Using a Personal Computer

Skip this page if you’re working on a lab computer.

If you wish to work on the exercises outside the lab, this page helps you to set up the lab workspace on a personal computer.

Requirements

Operating System

Any recent release of Ubuntu (20.04 Focal and later) is recommended.

Other Linux distributions, particularly Ubuntu-based ones like Linux Mint or Pop!_OS, can also be used. However, specific instructions or support for these or other distributions are beyond the scope of this course.

Softwares

Git - apt install git
Docker - documentation
Visual Studio Code - website
- Dev Containers Extension - website
- Docker Extension - website
Additional packages for using GPU - next section

Note

Make sure to also follow the post-installation steps for Docker.

GPU Acceleration (Optional)

The base configuration, 467-base, utilizes either the integrated GPU or no GPU at all, depending on the processor for graphics applications (e.g., Gazebo and RViz). However, it is compatible with a wide range of computers.

Simulation performance can be significantly enhanced by using a discrete GPU if your computer supports one.

NVIDIA GPUs

Install NVIDIA Container Toolkit on the host operating system by following the steps from documentation.

Then use the 467-nvidia-gpu configuration when starting the Dev Container.

AMD GPUs

Install AMD ROCm software on the host operating system by following the steps from documentation.

Then use the 467-amd-gpu configuration when starting the Dev Container.

Starting the Container

They’re similar to the steps shown in the this page. Use any of the 467-<gpu-config> configurations when reopening the workspace folder in container. The quickest way to get started is to use the 467-base configuration.