Video: http://www.youtube.com/watch?v=l1Qk2YPdCY8
Hi All,
So, here’s are preliminary traction control demo. Don’t mind the flooring or the two very dillusional people muttering away.:ahh:
Cheers,
M_M and JNo.
Video: http://www.youtube.com/watch?v=l1Qk2YPdCY8
Hi All,
So, here’s are preliminary traction control demo. Don’t mind the flooring or the two very dillusional people muttering away.:ahh:
Cheers,
M_M and JNo.
That’s pretty neat. Quite cool.
How are you guys detecting a loss of traction? Encoders are my only guess…
-Tanner
Yep, there’s an encoder in the system. Actually there’s two, and some secret sauce.
It’s amazing how 2 years of kinematics can actually be applied to real life.
And no, there’s no accelerometers, or idle wheels.
M_M
Wow, very amazing guys. I’m not even sure how we would do that…
Thumbs up to ya’ll! Good luck with it.
-Tanner
Thanks!
You too.
M_M
That’s sick.
Someone deserves a high five.
High Five
Care to elaborate on the mechanics and the programming theory behind it?
Already Done.
Helloooo from the North East:D
Oh Boy that is a great job… DRIVE the bot and lots of great times will be ahead for your Team …:yikes:
GOOD LUCK in 2009;)
MOE and Team 88 TJ2 TYE DYE for ever oh yeah ??? OH YEAH !!!:o
Well, I’d love to tell you all exactly how this was pulled off, but I’m honestly not sure how much detail I"m allowed to reveal. (We haven’t had a discussion with the team about this yet, so I don’t want to jump the gun.)
Here’s what I can tell you though:
That video is no where near the final product btw. We have to calibrate and optimize for the playing surface and the weight of the trainer.
Anyway, I’ll tell you what I can. Please feel free to ask quesitons. If anyone can guess what we did I’d be happy to PM you with our solution. It can be a game of sorts.
BUT, I’ll probably have a white paper drawn out by our first regional (Toronto) and it’ll be posted for all to see.
M_M*
I’m glad to hear that you won’t be littering the field with wheel spinach. I don’t think the Swifter would be much help in cleaning up that kind of mess!
Seriously, that looks like a really good traction control system. From the demo it looks like the robot is a lot easier to push around with the system turned off. Is that true?
Great Job Team!!
Very Impressive
This is the most efficient and incredible traction control system our team has ever seen. We would like to use the encoder as well to assist in our traction control. Can you help us?
Sure, what do you want to know?
wow guys well done…
Is there any way you guys can share that and help us out?
We would like to use the encoder to measure the rotations of the wheel per second then multiply by the radius of the wheel in order to find the distance the wheel should be traveling (theoretical distance). Then we would use another sensor to measure the distance our robot has actually traveled. If the actual distance is less than the theoretical distance our wheel is slipping. Do you have any suggestions on the sensor we should use to measure the actual distance traveled or any suggested code we could use in order for the change in speed of the motor, in turn lowering or speeding up the rev/sec., to be automatic?
that robot looks a whole lot better than my team’s rookie bot
Does your ystem work for acceleration as well, or just shoving? It would be nice to see a comparison of acceleration with and without TC. The pushing thing–it looks nice, but have you collected more empirical data than “he stumbles back more with traction control on”?
Really impressive - I’m really looking forward to watching these bots in action! In what language did you implement the traction code?
If you listen to the audio on the video you can hear the traction control at work. With the TC off you can hear the motors whirring away and the wheels spinning even when the robot is held stationary. With the TC on you can hear that the sound is very different, the wheels are not spinning even though the robot is being told to go forward, but held from doing so.