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osvr::kalman::PoseSeparatelyDampedConstantVelocityProcessModel Class Reference

#include <osvr/Kalman/PoseSeparatelyDampedConstantVelocity.h>

Public Types

using State = pose_externalized_rotation::State
 
using StateVector = pose_externalized_rotation::StateVector
 
using StateSquareMatrix = pose_externalized_rotation::StateSquareMatrix
 
using BaseProcess = PoseConstantVelocityProcessModel
 
using NoiseAutocorrelation = BaseProcess::NoiseAutocorrelation
 

Public Member Functions

 PoseSeparatelyDampedConstantVelocityProcessModel (double positionDamping=0.3, double orientationDamping=0.01, double positionNoise=0.01, double orientationNoise=0.1)
 
void setNoiseAutocorrelation (double positionNoise=0.01, double orientationNoise=0.1)
 
void setNoiseAutocorrelation (NoiseAutocorrelation const &noise)
 
void setDamping (double posDamping, double oriDamping)
 Set the damping - must be in (0, 1)
 
StateSquareMatrix getStateTransitionMatrix (State const &, double dt) const
 Also known as the "process model jacobian" in TAG, this is A.
 
void predictState (State &s, double dt)
 
StateSquareMatrix getSampledProcessNoiseCovariance (double dt) const
 
StateVector computeEstimate (State &state, double dt) const
 

Detailed Description

A basically-constant-velocity model, with the addition of some damping of the velocities inspired by TAG. This model has separate damping/attenuation of linear and angular velocities.

Definition at line 43 of file PoseSeparatelyDampedConstantVelocity.h.

Member Function Documentation

StateSquareMatrix osvr::kalman::PoseSeparatelyDampedConstantVelocityProcessModel::getSampledProcessNoiseCovariance ( double  dt) const
inline

This is Q(deltaT) - the Sampled Process Noise Covariance

Returns
a matrix of dimension n x n. Note that it is real symmetrical (self-adjoint), so .selfAdjointView<Eigen::Upper>() might provide useful performance enhancements.

Definition at line 96 of file PoseSeparatelyDampedConstantVelocity.h.

StateVector osvr::kalman::PoseSeparatelyDampedConstantVelocityProcessModel::computeEstimate ( State state,
double  dt 
) const
inline

Returns a 12-element vector containing a predicted state based on a constant velocity process model.

Definition at line 102 of file PoseSeparatelyDampedConstantVelocity.h.


The documentation for this class was generated from the following file: