Getting Start with MRST
Before the installation, please check that your computer satfied the basic requirements:
Ubuntu 16+
GeForce 1080+
C++ 8.0+
Frist, we need to install the ROS and gazebo
Note
This installation is for the beginner. If you already install the ros and gazebo, please skill this part.
# Set up the key
sudo apt install curl # if you haven't already installed curl
curl -s https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc | sudo apt-key add -
# Install the ROS-melodic and turtlebot3 in Unbuntu 18
sudo apt install ros-melodic-desktop-full
sudo apt install ros-melodic-turtlebot3-*
echo "source /opt/ros/melodic/setup.bash" >> ~/.bashrc
source ~/.bashrc
# Create catkin workspace
mkdir -p ~/catkin_ws/src
cd ~/catkin_ws/src
catkin_init_workspace
Next, please clone our repository from github and move the floder ‘mrst_simulation’ into ‘catkin_ws/src’.
Build our simulation environment.
cd ~/catkin_ws/src
catkin_make
Then, we can use the ‘’roslaunch’’ to launch the simulation environment. For example, we can launch the roundabout scenario with following command.
roslaunch mrst_simulation turtlebot3_autorace_roundabout.launch
roslaunch mrst_simulation turtlebot3_autorace_control_roundabout.launch
Finally, we can training our algorithmn using the API we provides. Here is a simple excample for coding.
from Env import Env
def main():
env=Env(scenario="roundabout")
n_episodes = 100
n_agents=12
episode_length=15
for e in range(n_episodes):
env.reset()
for et_i in range(episode_length):
print(et_i)
actions=[[1] for i in range(n_agents)]
next_obs, rewards, dones, speeds = env.step(actions, isTeamReward=True)
if __name__ == "__main__":
main()
In the next section, we will introduce the other scenarios we provided and the APIs for agent-envrionment interaction.