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An up to date information to Docker and ROS 2

An up to date information to Docker and ROS 2


2 years in the past, I wrote A Information to Docker and ROS, which is considered one of my most often seen posts — seemingly as a result of it’s a difficult subject and folks had been searching for solutions. Since then, I’ve had the prospect to make use of Docker extra in my work and have picked up some new methods. This was lengthy overdue, however I’ve lastly collected my up to date learnings on this put up.

Not too long ago, I encountered an article titled ROS Docker; 6 the explanation why they aren’t an excellent match, and I largely agree with it. Nevertheless, the truth is that it’s nonetheless fairly troublesome to make sure a reproducible ROS atmosphere for individuals who haven’t spent years preventing the ROS studying curve and are adept at debugging dependency and/or construct errors… so Docker remains to be very a lot a crutch that we fall again on to get working demos (and generally merchandise!) out the door.

If the article above hasn’t fully discouraged you from embarking on this Docker journey, please take pleasure in studying.

Revisiting Our Dockerfile with ROS 2

Now that ROS 1 is on its last model and approaching finish of life in 2025, I believed it will be acceptable to rehash the TurtleBot3 instance repo from the earlier put up utilizing ROS 2.

A lot of the large modifications on this improve must do with ROS 2, together with consumer libraries, launch recordsdata, and configuring DDS. The examples themselves have been up to date to make use of the most recent instruments for habits bushes: BehaviorTree.CPP 4 / Groot 2 for C++ and py_trees / py_trees_ros_viewer for Python. For extra data on the instance and/or habits bushes, seek advice from my Introduction to Conduct Timber put up.

From a Docker standpoint, there aren’t too many variations. Our container structure will now be as follows:

Layers of our TurtleBot3 instance Docker picture.

We’ll begin by making our Dockerfile, which defines the contents of our picture. Our preliminary base layer inherits from one of many public ROS photos, osrf/ros:humble-desktop, and units up the dependencies from our instance repository into an underlay workspace. These are outlined utilizing a vcstool repos file.

Discover that we’ve arrange the argument, ARG ROS_DISTRO=humble, so it may be modified for different distributions of ROS 2 (Iron, Rolling, and so forth.). Fairly than creating a number of Dockerfiles for various configurations, it is best to strive utilizing construct arguments like these as a lot as potential with out being “overly intelligent” in a method that impacts readability.


# Base Picture for TurtleBot3 Simulation #
FROM osrf/ros:${ROS_DISTRO}-desktop as base
SHELL [“/bin/bash”, “-c”]

# Create Colcon workspace with exterior dependencies
RUN mkdir -p /turtlebot3_ws/src
WORKDIR /turtlebot3_ws/src
COPY dependencies.repos .
RUN vcs import < dependencies.repos

# Construct the bottom Colcon workspace, putting in dependencies first.
WORKDIR /turtlebot3_ws
RUN supply /decide/ros/${ROS_DISTRO}/setup.bash
&& apt-get replace -y
&& rosdep set up –from-paths src –ignore-src –rosdistro ${ROS_DISTRO} -y
&& colcon construct –symlink-install

To construct your picture with a selected argument — let’s say you need to use ROS 2 Rolling as a substitute — you can do the next… supplied that every one your references to ${ROS_DISTRO} even have one thing that appropriately resolves to the rolling distribution.

docker construct -f docker/Dockerfile
--target base -t turtlebot3_behavior:base .

I personally have had many points in ROS 2 Humble and later with the default DDS vendor (FastDDS), so I like to modify my default implementation to Cyclone DDS by putting in it and setting an atmosphere variable to make sure it’s at all times used.

# Use Cyclone DDS as middleware
RUN apt-get replace && apt-get set up -y --no-install-recommends
ENV RMW_IMPLEMENTATION=rmw_cyclonedds_cpp

Now, we are going to create our overlay layer. Right here, we are going to copy over the instance supply code, set up any lacking dependencies with rosdep set up, and arrange an entrypoint to run each time a container is launched.

# Overlay Picture for TurtleBot3 Simulation #
FROM base AS overlay

# Create an overlay Colcon workspace
RUN mkdir -p /overlay_ws/src
WORKDIR /overlay_ws
COPY ./tb3_autonomy/ ./src/tb3_autonomy/
COPY ./tb3_worlds/ ./src/tb3_worlds/
RUN supply /turtlebot3_ws/set up/setup.bash
&& rosdep set up –from-paths src –ignore-src –rosdistro ${ROS_DISTRO} -y
&& colcon construct –symlink-install

# Arrange the entrypoint
COPY ./docker/entrypoint.sh /
ENTRYPOINT [ “/entrypoint.sh” ]

The entrypoint outlined above is a Bash script that sources ROS 2 and any workspaces which are constructed, and units up atmosphere variables essential to run our TurtleBot3 examples. You need to use entrypoints to do another forms of setup you may discover helpful on your software.

# Primary entrypoint for ROS / Colcon Docker containers

# Supply ROS 2
supply /decide/ros/${ROS_DISTRO}/setup.bash

# Supply the bottom workspace, if constructed
if [ -f /turtlebot3_ws/install/setup.bash ]
supply /turtlebot3_ws/set up/setup.bash
export TURTLEBOT3_MODEL=waffle_pi
export GAZEBO_MODEL_PATH=$GAZEBO_MODEL_PATH:$(ros2 pkg prefix turtlebot3_gazebo)/share/turtlebot3_gazebo/fashions

# Supply the overlay workspace, if constructed
if [ -f /overlay_ws/install/setup.bash ]
supply /overlay_ws/set up/setup.bash
export GAZEBO_MODEL_PATH=$GAZEBO_MODEL_PATH:$(ros2 pkg prefix tb3_worlds)/share/tb3_worlds/fashions

# Execute the command handed into this entrypoint
exec “$@”

At this level, it is best to be capable of construct the total Dockerfile:

docker construct
-f docker/Dockerfile --target overlay
-t turtlebot3_behavior:overlay .

Then, we are able to begin considered one of our instance launch recordsdata with the suitable settings with this mouthful of a command. Most of those atmosphere variables and volumes are wanted to have graphics and ROS 2 networking functioning correctly from inside our container.

docker run -it --net=host --ipc=host --privileged
bash -c "ros2 launch tb3_worlds tb3_demo_world.launch.py"

Our TurtleBot3 instance simulation with RViz (left) and Gazebo basic (proper).

Introducing Docker Compose

From the previous couple of snippets, we are able to see how the docker construct and docker run instructions can get actually lengthy and unwieldy as we add extra choices. You may wrap this in a number of abstractions, together with scripting languages and Makefiles… however Docker has already solved this drawback by means of Docker Compose.

Briefly, Docker Compose lets you create a YAML file that captures all of the configuration wanted to arrange constructing photos and working containers.

Docker Compose additionally differentiates itself from the “plain” Docker command in its capability to orchestrate companies. This entails constructing a number of photos or targets throughout the identical picture(s) and launching a number of applications on the identical time that comprise a whole software. It additionally helps you to prolong current companies to attenuate copy-pasting of the identical settings in a number of locations, outline variables, and extra.

The top aim is that we have now quick instructions to handle our examples:

  • docker compose construct will construct what we’d like
  • docker compose up will launch what we’d like

Docker Compose permits us to extra simply construct and run our containerized examples.

The default identify of this magical YAML file is docker-compose.yaml. For our instance, the docker-compose.yaml file seems to be as follows:

model: "3.9"
# Base picture containing dependencies.
picture: turtlebot3_behavior:base
context: .
dockerfile: docker/Dockerfile
ROS_DISTRO: humble
goal: base
# Interactive shell
stdin_open: true
tty: true
# Networking and IPC for ROS 2
network_mode: host
ipc: host
# Wanted to show graphical purposes
privileged: true
# Wanted to outline a TurtleBot3 mannequin kind
# Permits graphical applications within the container.
# Permits graphical applications within the container.
- /tmp/.X11-unix:/tmp/.X11-unix:rw
- ${XAUTHORITY:-$HOME/.Xauthority}:/root/.Xauthority

# Overlay picture containing the instance supply code.
extends: base
picture: turtlebot3_behavior:overlay
context: .
dockerfile: docker/Dockerfile
goal: overlay

# Demo world
extends: overlay
command: ros2 launch tb3_worlds tb3_demo_world.launch.py

# Conduct demo utilizing Python and py_trees
extends: overlay
command: >
ros2 launch tb3_autonomy tb3_demo_behavior_py.launch.py

# Conduct demo utilizing C++ and BehaviorTree.CPP
extends: overlay
command: >
ros2 launch tb3_autonomy tb3_demo_behavior_cpp.launch.py

As you possibly can see from the Docker Compose file above, you possibly can specify variables utilizing the acquainted $ operator in Unix based mostly techniques. These variables will by default be learn from both your host atmosphere or by means of an atmosphere file (normally referred to as .env). Our instance.env file seems to be like this:

# TurtleBot3 mannequin

# Conduct tree kind: May be naive or queue.

# Set to true to make use of imaginative and prescient, else false to solely do navigation behaviors.

# Goal coloration for imaginative and prescient: May be purple, inexperienced, or blue.

At this level, you possibly can construct all the pieces:

# By default, picks up a `docker-compose.yaml` and `.env` file.
docker compose construct

# You may also explicitly specify the recordsdata
docker compose –file docker-compose.yaml –env-file .env construct

Then, you possibly can run the companies you care about:

# Carry up the simulation
docker compose up demo-world

# After the simulation has began,
# launch considered one of these in a separate Terminal
docker compose up demo-behavior-py
docker compose up demo-behavior-cpp

The complete TurtleBot3 demo working with py_trees because the Conduct Tree.

Establishing Developer Containers

Our instance to date works nice if we need to bundle up working examples to different customers. Nevertheless, if you wish to develop the instance code inside this atmosphere, you will want to beat the next obstacles:

  • Each time you modify your code, you will want to rebuild the Docker picture. This makes it extraordinarily inefficient to get suggestions on whether or not your modifications are working as meant. That is already an prompt deal-breaker.
  • You may remedy the above through the use of bind mounts to sync up the code in your host machine with that within the container. This will get us heading in the right direction, however you’ll discover that any recordsdata generated contained in the container and mounted on the host will likely be owned by root as default. You may get round this by whipping out the sudo and chown hammer, but it surely’s not needed.
  • All of the instruments it’s possible you’ll use for improvement, together with debuggers, are seemingly lacking contained in the container… except you put in them within the Dockerfile, which may bloat the dimensions of your distribution picture.

Fortunately, there’s a idea of a developer container (or dev container). To place it merely, it is a separate container that allows you to truly do your improvement in the identical Docker atmosphere you’ll use to deploy your software.

There are lots of methods of implementing dev containers. For our instance, we are going to modify the Dockerfile so as to add a brand new dev goal that extends our current overlay goal.

Dev containers enable us to develop inside a container from our host system with minimal overhead.

This dev container will do the next:

  • Set up extra packages that we could discover useful for improvement, corresponding to debuggers, textual content editors, and graphical developer instruments. Critically, these won’t be a part of the overlay layer that we are going to ship to finish customers.
  • Create a brand new consumer that has the identical consumer and group identifiers because the consumer that constructed the container on the host. It will make it such that every one recordsdata generated throughout the container (in folders we care about) have the identical possession settings as if we had created the file on our host. By “folders we care about”, we’re referring to the ROS workspace that comprises the supply code.
  • Put our entrypoint script within the consumer’s Bash profile (~/.bashrc file). This lets us supply our ROS atmosphere not simply at container startup, however each time we connect a brand new interactive shell whereas our dev container stays up.

# Improvement Picture #
FROM overlay as dev

# Dev container arguments
ARG UID=1000

# Set up additional instruments for improvement
RUN apt-get replace && apt-get set up -y –no-install-recommends
gdb gdbserver nano

# Create new consumer and residential listing
RUN groupadd –gid $GID $USERNAME
&& useradd –uid ${GID} –gid ${UID} –create-home ${USERNAME}
&& echo ${USERNAME} ALL=(root) NOPASSWD:ALL > /and so forth/sudoers.d/${USERNAME}
&& chmod 0440 /and so forth/sudoers.d/${USERNAME}
&& mkdir -p /residence/${USERNAME}
&& chown -R ${UID}:${GID} /residence/${USERNAME}

# Set the possession of the overlay workspace to the brand new consumer
RUN chown -R ${UID}:${GID} /overlay_ws/

# Set the consumer and supply entrypoint within the consumer’s .bashrc file
RUN echo “supply /entrypoint.sh” >> /residence/${USERNAME}/.bashrc

You may then add a brand new dev service to the docker-compose.yaml file. Discover that we’re including the supply code as volumes to mount, however we’re additionally mapping the folders generated by colcon construct to a .colcon folder on our host file system. This makes it such that generated construct artifacts persist between stopping our dev container and bringing it again up, in any other case we’d must do a clear rebuild each time.

extends: overlay
picture: turtlebot3_behavior:dev
context: .
dockerfile: docker/Dockerfile
goal: dev
- UID=${UID:-1000}
- GID=${UID:-1000}
# Mount the supply code
- ./tb3_autonomy:/overlay_ws/src/tb3_autonomy:rw
- ./tb3_worlds:/overlay_ws/src/tb3_worlds:rw
# Mount colcon construct artifacts for quicker rebuilds
- ./.colcon/construct/:/overlay_ws/construct/:rw
- ./.colcon/set up/:/overlay_ws/set up/:rw
- ./.colcon/log/:/overlay_ws/log/:rw
consumer: ${USERNAME:-devuser}
command: sleep infinity

At this level you are able to do:

# Begin the dev container
docker compose up dev

# Connect an interactive shell in a separate Terminal
# NOTE: You are able to do this a number of occasions!
docker compose exec -it dev bash

As a result of we have now mounted the supply code, you can also make modifications in your host and rebuild contained in the dev container… or you need to use helpful instruments just like the Visible Studio Code Containers extension to immediately develop contained in the container. As much as you.

For instance, when you’re contained in the container you possibly can construct the workspace with:

colcon construct

Attributable to our quantity mounts, you’ll see that the contents of the .colcon/construct, .colcon/set up, and .colcon/log folders in your host have been populated. Which means that should you shut down the dev container and produce up a brand new occasion, these recordsdata will live on and can velocity up rebuilds utilizing colcon construct.

Additionally, as a result of we have now gone by means of the difficulty of constructing a consumer, you’ll see that these recordsdata are usually not owned by root, so you possibly can delete them should you’d like to wash out the construct artifacts. You must do this with out making the brand new consumer and also you’ll run into some annoying permissions roadblocks.

$ ls -al .colcon
whole 20
drwxrwxr-x 5 sebastian sebastian 4096 Jul 9 10:15 .
drwxrwxr-x 10 sebastian sebastian 4096 Jul 9 10:15 ..
drwxrwxr-x 4 sebastian sebastian 4096 Jul 9 11:29 construct
drwxrwxr-x 4 sebastian sebastian 4096 Jul 9 11:29 set up
drwxrwxr-x 5 sebastian sebastian 4096 Jul 9 11:31 log

The idea of dev containers is so widespread at this level that an ordinary has emerged at containers.dev. I additionally need to level out another nice sources together with Allison Thackston’s weblog, Griswald Brooks’ GitHub repo, and the official VSCode dev containers tutorial.


On this put up, you have got seen how Docker and Docker Compose might help you create reproducible ROS 2 environments. This contains the flexibility to configure variables at construct and run time, in addition to creating dev containers that will help you develop your code in these environments earlier than distributing it to others.

We’ve solely scratched the floor on this put up, so be sure you poke round on the sources linked all through, check out the instance repository, and customarily keep interested by what else you are able to do with Docker to make your life (and your customers’ lives) simpler.

As at all times, please be happy to succeed in out with questions and suggestions. Docker is a extremely configurable software, so I’m genuinely interested by how this works for you or whether or not you have got approached issues in a different way in your work. I’d be taught one thing new!

Sebastian Castro
is a Senior Robotics Engineer at PickNik.



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