Installation
This page details the instructions to install the Unified Autonomy Stack.
The instructions explain how to setup the entire stack to use in your work or run the provided demos. Further details about the structuring of the stack can be found on the Deployment page.
Requirements
Computer requirements
The stack has been tested on Ubuntu 20.04 and 22.04. As the stack includes learning-based navigation modules, an Nvidia GPU is required to run those.
Docker
The stack is organized as a collection of docker containers, hence, first install docker using the instructions on the official webpage.
Docker configuration
Configure the /etc/docker/daemon.json as follows:
Note: Do not use "nvidia" as the default run time as this may cause issues with some of the packages.
Add the following line to ~/.bashrc or ~/.zshrc:
Install other dependencies
Unified Autonomy Stack Installation
Clone the required packages
Clone the base repository:
Clone individual packages:
cd unified_autonomy_stack
mkdir workspaces
./scripts/import_all_repos.sh # recursively clones all the repositories
Note: Cloning all repositories will take some time (especially ws_sim.repos), please be patient
Generate docker images
Note: Building the images for the firs time will take some time, please be patient
Build the code
There are two ways to build the code:
Option1: Build all workspaces in parallel. This method is faster but it can be tedious to see the output of individual workspaces.
Option2: Build one workspace at a time. This method is slower but easier to track the output of each workspace.
Note: If you are building the stack on a low ram computer, it is advised to use Option2 as it will not make the ram fill up causing the build to fail.
Configure ROS_DOMAIN_ID
Set the variable DOMAIN_ID in the unified_autonomy_stack/.env file