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gtsam::NonlinearFactor::shared_ptr | clone () const override |
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| CombinedImuFactor () |
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| CombinedImuFactor (Key pose_i, Key vel_i, Key pose_j, Key vel_j, Key bias_i, Key bias_j, const PreintegratedCombinedMeasurements &preintegratedMeasurements) |
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Vector | evaluateError (const Pose3 &pose_i, const Vector3 &vel_i, const Pose3 &pose_j, const Vector3 &vel_j, const imuBias::ConstantBias &bias_i, const imuBias::ConstantBias &bias_j, OptionalMatrixType H1, OptionalMatrixType H2, OptionalMatrixType H3, OptionalMatrixType H4, OptionalMatrixType H5, OptionalMatrixType H6) const override |
| vector of errors More...
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const PreintegratedCombinedMeasurements & | preintegratedMeasurements () const |
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| ~CombinedImuFactor () override |
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Key | key () const |
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virtual Vector | unwhitenedError (const Values &x, OptionalMatrixVecType H=nullptr) const =0 |
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Vector | unwhitenedError (const Values &x, std::vector< Matrix > &H) const |
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| ~NoiseModelFactorN () override |
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| NoiseModelFactorN () |
| Default Constructor for I/O. More...
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| NoiseModelFactorN (const SharedNoiseModel &noiseModel, KeyType< ValueTypes >... keys) |
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| NoiseModelFactorN (const SharedNoiseModel &noiseModel, CONTAINER keys) |
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Vector | unwhitenedError (const Values &x, OptionalMatrixVecType H=nullptr) const override |
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virtual Vector | evaluateError (const ValueTypes &... x, OptionalMatrixTypeT< ValueTypes >... H) const=0 |
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Vector | evaluateError (const ValueTypes &... x, MatrixTypeT< ValueTypes > &... H) const |
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Vector | evaluateError (const ValueTypes &... x) const |
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AreAllMatrixRefs< Vector, OptionalJacArgs... > | evaluateError (const ValueTypes &... x, OptionalJacArgs &&... H) const |
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AreAllMatrixPtrs< Vector, OptionalJacArgs... > | evaluateError (const ValueTypes &... x, OptionalJacArgs &&... H) const |
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Key | key1 () const |
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Key | key2 () const |
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Key | key3 () const |
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Key | key4 () const |
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Key | key5 () const |
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Key | key6 () const |
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shared_ptr | cloneWithNewNoiseModel (const SharedNoiseModel newNoise) const |
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size_t | dim () const override |
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bool | equals (const NonlinearFactor &f, double tol=1e-9) const override |
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double | error (const Values &c) const override |
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std::shared_ptr< GaussianFactor > | linearize (const Values &x) const override |
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const SharedNoiseModel & | noiseModel () const |
| access to the noise model More...
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| NoiseModelFactor () |
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template<typename CONTAINER > |
| NoiseModelFactor (const SharedNoiseModel &noiseModel, const CONTAINER &keys) |
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void | print (const std::string &s="", const KeyFormatter &keyFormatter=DefaultKeyFormatter) const override |
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Vector | unweightedWhitenedError (const Values &c) const |
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Vector | unwhitenedError (const Values &x, std::vector< Matrix > &H) const |
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double | weight (const Values &c) const |
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Vector | whitenedError (const Values &c) const |
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| ~NoiseModelFactor () override |
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| NonlinearFactor () |
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template<typename CONTAINER > |
| NonlinearFactor (const CONTAINER &keys) |
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double | error (const HybridValues &c) const override |
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virtual bool | active (const Values &) const |
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virtual shared_ptr | rekey (const std::map< Key, Key > &rekey_mapping) const |
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virtual shared_ptr | rekey (const KeyVector &new_keys) const |
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virtual bool | sendable () const |
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virtual | ~Factor ()=default |
| Default destructor. More...
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bool | empty () const |
| Whether the factor is empty (involves zero variables). More...
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Key | front () const |
| First key. More...
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Key | back () const |
| Last key. More...
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const_iterator | find (Key key) const |
| find More...
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const KeyVector & | keys () const |
| Access the factor's involved variable keys. More...
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const_iterator | begin () const |
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const_iterator | end () const |
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size_t | size () const |
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virtual void | printKeys (const std::string &s="Factor", const KeyFormatter &formatter=DefaultKeyFormatter) const |
| print only keys More...
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bool | equals (const This &other, double tol=1e-9) const |
| check equality More...
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KeyVector & | keys () |
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iterator | begin () |
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iterator | end () |
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constexpr static auto | N |
| N is the number of variables (N-way factor) More...
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using | Base = NoiseModelFactor |
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using | KeyType = Key |
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using | MatrixTypeT = Matrix |
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using | OptionalMatrixTypeT = Matrix * |
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using | This = NoiseModelFactorN< ValueTypes... > |
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using | IsConvertible = typename std::enable_if< std::is_convertible< From, To >::value, void >::type |
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using | IndexIsValid = typename std::enable_if<(I >=1) &&(I<=N), void >::type |
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using | ContainerElementType = typename std::decay< decltype(*std::declval< Container >().begin())>::type |
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using | IsContainerOfKeys = IsConvertible< ContainerElementType< Container >, Key > |
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using | AreAllMatrixRefs = std::enable_if_t<(... &&std::is_convertible< Args, Matrix & >::value), Ret > |
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using | IsMatrixPointer = std::is_same< typename std::decay_t< Arg >, Matrix * > |
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using | IsNullpointer = std::is_same< typename std::decay_t< Arg >, std::nullptr_t > |
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using | AreAllMatrixPtrs = std::enable_if_t<(... &&(IsMatrixPointer< Args >::value||IsNullpointer< Args >::value)), Ret > |
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typedef NonlinearFactor | Base |
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typedef NoiseModelFactor | This |
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typedef Factor | Base |
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typedef NonlinearFactor | This |
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| NoiseModelFactor (const SharedNoiseModel &noiseModel) |
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| Factor () |
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template<typename CONTAINER > |
| Factor (const CONTAINER &keys) |
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template<typename ITERATOR > |
| Factor (ITERATOR first, ITERATOR last) |
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template<typename CONTAINER > |
static Factor | FromKeys (const CONTAINER &keys) |
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template<typename ITERATOR > |
static Factor | FromIterators (ITERATOR first, ITERATOR last) |
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SharedNoiseModel | noiseModel_ |
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KeyVector | keys_ |
| The keys involved in this factor. More...
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CombinedImuFactor is a 6-ways factor involving previous state (pose and velocity of the vehicle, as well as bias at previous time step), and current state (pose, velocity, bias at current time step). Following the pre- integration scheme proposed in [2], the CombinedImuFactor includes many IMU measurements, which are "summarized" using the PreintegratedCombinedMeasurements class. There are 3 main differences wrpt the ImuFactor class: 1) The factor is 6-ways, meaning that it also involves both biases (previous and current time step).Therefore, the factor internally imposes the biases to be slowly varying; in particular, the matrices "biasAccCovariance" and "biasOmegaCovariance" described the random walk that models bias evolution. 2) The preintegration covariance takes into account the noise in the bias estimate used for integration. 3) The covariance matrix of the PreintegratedCombinedMeasurements preserves the correlation between the bias uncertainty and the preintegrated measurements uncertainty.
Definition at line 205 of file CombinedImuFactor.h.