OSVR-Core
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A constant-velocity model for a 6DOF pose (with velocities) More...
#include <PoseConstantVelocity.h>
Public Types | |
using | State = pose_externalized_rotation::State |
using | StateVector = pose_externalized_rotation::StateVector |
using | StateSquareMatrix = pose_externalized_rotation::StateSquareMatrix |
using | NoiseAutocorrelation = types::Vector< 6 > |
Public Member Functions | |
PoseConstantVelocityProcessModel (double positionNoise=0.01, double orientationNoise=0.1) | |
void | setNoiseAutocorrelation (double positionNoise=0.01, double orientationNoise=0.1) |
void | setNoiseAutocorrelation (NoiseAutocorrelation const &noise) |
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 |
This is Q(deltaT) - the Sampled Process Noise Covariance. More... | |
StateVector | computeEstimate (State &state, double dt) const |
Returns a 12-element vector containing a predicted state based on a constant velocity process model. More... | |
A constant-velocity model for a 6DOF pose (with velocities)
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Returns a 12-element vector containing a predicted state based on a constant velocity process model.
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inline |
This is Q(deltaT) - the Sampled Process Noise Covariance.
Like all covariance matrices, it is real symmetrical (self-adjoint), so .selfAdjointView<Eigen::Upper>() might provide useful performance enhancements in some algorithms.