The WCG AI Masters simulation environment for usage in local PCs.
- There are two ways to download the WCG AI Masters simulation program.
- WCG AI Masters simulation program requires Webots Robot Simulator. Please refer to Webots official website's installation procedure to install Webots (Webots version should be R2019a-rev1).
- Downloading the ZIP file through 'Download ZIP' will not work. It does not download the submodules related to the program.
How to download the simulation program
Method 1. Go to releases and download the latest version.
Method 2. Use following git command
git clone https://github.com/wcgaimasters/wcg_ai_soccer.git --recurse-submodules
How to run the simulation program
Please refer to the Wiki pages.
Descriptions
controllers: Contains programs for managing WCG AI Masters simulation game system (You can modify the controllers to aid your development. However, the games at the competition will use the default controllers)
-
soccer_robot: A program that changes robot wheel movements based on received data
-
supervisor: A referee program that manages AI Soccer game as whole (Participant programs communicate with this program to control the robots)
examples: Contains sample programs participants can refer to (Participants may implement AI programs referring to the sample programs provided in this directory)
-
common: Contains a basic interface for information handling and communication with the simulation program
-
extlibs: Contains external libraries used in sample programs
-
team_a_data and team_b_data: Directories where participants' program may write some files into if needed
-
Remaining directories contain samples participants can refer to.
-
general_check-varaibles: A program that prints game information variables sent from the simulation program to participants program
-
general_frame-skip: A program that implements framing skipping. Frame skipping is advised when your program takes more than 50 ms in each game frame in generating the output control signal
-
general_image-fetch: A program that shows the game image frames using OpenCV
-
player_deep-learning-play and player_deep-learning-train: Programs that implement a base skeleton for deep learning using Deep-Q-Network (DQN)
-
player_random-walk: A program that simply sets robot wheel speeds to random value in each game frame
-
player_rulebased-A, player_rulebased-B: Programs that implement a rule-based control of a team )'rulebased-B' is a simplified version of 'rulebased-A')
-
player_skeleton: A base skeleton for the participant program
extlibs: Contains external libraries used in WCG AI Masters simulation
plugins: Contains a physics plugin used for ball-robot collision detection
protos: Contains WCG AI Masters object models (robot, ball, stadium, etc.)
worlds: Contains WCG AI Masters simulation world files (Files in this directory can be run using Webots Robot Simulator)
- aiwc.wbt: Webots world file
config.json: Configuration file for setting player executables, setting game duration, and setting some rules on/off for effective training. Please refer to the Wiki page for parameter descriptions (Participants should modify the player information in this file to tell the simulation which program to execute)