simple_optimize.cpp

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// 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.

#include <iostream>

#include "g2o/core/sparse_optimizer.h"
#include "g2o/core/block_solver.h"
#include "g2o/core/optimization_algorithm_gauss_newton.h"
#include "g2o/core/optimization_algorithm_levenberg.h"
#include "g2o/solvers/csparse/linear_solver_csparse.h"

#include "g2o/core/factory.h"
//#include "g2o/types/slam3d/types_slam3d.h"
//#include "g2o/types/slam2d/types_slam2d.h"

#include "g2o/stuff/command_args.h"

using namespace std;
using namespace g2o;

// we use the 2D and 3D SLAM types here
G2O_USE_TYPE_GROUP(slam2d);
G2O_USE_TYPE_GROUP(slam3d);

int main(int argc, char** argv)
{
  // Command line parsing
  int maxIterations;
  string outputFilename;
  string inputFilename;
  CommandArgs arg;
  arg.param("i", maxIterations, 10, "perform n iterations, if negative consider the gain");
  arg.param("o", outputFilename, "", "output final version of the graph");
  arg.paramLeftOver("graph-input", inputFilename, "", "graph file which will be processed");
  arg.parseArgs(argc, argv);

  // create the linear solver
  BlockSolverX::LinearSolverType * linearSolver = new LinearSolverCSparse<BlockSolverX::PoseMatrixType>();

  // create the block solver on top of the linear solver
  BlockSolverX* blockSolver = new BlockSolverX(linearSolver);

  // create the algorithm to carry out the optimization
  //OptimizationAlgorithmGaussNewton* optimizationAlgorithm = new OptimizationAlgorithmGaussNewton(blockSolver);
  OptimizationAlgorithmLevenberg* optimizationAlgorithm = new OptimizationAlgorithmLevenberg(blockSolver);

  // NOTE: We skip to fix a variable here, either this is stored in the file
  // itself or Levenberg will handle it.

  // create the optimizer to load the data and carry out the optimization
  SparseOptimizer optimizer;
  optimizer.setVerbose(true);
  optimizer.setAlgorithm(optimizationAlgorithm);

  ifstream ifs(inputFilename.c_str());
  if (! ifs) {
    cerr << "unable to open " << inputFilename << endl;
    return 1;
  }
  optimizer.load(ifs);
  optimizer.initializeOptimization();
  optimizer.optimize(maxIterations);

  if (outputFilename.size() > 0) {
    if (outputFilename == "-") {
      cerr << "saving to stdout";
      optimizer.save(cout);
    } else {
      cerr << "saving " << outputFilename << " ... ";
      optimizer.save(outputFilename.c_str());
    }
    cerr << "done." << endl;
  }
  return 0;
}