Congratulations !

Kiedro · Joined: 08 Mar 2006 Posts: 81

Here is a code snippet for differential ADC on an AT128 - AT2560 is similar:

Matrixx · Joined: 30 Nov 2005 Posts: 158

Thank you Kiedro,

I have been reading the M2560 datasheet and dig some on differential inputs. I'm kinda slow to understand Embarassed

However I don't see how I will use differential input on Gyro signal as it is singe ended. I mean the gyro axis output is going from say 0.9V to 1.6V so there is no differential output.

Maybe if I put a load resistors and attach the diff inputs to the ends of one of them..? and set gain of 200?

Or using a opamp.

Well, Looks my budget is geting fine so I will order some low scale gyros from sparkfun. I'm in doubt to order 30deg/sec or 60deg/sec gyros. I think a gyro under 100deg/sec will be fine for my application.

Kiedro · Joined: 08 Mar 2006 Posts: 81

Oh, I forgot to mention this: The gyros have a Vref output, 1.? V. I would just feed Vref to a voltage divider, e.g. two 10k resistors:

Vref---R---ADC0---R---GND. Have ADC0 connected to ADC0 and ADC2, gyro x to ADC1 and gyro y to ADC3. Differential ADC needs a little work on calibration/offsetting (described in the data sheet) - but it pays back. I would start using gain 10, with 200 you might run into a saturation problem.

Natalius

Matrixx · Joined: 30 Nov 2005 Posts: 158

Hello!!

Time has been passed. I continued this year with my hobby projects left due to lack of time.

I'm getting again to the vehicle and driving forces. Now I have built a IMU unit using 3 Gyros and 3 Accelerometers. For automotive application I choose XV-8000 single axis gyros, and ADXL202 +/-2G accelerometers.

I mounted the sensors in a 3D configuration. Form my past experience the Gyro range was big enough for my application so now I bough +/-60 degs'sec range ones. In my corners I expect +/-30 Deg/sec.

I'm now using a Arduino M2560 R3 but just the hardware, all the current and new firmware is written in Bascom.

I tested the IMU with both Lauzus Kalman algorythm and complementary filter as well (Ported Luzus algorythm to Delphi to avoid reflashing the M2560) so the Atmel just send ADC values thru serial port.

I would like to test with DCM.

This is new for me, I have the IMU running, but now I'm looking what to do with... Razz

My original target is 'separating' the gravity forces from the accelerometer but as one of you mentioned, with the anterior 5DOF I was lacking the Yaw. Altough I have now Z gyro, I realized I need more DOF (Zgyro + Compass). In one chance I will get a compass to complement the IMU.

Per Svensson · Joined: 03 Oct 2004 Posts: 235 Location: Gothenburg, Sweden

Kiedro,

After a very long time with other matters I return to the Inertial sensor world of problems.
I read your threads again and I must say I'm amazed how much work and insights you have dug down into
this forum when it comes to sensor fusing and all math involved. I am truly impressed

I remember that I wrote a thread about Kalman filters some time ago
( http://www.mcselec.com/index2.php?option=com_forum&Itemid=59&page=viewtopic&t=11265&highlight=dummies )
and maybe it is time to contribute with something else soon...

Anyway, as some time has passed and new sensor devices has been introduced at an unstoppable pace.
I now wonder if someone here (perhaps you Kiedro) have evaluated the Invensense 9250 http://www.invensense.com/mems/gyro/mpu9250.html
It incorporate 3D Accel+Gyro plus input for 3D Magnetometers. And it also contains software for 9DOF sensor fusion.
All on the same chip (4x4mm) !!!
I have not yet read all the documentation, and I'm particularly interested to see if the firmware have support for Soft-iron calibration
of the magnetometers.

My current interest is to design a full 3D compass solution with hard and soft iron compensation ON THE FLY.
That is, adaptive recognition and elimination of offsets and non-linear flux for full 3D use.
The idea is that the device shall successively learn the distortion of the surrounding magnetic field lines due to magnetic objects attached to the
sensor frame, and eliminate it.
There are many many academic articles written about this problem and I have read most of them but still not found an engineering approach to the problem.
Many of them can do a static calibration with the use of massive matrix math, but few or none can do it as a natural part of the device operation.

The thing is that if you make a device that MUST be calibrated AFTER the device was mounted on the target equipment, then the procedure must
be simple enough for an unskilled person to perform it.
In practice, this doesn't work. End-users don't even want to get involved in these delicate matters. It should simply work out_of_the_box.

So the only solution for good sensor solutions today rely on two corner stones as i see it:
1: Multiple sensor fusion (and perhaps redundant sensors)
2. Adaptive calibration algorithms (Preferably no special modes. Just plain run)

So if you who bothered to read this far. Perhaps you could also give some thoughts or experience from how to turn academic
fire-flies into real embedded solutions...

Friday afternoon now. Time for a glass of wine and drift away from sensors and ugly software.
Cheers

/Per

Some links about magnetometer calibration:
----------------------------------------------
http://www.roboticsproceedings.org/rss09/p50.pdf
http://www.sgp.geodezja.org.pl/ptfit/wydawnictwa/krakow2011/APCRS%20vol.%2022%20pp.%209-23.pdf
http://www.ignss.org/LinkClick.aspx?fileticket=7oH5%2FnHXZyY%3D&tabid=88&mid=424
http://sailboatinstruments.blogspot.se/2011/08/improved-magnetometer-calibration.html <- I have tested this with good results, but it offers static calibration only
http://sailboatinstruments.blogspot.se/2011/09/improved-magnetometer-calibration-part.html