Matlab and C++ code for implementation of the Extended Kalman Filter for estimating dynamic quantities for a single rigid body with distributed force/torque measurements and distributed gyroscopes and accelerometers measurements.It also include estimation of the orientation under the quaternion representation.
@prashanthr05 For a sanity check on the results, it is recommended that the following checklist is followed:
[x] Check IMU rotation
[x] Check CoM frame position and orientation
[x] Check sensor homogenous transforms in CoM frame (com_X_imu, com_X_ft)
[ ] verify raw data signs
[ ] sanity check on raw data magnitudes
[ ] verify calibrated and rotated data signs
[ ] sanity check on calibrated and rotated data magnitudes
[x] verify process model equations
[x] verify measurement model equations
Tuning must be performed only after each of these are verified through checking the measured data. Both the calibration phase (robot standing) and dynamic phase (robot toppling) parts must be verified.
@prashanthr05 For a sanity check on the results, it is recommended that the following checklist is followed:
Tuning must be performed only after each of these are verified through checking the measured data. Both the calibration phase (robot standing) and dynamic phase (robot toppling) parts must be verified.