The Kobuki charger costs an extra $49 when you buy the Deep Learning Robot and is well worth throwing into the package. With a few simple commands you can get your robot to dock and recharge itself, providing it is in the general vicinity of the charging station. The following is adapted from the Kobuki / ROS tutorials.
Here’s a video of docking place in my crowded living room. Please forgive the baby noises:
Getting your robot to obey “Go to the kitchen” seems like it should be a simple problem to solve. In fact, it requires some advanced mathematics and a lot of programming. Having ROS built into the Deep Learning Robot means that this is all available via the ROS navigation stack, but that doesn’t make it a set-and-forget feature. In this post, we’ll walk through both SLAM and autonomous navigation (derived from the Turtlebot tutorials), show you how they work, give you an overview of troubleshooting and outline the theory behind it all.
Once you’ve completed the missing instructions for your Deep Learning Robot to get the various “Hello Worlds” running, you’ll soon want try using some of the ROS visualization tools. To do this, you’ll need ROS installed on a laptop or workstation and get it networked with the robot. The Turtlebot tutorials do describe this, but I ran into various issues. Hopefully, this guide will help others who tread the same path.
This is the setup we’re shooting for:
