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.
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Consistency check for the quaternionEKF module #25
The module as of today is fully written and should be "functional". This doesn't mean that the estimate is correct. This issue has been created simply to analyze in an organized way the filtering process in this module. Up next, the different stages by which it is composed
Correct initialization
[x] All the filter parameters are passed and set correctly to their initial values in the corresponding configuration file.
[x] Initial gaussian system noise uncertainty (mean and covariance) makes sense.
[x] Initial gaussian measurement noise uncertainty (mean and covariance) makes sense.
[x] Priors make sense (mu and covariance)
Online Estimation
[x] Convert read angular velocity to rad/s
[x] nonLinearAnalyticConditionalGaussian::ExpectedValueGet() should return the state prior prediction.
[x] nonLinearAnalyticConditionalGaussian::dfGet() should return the transition matrix.
[x] nonLinearMeasurementGaussianPdf::ExpectedValueGet()` should return the acceleration model output.
[x] nonLinearMeasurementGaussianPdf::dfGet() should return the jacobian evaluated at the current estimate.
The module as of today is fully written and should be "functional". This doesn't mean that the estimate is correct. This issue has been created simply to analyze in an organized way the filtering process in this module. Up next, the different stages by which it is composed
nonLinearAnalyticConditionalGaussian::ExpectedValueGet()should return the state prior prediction.nonLinearAnalyticConditionalGaussian::dfGet()should return the transition matrix.nonLinearMeasurementGaussianPdf::ExpectedValueGet()` should return the acceleration model output.nonLinearMeasurementGaussianPdf::dfGet()should return the jacobian evaluated at the current estimate.