Well, I spent today pounding my head against the wall that is the Beagle Board xM. I got one by UPS this afternoon, and have been trying to make a MicroSD card image for it since then. Yes, I know it comes with a test image of Angstrom, and Angstrom is what I’ll use on it, but I don’t want to connect a display and keyboard to the Beagle Board, It will be “headless” in use, so I want to do this right, by figuring out how to make the most effective MicroSD on a development system, and then plugging it into the robot.
It’s really complicated! And I don’t have “real” internet… I have satellite internet. (Remember, my top secret lair is deep in the Missouri Ozarks. Real Deep, so deep I have to have satellite internet!) So I can’t download Ubuntu all at once. LOL.
Anyway, I was pondering my predicament and I suddenly thought of something.
The common use for range detectors is to place them in a cone looking forward of the robot. I contend that that’s useless, that the info you get back is not really useful for avoiding collisions.
But. What if you oriented them to point to the sides? You’re not looking for obstacles, you’re looking for the curb, but ONLY in pipe sections where you know a curb should be on one side of the robot or the other. If your nav system is working, you should be traveling roughly parallel to the curb, making measuring it’s distance from the robot very accurate. If you knew in advance (And you do… the curbs don’t move.) how many feet you needed to be from the curb while you were traveling to the Arch, it would be easy to use a side scanning sensor to detect the curb and use that data to adjust your heading and distance from the curb.
I thought of this when I was looking at a picture of Pete Doktor pointing out the arch on the course. The curb was right there. And it was perfectly parallel to the robot’s course leading up to the arch.
Hmm. Use the terrain to your advantage. Don’t think of the course as a “black box” that you have to use a brilliant collision avoidance routine to navigate.
Oh, and of course, Once I crack the Beagle Board, I’ll post my findings.
Great idea. I agree, use whatever you can in your environment to your advantage.
I’ve been trying to figure out some way to identify features, too. Having walked the course up close and personal I was disappointed to find that the curb is not always present and when it is, it has differing heights along the way. Some parts the curb are maybe 2″ and others it is 4-6″ and others there’s a gap covered by an iron plate (drainage). It’s quite a mess.
Still, if you know a curb is present in a particular area, you could try to measure it and if successful feed that into whatever sensor fusion/filtering thingy you’ve implemented. The other trick is… curbs are (apparently) fairly hard to detect as there’s a possibility of bounceback from the ground.
One of the 2010 competitors from my robotics club attempted to measure distance to the building wall itself using a high-zoot laser rangefinder. Didn’t work very well.
That’s too bad about the curb quality, I was wondering about that from looking at the pictures. (I’ve never been to the building personally.)
That kind of unknown quantities tells me that it is indeed the core navigation ability that has to rock, and is where the effort needs to be.