An efficient orientation filter for IMUs (real-time demonstration)

University of Bristol, Mechanical Engineering Department, PhD year 1/3 (2009-10) - An efficient orientation filter for IMUs (Inertial Measurement Units).

A real-time demonstration of an efficient orientation filter capable of providing an estimate of the IMU's orientation relative to the earth through the fusion of tri-axis gyroscope and tri-axis accelerometer data. The sensor has no absolute reference of yaw and so will be subject to an accumulating error in this axis. The algorithm is an alternative to more computationally expensive Kalman based solutions that are commonly used in this application. The total computation requirement of this filter is 109 scalar arithmetic operations per sample.

Source code and documentation available here: http://code.google.com/p/imumargalgorithm30042010sohm/

Hardware used in video: Sparkfun 6DOF IMU Razor (ADXL335, LPR530 and LPY530) with gyroscope RC HP filters removed, x-io Board with .NET interface library (http://www.x-io.co.uk).

Category:

Science & Technology

Tags:

• IMU
• MEMS
• accelerometers
• gyroscopes
• Kalman
• Sparkfun
• x-io Board

[Nomoreidsleft]

I'm experimenting with 3-axis magnetometer to get orientation and speed. Basic idea is to read x-y-z field strengths relative to North Pole to determine orientation and reading magnetic flux on the sensors to determine velocity.

Would like to hear your opinion on that.

[SebMadgwickResearch]

A single orientation solution cannot be found, there will be infinite solutions represented by all orientations achieved when rotating the sensor around an axis aligned with the direction magnetic flux. See my paper by following link in video description.

I don’t see how you can determine velocity from a homogonous magnetic field unless you are inducing current and limit your system to 1DOF which would be impractical.

[SebMadgwickResearch]

These very basic graphics were created in 2D with a C# form. Check out the open-source x-IMU GUI [Google it] for far better 3D graphics using open GL.

[skwex]

If a linear acceleration is applied to some direction (besides gravity direction) during some time, how much damage the orientation estimate suffers during that acceleration?

[SebMadgwickResearch]

It depends on the algorithm tuning. You would tune 'how much you trust' the gyroscope. More trust (low gain) would mean that translational accelerations would have less effect on the orientation.

[Cadilac789]

What software I can use to view data in real time on the pc and make that animation?

[asifadio]

great video!

[SebMadgwickResearch]

Incorporating an on-line tuning mechanism or 'adaptive gains’ will have obviously benefits but may represent a significantly more complex and less transparent system. I think most situations require only one-off tuning and for your efforts to be focussed on individual sensor calibration.

[skwex]

@SebMadgwickResearch It makes sense, but again, how much damage the orientation suffers if I don't trust enough my accelerometer to correct gyro drift? Regarding your experience, do you think there is a "tunning sweet spot" or another level of intelligence is need to switch tunnings during execution time?

[Elardification]

Thanks, now I understand everything.