This repo contains a basic library of python objects and scripts to make development on the Small-Vehicles-for-Autonomy (SVEA) platform simpler and cleaner.
The design principle of this library is to help create projects that are more modular and easier to troubleshoot. As opposed to the standard approach of creating a large web of Subscriber/Publisher nodes, we modularly wrap different ROS entities in Python objects, while exposing only the useful features with object-oriented interfaces.
Before continuing to the next sections, consider taking some time to read up on two important concepts for this code base: the Robotic Operating System (ROS) and Object Oriented Programming (OOP).
To read up on ROS, check out the ROS Start Guide. However, do not spend too much time diving into the guide. The structure and tutorials are not very intuitive, but glossing over them will give a sense of what ROS is and how you are meant to use it. The rest of the learning curve is overcome by trying it out yourself.
To read up on OOP, check out Real Python's introduction on OOP.
In the instructions below, we describe the system requirements, installation process, and run instructions using Docker. If you want to set up this code base natively, then check out our Building the SVEA Stack Natively instructions.
For the instructions below to work, you need to first install Docker Engine.
For Windows users, you will need to first install WSL 2 and set it's distribution to Ubuntu (either 18 or 20). Use the commands listed here to "Install", "List available Linux distributions", and "Set default WSL Version" to Ubuntu 18 or 20.
To install Docker Engine, follow the instructions for your operating system here.
Start by going to the folder where you want the code to reside. For example, choose the home directory or a directory for keeping projects in. Once you are in the chosen directory, use the command:
git clone https://github.com/KTH-SML/sveato download the library. Then, a new directory will appear called
./svea. Go into the directory with command:
cd sveaTo install the Docker image containing the entire codebase run:
util/buildIf it all runs without an error, you have installed the Docker image!
Although this code base supports matplotlib and rviz, the main visualization tool used is Foxglove Studio. To install Foxglove Studio, follow the instructions for your operating system here
Note: alternatively, you can use the Web version of Foxglove Studio which is also available from the installation link.
The intended workflow with the code base is as follows:
- Write new features/software
- Debug the new contributions in simulation
- Perform basic tuning and adjustments in simulation
- Evaluate actual performance on a SVEA car
The simulated vehicles provide identical interfaces and information patterns to the real SVEA cars, thus by following this workflow, development work should always start in simulation and code can be directly ported to the real cars. However, this does not mean the code will work on a real vehicle without further tuning or changes.
There are pre-written scripts to serve as examples of how to use the
core library. See and read the source code in
svea_examples/scripts.
Start by entering into the installed Docker image by going to the root of svea
and running
util/run-devThen, for a simulated, pure pursuit example, call:
roslaunch svea_examples floor2.launchThen, open Foxglove Studio natively or in the browser, and on the first prompt
click "Open connection", then click "Open" with the default settings. Next,
click on the "Layout" dropdown menu and select "Import from file...". Finally,
navigate to svea/foxglove and select Floor2 Pure Pursuit.json. After it
finishes loading, you should see something that looks like this:
Now you are ready to read through the tutorials! You can find them here.
Note, you only have to follow this section when running the real cars!
To your roslaunch file, add
<!--open serial connection for controlling SVEA-->
<node pkg="rosserial_python" type="serial_node.py" name="serial_node">
<param name="port" value="/dev/ttyACM0"/>
<param name="baud" value="250000"/>
</node>Running the localization amounts to adding localize.launch to your project launch:
<include file="$(find svea_sensors)/launch/localize.launch"/>Instead of using util/run-dev, which is intended for development environments
and simulation, to access all hardware on the real SVEA you must start
a container with the priviliged run script:
util/runAfter cloning the repository, you can open the core library's documentation by opening docs/library/_build/index.html in your favorite browser.