P_EEMEF_DARC

Project Description

P_EEMEF_DARC is an advanced robotics project focusing on autonomous navigation and collision avoidance using deep reinforcement learning. The main purpose is to provide a robust framework for TurtleBot3 to navigate complex environments autonomously.

Demo Video: Watch Here

Getting Started

These instructions will help you get a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

Ensure you have the following software installed on your machine:

• Ubuntu 18.04
• ROS Melodic
• PyTorch (1.4)
• NumPy (1.16.6)

Installation Steps

1. Activate your Python environment:

   conda activate <environment_name>
   source activate <environment_name>

2. Install the required Python packages:

   pip install -r requirements.txt

3. Install ROS Melodic and other dependencies:

   sudo apt-get update
   sudo apt-get upgrade
   wget https://raw.githubusercontent.com/ROBOTIS-GIT/robotis_tools/master/install_ros_melodic.sh && chmod 755 ./install_ros_melodic.sh && bash ./install_ros_melodic.sh
   sudo apt-get install ros-melodic-joy ros-melodic-teleop-twist-joy ros-melodic-teleop-twist-keyboard ros-melodic-laser-proc ros-melodic-rgbd-launch ros-melodic-depthimage-to-laserscan ros-melodic-rosserial-arduino ros-melodic-rosserial-python ros-melodic-rosserial-server ros-melodic-rosserial-client ros-melodic-rosserial-msgs ros-melodic-amcl ros-melodic-map-server ros-melodic-move-base ros-melodic-urdf ros-melodic-xacro ros-melodic-compressed-image-transport ros-melodic-rqt-image-view ros-melodic-gmapping ros-melodic-navigation ros-melodic-interactive-markers

4. Clone the necessary repositories and compile the workspace:

   cd ~/catkin_nav/src/
   git clone https://github.com/ROBOTIS-GIT/turtlebot3_msgs.git
   git clone https://github.com/ROBOTIS-GIT/turtlebot3.git
   git clone https://github.com/hanlinniu/turtlebot3_ddpg_collision_avoidance.git
   cd ~/catkin_nav && catkin_make
   echo "export TURTLEBOT3_MODEL=waffle" >> ~/.bashrc
   source ~/.bashrc

Usage

1. Launch Gazebo World

To start the simulation in Gazebo, use the following commands to launch different environments:

1.1. Launch Corridor 1 World

roslaunch turtlebot_darc turtlebot3_empty_world.launch world_file:='/home/he/catkin_nav/src/turtlebot3_darc_nav/turtlebot_darc/world/3_corridor.world'

1.2. Launch Corridor 2 World

roslaunch turtlebot_darc turtlebot3_empty_world.launch world_file:='/home/he/catkin_nav/src/turtlebot3_darc_nav/turtlebot_darc/world/2_corridor.world'

2. Collect Priority Excellent Experience Data

roslaunch turtlebot_darc turtlebot3_empty_world.launch world_file:='/home/he/catkin_nav/src/turtlebot3_darc_nav/turtlebot_darc/world/record_maze.world'

3. Train and Test

3.1. Train and Play with DARC Using Human Data

1. Open the environment:

   cd ~/catkin_nav/src/turtlebot3_darc_nav/turtlebot_nav/scripts/record_data

2. Open two terminals and run the following scripts:

   python record_control.py
   python record_data.py

3.2. Training

1. Open the environment:

   cd ~/catkin_nav/src/turtlebot3_darc_nav/turtlebot_nav/scripts

2. Open the terminal and run one of the following Python files:

   python darc_turtlebot3_original_darc.py
   python p_darc_turtlebot3_original.py
   python turtlebot_turtlebot3_peemef_darc_env.py

Authors

nfhe