kalibr_allan

This has some nice utility scripts and packages that allow for calculation of the noise values for use in both kalibr and IMU filters. The dataset of the manufacture can find the "white noise" values for the system, but the bias noises need to be found through experimental tests. The gyroscope_random_walk and accelerometer_random_walk values can normally be found on the IMU datasheet as either angular random walk or velocity random walk, respectively.

IMU Noise Values

Parameter | YAML element | Symbol | Units --- | --- | --- | --- Gyroscope "white noise" | gyroscope_noise_density | <img src="https://latex.codecogs.com/svg.latex?{%5Csigma_g}"> | <img src="https://latex.codecogs.com/svg.latex?{%5Cfrac%7Brad%7D%7Bs%7D%5Cfrac%7B1%7D%7B%5Csqrt%7BHz%7D%7D}"> Accelerometer "white noise" | accelerometer_noise_density | <img src="https://latex.codecogs.com/svg.latex?{%5Csigma_a}"> | <img src="https://latex.codecogs.com/svg.latex?{%5Cfrac%7Bm%7D%7Bs^2%7D%5Cfrac%7B1%7D%7B%5Csqrt%7BHz%7D%7D}"> Gyroscope "random walk" | gyroscope_random_walk | <img src="https://latex.codecogs.com/svg.latex?{%5Csigma_b_g}"> | <img src="https://latex.codecogs.com/svg.latex?{%5Cfrac%7Brad%7D%7Bs^2%7D%5Cfrac%7B1%7D%7B%5Csqrt%7BHz%7D%7D}"> Accelerometer "random walk" | accelerometer_random_walk | <img src="https://latex.codecogs.com/svg.latex?{%5Csigma_b_a}"> | <img src="https://latex.codecogs.com/svg.latex?{%5Cfrac%7Bm%7D%7Bs^3%7D%5Cfrac%7B1%7D%7B%5Csqrt%7BHz%7D%7D}">

Experiment Steps

1. With the IMU remaining still, record a ROS bag of the readings (we collected a bag for about 4 hours)
2. Convert the ROS bag into a matlab mat file.
   • Use the included bagconvert ROS package to do this
   • Example: rosrun bagconvert bagconvert imu.bag /imu0
3. Run the included matlab scripts to generate an allan deviation plot for the readings
   • If using the parallel version, it uses the matlab parallel toolbox
   • Need to specify the mat file that the bagconverter made, and the rate of IMU messages