Visual Servoing Platform
version 3.6.1 under development (2024-11-21)
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#include <visp3/core/vpKalmanFilter.h>
Public Member Functions | |
vpKalmanFilter () | |
VP_EXPLICIT | vpKalmanFilter (unsigned int n_signal) |
vpKalmanFilter (unsigned int size_state, unsigned int size_measure, unsigned int n_signal) | |
virtual | ~vpKalmanFilter () |
void | setNumberOfSignal (unsigned int n_signal) |
void | init (unsigned int size_state, unsigned int size_measure, unsigned int n_signal) |
void | prediction () |
void | filtering (const vpColVector &z) |
unsigned int | getStateSize () |
unsigned int | getMeasureSize () |
unsigned int | getNumberOfSignal () |
long | getIteration () |
void | verbose (bool on) |
Public Attributes | |
vpColVector | Xest |
vpColVector | Xpre |
vpMatrix | F |
vpMatrix | H |
vpMatrix | R |
vpMatrix | Q |
double | dt |
vpMatrix | Ppre |
vpMatrix | Pest |
Protected Attributes | |
long | iter |
unsigned int | size_state |
unsigned int | size_measure |
unsigned int | nsignal |
bool | verbose_mode |
vpMatrix | W |
vpMatrix | I |
This class provides a generic Kalman filtering algorithm along with some specific state model (constant velocity, constant acceleration) which are implemented in the vpLinearKalmanFilterInstantiation class.
The state evolution equation is given by:
where is the unknown state at iteration .
The measurement equation is given by:
where is the measure (also named observation) at iteration .
The predicted state is obtained by:
where
Filtering equation are:
where is the filter gain.
Notice that there is a recursion for the inverse covariance
where is the inverse of the covariance matrix.
ViSP provides different state evolution models implemented in the vpLinearKalmanFilterInstantiation class.
Definition at line 105 of file vpKalmanFilter.h.
vpKalmanFilter::vpKalmanFilter | ( | ) |
Construct a default Kalman filter.
The verbose mode is disabled by default
Definition at line 89 of file vpKalmanFilter.cpp.
vpKalmanFilter::vpKalmanFilter | ( | unsigned int | n_signal | ) |
Construct a default Kalman filter by setting the number of signal to filter.
The verbose mode is disabled by default
n_signal | : Number of signal to filter. |
Definition at line 101 of file vpKalmanFilter.cpp.
vpKalmanFilter::vpKalmanFilter | ( | unsigned int | size_state_vector, |
unsigned int | size_measure_vector, | ||
unsigned int | n_signal | ||
) |
Construct a Kalman filter.
The verbose mode is disabled by default
size_state_vector | : Size of the state vector for one signal. |
size_measure_vector | : Size of the measure vector for one signal. |
n_signal | : Number of signal to filter. |
Definition at line 119 of file vpKalmanFilter.cpp.
References init().
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Destructor that does noting.
Definition at line 129 of file vpKalmanFilter.h.
void vpKalmanFilter::filtering | ( | const vpColVector & | z | ) |
Update the Kalman filter by applying the filtering equations and increment the filter iteration (vpKalmanFilter::iter).
z | : Measure (or observation) provided at iteration . |
The filtering equation is given by:
where is the filter gain computed using the formula:
and where the updated covariance of the state is given by
or in a symmetric form
with
Definition at line 199 of file vpKalmanFilter.cpp.
References H, vpMatrix::inverseByLU(), iter, Pest, Ppre, R, vpMatrix::t(), verbose_mode, W, Xest, and Xpre.
Referenced by vpLinearKalmanFilterInstantiation::filter().
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Return the iteration number.
Definition at line 154 of file vpKalmanFilter.h.
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Return the size of the measure vector for one signal.
Definition at line 146 of file vpKalmanFilter.h.
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Return the number of signal to filter.
Definition at line 150 of file vpKalmanFilter.h.
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Return the size of the state vector for one signal.
Definition at line 142 of file vpKalmanFilter.h.
BEGIN_VISP_NAMESPACE void vpKalmanFilter::init | ( | unsigned int | size_state_vector, |
unsigned int | size_measure_vector, | ||
unsigned int | n_signal | ||
) |
Initialize the Kalman filter.
size_state_vector | : Size of the state vector for one signal. |
size_measure_vector | : Size of the measure vector for one signal. |
n_signal | : Number of signal to filter. |
Definition at line 58 of file vpKalmanFilter.cpp.
References dt, F, H, I, iter, nsignal, Pest, Q, R, vpColVector::resize(), vpArray2D< Type >::resize(), size_measure, size_state, Xest, and Xpre.
Referenced by vpLinearKalmanFilterInstantiation::initStateConstAccWithColoredNoise_MeasureVel(), vpLinearKalmanFilterInstantiation::initStateConstVel_MeasurePos(), vpLinearKalmanFilterInstantiation::initStateConstVelWithColoredNoise_MeasureVel(), and vpKalmanFilter().
void vpKalmanFilter::prediction | ( | ) |
Update the Kalman filter by applying the prediction equations.
The predicted state is given by
and the state prediction covariance by
Definition at line 142 of file vpKalmanFilter.cpp.
References F, vpException::fatalError, vpArray2D< Type >::getRows(), nsignal, Pest, Ppre, Q, size_state, vpMatrix::t(), verbose_mode, Xest, and Xpre.
Referenced by vpLinearKalmanFilterInstantiation::filter().
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Set the number of signal to filter.
Definition at line 133 of file vpKalmanFilter.h.
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Sets the verbose mode.
on | : If true, activates the verbose mode which consists in printing the Kalman filter internal values. |
Definition at line 160 of file vpKalmanFilter.h.
double vpKalmanFilter::dt |
Sampling time in second between two successive iterations. Only used in some specific state models implemented in vpLinearKalmanFilterInstantiation.
Definition at line 188 of file vpKalmanFilter.h.
Referenced by vpLinearKalmanFilterInstantiation::filter(), init(), vpLinearKalmanFilterInstantiation::initStateConstAccWithColoredNoise_MeasureVel(), and vpLinearKalmanFilterInstantiation::initStateConstVel_MeasurePos().
vpMatrix vpKalmanFilter::F |
Transition matrix that describes the evolution of the state.
Definition at line 176 of file vpKalmanFilter.h.
Referenced by init(), vpLinearKalmanFilterInstantiation::initStateConstAccWithColoredNoise_MeasureVel(), vpLinearKalmanFilterInstantiation::initStateConstVel_MeasurePos(), vpLinearKalmanFilterInstantiation::initStateConstVelWithColoredNoise_MeasureVel(), and prediction().
vpMatrix vpKalmanFilter::H |
Matrix that describes the evolution of the measurements.
Definition at line 179 of file vpKalmanFilter.h.
Referenced by filtering(), init(), vpLinearKalmanFilterInstantiation::initStateConstAccWithColoredNoise_MeasureVel(), vpLinearKalmanFilterInstantiation::initStateConstVel_MeasurePos(), and vpLinearKalmanFilterInstantiation::initStateConstVelWithColoredNoise_MeasureVel().
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Filter step or iteration. When set to zero, initialize the filter.
Definition at line 111 of file vpKalmanFilter.h.
Referenced by vpLinearKalmanFilterInstantiation::filter(), filtering(), init(), vpLinearKalmanFilterInstantiation::initStateConstAccWithColoredNoise_MeasureVel(), vpLinearKalmanFilterInstantiation::initStateConstVel_MeasurePos(), and vpLinearKalmanFilterInstantiation::initStateConstVelWithColoredNoise_MeasureVel().
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Number of signal to filter.
Definition at line 118 of file vpKalmanFilter.h.
Referenced by vpLinearKalmanFilterInstantiation::filter(), init(), vpLinearKalmanFilterInstantiation::initStateConstAccWithColoredNoise_MeasureVel(), and prediction().
vpMatrix vpKalmanFilter::Pest |
The updated covariance of the state where .
Definition at line 202 of file vpKalmanFilter.h.
Referenced by filtering(), init(), vpLinearKalmanFilterInstantiation::initStateConstAccWithColoredNoise_MeasureVel(), vpLinearKalmanFilterInstantiation::initStateConstVel_MeasurePos(), vpLinearKalmanFilterInstantiation::initStateConstVelWithColoredNoise_MeasureVel(), and prediction().
vpMatrix vpKalmanFilter::Ppre |
The state prediction covariance where .
Definition at line 195 of file vpKalmanFilter.h.
Referenced by filtering(), and prediction().
vpMatrix vpKalmanFilter::Q |
Process noise covariance matrix .
Definition at line 184 of file vpKalmanFilter.h.
Referenced by init(), vpLinearKalmanFilterInstantiation::initStateConstAccWithColoredNoise_MeasureVel(), vpLinearKalmanFilterInstantiation::initStateConstVel_MeasurePos(), vpLinearKalmanFilterInstantiation::initStateConstVelWithColoredNoise_MeasureVel(), and prediction().
vpMatrix vpKalmanFilter::R |
Measurement noise covariance matrix .
Definition at line 182 of file vpKalmanFilter.h.
Referenced by filtering(), init(), vpLinearKalmanFilterInstantiation::initStateConstAccWithColoredNoise_MeasureVel(), vpLinearKalmanFilterInstantiation::initStateConstVel_MeasurePos(), and vpLinearKalmanFilterInstantiation::initStateConstVelWithColoredNoise_MeasureVel().
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Size of the measure vector .
Definition at line 116 of file vpKalmanFilter.h.
Referenced by vpLinearKalmanFilterInstantiation::filter(), init(), vpLinearKalmanFilterInstantiation::initStateConstAccWithColoredNoise_MeasureVel(), vpLinearKalmanFilterInstantiation::initStateConstVel_MeasurePos(), vpLinearKalmanFilterInstantiation::initStateConstVelWithColoredNoise_MeasureVel(), and vpLinearKalmanFilterInstantiation::setStateModel().
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Size of the state vector .
Definition at line 114 of file vpKalmanFilter.h.
Referenced by vpLinearKalmanFilterInstantiation::filter(), init(), vpLinearKalmanFilterInstantiation::initStateConstAccWithColoredNoise_MeasureVel(), vpLinearKalmanFilterInstantiation::initStateConstVel_MeasurePos(), vpLinearKalmanFilterInstantiation::initStateConstVelWithColoredNoise_MeasureVel(), prediction(), and vpLinearKalmanFilterInstantiation::setStateModel().
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When set to true, print the content of internal variables during filtering() and prediction().
Definition at line 122 of file vpKalmanFilter.h.
Referenced by filtering(), and prediction().
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vpColVector vpKalmanFilter::Xest |
The updated state estimate where .
Definition at line 168 of file vpKalmanFilter.h.
Referenced by vpLinearKalmanFilterInstantiation::filter(), filtering(), init(), vpLinearKalmanFilterInstantiation::initStateConstAccWithColoredNoise_MeasureVel(), vpLinearKalmanFilterInstantiation::initStateConstVel_MeasurePos(), vpLinearKalmanFilterInstantiation::initStateConstVelWithColoredNoise_MeasureVel(), and prediction().
vpColVector vpKalmanFilter::Xpre |
The predicted state where .
Definition at line 173 of file vpKalmanFilter.h.
Referenced by filtering(), init(), and prediction().