jianboliang d19355a27e basic reserse dir 4 年 前
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FootRight8_CalInertialAndMag.csv d19355a27e basic reserse dir 4 年 前
LoggedData1_CalInertialAndMag.csv d19355a27e basic reserse dir 4 年 前
LoggedData2_CalInertialAndMag.csv d19355a27e basic reserse dir 4 年 前
LoggedData3.csv d19355a27e basic reserse dir 4 年 前
LoggedData_CalInertialAndMag.csv d19355a27e basic reserse dir 4 年 前
README.md d19355a27e basic reserse dir 4 年 前
SixDofAnimation.m d19355a27e basic reserse dir 4 年 前
compVq.m d19355a27e basic reserse dir 4 年 前
main.m d19355a27e basic reserse dir 4 年 前
new_scipt.m d19355a27e basic reserse dir 4 年 前
orien.m d19355a27e basic reserse dir 4 年 前
plot_result.m d19355a27e basic reserse dir 4 年 前
result.txt d19355a27e basic reserse dir 4 年 前
test.m d19355a27e basic reserse dir 4 年 前
zupt.m d19355a27e basic reserse dir 4 年 前

README.md

ImuFusion

EKF IMU Fusion Algorithms

  1. orien.m uses Kalman filter for fusing the gyroscope's and accelerometer's readings to get the IMU's attitude(quaternion).
  2. zupt.m implenments the so called 'zero-velocity-update' algorithm for pedestrian tracking(gait tracking), it's also a ekf filter.
  3. Video: http://v.youku.com/v_show/id_XMTg2NjI4NTI4NA==.html

Usage

Example data already included.
Simply run the orien.m or zupt.m. For zupt, set 'CreateVideo' as true if you'd like to save the results as a video.
Note that the datasets and the code for visualizing the results were from: https://github.com/xioTechnologies/Gait-Tracking-With-x-IMU

References:

[1] S. Madgwick. An efficient orientation filter for inertial and inertial/magnetic sensor arrays.
[2] Fischer C, et. Implementing a Pedestrian Tracker Using inertial Sensors.
[3] Isaac Skog, et. Zero-Velocity Detection — An Algorithm Evaluation.