/* ---------------------------------------------------------------------------- * GTSAM Copyright 2010, Georgia Tech Research Corporation, * Atlanta, Georgia 30332-0415 * All Rights Reserved * Authors: Frank Dellaert, et al. (see THANKS for the full author list) * See LICENSE for the license information * -------------------------------------------------------------------------- */ /** * @file IncrementalFixedLagSmoother.h * @brief An iSAM2-based fixed-lag smoother. * * @author Michael Kaess, Stephen Williams * @date Oct 14, 2012 */ // \callgraph #pragma once #include #include namespace gtsam { /** * This is a base class for the various HMF2 implementations. The HMF2 eliminates the factor graph * such that the active states are placed in/near the root. This base class implements a function * to calculate the ordering, and an update function to incorporate new factors into the HMF. */ class IncrementalFixedLagSmoother : public FixedLagSmoother { public: /// Typedef for a shared pointer to an Incremental Fixed-Lag Smoother typedef boost::shared_ptr shared_ptr; /** default constructor */ IncrementalFixedLagSmoother(double smootherLag = 0.0, const ISAM2Params& parameters = ISAM2Params()) : FixedLagSmoother(smootherLag), isam_(parameters) { }; /** destructor */ virtual ~IncrementalFixedLagSmoother() { }; /** Print the factor for debugging and testing (implementing Testable) */ virtual void print(const std::string& s = "IncrementalFixedLagSmoother:\n", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const; /** Check if two IncrementalFixedLagSmoother Objects are equal */ virtual bool equals(const FixedLagSmoother& rhs, double tol = 1e-9) const; /** Add new factors, updating the solution and relinearizing as needed. */ Result update(const NonlinearFactorGraph& newFactors = NonlinearFactorGraph(), const Values& newTheta = Values(), const KeyTimestampMap& timestamps = KeyTimestampMap()); /** Compute an estimate from the incomplete linear delta computed during the last update. * This delta is incomplete because it was not updated below wildfire_threshold. If only * a single variable is needed, it is faster to call calculateEstimate(const KEY&). */ Values calculateEstimate() const { return isam_.calculateEstimate(); } /** Compute an estimate for a single variable using its incomplete linear delta computed * during the last update. This is faster than calling the no-argument version of * calculateEstimate, which operates on all variables. * @param key * @return */ template VALUE calculateEstimate(Key key) const { return isam_.calculateEstimate(key); } /** return the current set of iSAM2 parameters */ const ISAM2Params& params() const { return isam_.params(); } protected: /** An iSAM2 object used to perform inference. The smoother lag is controlled * by what factors are removed each iteration */ ISAM2 isam_; /** Erase any keys associated with timestamps before the provided time */ void eraseKeysBefore(double timestamp); /** Fill in an iSAM2 ConstrainedKeys structure such that the provided keys are eliminated before all others */ void createOrderingConstraints(const std::set& marginalizableKeys, FastMap& constrainedKeys) const; private: /** Private methods for printing debug information */ static void PrintKeySet(const std::set& keys, const std::string& label = "Keys:"); static void PrintSymbolicFactor(const GaussianFactor::shared_ptr& factor, const gtsam::Ordering& ordering); static void PrintSymbolicGraph(const GaussianFactorGraph& graph, const gtsam::Ordering& ordering, const std::string& label = "Factor Graph:"); static void PrintSymbolicTree(const gtsam::ISAM2& isam, const std::string& label = "Bayes Tree:"); static void PrintSymbolicTreeHelper(const gtsam::ISAM2Clique::shared_ptr& clique, const gtsam::Ordering& ordering, const std::string indent = ""); }; // IncrementalFixedLagSmoother } /// namespace gtsam