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A ROS package tool to analyze the IMU performance.

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gaowenliang/imu_utils

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A ROS package tool to analyze the IMU performance. C++ version of Allan Variance Tool.The figures are drawn by Matlab, inscripts.

Actually, just analyze the Allan Variance for the IMU data. Collect the data while the IMU is Stationary, with a two hours duration.

refrence

Refrence technical report:Allan Variance: Noise Analysis for Gyroscopes,vectornav gyroscope andAn introduction to inertial navigation.

Woodman, O.J., 2007. An introduction to inertial navigation (No. UCAM-CL-TR-696). University of Cambridge, Computer Laboratory.

Refrence Matlab code:GyroAllan

IMU Noise Values

ParameterYAML elementSymbolUnits
Gyroscope "white noise"gyr_n
Accelerometer "white noise"acc_n
Gyroscope "bias Instability"gyr_w
Accelerometer "bias Instability"acc_w

  • White noise is at tau=1;

  • Bias Instability is around the minimum;

(according to technical report:Allan Variance: Noise Analysis for Gyroscopes)

sample test

  • blue : Vi-Sensor, ADIS16448,200Hz
  • red : 3dm-Gx4,500Hz
  • green : DJI-A3,400Hz
  • black : DJI-N3,400Hz
  • circle : xsens-MTI-100,100Hz

How to build and run?

to build

sudo apt-get install libdw-dev

  • download requiredcode_utils;

  • put the ROS packageimu_utils andcode_utils into your workspace, usually namedcatkin_ws;

  • cd to your workspace, build withcatkin_make;

to run

  • collect the data while the IMU is Stationary, with a two hours duration;

  • (or) play rosbag dataset;

 rosbag play -r 200 imu_A3.bag
  • roslaunch the rosnode;
roslaunch imu_utils A3.launch

Be careful of your roslaunch file:

<launch>    <node pkg="imu_utils" type="imu_an" name="imu_an" output="screen">        <param name="imu_topic" type="string" value= "/djiros/imu"/>        <param name="imu_name" type="string" value= "A3"/>        <param name="data_save_path" type="string" value= "$(find imu_utils)/data/"/>        <param name="max_time_min" type="int" value= "120"/>        <param name="max_cluster" type="int" value= "100"/>    </node></launch>

sample output:

type: IMUname: A3Gyr:   unit: " rad/s"   avg-axis:      gyr_n: 1.0351286977809465e-04      gyr_w: 2.9438676109223402e-05   x-axis:      gyr_n: 1.0312669892959053e-04      gyr_w: 3.3765827874234673e-05   y-axis:      gyr_n: 1.0787155789128671e-04      gyr_w: 3.1970693666470835e-05   z-axis:      gyr_n: 9.9540352513406743e-05      gyr_w: 2.2579506786964707e-05Acc:   unit: " m/s^2"   avg-axis:      acc_n: 1.3985049290745563e-03      acc_w: 6.3249251509920116e-04   x-axis:      acc_n: 1.1687799474421937e-03      acc_w: 5.3044554054317266e-04   y-axis:      acc_n: 1.2050535351630543e-03      acc_w: 6.0281218607825414e-04   z-axis:      acc_n: 1.8216813046184213e-03      acc_w: 7.6421981867617645e-04

dataset

DJI A3:400Hz

Download link:百度网盘

DJI A3:400Hz

Download link:百度网盘

ADIS16448:200Hz

Download link:百度网盘

3dM-GX4:500Hz

Download link:百度网盘

xsens-MTI-100:100Hz

Download link:百度网盘

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