gtsam  4.0.0
gtsam
gtsam::TransformBtwRobotsUnaryFactor< VALUE > Class Template Reference
+ Inheritance diagram for gtsam::TransformBtwRobotsUnaryFactor< VALUE >:

Public Member Functions

 TransformBtwRobotsUnaryFactor ()
 default constructor - only use for serialization
 
 TransformBtwRobotsUnaryFactor (Key key, const VALUE &measured, Key keyA, Key keyB, const gtsam::Values &valA, const gtsam::Values &valB, const SharedGaussian &model)
 Constructor.
 
virtual gtsam::NonlinearFactor::shared_ptr clone () const
 Clone.
 
virtual void print (const std::string &s, const KeyFormatter &keyFormatter=DefaultKeyFormatter) const
 implement functions needed for Testable More...
 
virtual bool equals (const NonlinearFactor &f, double tol=1e-9) const
 equals
 
void setValAValB (const gtsam::Values &valA, const gtsam::Values &valB)
 implement functions needed to derive from Factor
 
virtual double error (const gtsam::Values &x) const
 Calculate the error of the factor This is typically equal to log-likelihood, e.g. More...
 
virtual boost::shared_ptr< gtsam::GaussianFactorlinearize (const gtsam::Values &x) const
 Linearize a non-linearFactorN to get a gtsam::GaussianFactor, \( Ax-b \approx h(x+\delta x)-z = h(x) + A \delta x - z \) Hence \( b = z - h(x) = - \mathtt{error\_vector}(x) \).
 
gtsam::Vector whitenedError (const gtsam::Values &x, boost::optional< std::vector< gtsam::Matrix > & > H=boost::none) const
 
gtsam::Vector unwhitenedError (const gtsam::Values &x) const
 
std::size_t size () const
 number of variables attached to this factor
 
virtual size_t dim () const
 get the dimension of the factor (number of rows on linearization)
 

Public Types

typedef VALUE T
 
typedef boost::shared_ptr< TransformBtwRobotsUnaryFactorshared_ptr
 concept check by type
 

Friends

class boost::serialization::access
 Serialization function.
 

Member Function Documentation

◆ error()

template<class VALUE >
virtual double gtsam::TransformBtwRobotsUnaryFactor< VALUE >::error ( const gtsam::Values c) const
inlinevirtual

Calculate the error of the factor This is typically equal to log-likelihood, e.g.

\( 0.5(h(x)-z)^2/sigma^2 \) in case of Gaussian. You can override this for systems with unusual noise models.

Implements gtsam::NonlinearFactor.

◆ print()

template<class VALUE >
virtual void gtsam::TransformBtwRobotsUnaryFactor< VALUE >::print ( const std::string &  s,
const KeyFormatter keyFormatter = DefaultKeyFormatter 
) const
inlinevirtual

implement functions needed for Testable

print

Reimplemented from gtsam::NonlinearFactor.


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