github.com/magmaOffenburg/RoboViz

To build:

cmake .

(If cmake can't find RCSSNET3D set the SPARK_DIR environmental variable to the path where you installed the server and then rerun cmake. Also, if you installed rcssserver3d from a package instead of building it from source, you might need to install the rcssserver3d-dev package.)

make

Instructions for running agent:

First be sure to start the simulation server running.

Run full team:

./start.sh <host>

Run penalty kick shooter:

./start_penalty_kicker.sh <host>

Run penalty kick goalie:

./start_penalty_goalie.sh <host>

Run team with fat proxy:

./start_fat_proxy.sh <host> -p <proxy_port>

Run simple soccer example team:

./start_simple_soccer.sh <host>

Run agent for Gazebo RoboCup 3D simulation plugin:

./start_gazebo.sh <host>

Video of default walking behavior in Gazebo: (YouTube, mp4)

Kill team:

./kill.sh

List command line options:

./agentspark --help

Documentation:

See DOCUMENTATION for some high level documentation about the codebase.
View a tutorial about using the code base (YouTube, mp4).

Demo behaviors:

See the methods in selectSkill() in behaviors/strategy.cc for demo behaviors.
See behaviors/simplesoccer.cc for an example simple soccer team behavior with a basic formation and dynamic greedy role assignment.

Optimization task examples:

See the optimization directory.

UT Austin Villa 3D simulation team homepage:

(http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/)

More information (team publications):

(http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/publications.html)

If you use this code for research purposes, please consider citing one or more research papers listed at the above link which includes the following topics and papers:

Code Release

Patrick MacAlpine and Peter Stone.
UT Austin Villa RoboCup 3D Simulation Base Code Release.
In Sven Behnke, Daniel D. Lee, Sanem Sariel, and Raymond Sheh, editors, RoboCup 2016: Robot Soccer World Cup XX, Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2016. (http://www.cs.utexas.edu/~pstone/Papers/bib2html/b2hd-LNAI16-MacAlpine2.html)

Walk Engine

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. (http://www.cs.utexas.edu/~pstone/Papers/bib2html/b2hd-AAAI12-MacAlpine.html)

Optimization

Patrick MacAlpine and Peter Stone.
Overlapping Layered Learning.
Artificial Intelligence (AIJ), 254:21-43, Elsevier, January 2018. (http://www.cs.utexas.edu/~pstone/Papers/bib2html/b2hd-AIJ18-MacAlpine.html)

Winning team paper

Patrick MacAlpine, Josiah Hanna, Jason Liang, and Peter Stone.
UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions.
In Luis Almeida, Jianmin Ji, Gerald Steinbauer, and Sean Luke, editors, RoboCup-2015: Robot Soccer World Cup XIX, Lecture Notes in Artificial Intelligence, Springer Verlag, Berlin, 2016. (http://www.cs.utexas.edu/~pstone/Papers/bib2html/b2hd-LNAI15-MacAlpine.html)

UT Austin Villa team contacts:

Patrick MacAlpine (patmac@cs.utexas.edu)
Peter Stone (pstone@cs.utexas.edu)

LARG/utaustinvilla3d