optimization_algorithm_gauss_newton.h

// g2o - General Graph Optimization
// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// * Redistributions of source code must retain the above copyright notice,
//   this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright
//   notice, this list of conditions and the following disclaimer in the
//   documentation and/or other materials provided with the distribution.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
// IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
// TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
// PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
// HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
// TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
#ifndef G2O_OPTIMIZATION_ALGORITHM_GAUSS_NEWTON_H
#define G2O_OPTIMIZATION_ALGORITHM_GAUSS_NEWTON_H
 
#include "optimization_algorithm_with_hessian.h"
 
namespace NDEVR {

    template<class t_type>
    class  OptimizationAlgorithmGaussNewton : public OptimizationAlgorithmWithHessian<t_type>
    {
    public:
        explicit OptimizationAlgorithmGaussNewton() {};
        virtual ~OptimizationAlgorithmGaussNewton() {};
        void optimize(uint04 iterations, bool online, IndexScratch& scratch)
        {
            //WLock lock(blockPoseIndices);
            if (!OptimizationAlgorithmWithHessian<t_type>::optimizer().isReadyToUpdate())
                return;
            if (!OptimizationAlgorithmWithHessian<t_type>::init(online))
                return;
            for (uint04 i = 0; i < iterations; i++)
            {
                if (OptimizationAlgorithmWithHessian<t_type>::optimizer().terminate())
                    return;
                OptimizationAlgorithm::SolverResult result = solve(i, online, scratch);
                if (result != OptimizationAlgorithm::OK)
                    return;
            }
        }

        virtual OptimizationAlgorithm::SolverResult solve(int iteration, bool online, IndexScratch& scratch)
        {
            bool ok = true;
            OptimizationAlgorithmWithHessian<t_type>::optimizer().computeActiveErrors();
            if (iteration == 0 && !online) // built up the CCS structure, here due to easy time measure
            {
                ok = OptimizationAlgorithmWithHessian<t_type>::solver.buildStructure(false, scratch);
                if (!ok)
                    return OptimizationAlgorithm::Fail;
            }
            OptimizationAlgorithmWithHessian<t_type>::solver.buildSystem();
            ok = OptimizationAlgorithmWithHessian<t_type>::solver.solve();
            OptimizationAlgorithmWithHessian<t_type>::optimizer().update(OptimizationAlgorithmWithHessian<t_type>::solver.x());
 
            if (ok)
                return OptimizationAlgorithm::OK;
            else
                return OptimizationAlgorithm::Fail;
        }
    };
 
} // end namespace
 
#endif