Slashdot is powered by your submissions, so send in your scoop


Forgot your password?

Inside DARPA's Robot Race 135

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."
This discussion has been archived. No new comments can be posted.

Inside DARPA's Robot Race

Comments Filter:
  • by rob_squared ( 821479 ) <.moc.derauqs-bor. .ta. .bor.> on Wednesday March 29, 2006 @01:31PM (#15018921)
    I remember an old nova special about self-navigating robots, and at first it took about a day to cross a room.

    But mostly these robots depend on the assumption that everything remains still.
  • by Anonymous Coward on Wednesday March 29, 2006 @01:31PM (#15018927)
    Unlike Carnegie's "H1ghlander" and "Sandstorm", Stanford's "Stanley" VW Touareg had no fancy motion compensated sensors and the team didn't flesh out the race course with more GPS data and tell the vehicle how fast it could drive in certain areas. Stanley's software did all that on the fly.

    Also, the SuperDAD Toyota pickup looked like it had a tenth of the tech of Stanley but it was doing almost as well. If only the laser sensor hadn't detached itself from the roof.
  • by hackstraw ( 262471 ) * on Wednesday March 29, 2006 @01:37PM (#15018980)

    I will say, I was impressed, and surprised that I did not see an article on it at /.. I believe there was one last year.

    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.

  • Seen it-One eyed. (Score:2, Interesting)

    by Anonymous Coward on Wednesday March 29, 2006 @01:38PM (#15018984)
    The interesting thing for me is that the method we use (our eyes) was too difficult for machines. That's why all those robots used lasers, and other techniques. We've come far, but we still have a long way to go.
  • Re:Great show but... (Score:2, Interesting)

    by Machina Fortuno ( 963320 ) on Wednesday March 29, 2006 @01:53PM (#15019113)
    I love PBS documentaries man. You can learn sooo much from them in a nice little narrated package.

    Maybe all these guys are geniuses and get grants to work on the stuff. Maybe university supported or something like that. Or! They make their money in half a year, and build robot cars the rest of the time.
  • by Jett ( 135113 ) on Wednesday March 29, 2006 @01:54PM (#15019121)
    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.

  • by Anonymous Coward on Wednesday March 29, 2006 @02:19PM (#15019323)
    Last Saturday, Digital Village Radio [] did an interview with Jason Spingarn-Koff, the filmaker of The Great Robot Race, and Sebastian Thrun, the leader of the winning Team Stanford. Here's a link to the mp3 [].
  • but would it work? (Score:3, Interesting)

    by lardlad ( 959872 ) on Wednesday March 29, 2006 @02:25PM (#15019370)
    So DARPA funds this to create autonomous supply vehicles, which might work in a traditional battle with clearly drawn front lines and relatively secure transport routes behind the lines.

    It seems to me like 21st century warfare is a whole different animal - how hard would it be for a motivated, talented individual to figure out some simple attacks for the navigation systems on these vehicles, and get loads of sweet US munitions delivered to their doorstep? How effective would one of these vehicles be in an urban setting? How easy would it be to create a series of obstacles that would paralyze one of these vehicles?

    It's amazing technology, for sure, and the Stanford and CMU teams deserve kudos. I'm just concerned that with the current rush to technological solutions and shift away from "boots on the ground", this technology will be in battle zones far too quickly.
  • Re:Great show but... (Score:2, Interesting)

    by Anonymous Coward on Wednesday March 29, 2006 @03:25PM (#15019892)
    To answer your question regarding who owns what. I can't speak for the large University teams because they are just in a different universe as the rest of us were. Most teams didn't bother filling out patents because we were all just too damn busy. What we do rely on is our IP though. I was on a finalist team and we did write some pretty cool software that we are trying to do some stuff with on another project now. We own all the code (we wrote it). CMU and Stanford are a different beast altogether. I assume the university owns much of the code that they wrote. But really that's not a big loss for them, if it wasn't for the threat of DARPA taking contracts somewhere else that Stanford and CMU already had ( before the race was ever announced ) they wouldn't have even competed. They were competing to save their contracts, not for the money or to do something *neat*. Of course I am a little biased. I was on a small team with the only funding coming from our own pockets. We worked our day jobs and spent all night working on the vehicle. Even during the qualifying we were soldering boards in the motel that night. I'll admit, I wish I had a team of VW engineers working on a vehicle they designed and giving us all the I/O info needed to use the onboard vehicle computer directly.
  • by c41rn ( 880778 ) on Wednesday March 29, 2006 @04:59PM (#15020678)
    If I remember correctly, the object sensors on these 'bots can not distinguish between a solid, impassable obstacle and a harmless bunch of scrub that could be driven through. Assuming this is true, couldn't you create a 'wall' out of bedsheets or some other cheap material and box one of these vehicles in very quickly. Once disabled (confused), you could unload the supplies or damage the vehicle.

    This is just conjecture based on a half-recollection but I don't thik it would be too difficult to attack a relativly slow moving, unarmed autonomous vehicle such as demonstarated by the Grand Challenge vehicles which are at the state of the art.

  • by Yokaze ( 70883 ) on Wednesday March 29, 2006 @05:13PM (#15020796)
    > Now once at Stanford they changed how they did things entirely and wrote a ton of code to make everything play much nicer than CMU's platform.

    This sounds a little bit more like that, what I have heard. I've read, that they throw away most of the code and rewrote a large deal. E.g the classification of driveable terrain by the laser scanner was rewritten and learned. AFAIK, most of what has been published (and to what you pointed) is fairly generic stuff.

    To the best of my knowledge [], it has not been published how they learned the far range vision based on the near range laser scanner, which, to my eyes, is the most interesting part of the project.

    > Nice try, I wasn't on CMU either.

    Well, the comment on Sebastian Thruns previous affiliation and the code development sounds like something Mr. Whittaker could have said. But from what I've heard, he followed a fully stochastically approach and less reliance on the physical stability of the sensors and GPS, which AFAIK was quite different to the Red Teams approach and resulted in a much smaller code base.

  • Re:Seen it (Score:3, Interesting)

    by vistic ( 556838 ) on Wednesday March 29, 2006 @05:35PM (#15020997)
    I caught the show yesterday also.

    I was really happy Stanford won the competition. The "red" team with two entries (from Carnegie Mellon?) also finished but were behind on time... the thing is though not only was Stanford's win absolute, they also did it much "smarter".

    Stanford took an approach of focusing on software, to make their vehicle more smart. They gave it the course, but left it up to the vehicle to decide how fast to go and the specifics of how soon to turn, etc.

    Meanwhile Carnegie Mellon took the approach of focusing on hardware, and it took them something like 2 hours to go over the course and specifically map out a path for the vehicle to follow and the speed it should take (as opposed to I think they said 27 minutes to just give the course details to the Stanford vehicle). Carnegie Mellon had a team of at least a dozen grad students figuring it all out.

    So I was much happier with Stanford's win, it seemed like more of an accomplishment.
  • by Anonymous Coward on Wednesday March 29, 2006 @07:55PM (#15022095)
    A bit torrent link to "Why We Fight". []

    Purchase this movie if you at all enjoyed it. That is your civic duty. True

The intelligence of any discussion diminishes with the square of the number of participants. -- Adam Walinsky