#include <mrpt/poses/CPose3DPDFSOG.h>
Classes | |
struct | TGaussianMode |
The struct for each mode:. More... | |
Public Types | |
typedef std::deque< TGaussianMode > | TModesList |
typedef std::deque < TGaussianMode > ::const_iterator | const_iterator |
typedef std::deque < TGaussianMode >::iterator | iterator |
Public Member Functions | |
CPose3DPDFSOG (size_t nModes=1) | |
Default constructor. | |
void | clear () |
Clear all the gaussian modes. | |
void | resize (const size_t N) |
Set the number of SOG modes. | |
size_t | size () const |
Return the number of Gaussian modes. | |
bool | empty () const |
Return whether there is any Gaussian mode. | |
iterator | begin () |
iterator | end () |
const_iterator | begin () const |
const_iterator | end () const |
void | getMean (CPose3D &mean_pose) const |
Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF), computed as a weighted average over all m_particles. | |
void | getCovarianceAndMean (CMatrixDouble66 &cov, CPose3D &mean_point) const |
Returns an estimate of the pose covariance matrix (6x6 cov matrix) and the mean, both at once. | |
void | normalizeWeights () |
Normalize the weights in m_modes such as the maximum log-weight is 0. | |
void | getMostLikelyMode (CPose3DPDFGaussian &outVal) const |
Return the Gaussian mode with the highest likelihood (or an empty Gaussian if there are no modes in this SOG). | |
void | copyFrom (const CPose3DPDF &o) |
Copy operator, translating if necesary (for example, between particles and gaussian representations). | |
void | saveToTextFile (const std::string &file) const |
Save the density to a text file, with the following format: There is one row per Gaussian "mode", and each row contains 10 elements:
| |
void | changeCoordinatesReference (const CPose3D &newReferenceBase) |
This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which "to project" the current pdf. | |
void | bayesianFusion (CPose3DPDF &p1, CPose3DPDF &p2) |
Bayesian fusion of two pose distributions, then save the result in this object (WARNING: Currently p1 must be a mrpt::poses::CPose3DPDFSOG object and p2 a mrpt::poses::CPose3DPDFSOG object). | |
void | drawSingleSample (CPose3D &outPart) const |
Draws a single sample from the distribution. | |
void | drawManySamples (size_t N, std::vector< vector_double > &outSamples) const |
Draws a number of samples from the distribution, and saves as a list of 1x6 vectors, where each row contains a (x,y,z,yaw,pitch,roll) datum. | |
void | inverse (CPose3DPDF &o) const |
Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF. | |
void | appendFrom (const CPose3DPDFSOG &o) |
Append the Gaussian modes from "o" to the current set of modes of "this" density. | |
Protected Member Functions | |
void | assureSymmetry () |
Assures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor lead to non-symmetric matrixes!). | |
Protected Attributes | |
TModesList | m_modes |
Access directly to this array for modify the modes as desired. |
This class implements that PDF as the following multi-modal Gaussian distribution:
Where the number of modes N is the size of CPose3DPDFSOG::m_modes. Angles are always in radians.
See mrpt::poses::CPose3DPDF for more details.
Definition at line 53 of file CPose3DPDFSOG.h.
typedef std::deque<TGaussianMode>::const_iterator mrpt::poses::CPose3DPDFSOG::const_iterator |
Definition at line 76 of file CPose3DPDFSOG.h.
typedef std::deque<TGaussianMode>::iterator mrpt::poses::CPose3DPDFSOG::iterator |
Definition at line 77 of file CPose3DPDFSOG.h.
typedef std::deque<TGaussianMode> mrpt::poses::CPose3DPDFSOG::TModesList |
Definition at line 75 of file CPose3DPDFSOG.h.
mrpt::poses::CPose3DPDFSOG::CPose3DPDFSOG | ( | size_t | nModes = 1 |
) |
void mrpt::poses::CPose3DPDFSOG::appendFrom | ( | const CPose3DPDFSOG & | o | ) |
Append the Gaussian modes from "o" to the current set of modes of "this" density.
void mrpt::poses::CPose3DPDFSOG::assureSymmetry | ( | ) | [protected] |
Assures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor lead to non-symmetric matrixes!).
void mrpt::poses::CPose3DPDFSOG::bayesianFusion | ( | CPose3DPDF & | p1, | |
CPose3DPDF & | p2 | |||
) | [virtual] |
Bayesian fusion of two pose distributions, then save the result in this object (WARNING: Currently p1 must be a mrpt::poses::CPose3DPDFSOG object and p2 a mrpt::poses::CPose3DPDFSOG object).
Implements mrpt::poses::CPose3DPDF.
const_iterator mrpt::poses::CPose3DPDFSOG::begin | ( | ) | const [inline] |
Definition at line 103 of file CPose3DPDFSOG.h.
iterator mrpt::poses::CPose3DPDFSOG::begin | ( | ) | [inline] |
Definition at line 101 of file CPose3DPDFSOG.h.
void mrpt::poses::CPose3DPDFSOG::changeCoordinatesReference | ( | const CPose3D & | newReferenceBase | ) | [virtual] |
This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which "to project" the current pdf.
Result PDF substituted the currently stored one in the object.
Implements mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >.
void mrpt::poses::CPose3DPDFSOG::clear | ( | ) |
Clear all the gaussian modes.
void mrpt::poses::CPose3DPDFSOG::copyFrom | ( | const CPose3DPDF & | o | ) | [virtual] |
Copy operator, translating if necesary (for example, between particles and gaussian representations).
Implements mrpt::poses::CPose3DPDF.
void mrpt::poses::CPose3DPDFSOG::drawManySamples | ( | size_t | N, | |
std::vector< vector_double > & | outSamples | |||
) | const [virtual] |
Draws a number of samples from the distribution, and saves as a list of 1x6 vectors, where each row contains a (x,y,z,yaw,pitch,roll) datum.
Reimplemented from mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >.
void mrpt::poses::CPose3DPDFSOG::drawSingleSample | ( | CPose3D & | outPart | ) | const |
Draws a single sample from the distribution.
bool mrpt::poses::CPose3DPDFSOG::empty | ( | ) | const [inline] |
const_iterator mrpt::poses::CPose3DPDFSOG::end | ( | ) | const [inline] |
Definition at line 104 of file CPose3DPDFSOG.h.
iterator mrpt::poses::CPose3DPDFSOG::end | ( | ) | [inline] |
Definition at line 102 of file CPose3DPDFSOG.h.
void mrpt::poses::CPose3DPDFSOG::getCovarianceAndMean | ( | CMatrixDouble66 & | cov, | |
CPose3D & | mean_point | |||
) | const |
Returns an estimate of the pose covariance matrix (6x6 cov matrix) and the mean, both at once.
void mrpt::poses::CPose3DPDFSOG::getMean | ( | CPose3D & | mean_pose | ) | const |
Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF), computed as a weighted average over all m_particles.
void mrpt::poses::CPose3DPDFSOG::getMostLikelyMode | ( | CPose3DPDFGaussian & | outVal | ) | const |
Return the Gaussian mode with the highest likelihood (or an empty Gaussian if there are no modes in this SOG).
void mrpt::poses::CPose3DPDFSOG::inverse | ( | CPose3DPDF & | o | ) | const [virtual] |
void mrpt::poses::CPose3DPDFSOG::normalizeWeights | ( | ) |
Normalize the weights in m_modes such as the maximum log-weight is 0.
void mrpt::poses::CPose3DPDFSOG::resize | ( | const size_t | N | ) |
Set the number of SOG modes.
void mrpt::poses::CPose3DPDFSOG::saveToTextFile | ( | const std::string & | file | ) | const [virtual] |
Save the density to a text file, with the following format: There is one row per Gaussian "mode", and each row contains 10 elements:
Implements mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >.
size_t mrpt::poses::CPose3DPDFSOG::size | ( | ) | const [inline] |
TModesList mrpt::poses::CPose3DPDFSOG::m_modes [protected] |
Access directly to this array for modify the modes as desired.
Note that no weight can be zero!! We must use pointers to satisfy the mem-alignment of the matrixes
Definition at line 88 of file CPose3DPDFSOG.h.
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