F1TENTH gym environment ROS2 communication bridge

This is a containerized ROS communication bridge for the F1TENTH gym environment that turns it into a simulation in ROS2.

Installation

Supported System:

• Ubuntu (tested on 22.04) native with ROS 2
• Ubuntu (tested on 20.04) native with ROS 2
• Ubuntu (tested on 20.04) with an NVIDIA gpu and nvidia-docker2 support
• Windows 10, macOS, and Ubuntu without an NVIDIA gpu (using noVNC)

This installation guide will be split into instruction for installing the ROS 2 package natively, and for systems with or without an NVIDIA gpu in Docker containers.

Native on Ubuntu 22.04

Install the following dependencies:

• ROS 2 Follow the instructions here to install ROS 2 Iron.
• F1TENTH Gym

  git clone https://github.com/f1tenth/f1tenth_gym
  cd f1tenth_gym && pip3 install -e .

Installing the simulation:

• Create a workspace: cd $HOME && mkdir -p sim_ws/src
• Clone the repo into the workspace:

  cd $HOME/sim_ws/src
  git clone https://github.com/Autonomous-Racing-Labs/f1tenth_gym_ros.git

• Update correct parameter for path to map file: Go to sim.yaml https://github.com/f1tenth/f1tenth_gym_ros/blob/main/config/sim.yaml in your cloned repo, change the map_path parameter to point to the correct location. It should be '<your_home_dir>/sim_ws/src/f1tenth_gym_ros/maps/levine'
• Install dependencies with rosdep:

  source /opt/ros/iron/setup.bash
  cd ..
  apt install python3-rosdep2 python3-colcon-ros
  rosdep update
  rosdep install -i --from-path src --rosdistro iron -y

• Build the workspace: colcon build
• Run the simulation:

  source /opt/ros/iron/setup.bash
  source install/local_setup.bash
  ros2 launch f1tenth_gym_ros gym_bridge_launch.py

Configuring the simulation

• The configuration file for the simulation is at f1tenth_gym_ros/config/sim.yaml.
• Topic names and namespaces can be configured but is recommended to leave uncahnged.
• The map can be changed via the map_path parameter. You'll have to use the full path to the map file in the container. The map follows the ROS convention. It is assumed that the image file and the yaml file for the map are in the same directory with the same name. See the note below about mounting a volume to see where to put your map file.
• The num_agent parameter can be changed to either 1 or 2 for single or two agent racing.
• The ego and opponent starting pose can also be changed via parameters, these are in the global map coordinate frame.

The entire directory of the repo is mounted to a workspace /sim_ws/src as a package. All changes made in the repo on the host system will also reflect in the container. After changing the configuration, run colcon build again in the container workspace to make sure the changes are reflected.

Topics published by the simulation

In single agent:

/scan: The ego agent's laser scan

/ego_racecar/odom: The ego agent's odometry

/map: The map of the environment

A tf tree is also maintained.

In two agents:

In addition to the topics available in the single agent scenario, these topics are also available:

/opp_scan: The opponent agent's laser scan

/ego_racecar/opp_odom: The opponent agent's odometry for the ego agent's planner

/opp_racecar/odom: The opponent agents' odometry

/opp_racecar/opp_odom: The ego agent's odometry for the opponent agent's planner

Topics subscribed by the simulation

In single agent:

/drive: The ego agent's drive command via AckermannDriveStamped messages

/initalpose: This is the topic for resetting the ego's pose via RViz's 2D Pose Estimate tool. Do NOT publish directly to this topic unless you know what you're doing.

TODO: kb teleop topics

In two agents:

In addition to all topics in the single agent scenario, these topics are also available:

/opp_drive: The opponent agent's drive command via AckermannDriveStamped messages. Note that you'll need to publish to both the ego's drive topic and the opponent's drive topic for the cars to move when using 2 agents.

/goal_pose: This is the topic for resetting the opponent agent's pose via RViz's 2D Goal Pose tool. Do NOT publish directly to this topic unless you know what you're doing.

Keyboard Teleop

The keyboard teleop node from teleop_twist_keyboard is also installed as part of the simulation's dependency. To enable keyboard teleop, set kb_teleop to True in sim.yaml. After launching the simulation, in another terminal, run:

ros2 run teleop_twist_keyboard teleop_twist_keyboard

Then, press i to move forward, u and o to move forward and turn, , to move backwards, m and . to move backwards and turn, and k to stop in the terminal window running the teleop node.

Developing and creating your own agent in ROS 2

There are multiple ways to launch your own agent to control the vehicles.

• The first one is creating a new package for your agent in the /sim_ws workspace inside the sim container. After launch the simulation, launch the agent node in another bash session while the sim is running.
• The second one is to create a new ROS 2 container for you agent node. Then create your own package and nodes inside. Launch the sim container and the agent container both. With default networking configurations for docker, the behavior is to put The two containers on the same network, and they should be able to discover and talk to each other on different topics. If you're using noVNC, create a new service in docker-compose.yml for your agent node. You'll also have to put your container on the same network as the sim and novnc containers.