#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 |
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.
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inline |
This is Q(deltaT) - the Sampled Process Noise Covariance
Definition at line 96 of file PoseSeparatelyDampedConstantVelocity.h.
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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.