New Addition To TurtleBot 3 Manual: TensorFlow

TensorFlow LogoBeing on the leading edge carries its own kind of thrill. When I started looking over the TurtleBot 3 manual I noticed the index listed a “Machine Learning” chapter. As I read through all the sections in order, I was looking forward to that chapter. Sadly I was greatly disappointed when I reached that chapter and saw it was a placeholder with “Coming Soon!”

I didn’t know how soon that “soon” was going to be, but I did not expect it to be a matter of days. But when I went back to flip through the material today I was surprised to see it’s no longer a placeholder. The chapter got some minimal content within the past few days, as confirmed by Github history of that page. Nice! This is definitely a strength of an online electronic manual versus a printed one.

So it’s no longer “Coming Soon!” but it is also by no means complete. Or at least, the user is already assumed to understand machine learning via DQN algorithms. Since I put off my own TensorFlow explorations to look at ROS, I have no idea what that means or how I might tweak the parameters to improve results. This page looks especially barren when compared to the mapping section, where the manual had far more information on how the algorithm’s parameters can be modified.

Maybe they have plans to return a flesh it out some more in the future, which would be helpful. Alternatively, it’s possible that once I put some time into learning TensorFlow I will know exactly what’s going on with this page. But right now that’s not the case.

Still, it’s encouraging to know that there are documented ways to use TensorFlow machine learning algorithms in the context of driving a robot via ROS. I look forward to the day when I know enough to compose all these pieces together to build intelligent robots.

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