Skip to content

Odometry Trajectory Recursion Based on IMU Integral Interpolation.

License

Notifications You must be signed in to change notification settings

LuoXubo/IMU-Aided-Odometry

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

IMU-Aided-Odometry

Odometry Trajectory Recursion Based on IMU Integral Interpolation.

Notice

Overall I/O

Input

  • High frequency IMU topic (50Hz)
  • Low frequency Odometry topic (1Hz)

Output

  • High frequency pose trajectory after IMU estimation and Odometry correction

Method

Orientation estimation

$$ \Delta R ={ {\begin{bmatrix} 0& -w_z\times\Delta t& w_y\times \Delta t\

w_z\times\Delta t& 0& -w_x\times\Delta t\

-w_y\times\Delta t& w_x\times\Delta t& 0 \end{bmatrix}} }, $$

$$ \sigma = \sqrt{w_x^2 + w_y^2 + w_z^2} \times \Delta t, $$

$$ R_t =R_{t-1}\times (\mathbf{I}_3 + \frac{sin(\sigma)}{\sigma}\times \Delta R - \frac{1-cos(\sigma)}{\sigma^2}\times \Delta R^2), $$

$$ v_t = v_{t-1} + \Delta t \times (R_t \times a_{imu} - g), $$

$$ pos_t = pos_{t-1} + \Delta t \times v $$

Drift correction

  • Use the pose information from Odometry topic to cover the current pose vector.
  • Velocity correction:
    • Assume that $|v_{mid}| = |v_{t}|$
    • $v_{mid} = \frac{Pos_{t} - Pos_{t-1}}{\Delta t}$
    • $v_t = R_t\times R_{t-1}^{-1}\times v_{mid}$

Experimental verification

  • RMSE/Length = 0.10156%

About

Odometry Trajectory Recursion Based on IMU Integral Interpolation.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages