Installing ROS 2 Humble on Ubuntu

Downloading Debian packages to set up the latest LTS release for ROS 2 on your Linux machine

Esther Weon ·

5 min read

Published July 1, 2022

Check out our follow-up Iron Irwini tutorial to install the latest ROS 2 release.

Though it’s possible to install ROS 2 from source or archive, the easiest way to get ROS running on your Ubuntu machine is to install its corresponding Debian packages using apt, a command line utility for installing and managing packages on Linux distributions.

In this tutorial, we’ll walk you through installing the Debian packages for ROS 2 Humble Hawksbill, the latest LTS release for ROS 2, on Ubuntu Jammy (22.04 LTS).

Set up a UTF-8 system locale

Before installing anything, you’ll need to make sure your system locale supports UTF-8. Locale issues can cause unexpected problems further down the line, when using various ROS tools and libraries.

Run $ locale in a terminal window to view your currently installed locale – if UTF-8 appears in the listed output, you’re all set!

Otherwise, you'll need to set up your locale in one of two ways – choose a locale on your system or generate a new one.

Show more info.

Set up your source repos

Ubuntu programs are stored in repositories that make installing new software easy and secure. Ubuntu’s four main repositories are as follows:

Main (Canonical-supported open-source software)
Universe (community-maintained open source software)
Restricted (proprietary device drivers)
Multiverse (proprietary software)

For the purposes of installing ROS, we need to enable the Ubuntu Universe repository:

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

Now you can add the ROS 2 repository to your system. Authorize the public GPG (GNU Privacy Guard) key provided by ROS, then add the ROS 2 repository to your sources list:

$ sudo apt update && sudo apt install curl gnupg lsb-release
$ sudo curl -sSL https://raw.githubusercontent.com/ros/rosdistro/master/ros.key -o /usr/share/keyrings/ros-archive-keyring.gpg
$ echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/ros-archive-keyring.gpg] http://packages.ros.org/ros2/ubuntu $(source /etc/os-release && echo $UBUNTU_CODENAME) main" | sudo tee /etc/apt/sources.list.d/ros2.list > /dev/null

Install ROS 2 packages

Install your ROS 2 Humble desktop setup with the following commands:

$ sudo apt update # update your apt repo caches
$ sudo apt install ros-humble-desktop

This will install a few different components like the core ROS libraries, developer tools like RViz, and a set of beginner-friendly tutorials and demos to help you get started.

Show more info.

Source your setup file

Typically, you would need to source your setup file every time you open a terminal to use ROS:

$ source /opt/ros/humble/setup.bash

To save yourself the time, you can automatically trigger this step every time you launch a new shell. Run the following commands if you’re using a bash shell:

echo "source /opt/ros/humble/setup.bash" >> ~/.bashrc
source ~/.bashrc

Run the following commands if you’re using a zsh shell:

echo "source /opt/ros/humble/setup.zsh" >> ~/.zshrc
source ~/.zshrc

Run some examples

After completing the desktop install, let’s make sure that our APIs are working properly.

**Run the example C++ talker **at /opt/ros/humble/lib/demo_nodes_cpp/talker:

$ ros2 run demo_nodes_cpp talker

The output should confirm that the talker is successfully publishing messages:

[INFO] [1652382860.246687611] [talker]: Publishing: 'Hello World: 1'
[INFO] [1652382861.250208871] [talker]: Publishing: 'Hello World: 2'
[INFO] [1652382862.246508551] [talker]: Publishing: 'Hello World: 3'
...

In another terminal window, **run the example Python listener **at /opt/ros/humble/lib/demo_nodes_py/listener:

$ ros2 run demo_nodes_py listener

The output should confirm that the listener is hearing the published messages:

[INFO] [1652382936.495044030] [listener]: I heard: [Hello World: 1]
[INFO] [1652382937.478216343] [listener]: I heard: [Hello World: 2]
[INFO] [1652382938.487370309] [listener]: I heard: [Hello World: 3]
...

Both the C++ and Python APIs are working properly!

NOTE: If you’re experiencing issues here, make sure that you’ve enabled multicast – the network interface needs this in order to communicate via DDS.

Run the following commands in two separate terminal windows:

$ ros2 multicast receive
$ ros2 multicast send

If the first command does not return a successful output (i.e. Received from xx.xxx.xxx.xx:43751: 'Hello World!'), try updating your firewall configuration:

$ sudo ufw allow in proto udp to 224.0.0.0/4
$ sudo ufw allow in proto udp from 224.0.0.0/4

Then, restart your terminal and try starting up your talker and listener again.

What’s next

Continue with the official ROS 2 tutorials to configure your environment, record data, and create a workspace and packages.

To uninstall ROS 2, remove the repository from your system completely:

$ sudo apt remove ~nros-humble-desktop && sudo apt autoremove
$ sudo rm /etc/apt/sources.list.d/ros2.list
$ sudo apt update
$ sudo apt autoremove
$ sudo apt upgrade # for previously shadowed packages

Visualize and analyze your data with Foxglove

Once you’ve gotten the lay of the land and started recording your robots’ data, you’ll need to start visualizing your data to understand what’s going on under the hood of your robots.

This would be a good time to check out the specs for the MCAP file format. Not only are MCAP files smaller (and more performant!) than standard ROS 2 files, they’re also completely self-contained (unlike ROS 2 files that draw from message definitions living on your hard drive). This allows you to easily share these files with teammates for visualization. By adhering to a common container format, the MCAP file format encourages interoperability among third-party developer tools like Foxglove.

Foxglove provides a convenient mcap CLI tool to help you convert your ROS 2 (.db3) files into MCAP (.mcap) files. These files can then be imported directly into your Foxglove account, so your whole team can collaborate on organizing and tagging your data:

Foxglove

They can also be dragged and dropped into Foxglove for instant rich visualizations. Load up your data to view camera images, display 3D markers, review log messages, and more:

Foxglove