# robocup_demo

**Repository Path**: wycan/robocup_demo

## Basic Information

- **Project Name**: robocup_demo
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2019-11-03
- **Last Updated**: 2021-02-23

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 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.  

![demobehavior](https://cloud.githubusercontent.com/assets/7802157/17454416/142ef6c4-5b5a-11e6-900d-7b4fe81beb79.png)
*Video of default demo behavior: ([YouTube](https://www.youtube.com/watch?v=b47enPRhFR4), [mp4](http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2016/videos/UTABaseCodeReleaseDemoBehavior.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
* Support for Gazebo RoboCup 3D simulation plugin (https://bitbucket.org/osrf/robocup3ds)
* Scripts and code for collecting game statistics

#### What is not included: 
* The team's complete set of skills such as long kicks and goalie dives
* Optimized parameters for behaviors such as the 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)
* 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:
```bash
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.)
 
```bash
make
```

### Instructions for running agent:
First be sure to start the simulation server running.

##### Run full team:
```bash
./start.sh <host>
```
##### Run penalty kick shooter:
```bash
./start_penalty_kicker.sh <host>
```
##### Run penalty kick goalie:
```bash
./start_penalty_goalie.sh <host>
```
##### Run agent for Gazebo RoboCup 3D simulation plugin:
```bash
./start_gazebo.sh <host>
```
&nbsp;&nbsp;*Video of default walking behavior in Gazebo: ([YouTube](https://www.youtube.com/watch?v=E3LTkFFt5eA), [mp4](http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/AustinVilla3DSimulationFiles/2016/videos/GazeboWalk.mp4))*

&nbsp;

##### Kill team:
```bash
./kill.sh
```
##### List command line options:
```bash
./agentspark --help
```

### Documentation:
See [DOCUMENTATION](DOCUMENTATION.md) for some high level documentation about the codebase.


### Demo behaviors:
See the methods in `selectSkill()` in [behaviors/strategy.cc](behaviors/strategy.cc) for demo behaviors.


### Optimization task examples:
See the [optimization](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)