gtsam/gtsam_unstable/nonlinear/IncrementalFixedLagSmoother.h

104 lines
4.1 KiB
C++

/* ----------------------------------------------------------------------------
* 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 <gtsam_unstable/nonlinear/FixedLagSmoother.h>
#include <gtsam/nonlinear/ISAM2.h>
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<IncrementalFixedLagSmoother> 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<class VALUE>
VALUE calculateEstimate(Key key) const {
return isam_.calculateEstimate<VALUE>(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<Key>& marginalizableKeys, FastMap<Key,int>& constrainedKeys) const;
private:
/** Private methods for printing debug information */
static void PrintKeySet(const std::set<Key>& 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