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All Projects → kanakkabara → Autonomous-Drifting

kanakkabara / Autonomous-Drifting

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Autonomous Drifting using Reinforcement Learning

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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.

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