Arduino Forum

Topics => Science and Measurement => Topic started by: Frederic_Plante on Sep 17, 2016, 06:28 pm

Title: Force module, Newtonian physics, Galilean refencials. Classical physics?
Post by: Frederic_Plante on Sep 17, 2016, 06:28 pm
Doing those gravity force calculation(g), it's all very nice, but the fact is we don't know the masses of the mobiles, so all these don't mean much and in the real world. The fact is we are calculating the acceleration.

Newtonian physic is richer then simply calculating a gForce. With very little math, we can also calculate speed and position with kinda great accuracy, by using a Galilean referential and differential/integral calculation.

We live in a classical world, on the daily basis, so I'm pretty sure that we could get more from these module then just knowing that, I'm turning and the gravity is pointing this way. I got the calculus under hand and I would be pleased to take the challenge of making a smarter library, but this is not the kind of thing that can be done alone.
Title: Re: Force module, Newtonian physics, Galilean refencials. Classical physics?
Post by: jremington on Sep 17, 2016, 08:41 pm
Yep, agreed, classical physics all the way!
Title: Re: Force module, Newtonian physics, Galilean refencials. Classical physics?
Post by: Frederic_Plante on Sep 17, 2016, 10:20 pm
Ok then, if there is interest, let's start by choosing a standard chip, I have a few kind digital and analog output, to collect raw force data, then we can put them in some equation, code, to start with.

2aΔs= vf2 - vi2


vi2= vf2 - 2aΔs


vf2 = vi2 + 2aΔs


Δs= (vf2 - vi2) ÷ 2a


a = (vf2 - vi2) ÷ 2Δs


Where a is the acceleration, Δs the space within where a happen, vf the final velocity and vi the initial velocity.

From those simple elements, we can deduce lots of stuff.
Title: Re: Force module, Newtonian physics, Galilean refencials. Classical physics?
Post by: MarkT on Sep 24, 2016, 09:31 pm
MEMS accelerometers are hopeless for inertial guidance as they are too inaccurate and noisy.  Position
is the double integral of acceleration and that just drifts more and more with time.  There are ways to
compensate for drift if you have more information sources though.  For short term movement like
gesture recognition drift isn't an issue though.

And of course you need all 6DoF for any of this.