Let's Make Robots!

LMR's & Coursera

Wondering how many LMR's are doing the coursera " Control of mobile robots" course. I have been blown away with the global response to the course. It's my first involvement with such a course.I last attempted matices & eigenvalues over 45 years ago. Bit of a challenge now but managing 90 % at the moment. Really adds another dimension to thinking about projects.

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My sense of the culture here is that we shouldn't talk about 4Cs--but this video offers good examlses of feedback control.

http://www.youtube.com/watch?feature=player_embedded&v=C4IJXAVXgIo

There's been plenty of worry about the math on the discussion forum for the class. I'm in the same boat. I forgot all about this stuff years ago. 

Still, I took this class to shake the cobwebs off my grey matter, so I'm sticking with it. Just completed the week 4 quiz and got 100% on the 2nd try. The professor said the math will get lighter from here. I hope so.

In other news, I've decided to use a Rocket Brand Studios Tadpole as a test bed for the class. I should roll up my sleeves and learn MATLAB, but I'm much happier working with real hardware. I just got PID feedback working for the encoders. I totally used trial and error to pick the gains. Maybe one day I'll be able to figure the calculations out to do it "right".

I will post posted my code on a Robot page soon for anyone who wants to follow along. 

When I did my associate diploma of electronic engineering I had a teacher who was a theoretical physicist from England. He made the math twice as hard as it needed to be just to keep himself entertained and lowered the pass mark from 90% to 60%.

I managed to get 70% after a late night study session and a few hours sleep.

In his classes I learned all about differentiation, intergration, matricies etc. For everyday electronics and robotics I have never found a need for that stuff. Simple trigonometry and some boolean logic was all I have ever really needed. 20 years later I have forgotten it all.

I suppose what I am saying is don't worry too much if you can't get through the math. Unless you need to calculate the precise trajectory and amount of fuel required to land your robot within a 1Km square target zone on Mars after performing a slingshot maneuver around the moon with a slight detour to visit Haley's commet then the math is not that important.

According to Sheldon: Don't compare a theoretical physicist to a rocket scienctist. Apparently rocket science is no harder than asking a customer if they want fries with their order.

That's what I love about OpenX communities. We don't judge whether someone is able, whether ourselves or others, until they try. Or as an old economics professor stated, "In the Google age the barriers to an education are merely lacking a pc, Internet, and a hearty disregard for someone saying you can't." Being delusional about my limitations has always served me well. :)
The math is required for the modeling that is required at that level I guess. Like Ladvien says, it makes sense on one level so far but the next level(s) are way beyond me and what I even want to know. Maybe that's why Henry Ford named his car a Model "A" - it was the first attempt ;-) I'm just a trial and error... And error... And error.. Kind of guy I guess. Stephen

Thought I got it - until I made the first test. Now I am a watchmen - like TinHead, Isotope and Ladvien. 

I must admit that whenever you want to build a robot that has kinematic abilities it is very useful to have calculus and higher order differential equations at hand to roll-your-own PID controllers. I still want to get better interpreting and inventing these formulaes. 

But the level of mathematics in this course is very high. No time to work from simple calculus basics. You must be fluent in calculus and equation solving to be successful. Second order Taylor Aproximation. Laplace Transformation. Binominal Series of higher order differential equations. Quadratic extensions and other tricks to make an implicit formulae to an explicit formulae. The list of necessary skills goes on and on. :-)

 

You can adjust the parameters of a PID controller for simple things like steering by trial and error. Typically, start with P and find a value that gets a response. Usually, whatever you're controlling will overshoot and oscillate aboout the target position. Introduce a small negative D component and increase it until the oscillations stop. Everything should now work well, except that your device doesn't quite reach the target position, there's always a small offset. Fix that by introducing a small I coefficient. Try a few values.

When adjusting the parameters, at first, don't use small steps. Double or halve whatever you're adjusting.

You need to be able to dump a trace of what the controlled parameter (heading or whatever) is doing, compared with what it should be doing. Plot the results in Libreoffice or Excel. It's much easier to sort out what's happening by looking at a chart than by watching a robot careering all over the place. If you can dump some of the intermediate results at the same time, that will help with debugging.

Guys, you're not alone! :))

I'm there too, and my brain hurts whenever they show all this formulae and matrices and stuff. Also I'm, similarily as Ladvien, taking Calculus One course at the same Coursera. I still find the course very informative and helpfull! :)

I understand most of the concepts intuitively, but I'm embarrassed to say, I'm in the same boat as TinHead.  I've already gotten  some Cal for Dummies books to try keep up.  I wish there were more "pseudo code" examples, those I can follow fairly well.

It's interesting but the math is way over my head :/ Still nice to watch.