47 typedef boost::shared_ptr<ExtendedKalmanFilter<VALUE> > shared_ptr;
57 const Values& linearizationPoints,
66 noiseModel::Gaussian::shared_ptr P_initial);
73 void print(
const std::string& s=
"")
const {
74 std::cout << s <<
"\n";
76 priorFactor_->print(s+
"density");
84 T
predict(
const MotionFactor& motionFactor);
87 T
update(
const MeasurementFactor& measurementFactor);
Non-linear factor base classes.
T predict(const MotionFactor &motionFactor)
TODO: comment.
Definition: ExtendedKalmanFilter-inl.h:80
T update(const MeasurementFactor &measurementFactor)
TODO: comment.
Definition: ExtendedKalmanFilter-inl.h:115
Class to perform generic Kalman Filtering using nonlinear factor graphs.
Factor Graph Constsiting of non-linear factors.
A non-templated config holding any types of Manifold-group elements.
Definition: Values.h:75
void print(const std::string &s="") const
print
Definition: ExtendedKalmanFilter.h:73
size_t Key
Integer nonlinear key type.
Definition: types.h:59
A convenient base class for creating your own NoiseModelFactor with 1 variable.
Definition: NonlinearFactor.h:354
This is a generic Extended Kalman Filter class implemented using nonlinear factors.
Definition: ExtendedKalmanFilter.h:44
A Linear Factor Graph is a factor graph where all factors are Gaussian, i.e.
Definition: GaussianFactorGraph.h:65
boost::shared_ptr< This > shared_ptr
shared_ptr to this class
Definition: JacobianFactor.h:87