Deep-Reinforcement-Learning

• Author : Hwasu Lee
  
  
• Affiliation : UNICON LAB (Incheon National University, South Korea)
  
  
• Position : M.A. student
  
  
• E-mail : leehwasu96@naver.com (or leehwasu9696@inu.ac.kr)
  
  

Project Description

• This repository designs and validates an End-to-End controller that learns control inputs for moving a Turtlebot3 model
  
  to a desired location based on Deep Reinforcement Learning in the ROS Gazebo simulation environment.
  
  

Repository Description

• The 'project' directory contains packages related to DRL(Deep Reinforcement Learning).
  
  
• The 'turtlebot3_gazebo' directory is a folder that stores custom world information.
  
  

Development environment

• This practice was conducted in an Ubuntu 18.04 LTS and ROS(Robot Operating System) 1 Melodic environment.
  
  

How to use

1. Installing packages related to ROS Gazebo simulation.

cd ~/catkin_ws/src/

And

git clone https://github.com/ROBOTIS-GIT/turtlebot3
git clone https://github.com/ROBOTIS-GIT/turtlebot3_msgs
git clone https://github.com/ROBOTIS-GIT/turtlebot3_simulations
git clone https://github.com/leehwasu96/Deep-Reinforcement-Learning.git

2. Building and sourcing the catkin workspace

cd ~/catkin_ws && catkin_make
source devel/setup.bash

3. Configuring LiDAR scan data

• In: turtlebot3/turtlebot3_description/urdf/turtlebot3_burger.gazebo.xacro.

roscd turtlebot3_description/urdf

If you encounter the error "roscd: No such package/stack 'turtlebot3_description/urdf'", execute the following command and then source it:

echo 'export TURTLEBOT3_MODEL=burger' >> ~/.bashrc
echo 'export ROS_PACKAGE_PATH=$ROS_PACKAGE_PATH:/home/{your local PC name}/catkin_ws/src/turtlebot3:$ROS_PACKAGE_PATH' >> ~/.bashrc
echo 'export ROS_PACKAGE_PATH=$ROS_PACKAGE_PATH:/home/{your local PC name}/catkin_ws/src/turtlebot3_simulations/turtlebot3_gazebo:$ROS_PACKAGE_PATH' >> ~/.bashrc
echo 'export ROS_PACKAGE_PATH=/home/{your local PC name}/catkin_ws/src/Deep-Reinforcement-Learning/project:$ROS_PACKAGE_PATH' >> ~/.bashrc

Example image of a bashrc file

And

source ~/.bashrc

And

gedit turtlebot3_burger.gazebo.xacro

And

<xacro:arg name="laser_visual" default="false"/>

Visualization of LDS. If you want to see LDS, set it to true as follows:

<xacro:arg name="laser_visual" default="true"/>

And

<scan>
  <horizontal>
    <samples>360</samples>
    <resolution>1</resolution>
    <min_angle>0.0</min_angle>
    <max_angle>6.28319</max_angle>
  </horizontal>
</scan>

If you want to modify the LiDAR data to detect only the front 180 degrees and recognize only 10 scan data points, update the code as follows:

<scan>
  <horizontal>
    <samples>10</samples>             <!-- Number of LiDAR scan data samples modified to 10 -->
    <resolution>1</resolution>
    <min_angle>-1.5708</min_angle>    <!-- -π/2 in radians -->
    <max_angle>1.5708</max_angle>     <!-- π/2 in radians -->
  </horizontal>
</scan>

4. Setting up Turtlebot3 world file

cd ~ && cd catkin_ws/src/Deep-Reinforcement-Learning/turtlebot3_gazebo/worlds

And

cp * ~/catkin_ws/src/turtlebot3_simulations/turtlebot3_gazebo/worlds

And

roscd turtlebot3_gazebo/worlds

5. Configuring Turtlebot3 launch file

cd ~ && cd catkin_ws/src/Deep-Reinforcement-Learning/turtlebot3_gazebo/launch

And

cp * ~/catkin_ws/src/turtlebot3_simulations/turtlebot3_gazebo/launch

6. Configuring Goal model file

cd /home/{your local PC name}/catkin_ws/src/Deep-Reinforcement-Learning/turtlebot3_gazebo/models/turtlebot3_square/goal_box

And

cp model2.* ~/catkin_ws/src/turtlebot3_simulations/turtlebot3_gazebo/models/turtlebot3_square/goal_box

7. Run Code

First terminal:

roslaunch turtlebot3_gazebo hs_turtlebot3_stage_{number_of_stage}.launch

Example image of Gazebo simulation environment

In another terminal:

roslaunch project hs_ddpg_stage_{number_of_stage}.launch

8. Validation result

Validation Video 1

11.mp4

Validation Video 2

22.mp4

Validation Video 3

33.mp4

Validation Video 4

44.mp4