Example #1
0
void BaseMultiEdge<D, E>::constructQuadraticForm()
{
  const InformationType& omega = _information;
  Matrix<double, D, 1> omega_r = - omega * _error;

  for (size_t i = 0; i < _vertices.size(); ++i) {
    OptimizableGraph::Vertex* from = static_cast<OptimizableGraph::Vertex*>(_vertices[i]);
    bool istatus = !(from->fixed());

    if (istatus) {
      const MatrixXd& A = _jacobianOplus[i];

      MatrixXd AtO = A.transpose() * omega;
      int fromDim = from->dimension();
      Map<MatrixXd> fromMap(from->hessianData(), fromDim, fromDim);
      Map<VectorXd> fromB(from->bData(), fromDim);

      // ii block in the hessian
#ifdef G2O_OPENMP
      from->lockQuadraticForm();
#endif
      fromMap.noalias() += AtO * A;
      fromB.noalias() += A.transpose() * omega_r;

      // compute the off-diagonal blocks ij for all j
      for (size_t j = i+1; j < _vertices.size(); ++j) {
        OptimizableGraph::Vertex* to = static_cast<OptimizableGraph::Vertex*>(_vertices[j]);
#ifdef G2O_OPENMP
        to->lockQuadraticForm();
#endif
        bool jstatus = !(to->fixed());
        if (jstatus) {
          const MatrixXd& B = _jacobianOplus[j];
          int idx = computeUpperTriangleIndex(i, j);
          assert(idx < (int)_hessian.size());
          HessianHelper& hhelper = _hessian[idx];
          if (hhelper.transposed) { // we have to write to the block as transposed
            hhelper.matrix.noalias() += B.transpose() * AtO.transpose();
          } else {
            hhelper.matrix.noalias() += AtO * B;
          }
        }
#ifdef G2O_OPENMP
        to->unlockQuadraticForm();
#endif
      }

#ifdef G2O_OPENMP
      from->unlockQuadraticForm();
#endif
    }

  }

}
  bool SparseOptimizer::buildIndexMapping
     (SparseOptimizer::VertexContainer& vlist)
  {
    if (! vlist.size())
    {
      _ivMap.clear();
      return false;
    }

    _ivMap.resize(vlist.size());
    size_t i = 0;
    // Recorre todos los vertices dandoles un indice.
    // Si el vertice es fijo, su indice sera -1
    // Para los vertices no fijos, les da un indice incremental.
    // Primero se les da a los vertices no marginalizables y luego a los que si.
    // Al final _ivMap contendra todos los vertices no fijos con los vertices
    // no marginalizables en las primeras posiciones de _ivMap
    for (int k=0; k<2; k++)
      for (VertexContainer::iterator it=vlist.begin(); it!=vlist.end(); it++)
      {
         OptimizableGraph::Vertex* v = *it;
         if (! v->fixed())
         {
            if (static_cast<int>(v->marginalized()) == k)
            {
               v->setTempIndex(i);
               _ivMap[i]=v;
               i++;
            }
         }else   v->setTempIndex(-1);
      }

    _ivMap.resize(i);
    return true;
  }
  bool SparseOptimizer::buildIndexMapping(SparseOptimizer::VertexContainer& vlist){
    if (! vlist.size()){
      _ivMap.clear();
      return false;
    }

    _ivMap.resize(vlist.size());
    size_t i = 0;
    for (int k=0; k<2; k++)
      for (VertexContainer::iterator it=vlist.begin(); it!=vlist.end(); ++it){
      OptimizableGraph::Vertex* v = *it;
      if (! v->fixed()){
        if (static_cast<int>(v->marginalized()) == k){
          v->setHessianIndex(i);
          _ivMap[i]=v;
          i++;
        }
      }
      else {
        v->setHessianIndex(-1);
      }
    }
    _ivMap.resize(i);
    return true;
  }
Example #4
0
  void SparseOptimizer::computeInitialGuess(EstimatePropagatorCost& costFunction)
  {
    OptimizableGraph::VertexSet emptySet;
    std::set<Vertex*> backupVertices;
    HyperGraph::VertexSet fixedVertices; // these are the root nodes where to start the initialization
    for (EdgeContainer::iterator it = _activeEdges.begin(); it != _activeEdges.end(); ++it) {
      OptimizableGraph::Edge* e = *it;
      for (size_t i = 0; i < e->vertices().size(); ++i) {
        OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(e->vertex(i));
	if (!v)
	  continue;
        if (v->fixed())
          fixedVertices.insert(v);
        else { // check for having a prior which is able to fully initialize a vertex
          for (EdgeSet::const_iterator vedgeIt = v->edges().begin(); vedgeIt != v->edges().end(); ++vedgeIt) {
            OptimizableGraph::Edge* vedge = static_cast<OptimizableGraph::Edge*>(*vedgeIt);
            if (vedge->vertices().size() == 1 && vedge->initialEstimatePossible(emptySet, v) > 0.) {
              //cerr << "Initialize with prior for " << v->id() << endl;
              vedge->initialEstimate(emptySet, v);
              fixedVertices.insert(v);
            }
          }
        }
        if (v->hessianIndex() == -1) {
          std::set<Vertex*>::const_iterator foundIt = backupVertices.find(v);
          if (foundIt == backupVertices.end()) {
            v->push();
            backupVertices.insert(v);
          }
        }
      }
    }

    EstimatePropagator estimatePropagator(this);
    estimatePropagator.propagate(fixedVertices, costFunction);

    // restoring the vertices that should not be initialized
    for (std::set<Vertex*>::iterator it = backupVertices.begin(); it != backupVertices.end(); ++it) {
      Vertex* v = *it;
      v->pop();
    }
    if (verbose()) {
      computeActiveErrors();
      cerr << "iteration= -1\t chi2= " << activeChi2()
          << "\t time= 0.0"
          << "\t cumTime= 0.0"
          << "\t (using initial guess from " << costFunction.name() << ")" << endl;
    }
  }
Example #5
0
void BaseMultiEdge<D, E>::linearizeOplus()
{
#ifdef G2O_OPENMP
  for (size_t i = 0; i < _vertices.size(); ++i) {
    OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(_vertices[i]);
    v->lockQuadraticForm();
  }
#endif

  const double delta = 1e-9;
  const double scalar = 1.0 / (2*delta);
  ErrorVector errorBak;
  ErrorVector errorBeforeNumeric = _error;

  for (size_t i = 0; i < _vertices.size(); ++i) {
    //Xi - estimate the jacobian numerically
    OptimizableGraph::Vertex* vi = static_cast<OptimizableGraph::Vertex*>(_vertices[i]);

    if (vi->fixed())
      continue;

    const int vi_dim = vi->dimension();
#ifdef _MSC_VER
    double* add_vi = new double[vi_dim];
#else
    double add_vi[vi_dim];
#endif
    std::fill(add_vi, add_vi + vi_dim, 0.0);
    if (_jacobianOplus[i].rows() != _dimension || _jacobianOplus[i].cols() != vi_dim)
      _jacobianOplus[i].resize(_dimension, vi_dim);
    // add small step along the unit vector in each dimension
    for (int d = 0; d < vi_dim; ++d) {
      vi->push();
      add_vi[d] = delta;
      vi->oplus(add_vi);
      computeError();
      errorBak = _error;
      vi->pop();
      vi->push();
      add_vi[d] = -delta;
      vi->oplus(add_vi);
      computeError();
      errorBak -= _error;
      vi->pop();
      add_vi[d] = 0.0;

      _jacobianOplus[i].col(d) = scalar * errorBak;
    } // end dimension
#ifdef _MSC_VER
    delete[] add_vi;
#endif
  }
  _error = errorBeforeNumeric;

#ifdef G2O_OPENMP
  for (int i = (int)(_vertices.size()) - 1; i >= 0; --i) {
    OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(_vertices[i]);
    v->unlockQuadraticForm();
  }
#endif

}
Example #6
0
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);
  if (maxIterations > 0 && !i){
    cerr << "optimize failed, result might be invalid" << endl;
  }

  if (laserOffset) {
    cerr << "Calibrated laser offset (x, y, theta):" << laserOffset->estimate().toVector().transpose() << endl;
  }

  if (odomParamsVertex) {
    cerr << "Odometry parameters (scaling factors (v_l, v_r, b)): " << odomParamsVertex->estimate().transpose() << endl;
  }

  cerr << "vertices: " << optimizer.vertices().size() << endl;
  cerr << "edges: " << optimizer.edges().size() << endl;

  if (dumpGraphFilename.size() > 0) {
    cerr << "Writing " << dumpGraphFilename << " ... ";
    optimizer.save(dumpGraphFilename.c_str());
    cerr << "done." << endl;
  }

  // optional input of a seperate file for applying the odometry calibration
  if (odomTestFilename.size() > 0) {

    DataQueue testRobotLaserQueue;
    int numTestOdom = Gm2dlIO::readRobotLaser(odomTestFilename, testRobotLaserQueue);
    if (numTestOdom == 0) {
      cerr << "Unable to read test data" << endl;
    } else {

      ofstream rawStream("odometry_raw.txt");
      ofstream calibratedStream("odometry_calibrated.txt");
      const Vector3d& odomCalib = odomParamsVertex->estimate();
      RobotLaser* prev = dynamic_cast<RobotLaser*>(testRobotLaserQueue.buffer().begin()->second);
      SE2 prevCalibratedPose = prev->odomPose();

      for (DataQueue::Buffer::const_iterator it = testRobotLaserQueue.buffer().begin(); it != testRobotLaserQueue.buffer().end(); ++it) {
        RobotLaser* cur = dynamic_cast<RobotLaser*>(it->second);
        assert(cur);

        double dt = cur->timestamp() - prev->timestamp();
        SE2 motion = prev->odomPose().inverse() * cur->odomPose();

        // convert to velocity measurment
        MotionMeasurement motionMeasurement(motion.translation().x(), motion.translation().y(), motion.rotation().angle(), dt);
        VelocityMeasurement velocityMeasurement = OdomConvert::convertToVelocity(motionMeasurement);

        // apply calibration
        VelocityMeasurement calibratedVelocityMeasurment = velocityMeasurement;
        calibratedVelocityMeasurment.setVl(odomCalib(0) * calibratedVelocityMeasurment.vl());
        calibratedVelocityMeasurment.setVr(odomCalib(1) * calibratedVelocityMeasurment.vr());
        MotionMeasurement mm = OdomConvert::convertToMotion(calibratedVelocityMeasurment, odomCalib(2));

        // combine calibrated odometry with the previous pose
        SE2 remappedOdom;
        remappedOdom.fromVector(mm.measurement());
        SE2 calOdomPose = prevCalibratedPose * remappedOdom;

        // write output
        rawStream << prev->odomPose().translation().x() << " " << prev->odomPose().translation().y() << " " << prev->odomPose().rotation().angle() << endl;
        calibratedStream << calOdomPose.translation().x() << " " << calOdomPose.translation().y() << " " << calOdomPose.rotation().angle() << endl;

        prevCalibratedPose = calOdomPose;
        prev = cur;
      }
    }

  }

  if (outputfilename.size() > 0) {
    Gm2dlIO::updateLaserData(optimizer);
    cerr << "Writing " << outputfilename << " ... ";
    bool writeStatus = Gm2dlIO::writeGm2dl(outputfilename, optimizer);
    cerr << (writeStatus ? "done." : "failed") << endl;
  }

  return 0;
}