accelerometer-calibration
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A general method (with Python scripts) for calibrating accelerometer sensors.
Accelerometer Calibration Procedure
A general method (with Python scripts) for calibrating accelerometer sensors.
Developed By: Michael Wrona, B.S. Aerospace Engineering
GitHub: @michaelwro
YouTube: @MicWro Engr
Blog: mwrona.com
Pip Install Python3 Dependencies
$ pip3 install numpy matplotlib pandas # pip for Windows
Conda Install Python3 Dependencies
(myenv) $ conda install -c conda-forge numpy matplotlib pandas
IMPORTANT: Before following these steps, I highly recommend watching the video I created about this process. You can watch it at this link.
Step 1: Output Comma-Separated Data
record-data.py
expects to read comma-separated accelerometer data from a serial connection. Each sensor is different, so you will need to write your own microcontroller code to output comma-separated accelerometer measurements to a serial port, similar to this format:
0.0642208,-0.05490976,1.02357024
Step 2: Configure record-data.py
Open record-data.py
in a text editor. Change the variables at the top as required.
Step 3: Measure Accelerometer Data
Once you can output comma-separated raw accelerometer measurements over a serial connection, you can begin logging data. Run record-data.py
to begin logging data. Have the accelerometer flat and stationary and press ENTER as prompted. Then, type 'm' as prompted to take a measurement. Move the accelerometer to a different orientation, then take another measurement. Repeat for many accelerometer orientations (sideways, upside down, left, right, etc.).
Step 4: Save Measurements to File
Once you are satisfied with the number of measurements, type 'q' to save the measurements to a tab-delimited file.
Step 5: Calibrate with Magneto
Magneto is an ellipsoid-fitting software used to calibrate accelerometer and magnetometer sensors. Magneto expects raw measurements to be input as a tab-delimited text file. The norm of the gravitational field will be the ideal magnitude of your accelerometer measurements. For example, my accelerometer output data in G's, so my norm/magnitude would be 1. Load your text file generated by record-data.py
, then click 'calibrate.' BAM! It's that easy!
Step 6: Visualize Results
Open plot-calibration-data.py
in a text editor. Copy the A^-1 matrix and bias vector values to the Python code and specify the tab-delimited text file of uncalibrated measurements. Run the code and compare uncalibrated and calibrated data!