Prerequisites

Important: Building pre-requisites from below is only recommended if you have a powerful enough NVIDIA machine (RTX 2060 or more) and are willing to setup dual boot Ubuntu 24.04. If not follow the instructions at apptainer to create a container in the university computers where all the below is done.

This package is intended for the following:

• Ubuntu 24.04
• ROS 2 Jazzy
• Gazebo Harmonic

Important: For the most up-to-date installation instructions, please refer to the official pages:

• ROS 2 Jazzy Installation Guide
• Gazebo Harmonic Installation Guide

Make sure to install ros-jazzy-desktop (which includes RViz2).

Install ROS 2 Jazzy

1. Enable the Ubuntu Universe Repository:

   sudo apt install software-properties-common
   sudo add-apt-repository universe

2. Add ROS 2 GPG key:

   sudo apt update && sudo apt install curl -y
   sudo curl -sSL https://raw.githubusercontent.com/ros/rosdistro/master/ros.key -o /usr/share/keyrings/ros-archive-keyring.gpg

3. Add ROS 2 repository:

   echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/ros-archive-keyring.gpg] http://packages.ros.org/ros2/ubuntu $(. /etc/os-release && echo $UBUNTU_CODENAME) main" | sudo tee /etc/apt/sources.list.d/ros2.list > /dev/null

4. Install ROS 2:

   sudo apt update
   sudo apt upgrade
   sudo apt install ros-jazzy-desktop

Install Gazebo Harmonic

1. Install necessary tools:

   sudo apt-get update
   sudo apt-get install curl lsb-release gnupg

2. Add Gazebo repository:

   sudo curl https://packages.osrfoundation.org/gazebo.gpg --output /usr/share/keyrings/pkgs-osrf-archive-keyring.gpg
   echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/pkgs-osrf-archive-keyring.gpg] http://packages.osrfoundation.org/gazebo/ubuntu-stable $(lsb_release -cs) main" | sudo tee /etc/apt/sources.list.d/gazebo-stable.list > /dev/null

3. Install Gazebo Harmonic:

   sudo apt-get update
   sudo apt-get install gz-harmonic

---

Build Instructions

1. Source the ROS 2 Environment:

   source /opt/ros/jazzy/setup.bash

2. Create a Workspace:

   mkdir -p ~/colcon_ws/src
   cd ~/colcon_ws/src

3. Clone the Repository:

   git clone https://github.com/GryphonRacingAI/gra-ros2.git .

4. Install Necessary Tools

   sudo apt install -y python3-colcon-common-extensions
   sudo apt install -y python3-rosdep
   sudo rosdep init
   rosdep update

5. Resolve Dependencies:

   cd ~/colcon_ws
   rosdep install -i --from-path src --rosdistro jazzy -y

6. Build and Source the Workspace:

   cd ~/colcon_ws
   colcon build --symlink-install
   source install/setup.bash

---

Usage

Environment Setup

To source the overlays automatically every time you open a new terminal, add the following lines to the .bashrc script:

source /opt/ros/jazzy/setup.bash
source ~/colcon_ws/install/setup.bash

or simply run the following

echo "source /opt/ros/jazzy/setup.bash" >> ~/.bashrc
echo "source ~/colcon_ws/install/setup.bash" >> ~/.bashrc

Run the following command so Gazebo can find the vehicle mesh

echo "export GZ_SIM_RESOURCE_PATH=$HOME/colcon_ws/install/simulation/share/" >> ~/.bashrc

then continue in a new terminal.

Launch the Simulator

To run the simulator, run the following commands

ros2 launch simulation dynamic_event.launch.py autostart:=true

This should launch Gazebo Sim, with the acceleration track and ADS-DV vehicle model spawned in.

The following launch arguments are provided for dynamic_event.launch.py

Argument	Description	Options	Default
event	specifies which track to spawn in based on the dynamic event	acceleration, skidpad, autocross, trackdrive	acceleration
autostart	starts the simulation automatically	true, false	true
model_file	path to the vehicle model sdf file	Any valid path to vehicle sdf model	hard-coded path
name	sets the vehicle name in Gazebo	Any valid string	ads_dv
verbosity	sets the Gazebo console output verbosity	0 - 4	1

Launch Perception

To launch the perception nodes, use the following command

ros2 launch ultralytics_ros predict_with_cloud.launch.xml use_sim_time:=true yolo_model:=conev11n.pt input_topic:=/zed2i/depth_camera/image

Argument	Description	Options	Default
use_sim_time	uses simulation time published to /clock	true, false	true
yolo_model	sets the model for inference	conev11n.pt, conev8n.pt, conev8n_40.pt	conev11n.pt
input_topic	sets camera input topic	any valid camera video topic	/image_raw

All parameters for the 3D perception node predict_with_cloud_node are specified in config/predict_with_cloud_node.yaml