Base class for all Gaussian innovations defined in the module rtslam. More...

Detailed Description

Base class for all Gaussian innovations defined in the module rtslam.

It implements the trivial innovation model:

which is, after all,

so usual in Kalman filtering.

It also returns the Jacobian matrices:

Derive this class and overload the methods if you need other non-trivial innovation models (useful for line landmarks).

Definition at line 45 of file innovation.hpp.

Inheritance diagram for jafar::rtslam::Innovation:

Public Member Functions
	Innovation (const size_t _size)
	Size construction.
virtual	~Innovation ()
	mandatory virtual destructor
void	invertCov ()
	the inverse of the innovation covariance.
double	mahalanobis ()
	The Mahalanobis distance.
Public Attributes
jblas::sym_mat	iP_
	The inverse of the innovation covariances matrix.
double	mahalanobis_
	The Mahalanobis distance from the measurement to the expectation.
double	relevance
	The Mahalanobis distance of innovation.x wrt measurement.P.

Constructor & Destructor Documentation

jafar::rtslam::Innovation::Innovation ( const size_t _size )

Size construction.

Use this constructor for usual innovations with equal expectation, measurement and innovation sizes.

Parameters:

_size the innovation size

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