Welcome to a new series - setting up the JetBot to work with ROS2 Control interfaces! Previously, I showed how to set up the JetBot to work from ROS commands, but that was a very basic motor control method. It didn't need to be advanced because a human was remote controlling it. However, if we want autonomous control, we need to be able to travel a specific distance or follow a defined path, like a spline. A better way of moving a robot using ROS is by using the ROS Control interfaces; if done right, this means your robot can autonomously follow a path sent by the ROS navigation stack. That's our goal for this series: move the JetBot using RViz!

The first step towards this goal is giving ourselves the ability to control the motors using C++. That's because the controllers in ROS Control requires extending C++ classes. Unfortunately, the existing drivers are in Python, meaning we'll need to rewrite them in C++ - which is a good opportunity to learn how the serial control works. We use I²C to talk to the motor controller chip, an AdaFruit DC Motor + Stepper FeatherWing, which sets the PWM duty cycle that makes the motors move. I'll refer to this chip as the FeatherWing for the rest of this article.

First, we'll look at how I²C works in general. We don't need to know this, but it helps to understand how the serial communication works so we can understand the function calls in the code better.

Once we've seen how I²C works, we'll look at the commands sent to set up and control the motors. This will help us understand how to translate the ROS commands into something our motors will understand.

The stage after this will be in another article in this series, so stay tuned!

This post is also available in video form - check the video link below if you want to follow along!

In this post, I'll show how to use two major concepts together:

1. Docker images that can be privately hosted in Amazon Elastic Container Registry (ECR); and
2. AWS IoT Greengrass components containing Docker Compose files.

These Docker Compose files can be used to run public Docker components, or pull private images from ECR. This means that you can deploy your own system of microservices to any platform compatible with AWS Greengrass.

This post is also available in video form - check the video link below if you want to follow along!

This post shows how to build a Robot Operating System 2 node using Rust, a systems programming language built for safety, security, and performance. In the post, I'll tell you about Rust - the programming language, not the video game! I'll tell you why I think it's useful in general, then specifically in robotics, and finally show you how to run a ROS2 node written entirely in Rust that will send messages to AWS IoT Core.

This post is also available in video form - check the video link below if you want to follow along!