mazeCommRL-CORE

A communication-efficient reinforcement learning algorithm for solving maze exploration problems by a coordinated group of swarm robots in CORE simulation environment.

Quick Start Guide

In coutesy with Dr Wenzhan Song Micromouse Repository

Run in CORE - Quick Guide First make sure that CORE has been installed. If you have not installed CORE, follow CORE Tutorial to install. Also, Install python3-tk:

$ sudo apt-get install python3-tk

Download the MazeCommRL framework from MazeCommRL Github Page.

$ cd ~
$ git clone https://github.com/herolab-uga/MazeCommRL.git
$ cd MazeCommRL

Configure the CORE environment for running core_demo.py

$ sudo ./setCORE.sh

If you encounter any problems running the above script, you may need to manually configure the environment for CORE. Open the framework/gui.py before starting a session:

$ cd framework
$ python3 gui.py

Open CORE to demonstrate:

$ core-gui

Then open maze.xml, click the Start button.

Module Description

MazeCommRL
├── backservice.sh          //starting program in MyService
├── __init__.py             //module automatically read by CORE when core-gui opens
├── preload.py              //MyService class as an extra service that can be added into CORE, pointered by __init__.py
│                             and it specifies the starting program - backservice.sh
│                             Calling Relations: CORE -> __init__.py -> preload.py -> backservice.sh -> demo_core.py
├── framework               //framework written in Python3
├── icons                   //folder for icons of mice shown in CORE
├── mazes                   //folder for maze examples that png files are pictures for backgrounds and txt files 
│                             are corresponding maze presented in (*, |, etc) which should be parsed by a function. 
│                             See map.py -> readFromFile as a parser example.
├── maze.xml                //layout file opened and saved by CORE v4.8
└── README.md

Several Notes for understanding the code

auto-start design

It is based on 6.2 of CORE tutorial (https://docs.google.com/document/d/1LPkPc2lbStwFtiukYfCxhcW7KewD028XzNfMd20uFFA/edit#heading=h.2clxcd487uk4) as written in framework/demo_core.py. When we open a CORE GUI, it looks for the init.py in current fold whose path we have put in /etc/core/core.conf. __init__py then loads preload.py. Then preload.py then loads backservice.sh. And then backservice.sh runs demo_core.py

Change Maze for simulation

In (https://github.com/herolab-uga/MazeCommRL/tree/main/mazes) you will see number of mazes to simulate, use the following steps to change maze for simulation:

In (https://github.com/herolab-uga/MazeCommRL/tree/main/maze.xml) line 93

{name {Canvas1}} {wallpaper-style {scaled}} {wallpaper {~/mazeCommRL/tree/main/mazes/<maze_image>}} {size {1158 772}}

replace <maze_image> with one of the maze file name you find in mazes folder. For example, 2012japan-ef.png.

In (https://github.com/herolab-uga/MazeCommRL/tree/main/framework/demo_core.py) line 12:

mazeMap.readFromFile('~/MazeCommRL/tree/main/mazes/<maze_text_file>')

replace <maze_text_file> with the corresponding maze text file associated with your rpelace maze image. For example, 2012japan-ef.txt

Change Maze Coverage Strategy

We have implemented DFS and RL based strategies, you can test both of the by changing strategy call in In (https://github.com/herolab-uga/MazeCommRL/tree/main/framework/demo_core.py) line 18:

micromouse.addTask(StrategyCommMazeRL(micromouse))

node send message to host for moving itself

In (https://github.com/herolab-uga/MazeCommRL/tree/main/framework/demo_core.py) line 16:

micromouse.setMotorController(COREController(index, initPoint[index], controlNet='10.0.0.254'))

In framework/controller_core.py (https://github.com/herolab-uga/MazeCommRL/tree/main/framework/controller_core.py)

In goStraight() function:

os.system("coresendmsg -a " + self.controlNet + " node number=" + self.index + " xpos=" + str(self.xpos) + " ypos=" + str(self.ypos))