Gazebo Ackermann Steering Vehicle

This package, built with ROS 2 Jazzy Jalisco and Gazebo Harmonic, launches a simulation of an Ackermann steering vehicle. The vehicle model includes steering angle and velocity control, along with an embedded front camera that streams live images for vision-based tasks. This setup could be used for developing and testing autonomous driving algorithms in a simulated environment.

For the complete documentation on the development of this package, including setup, modeling, and simulation steps, please refer to the full guide here: Ackermann Steering Vehicle Simulation

💻 Installation

Clone this repository into your

``` folder. If you don't have a workspace set up, you can learn more about creating one in the [ROS 2 workspace tutorial](https://docs.ros.org/en/jazzy/Tutorials/Beginner-Client-Libraries/Creating-A-Workspace/Creating-A-Workspace.html).


```bash
cd <path_to_your_workspace>/src

git clone git@github.com:lucasmazzetto/gazebo_ackermann_steering_vehicle.git

🐧 Linux Setup

This project is designed to run on Linux Ubuntu 24.04 and may also work on other Linux versions or distributions, although additional adjustments might be required.

📚 Requirements

To use this package, you’ll need the following:

• Linux Ubuntu 24.04
• ROS2 Jazzy Jalisco
• Gazebo Harmonic

Make sure to install the following ROS 2 Jazzy Jalisco packages:

sudo apt install -y \
     ros-jazzy-ros2-controllers \
     ros-jazzy-gz-ros2-control \
     ros-jazzy-ros-gz \
     ros-jazzy-ros-gz-bridge \
     ros-jazzy-joint-state-publisher \
     ros-jazzy-robot-state-publisher \
     ros-jazzy-xacro \
     ros-jazzy-joy                           

🛠️ Build

Source the ROS 2 environment and build the package:

source /opt/ros/jazzy/setup.bash

cd <path_to_your_workspace>

colcon build

After a successful build, the package is ready to be used.

🐳 Docker Setup

Docker is required to build and run this project using the Docker setup. It ensures a consistent environment and simplifies dependency management across different systems. Make sure Docker is properly installed and running on your machine before proceeding with the build and execution steps.

🛠️ Build

Navigate to the project directory and run the build_docker.sh script to build the Docker container. Make sure you’re inside the folder, as the script depends on local files. The build may take a while, depending on your internet speed and system performance.

cd <path_to_your_workspace>/src/gazebo_ackermann_steering_vehicle

./build_docker.sh

🏃 Run

To run the Docker container, make sure you’re in the project directory and execute the run_docker.sh script. This will open a command line with the environment fully configured. You can run this script as many times as needed, and each time it will launch a new command line session inside the Docker container, ready to execute commands within the configured environment.

cd <path_to_your_workspace>/src/gazebo_ackermann_steering_vehicle

./run_docker.sh

For instance, if you need to run the simulation, simply execute the run_docker.sh script to open a command line inside the Docker container and execute the following command:

cd <path_to_your_workspace>/src/gazebo_ackermann_steering_vehicle

./run_docker.sh

ros2 launch gazebo_ackermann_steering_vehicle vehicle.launch.py

To use the joystick, open a new command line inside the Docker container by running the run_docker.sh script again in a new terminal. Once inside, execute the following command:

```bash cd /src/gazebo_ackermann_steering_vehicle

./run_docker.sh

ros2 launch gazebo_ackermann_steering_vehicle joystick.launch.py

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