gtsam/examples/vSLAMexample/ISAMLoop-inl.h

94 lines
2.5 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
* -------------------------------------------------------------------------- */
/*
* ISAMLoop.cpp
*
* Created on: Jan 19, 2010
* Author: Viorela Ila and Richard Roberts
*/
#pragma once
#include <gtsam/linear/GaussianFactorGraph.h>
#include <gtsam/inference/ISAM-inl.h>
#include <gtsam/nonlinear/Ordering.h>
#include <boost/foreach.hpp>
#include "ISAMLoop.h"
using namespace gtsam;
/* ************************************************************************* */
template<class Values>
void ISAMLoop<Values>::update(const Factors& newFactors, const Values& initialValues) {
if(newFactors.size() > 0) {
// Reorder and relinearize every reorderInterval updates
if(reorderInterval_ > 0 && ++reorderCounter_ >= reorderInterval_) {
reorder_relinearize();
reorderCounter_ = 0;
}
factors_.push_back(newFactors);
// Linearize new factors and insert them
// TODO: optimize for whole config?
linPoint_.insert(initialValues);
// Augment ordering
BOOST_FOREACH(const typename Factors::sharedFactor& factor, newFactors) {
BOOST_FOREACH(const Symbol& key, factor->keys()) {
ordering_.tryInsert(key, ordering_.nVars());
}
}
boost::shared_ptr<GaussianFactorGraph> linearizedNewFactors(newFactors.linearize(linPoint_, ordering_));
// Update ISAM
isam.update(*linearizedNewFactors);
}
}
/* ************************************************************************* */
template<class Values>
void ISAMLoop<Values>::reorder_relinearize() {
cout << "Reordering, relinearizing..." << endl;
// Obtain the new linearization point
const Values newLinPoint = estimate();
isam.clear();
// Compute an ordering
ordering_ = *factors_.orderingCOLAMD(newLinPoint);
// Create a linear factor graph at the new linearization point
boost::shared_ptr<GaussianFactorGraph> gfg(factors_.linearize(newLinPoint, ordering_));
// Just recreate the whole BayesTree
isam.update(*gfg);
// Update linearization point
linPoint_ = newLinPoint;
}
/* ************************************************************************* */
template<class Values>
Values ISAMLoop<Values>::estimate() {
if(isam.size() > 0)
return linPoint_.expmap(optimize(isam), ordering_);
else
return linPoint_;
}