C++ SparseOptimizer::setForceStopFlag方法代码示例

//.........这里部分代码省略.........

#ifndef G2O_DISABLE_DYNAMIC_LOADING_OF_LIBRARIES
  // registering all the types from the libraries
  DlWrapper dlTypesWrapper;
  loadStandardTypes(dlTypesWrapper, argc, argv);
  // register all the solvers
  DlWrapper dlSolverWrapper;
  loadStandardSolver(dlSolverWrapper, argc, argv);
#else
  if (verbose)
    cout << "# linked version of g2o" << endl;
#endif

  OptimizationAlgorithmFactory* solverFactory = OptimizationAlgorithmFactory::instance();
  if (listSolvers) {
    solverFactory->listSolvers(cout);
  }

  if (listTypes) {
    Factory::instance()->printRegisteredTypes(cout, true);
  }

  if (listRobustKernels) {
    std::vector<std::string> kernels;
    RobustKernelFactory::instance()->fillKnownKernels(kernels);
    cout << "Robust Kernels:" << endl;
    for (size_t i = 0; i < kernels.size(); ++i) {
      cout << kernels[i] << endl;
    }
  }

  SparseOptimizer optimizer;
  optimizer.setVerbose(verbose);
  optimizer.setForceStopFlag(&hasToStop);

  SparseOptimizerTerminateAction* terminateAction = 0;
  if (maxIterations < 0) {
    cerr << "# setup termination criterion based on the gain of the iteration" << endl;
    maxIterations = maxIterationsWithGain;
    terminateAction = new SparseOptimizerTerminateAction;
    terminateAction->setGainThreshold(gain);
    terminateAction->setMaxIterations(maxIterationsWithGain);
    optimizer.addPostIterationAction(terminateAction);
  }

  // allocating the desired solver + testing whether the solver is okay
  OptimizationAlgorithmProperty solverProperty;
  optimizer.setAlgorithm(solverFactory->construct(strSolver, solverProperty));
  if (! optimizer.solver()) {
    cerr << "Error allocating solver. Allocating \"" << strSolver << "\" failed!" << endl;
    return 0;
  }
  
  if (solverProperties.size() > 0) {
    bool updateStatus = optimizer.solver()->updatePropertiesFromString(solverProperties);
    if (! updateStatus) {
      cerr << "Failure while updating the solver properties from the given string" << endl;
    }
  }
  if (solverProperties.size() > 0 || printSolverProperties) {
    optimizer.solver()->printProperties(cerr);
  }

  // Loading the input data
  if (loadLookup.size() > 0) {
    optimizer.setRenamedTypesFromString(loadLookup);

int main(int argc, char** argv)
{
  bool fixLaser;
  int maxIterations;
  bool verbose;
  string inputFilename;
  string outputfilename;
  string rawFilename;
  string odomTestFilename;
  string dumpGraphFilename;
  // command line parsing
  CommandArgs commandLineArguments;
  commandLineArguments.param("i", maxIterations, 10, "perform n iterations");
  commandLineArguments.param("v", verbose, false, "verbose output of the optimization process");
  commandLineArguments.param("o", outputfilename, "", "output final version of the graph");
  commandLineArguments.param("test", odomTestFilename, "", "apply odometry calibration to some test data");
  commandLineArguments.param("dump", dumpGraphFilename, "", "write the graph to the disk");
  commandLineArguments.param("fixLaser", fixLaser, false, "keep the laser offset fixed during optimization");
  commandLineArguments.paramLeftOver("gm2dl-input", inputFilename, "", "gm2dl file which will be processed");
  commandLineArguments.paramLeftOver("raw-log", rawFilename, "", "raw log file containing the odometry");

  commandLineArguments.parseArgs(argc, argv);

  SparseOptimizer optimizer;
  optimizer.setVerbose(verbose);
  optimizer.setForceStopFlag(&hasToStop);

  allocateSolverForSclam(optimizer);

  // loading
  if (! Gm2dlIO::readGm2dl(inputFilename, optimizer, false)) {
    cerr << "Error while loading gm2dl file" << endl;
  }
  DataQueue robotLaserQueue;
  int numLaserOdom = Gm2dlIO::readRobotLaser(rawFilename, robotLaserQueue);
  if (numLaserOdom == 0) {
    cerr << "No raw information read" << endl;
    return 0;
  }
  cerr << "Read " << numLaserOdom << " laser readings from file" << endl;

  bool gaugeFreedom = optimizer.gaugeFreedom();

  OptimizableGraph::Vertex* gauge = optimizer.findGauge();
  if (gaugeFreedom) {
    if (! gauge) {
      cerr <<  "# cannot find a vertex to fix in this thing" << endl;
      return 2;
    } else {
      cerr << "# graph is fixed by node " << gauge->id() << endl;
      gauge->setFixed(true);
    }
  } else {
    cerr << "# graph is fixed by priors" << endl;
  }

  addOdometryCalibLinksDifferential(optimizer, robotLaserQueue);

  // sanity check
  HyperDijkstra d(&optimizer);
  UniformCostFunction f;
  d.shortestPaths(gauge, &f);
  //cerr << PVAR(d.visited().size()) << endl;

  if (d.visited().size()!=optimizer.vertices().size()) {
    cerr << CL_RED("Warning: d.visited().size() != optimizer.vertices().size()") << endl;
    cerr << "visited: " << d.visited().size() << endl;
    cerr << "vertices: " << optimizer.vertices().size() << endl;
    if (1)
      for (SparseOptimizer::VertexIDMap::const_iterator it = optimizer.vertices().begin(); it != optimizer.vertices().end(); ++it) {
        OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(it->second);
        if (d.visited().count(v) == 0) {
          cerr << "\t unvisited vertex " << it->first << " " << (void*)v << endl;
          v->setFixed(true);
        }
      }
  }

  for (SparseOptimizer::VertexIDMap::const_iterator it = optimizer.vertices().begin(); it != optimizer.vertices().end(); ++it) {
    OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(it->second);
    if (v->fixed()) {
      cerr << "\t fixed vertex " << it->first << endl;
    }
  }

  VertexSE2* laserOffset = dynamic_cast<VertexSE2*>(optimizer.vertex(Gm2dlIO::ID_LASERPOSE));
  VertexOdomDifferentialParams* odomParamsVertex = dynamic_cast<VertexOdomDifferentialParams*>(optimizer.vertex(Gm2dlIO::ID_ODOMCALIB));

  if (fixLaser) {
    cerr << "Fix position of the laser offset" << endl;
    laserOffset->setFixed(true);
  }

  signal(SIGINT, sigquit_handler);
  cerr << "Doing full estimation" << endl;
  optimizer.initializeOptimization();
  optimizer.computeActiveErrors();
  cerr << "Initial chi2 = " << FIXED(optimizer.chi2()) << endl;

  int i=optimizer.optimize(maxIterations);
//.........这里部分代码省略.........