A co-worker brought in his Segway yesterday, so I had to take the opportunity for a photoshoot with my balancing robot Gizmo and his bigger cousin.

I took my inverted pendulum balancing robot, added a camera and wireless transmitter, and let everyone around the office take a spin. The event was not without mishap, but it’s a lot of fun to watch people interact with the robot, and not so much fun when they try to block it’s view, or just don’t get out of it’s way. Or they kick volleyballs at it. That’s just mean.

I added feedback from the motor encoders this week, which allows the robot to know that it is moving. Previously it only knew it was tilted, so it wanted to run away if it was only tilted slightly. I also wired up the batteries, which were salvaged from a less-than-optimal dell laptop battery. I’ve still got some work to do, but the velocity feedback is now countering it’s tendency to run away. The center of gravity is still really low (I’m waiting for mounts to get made to move the batteries up to the top), so it can still outrun itself really easily. Next on the list is to add control from the PC via the bluetooth module that is currently attached.

This is the beginnings of a robot I’ve been working on. Katie named it Gizmo. Eventually, it will be a two-wheeled balancer and stand up like this on its own. The picture is a little deceiving, the wheelbase is about 14" and it stands 24" high. The electronics for this are almost complete, it will be gyroscope stabilized like a Segway and eventually roam around on its own avoiding obstacles. This hardware is a quick hack so I can get started on the software, at some point the hose-clamp motor mounts will be replaced by something more permanent.

Lemonodor took the info from this Carnegie Mellon page and turned it into a Google Earth KML file. If you save that page as a .kml file, and open it with Google Earth, you’ll get a nice track of the course route.

Lemonodor doesn’t claim this is the official track, and personally I hope its not—it is way too fine with respect to detail. If this is the course the ‘bots ran, and they had waypoints this close together, I’m amazed that more didn’t finish. Without too much AI, and with much more GPS-connect-the-dots, this course is very doable. My feeling is that the actual course is closer to that seen on the CMU website, which has points separated by a bit, with hard-core navigation between the points necessary by good AI. Maybe someone will release the official route soon.

Stanford’s autonomous robotic vehicle ‘Stanley’ took home the $2-million first prize in the DARPA Grand Challenge. Traversing the 131.6 mile course in just under 7 hours, Stanley beat out both teams from Carnegie Mellon University, H1lander and Sandstorm, by over 10 minutes. only 15 minutes behind the lead pack at 7.5 hours was the Gray Team’s KAT-5, so named because the team’s home of Metarie, LA, just outside of New Orleans, was damaged by hurricane Katrina. The Oshkosh Truck Company’s entry TerraMax was allowed to complete the course this morning, and was the only finisher that crossed the line beyond the 10-hour time limit, at almost 13-hours moving time, and over 26 hours on the course (the ‘bot was paused a number of times because of course obstuctions, and spent the night paused on the course).

With a great deal of respect for the teams that competed, I will have to say that while I am excited that 5 teams were able to complete the course, it seems like the course was a good deal less complicated than last year. There were a number of obstructions, including tunnels, high-tension power line towers, and a precarious mountain pass, but a great majority of the time the vehicles were on ground that a compact sedan could traverse. I think that DARPA did a good job of making certain that at least a few of the teams would finish, after last year’s PR nightmare when the best contender only travelled 7.5 miles. But, I have to ask, was this really a Grand Challenge, or was it more of a task tailored to the capabilites of the vehicles competing? Regardless of the answer, it is poingant to note that DARPA managed to get tens of millions of dollars of research and development from a few million investment by putting on the Grand Challenge. And, knowing DARPA’s history of return on investments (their motto is to go after high-risk, high payoff research), this may have been their best turn-around yet.

Katie and I are leaving in about an hour to head to Primm, NV for tomorrow’s running of the DARPA’s Grand Challenge. You can track the vehicles, if you so desire, via grandchallenge.org starting at 6:00AM PST tomorrow morning. This year, there are a few very promising entries, with Carnegie Mellon’s Red Team holding the pole position, just in front of Stanford’s entry named Stanley, followed closely in third by Carnegie Mellon’s other entry, the modified hummer that went the farthest in last year’s race. Depending on the availability of internet in Primm, pictures will be forthcoming as soon as possible.