Duckietown Is Full Of Autonomous Duckiebots

According to its website, the Duckietown started as a platform to teach a 2016 MIT class on autonomous vehicles. Browsing through their public Github repository it appears all logic is expressed as a ROS stack and executed on board its Raspberry Pi, no sending work to a desktop computer over network like the TurtleBot 3. A basic Duckiebot has minimal input and output to contend with - just a camera for input and two motors for output. No wheel encoders, no distance scanners, no fancy odometry calculations. And while machine vision can be computationally intensive, it's the type of task that can be dialed back and shoehorned into a small computer like the Pi.
Making this task easier is assisted by Duckietown, an environment designed to help Duckiebots function by leveraging its strengths and mitigating its weaknesses. Roads have clear contrast to make vision processing easier. Objects have machine-friendly markers to aid object identification. And while such measures imply a Duckiecar won't function very well away from a Duckietown, it's still a capable little robotics platform for exploring basic concepts.
At first glance the "Duckiebooks" documentation area has a lot of information, but I was quickly disappointed by finding many pages filled with TODO and links to "404 Not Found". I suppose it'll be filled out in coming months, but for today it appears I must look elsewhere for guidelines on building complete robots running ROS on Raspberry Pi.