It's officially the Fall 2016 semester of the GT OMS CS program, and this is a big one - Artificial Intelligence for Robotics. I've been looking forward to this class for years. The course is taught by Sebastian Thrun, who headed up the Stanford team that won the DARPA Grand Challenge and came in second in the DARPA Ubran Challenge. The Grand Challenge robot "Stanley" found its way into the Smithsonian National Air and Space Museum for that, and Thrun himself went on to head up the Google self-driving car project. So the course pedigree is solid, to say the least.
I've been fascinated about autonomous robots since I watched the PBS Nova episode "The Great Robot Race." Looking back on it, this show is partly responsible for my being in graduate school at all right now. Programming had become less exciting - it seemed more like plumbing than like problem-solving, and I was wondering "what next?" (No offense to plumbers, actually. It's just not what I find exciting.) And then there was this inspiring show about solving these crazy fuzzy problems with this insane, wonderful fusion of hardware, software, and math and, well, I loved it. It confirmed to me that there was more to learn, and that's always good.
The course focuses on software, on the AI side - things like Bayes Rule and Kalman filters. There's a reason I work on the software side of the world and didn't become a mechanical engineer instead. But... There's no way I'm getting out of this class without building a physical robot. That's not my style. So I've got a couple projects ahead of me, it seems. Stay tuned for discussions of the hardware chosen, the project goals, and progress updates.