The goal of this repository is to maintain a collection of Dockerfiles that can be used for the different projects in RCDT.
Docker enables easy creation of complete system images. This simplifies the installation process of all the software required in a (robotic) project and ensures consistency between different users/devices.
Follow these instructions to install Docker Engine in your Ubuntu system (also when using WSL):
https://docs.docker.com/engine/install/ubuntu/
Next, add yourself to the docker group to avoid the use of sudo when running docker commands:
https://docs.docker.com/engine/install/linux-postinstall/#manage-docker-as-a-non-root-user
The installation is successful when the hello-world example is working without sudo.
If you have an Nvidia GPU, follow the "Installing with Apt" instructions to install the NVIDIA Container Toolkit:
Next, configure docker by following these two steps:
Finally, you can test whether the installation was successful by running the nvidia-smi command in docker:
To run a docker image, simply execute the run script when located in the main directory of this repository:
. run
A menu will appear where you can select one of the images located in the dockerfiles directory of this repository. If the image is not installed yet, it will ask you to install the image. If the image is already installed, it will run the image for you. To enable GPU output, the script automatically gives access to xhost when starting an image and removes this access when the image is closed.
It is recommend to use vscode for code development in combination with the docker images. It is possible to "attach" to a running docker image in vscode using the "Dev Containers" plugin:
https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers
With this plugin installed and a docker image running, it should be possible to attach to this container by click on the "Open a Remote Window" button (blue button at the bottom left corner in vscode). This should give the option to "Attach to running container...".
A new vscode window should be opened where the docker container is used a system. This means that vscode should be able to find all (ROS) packages installed in the container.
When developing in Python, it is also recommend to install the "Ruff" plugin:
https://marketplace.visualstudio.com/items?itemName=charliermarsh.ruff
This plugin enables linting (code style and quality checks) and formatting. The rules for this are automatically installed in the docker images as a file called "pyproject.toml" in the home directory. Ruff should be able to detect this file and follow the rules without further configuration.
This project is licensed under the Apache License Version 2.0 - see LICENSE for details.
Please read CODE_OF_CONDUCT, CONTRIBUTING, and PROJECT GOVERNANCE located in the overarching RCDT robotics project repository for details on the process for submitting pull requests to us.