belajarqywok / Autonomous-Drifting

Autonomous Drifting using Reinforcement Learning

Autonomous-Drifting

Autonomous Drifting using Reinforcement Learning

Installation

1. sudo ./setup_env.sh
2. cd fyp_ws
3. catkin_make
4. . devel/setup.bash (add source [full path to setup.bash] in your .bashrc)
5. roscd drift_car_env/scripts/
6. sudo pip install -e .
7. roscd drift_car/scripts/rl
8. sudo pip install -r requirements.txt

The first time you open Gazebo, it will download all models from the Gazebo servers, which may take some time. Run rosrun gazebo_ros gazebo to run Gazebo and install models.

Commands

To run	Command
ROS Core	roscore
Gazebo Simulator	roslaunch drift_car_gazebo drift_car.launch
Controller	roslaunch drift_car_gazebo_control drift_car_control.launch
Keyboard Teleop	rosrun drift_car_gazebo_control teleop_gazebo.py
Joystick Gazebo Controller	rosrun drift_car_gazebo_control joystick_gazebo.py
Joystick Car Controller	rosrun drift_car_gazebo_control joystick_car.py
Double Dueling Deep Q-Network	rosrun drift_car main.py

PILCO

1. Install MATLAB, enabled with Robotics System Toolbox.
2. Add src/drift_car/scripts/rl/modules and src/drift_car/scripts/rl/pilco to MATLAB path.
3. Start the bridge library with rosrun drift_car_env matlab_bridge.py.
4. To train - drift_car_learn.
5. To apply learned controller - applyController.

Car Model

To run using the Monster Truck, rosed drift_car_gazebo drift_car.launch and toggle the comments to load truck.xacro.urdf.