Cognitoware.Robotics.dll

Class KalmanActionModel<U, X>

System.Object

Cognitoware.Robotics.StateEstimation.KalmanActionModel<U, X>

An action model based on the linear system Xt+1 = A*Xt + B*actiont + C + error.

ConditionBy(U, X)

Creates a new GaussianMoment using GetMean and GetError.

Equals(Object)

Inherited from System.Object

Finalize()

Inherited from System.Object

GetActionJacobian(U, X)

GetError(U, X)

Creates an covariance matrix that describes the Gaussian error around the final x mean.

GetHashCode()

Inherited from System.Object

GetMean(U, X)

Creates the expected x resulting from performing an action at another x.

GetStateJacobian(U, X)

GetType()

Inherited from System.Object

MemberwiseClone()

Inherited from System.Object

ToString()

Inherited from System.Object

A linear sensor model is an implementation of GaussianActionModel and RandomConditional.
The expected next x is found using the linear system Xt+1 = A*Xt + B*actiont + C + error.
The error is the constant covariance matrix error.
Because of the requirement to interact with Matrix, U and X must both be of type Vector or inherited from Vector.
Linear action models are also referred to as "Linear Gaussians".

public KalmanActionModel()

public final virtual RandomDistribution<X> ConditionBy(U action, X state)

Creates a new GaussianMoment using GetMean and GetError.

`action`

- The action performed at the start x.`x`

- The start x.A new Gaussian distribution.

public final virtual Matrix GetActionJacobian(U action, X state)

public final virtual Matrix GetError(U action, X state)

Creates an covariance matrix that describes the Gaussian error around the final x mean.
This function is used to calcualte the covariance of the GaussianMoment returned by ActionModel.ConditionBy.
This function returns the constant value R.

`action`

- The action being performed.`x`

- The x where the action is performed.A covariance matix that describes the error of the mean.

public final virtual X GetMean(U action, X state)

Returns the expected x resulting from performing an action at another x.
This function is used to calcualte the mean of the GaussianMoment returned by ActionModel.ConditionBy.
Xt+1 = A * Xt + B * U + C.

`action`

- The action performed at the start x.`x`

- The start x.The average end x.

public final virtual Matrix GetStateJacobian(U action, X state)