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Inside DARPA's Robot Race
Belfegor writes "The PBS series Nova has a great feature on their website, regarding the coverage of the DARPA-sponsored 'Robot Race' in which driverless vehicles 'competed' in a 130-mile race across the Mojave Desert. The full show is available on the website, and besides that they have plenty more information about the robotics behind the challenge, and also some pretty cool out-takes from the show."
PBS broadcast that show last night. While I realise that is is a little 2001 to actually watch a program when it is braodcast, I did. And I really enjoyed it. I am hardly current on the status of autonomous robotics and I was pleasantly surprised by how far along the technology is. 130 miles through the dessert using only GPS and local sensors is a pretty amazing feat, and that course was tough. It features mountain switchbacks, tunnels and other hazards. If you even have a passing interest in robotics I recommend watching the show.
it is interesting just how involved the contestants are. This contest is their life. They mentioned several times in the show how many months of long workdays they spent to build and program these cars. And, then, who owns the work? Do they at least get patent recognition on some of the innovations? Some of the software they talked about was truly seriously cool stuff.
Sidenote: One hour of Nova or Frontline is like watching 5 days worth of "learning" and "discovery" shows elsewhere. It's amazing how good some of these shows are.
I will say, I was impressed, and surprised that I did not see an article on it at
I will say, that aside from "Stanley" winning the race on completion and time, I also believe that Stanley was the best technology. The H1lander and friend were micromanaged, and there were two vehicles that had different strategies (the tortoise and the hair) and it took almost the whole 2 hours of a team of people to map out the course and program the robots. They then added the fudge factor for human error with the fast and slow strategies.
Stanley was programmed in minutes of receiving the map, and it calculated its speed dynamically on its own. Stanley had "adaptive vision" which overlaid laser, video, and other sensory data to create a dynamic field of view of what was safe to drive through.
Now, what shocked me, was that so many teams finished this year. Nobody got past 7 or 9 miles last year, and many vehicles passed the entire 132 mile trip this year. Watching the vehicles drive was impressive. Most of the time, they appeared to be manned.
The course was not easy, by any stretch of the imagination. With the success of Stanley, I believe that this will increase the adaptive and learning capabilities in current software controlled systems. Currently, software is brute forced into trying to accommodate all possible logical conditions, which is impossible, and often just wrong.
http://www.mininova.org/tor/266446
I hadn't heard about it being for an autonomous gun platform. I watched the show last night and they presented it as purely for supply transports. They specifically mentioned Jessica Lynch and how she was just a truck driver who should never of been exposed to combat. They also mentioned that the DOD want's 1/3rd of their transport trucks to be autonomous within 10 years.
What do you do in the future when one of these is mass-produced and forgets its turn signal and cuts you off?
Do you scream and give it the finger?
Throw rocks at it?
Run it off the road?
Launch a homing missile at it?
Any way around it, driverless vehicles will have no rights in our future society!
Who will speak up for the robots?
He who knows best knows how little he knows. - Thomas Jefferson
Do a google search on Sabastian Thrun, he was the team lead for Stanford, and formally at CMU (what a non-coincidence). Most of the software they used on Stanly (Stanford's bot) was either written by Sebastian in his former research or taken from experience gained on CMU's team the previous year. The ladar mapping he used, I know I saw on some former page of his that had all the gory algorithm details. It might just take a little bit of searching. He also has a c library out there somewhere that does a lot of this stuff, but I can't seem to find it now.
u blic_html/papers/thrun.ces-tr.html (sorry, no linky, writing in a hurry)
/ bfl-trunk/
h tml
One paper that's of interest might be here: http://www.cs.cmu.edu/afs/cs.cmu.edu/user/thrun/p
And that paper is mentioned in the readme of the BFL (Bayesian Filtering Library) found here:
http://people.mech.kuleuven.be/~kgadeyne/software
Lastly, at one point all of us competitors were required to give our design documents to DARPA, and they put them up on their webpage here:
http://www.darpa.mil/grandchallenge05/techpapers.
BTW, I wasn't on Stanford's team, but I was on another finalist team.
"We need a fourth law of Robotics: Stop Fingering My Wife"