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Installation Guide

This tutorial provides a reproducible ROS 2 Jazzy environment compatible with MATLAB R2025.

It supports:

  • Docker-based environments (recommended)
  • Native Ubuntu installation (advanced users)

MATLAB Requirements

Supported Versions

  • MATLAB R2025a
  • MATLAB R2025b

Required Toolboxes

  • Simulink
  • ROS Toolbox
  • Robotics System Toolbox
  • Symbolic Math Toolbox
  • Universal Robots Support Package

Supported Environments

You can run this tutorial using:

  • Windows 11 + WSL2 + Docker
  • Ubuntu 24 + Docker
  • Ubuntu 24 Native (no Docker)

Installation Using the Script

All environments use:

bash install.sh

Script Modes Overview

Mode Installs Docker Installs ROS Builds Workspace Use Case
fulldocker ✅ Yes Inside container ✅ Yes Fresh machine
docker ❌ No Inside container ✅ Yes Docker already installed
fullnative ❌ No ✅ Yes ✅ Yes Native Ubuntu
native ❌ No ❌ No ✅ Yes ROS already installed

Docker provides:

  • Reproducibility
  • MATLAB integration
  • Easy setup

Windows 11 + WSL2 + Docker

1. Install WSL2

Install Ubuntu 24:

https://learn.microsoft.com/en-us/windows/wsl/install

2. Install Using Script

Inside WSL:

  1. git clone -b docker https://github.com/iocroblab/from_code_to_robot_ros2_stack.git
  2. cd from_code_to_robot_ros2_stack/scripts
  3. bash install.sh fulldocker

This will:

  • Install Docker Engine
  • Build the tutorial Docker image
  • Create the container named FCTR-container

If Docker is already installed in WSL

  1. git clone -b docker https://github.com/iocroblab/from_code_to_robot_ros2_stack.git
  2. cd from_code_to_robot_ros2_stack/scripts
  3. bash install.sh docker

This will:

  • Build the tutorial Docker image
  • Create the preconfigured container

Docker Container Behavior

The installer:

  • Builds the image
  • Creates a named container
  • Leaves it stopped

MATLAB will:

  • Start the container
  • Attach to it
  • Manage lifecycle automatically

Custom Docker Options

If using a custom container name:

StartTutorialApplication('Rviz','model','ur3','DockerName','YourContainerName');

If workspace location differs:

StartTutorialApplication('Rviz','model','ur3','Workspace','path/to/workspace');

Ubuntu 24 + Docker

If Docker is NOT installed yet (recommended path)

Install everything via script:

  1. git clone -b docker https://github.com/iocroblab/from_code_to_robot_ros2_stack.git
  2. cd from_code_to_robot_ros2_stack/scripts
  3. bash install.sh fulldocker

If Docker is already installed

To install Docker manually follow:

https://docs.docker.com/engine/install/ubuntu/

Then run:

  1. git clone -b docker https://github.com/iocroblab/from_code_to_robot_ros2_stack.git
  2. cd from_code_to_robot_ros2_stack/scripts
  3. bash install.sh docker

This will:

  • Build your custom tutorial Docker image
  • Create container FCTR-container (stopped)

Manually install docker (no script)

Step 1 — Install docker

To install Docker manually follow:

https://docs.docker.com/engine/install/ubuntu/

Step 2 — Clone the Tutorial Repository

  1. git clone -b docker https://github.com/iocroblab/from_code_to_robot_ros2_stack.git
  2. cd from_code_to_robot_ros2_stack

Step 3 — Build the Tutorial Docker Image

Navigate to the Docker folder (location may vary slightly depending on repo structure):

docker build -t from-code-to-robot-tutorial-docker docker

This builds the custom tutorial image containing:

  • ROS 2 Jazzy
  • Gazebo / ros_gz
  • ros2_control stack
  • Tutorial workspace

Step 4 — Create the Tutorial Container

Create the container manually:

xhost +``local:docker

docker create \\

--name FCTR-container \\

--env``=``"DISPLAY=``\$DISPLAY``" \\

--env``=``"QT_X11_NO_MITSHM=1" \\

--volume``=``"/tmp/.X11-unix:/tmp/.X11-unix:rw" \\

--device /dev/snd \\

--net``=``host \\

from-code-to-robot-tutorial-docker \\

bash -lc "trap : TERM INT; sleep infinity & wait"

This creates a stopped container named:

FCTR-container

The container:

  • Is not running yet
  • Will be started automatically by MATLAB

Test in MATLAB (Ubuntu MATLAB)

Add the robotics folder and subfolders to path, then run:

StartTutorialApplication('Rviz','model','ur5e');

JointStatesToRviz([0,-pi/2,0,-pi/2,0,0]);

StopTutorialApplications();

StartTutorialApplication('Simulation','model','ur3e','controller','effort');

StopTutorialApplications();

Extra Docker info

If your container name differs:

StartTutorialApplication('Rviz','model','ur3','DockerName','YourContainerName');

If your workspace path differs:

StartTutorialApplication('Rviz','model','ur3','Workspace','path/to/workspace');

Native Ubuntu Installation (No Docker)

Native installation gives:

  • Higher performance
  • Lower latency
  • Better hardware access

Option 1 — Automatic Native Install (With ROS installation)

Installs ROS + dependencies + workspace.

  1. git clone -b docker https://github.com/iocroblab/from_code_to_robot_ros2_stack.git
  2. cd from_code_to_robot_ros2_stack/scripts
  3. bash install.sh fullnative

Installs:

  • ROS 2 Jazzy Desktop
  • Gazebo + ros_gz
  • ros2_control stack
  • DDS middleware
  • Workspace dependencies
  • Full build

Option 2 — Workspace Only (ROS already installed)

Use this if ROS 2 Jazzy is already installed.

  1. git clone -b docker https://github.com/iocroblab/from_code_to_robot_ros2_stack.git
  2. cd from_code_to_robot_ros2_stack/scripts
  3. bash install.sh native

This will:

  • Clone workspace
  • Import repositories
  • Run rosdep
  • Build with colcon

Option 3 — Manual Native Workspace Setup (No Script)

For advanced users who prefer manual setup.

1. Install ROS 2 Jazzy

Follow official guide:

https://docs.ros.org/en/jazzy/Installation/Ubuntu-Install-Debians.html

2. Install Required Tools

  1. sudo apt update
  2. sudo apt install -y \\
  3. git \\
  4. build-essential \\
  5. cmake \\
  6. pkg-config \\
  7. python3-pip \\
  8. python3-venv \\
  9. python3-colcon-common-extensions \\
  10. python3-rosdep \\
  11. python3-vcstool \\
  12. python3-argcomplete \\
  13. wget curl

3.Install ROS packages

  1. sudo apt install -y \
  2. ros-jazzy-desktop \
  3. ros-jazzy-ros-gz \
  4. ros-jazzy-gz-ros2-control \
  5. ros-jazzy-ros2-control \
  6. ros-jazzy-ros2-controllers \
  7. ros-jazzy-controller-manager \
  8. ros-jazzy-turtlebot3-msgs \
  9. ros-jazzy-rmw-cyclonedds-cpp \
  10. ros-jazzy-rmw-fastrtps-dynamic-cpp \
  11. ros-dev-tools

Initialize rosdep:

  1. sudo rosdep init
  2. rosdep update

4. Create Workspace

  1. mkdir -p ~/fctr_ws/src
  2. cd ~/fctr_ws/src
  3. git clone -b jazzy https://github.com/iocroblab/from_code_to_robot_ros2_stack.git
  4. source /opt/ros/jazzy/setup.bash
  5. cd ..
  6. mkdir -p src/modified-repositories
  7. vcs import src/modified-repositories < src/from_code_to_robot_ros2_stack/stack.repos

5. Build Workspace

  1. source /opt/ros/jazzy/setup.bash
  2. rosdep update
  3. rosdep install --ignore-src --from-paths src -y
  4. colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=Release

Using Native Mode in MATLAB

When using native Ubuntu:

StartTutorialApplication('Rviz','model','ur5e','Docker',false);

JointStatesToRviz([0,-pi/2,0,-pi/2,0,0];

StopTutorialApplications('Docker',false);

StartTutorialApplication('Simulation','model','ur3e','controller','effort','Docker',false);

StopTutorialApplications('Docker',false);

Troubleshooting

ROS not found

run and try again:

  1. source /opt/ros/jazzy/setup.bash

rosdep errors

  1. sudo rosdep init
  2. rosdep update

Docker permission errors

  1. sudo usermod -aG docker $USER

Then log out and back in.Recommended Setup

Use Case Recommended Mode
Students / teaching Docker
MATLAB workflows Docker
Real robots Native
Performance simulation Native
Development Native