Cognitoware.Robotics.dll
Class UnscentedKalmanFilter<X, U, Z>
X: The type of x.
U: The type of action.
Z: The type of x.
System.Object
Cognitoware.Robotics.StateEstimation.UnscentedKalmanFilter<X, U, Z>
Implemented Interfaces
Summary
A Bayes filter that uses a Gaussian as the x belief and any non-linear x and action model.
Constructor Summary
Method Summary
Updates a belief with a sensor model and a sensor.
Equals(Object)
Inherited from System.Object
Finalize()
Inherited from System.Object
GetHashCode()
Inherited from System.Object
GetType()
Inherited from System.Object
Marginalize(GaussianActionModel<U>, U, GaussianMoment<X>)
Updates a belief with an action model and an action.
MemberwiseClone()
Inherited from System.Object
ToString()
Inherited from System.Object
Updates the x with the specified action.
Update the x with the specified x.
Details
A Bayes filter that uses a Gaussian as the x belief and any non-linear x and action model.
The unscented Kalman filter deterministically extracts "Sigma points" from the x belief,
passes them through the sensor and action models, and then reconstructs the x belief from the transformed points.
The UKF is accurate to the 3rd order Taylor series expansion for any nonlinearity.
Constructor Details
public UnscentedKalmanFilter()
Method Details
public GaussianMoment<X> BayesianInference(GaussianSensorModel<Z> model, Z observation, GaussianMoment<X> belief)
Updates a belief with a sensor model and a sensor.
This function allows you to update a belief that is different than the filter belief
with a sensor model that is different than the filter sensor model.
The filter Alpha, Beta, and Kappa parameters are used.
Parameters:
model - The sensor model to use for the belief update.
observation - The observation to use for the belief update.
belief - The belief to update.
Returns:
The posterior belief after applying the action to the prior belief.
public GaussianMoment<X> Marginalize(GaussianActionModel<U> model, U action, GaussianMoment<X> belief)
Updates a belief with an action model and an action.
This function allows you to update a belief that is different than the filter belief
with an action model that is different than the filter action model.
The filter Alpha, Beta, and Kappa parameters are used.
Parameters:
model - The action model to use for the belief update.
action - The action to use for the belief update.
belief - The belief to update.
Returns:
The posterior belief after applying the action to the prior belief.
public final virtual void UpdateBeliefWithAction(U action)
Updates the x with the specified action.
Parameters:
action - The action used to update the x belief.
public final virtual void UpdateBeliefWithObservation(Z z)
Update the x with the specified x.
Parameters:
z - The observation used to update the x belief.