C++ VertexSE2::setEstimate方法代码示例

 void EdgeSE2::initialEstimate(const OptimizableGraph::VertexSet& from, OptimizableGraph::Vertex* /* to */)
 {
   VertexSE2* fromEdge = static_cast<VertexSE2*>(_vertices[0]);
   VertexSE2* toEdge   = static_cast<VertexSE2*>(_vertices[1]);
   if (from.count(fromEdge) > 0)
     toEdge->setEstimate(fromEdge->estimate() * _measurement);
   else
     fromEdge->setEstimate(toEdge->estimate() * _inverseMeasurement);
 }

void EdgeSE2PlaceVicinity::initialEstimate(
		const OptimizableGraph::VertexSet& from,
		OptimizableGraph::Vertex* /*to*/) {
	VertexSE2* fromEdge = static_cast<VertexSE2*>(_vertices[0]);
	VertexSE2* toEdge = static_cast<VertexSE2*>(_vertices[1]);

	if (from.count(fromEdge) > 0)
		toEdge->setEstimate(fromEdge->estimate());
	else
		fromEdge->setEstimate(toEdge->estimate());
  }

void EdgeSE2DistanceOrientation::initialEstimate(
		const OptimizableGraph::VertexSet& from,
		OptimizableGraph::Vertex* /*to*/) {
	VertexSE2* fromEdge = static_cast<VertexSE2*>(_vertices[0]);
	VertexSE2* toEdge = static_cast<VertexSE2*>(_vertices[1]);


	double dist = sqrt(_measurement[0] * _measurement[0] + _measurement[1] * _measurement[1]);
	double theta = _measurement[2];
	double x = dist * cos(theta), y = dist * sin(theta);
	SE2 tmpMeasurement(x,y,theta);
	SE2 inverseTmpMeasurement  = tmpMeasurement.inverse();
	if (from.count(fromEdge) > 0)
		toEdge->setEstimate(fromEdge->estimate() * tmpMeasurement);
	else
		fromEdge->setEstimate(toEdge->estimate() * inverseTmpMeasurement);
  }

void GraphSLAM::addData(SE2 currentOdom, RobotLaser* laser){
  boost::mutex::scoped_lock lockg(graphMutex);

  //Add current vertex
  VertexSE2 *v = new VertexSE2;

  SE2 displacement = _lastOdom.inverse() * currentOdom;
  SE2 currEst = _lastVertex->estimate() * displacement;

  v->setEstimate(currEst);
  v->setId(++_runningVertexId + idRobot() * baseId());
  //Add covariance information
  //VertexEllipse *ellipse = new VertexEllipse;
  //Matrix3f cov = Matrix3f::Zero(); //last vertex has zero covariance
  //ellipse->setCovariance(cov);
  //v->setUserData(ellipse);
  v->addUserData(laser);

  std::cout << std::endl << 
    "Current vertex: " << v->id() << 
    " Estimate: "<< v->estimate().translation().x() << 
    " " << v->estimate().translation().y() << 
    " " << v->estimate().rotation().angle() << std::endl;

  _graph->addVertex(v);

  //Add current odometry edge
  EdgeSE2 *e = new EdgeSE2;
  e->setId(++_runningEdgeId + idRobot() * baseId());
  e->vertices()[0] = _lastVertex;
  e->vertices()[1] = v;
      
  e->setMeasurement(displacement);
  
  // //Computing covariances depending on the displacement
  // Vector3d dis = displacement.toVector();
  // dis.x() = fabs(dis.x());
  // dis.y() = fabs(dis.y());
  // dis.z() = fabs(dis.z());
  // dis += Vector3d(1e-3,1e-3,1e-2);  
  // Matrix3d dis2 = dis*dis.transpose();
  // Matrix3d newcov = dis2.cwiseProduct(_odomK);

  e->setInformation(_odominf);
  _graph->addEdge(e);

  _odomEdges.insert(e);

  _lastOdom = currentOdom;
  _lastVertex = v;
}

void Localization::InitG2OGraph()
{
	optimizer.clear();
	LandmarkCount = 0;

	{
		VertexSE2 * l = new VertexSE2;
		l->setEstimate(Eigen::Vector3d(0, 0, 0));
		l->setFixed(true);
		l->setId(CenterL);
		optimizer.addVertex(l);
		LandmarkCount++;
	}
	{
		VertexSE2 * l = new VertexSE2;
		l->setEstimate(Eigen::Vector3d(A2, 0, 0));
		l->setFixed(true);
		l->setId(FrontL);
		optimizer.addVertex(l);
		LandmarkCount++;
	}
	{
		VertexSE2 * l = new VertexSE2;
		l->setEstimate(Eigen::Vector3d(-A2, 0, 0));
		l->setFixed(true);
		l->setId(BackL);
		optimizer.addVertex(l);
		LandmarkCount++;
	}
	{
		VertexSE2 * l = new VertexSE2;
		l->setEstimate(Eigen::Vector3d(0, -B2, 0));
		l->setFixed(true);
		l->setId(RightL);
		optimizer.addVertex(l);
		LandmarkCount++;
	}
	{
		VertexSE2 * l = new VertexSE2;
		l->setEstimate(Eigen::Vector3d(0, B2, 0));
		l->setFixed(true);
		l->setId(LeftL);
		optimizer.addVertex(l);
		LandmarkCount++;
	}
	PreviousVertexId = -1;
	CurrentVertexId = LandmarkCount;
	{
		VertexSE2 * l = new VertexSE2;
		l->setEstimate(
				Eigen::Vector3d(location.x, location.y, 0));
		l->setFixed(false);
		l->setId(LandmarkCount);
		optimizer.addVertex(l);
	}
}

	inline void updateVertexIdx()
	{
		if ((ros::Time::now() - lastSavedNodeTime).toSec() >= 0.03)
		{
			nodeCounter++;
			lastSavedNodeTime = ros::Time::now();
			PreviousVertexId = CurrentVertexId;
			CurrentVertexId++;
			if (CurrentVertexId - LandmarkCount >= 100)
			{
				CurrentVertexId = LandmarkCount;
			}

			{
				VertexSE2 * r = new VertexSE2;
				r->setEstimate(Eigen::Vector3d(location.x, location.y, 0));
				r->setFixed(false);
				r->setId(CurrentVertexId);
				if (optimizer.vertex(CurrentVertexId) != NULL)
				{
					optimizer.removeVertex(optimizer.vertex(CurrentVertexId));
				}

				optimizer.addVertex(r);
			}

			{
				EdgeSE2 * e = new EdgeSE2;
				e->vertices()[0] = optimizer.vertex(PreviousVertexId);
				e->vertices()[1] = optimizer.vertex(CurrentVertexId);
				Point2d dead_reck = getOdometryFromLastGet();
				e->setMeasurement(SE2(dead_reck.x, dead_reck.y, 0));
				Matrix3d information;
				information.fill(0.);
				information(0, 0) = 200;
				information(1, 1) = 200;
				information(2, 2) = 1;
				e->setInformation(information);
				optimizer.addEdge(e);
			}
		}
	}

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);

  allocateSolverForSclam(optimizer);

  // loading
  DataQueue odometryQueue;
  int numLaserOdom = Gm2dlIO::readRobotLaser(rawFilename, odometryQueue);
  if (numLaserOdom == 0) {
    cerr << "No raw information read" << endl;
    return 0;
  }
  cerr << "Read " << numLaserOdom << " laser readings from file" << endl;

  Eigen::Vector3d odomCalib(1., 1., 1.);
  SE2 initialLaserPose;
  DataQueue robotLaserQueue;
  int numRobotLaser = Gm2dlIO::readRobotLaser(inputFilename, robotLaserQueue);
  if (numRobotLaser == 0) {
    cerr << "No robot laser read" << endl;
    return 0;
  } else {
    RobotLaser* rl = dynamic_cast<RobotLaser*>(robotLaserQueue.buffer().begin()->second);
    initialLaserPose = rl->odomPose().inverse() * rl->laserPose();
    cerr << PVAR(initialLaserPose.toVector().transpose()) << endl;
  }

  // adding the measurements
  vector<MotionInformation, Eigen::aligned_allocator<MotionInformation> > motions;
  {
    std::map<double, RobotData*>::const_iterator it = robotLaserQueue.buffer().begin();
    std::map<double, RobotData*>::const_iterator prevIt = it++;
    for (; it != robotLaserQueue.buffer().end(); ++it) {
      MotionInformation mi;
      RobotLaser* prevLaser = dynamic_cast<RobotLaser*>(prevIt->second);
      RobotLaser* curLaser = dynamic_cast<RobotLaser*>(it->second);
      mi.laserMotion = prevLaser->laserPose().inverse() * curLaser->laserPose();
      // get the motion of the robot in that time interval
      RobotLaser* prevOdom = dynamic_cast<RobotLaser*>(odometryQueue.findClosestData(prevLaser->timestamp()));
      RobotLaser* curOdom = dynamic_cast<RobotLaser*>(odometryQueue.findClosestData(curLaser->timestamp()));
      mi.odomMotion = prevOdom->odomPose().inverse() * curOdom->odomPose();
      mi.timeInterval = prevOdom->timestamp() - curOdom->timestamp();
      prevIt = it;
      motions.push_back(mi);
    }
  }

  if (1) {
    VertexSE2* laserOffset = new VertexSE2;
    laserOffset->setId(Gm2dlIO::ID_LASERPOSE);
    laserOffset->setEstimate(initialLaserPose);
    optimizer.addVertex(laserOffset);
    VertexOdomDifferentialParams* odomParamsVertex = new VertexOdomDifferentialParams;
    odomParamsVertex->setId(Gm2dlIO::ID_ODOMCALIB);
    odomParamsVertex->setEstimate(Eigen::Vector3d(1., 1., 1.));
    optimizer.addVertex(odomParamsVertex);
    for (size_t i = 0; i < motions.size(); ++i) {
      const SE2& odomMotion = motions[i].odomMotion;
      const SE2& laserMotion = motions[i].laserMotion;
      const double& timeInterval = motions[i].timeInterval;
      // add the edge
      MotionMeasurement mm(odomMotion.translation().x(), odomMotion.translation().y(), odomMotion.rotation().angle(), timeInterval);
      OdomAndLaserMotion meas;
      meas.velocityMeasurement = OdomConvert::convertToVelocity(mm);
      meas.laserMotion = laserMotion;
      EdgeSE2PureCalib* calibEdge = new EdgeSE2PureCalib;
      calibEdge->setVertex(0, laserOffset);
      calibEdge->setVertex(1, odomParamsVertex);
      calibEdge->setInformation(Eigen::Matrix3d::Identity());
      calibEdge->setMeasurement(meas);
      if (! optimizer.addEdge(calibEdge)) {
        cerr << "Error adding calib edge" << endl;
        delete calibEdge;
      }
    }

    if (fixLaser) {
//.........这里部分代码省略.........

int main(int argc, char **argv) {
  /************************************************************************
   *                          Input handling                              *
   ************************************************************************/
  float rows, cols, gain, square_size;
  float resolution, max_range, usable_range, angle, threshold;
  string g2oFilename, mapFilename;
  g2o::CommandArgs arg;
  arg.param("resolution", resolution, 0.05f, "resolution of the map (how much is in meters a pixel)");
  arg.param("threshold", threshold, -1.0f, "threshold to apply to the frequency map (values under the threshold are discarded)");
  arg.param("rows", rows, 0, "impose the resulting map to have this number of rows");
  arg.param("cols", cols, 0, "impose the resulting map to have this number of columns");
  arg.param("max_range", max_range, -1.0f, "max laser range to consider for map building");
  arg.param("usable_range", usable_range, -1.0f, "usable laser range for map building");
  arg.param("gain", gain, 1, "gain to impose to the pixels of the map");
  arg.param("square_size", square_size, 1, "square size of the region where increment the hits");
  arg.param("angle", angle, 0, "rotate the map of x degrees");
  arg.paramLeftOver("input_graph.g2o", g2oFilename, "", "input g2o graph to use to build the map", false);
  arg.paramLeftOver("output_map", mapFilename, "", "output filename where to save the map (without extension)", false);  
  arg.parseArgs(argc, argv);

  angle = angle*M_PI/180.0;

  /************************************************************************
   *                          Loading Graph                               *
   ************************************************************************/
  // Load graph
  typedef BlockSolver< BlockSolverTraits<-1, -1> >  SlamBlockSolver;
  typedef LinearSolverCSparse<SlamBlockSolver::PoseMatrixType> SlamLinearSolver;
  SlamLinearSolver *linearSolver = new SlamLinearSolver();
  linearSolver->setBlockOrdering(false);
  SlamBlockSolver *blockSolver = new SlamBlockSolver(linearSolver);
  OptimizationAlgorithmGaussNewton *solverGauss = new OptimizationAlgorithmGaussNewton(blockSolver);
  SparseOptimizer *graph = new SparseOptimizer();
  graph->setAlgorithm(solverGauss);    
  graph->load(g2oFilename.c_str());
  
  // Sort verteces
  vector<int> vertexIds(graph->vertices().size());
  int k = 0;
  for(OptimizableGraph::VertexIDMap::iterator it = graph->vertices().begin(); it != graph->vertices().end(); ++it) {
    vertexIds[k++] = (it->first);
  }  
  sort(vertexIds.begin(), vertexIds.end());
  
  /************************************************************************
   *                          Compute map size                            *
   ************************************************************************/
  // Check the entire graph to find map bounding box
  Eigen::Matrix2d boundingBox = Eigen::Matrix2d::Zero();
  std::vector<RobotLaser*> robotLasers;
  std::vector<SE2> robotPoses;
  double xmin=std::numeric_limits<double>::max();
  double xmax=std::numeric_limits<double>::min();
  double ymin=std::numeric_limits<double>::max();
  double ymax=std::numeric_limits<double>::min();

  SE2 baseTransform(0,0,angle);

  for(size_t i = 0; i < vertexIds.size(); ++i) {
    OptimizableGraph::Vertex *_v = graph->vertex(vertexIds[i]);
    VertexSE2 *v = dynamic_cast<VertexSE2*>(_v);
    if(!v) { continue; }
    v->setEstimate(baseTransform*v->estimate());
    OptimizableGraph::Data *d = v->userData();

    while(d) {
      RobotLaser *robotLaser = dynamic_cast<RobotLaser*>(d);
      if(!robotLaser) {
	d = d->next();
	continue;
      }      
      robotLasers.push_back(robotLaser);
      robotPoses.push_back(v->estimate());
      double x = v->estimate().translation().x();
      double y = v->estimate().translation().y();
      
      xmax = xmax > x+usable_range ? xmax : x+usable_range;
      ymax = ymax > y+usable_range ? ymax : y+usable_range;
      xmin = xmin < x-usable_range ? xmin : x-usable_range;
      ymin = ymin < y-usable_range ? ymin : y-usable_range;
 
      d = d->next();
    }
  }

  boundingBox(0,0)=xmin;
  boundingBox(0,1)=xmax;
  boundingBox(1,0)=ymin;
  boundingBox(1,1)=ymax;

  std::cout << "Found " << robotLasers.size() << " laser scans"<< std::endl;
  std::cout << "Bounding box: " << std::endl << boundingBox << std::endl; 
  if(robotLasers.size() == 0)  {
    std::cout << "No laser scans found ... quitting!" << std::endl;
    return 0;
  }

  /************************************************************************
   *                          Compute the map                             *
//.........这里部分代码省略.........

void GraphSLAM::addDataSM(SE2 currentOdom, RobotLaser* laser){
  boost::mutex::scoped_lock lockg(graphMutex);

  //Add current vertex
  VertexSE2 *v = new VertexSE2;

  SE2 displacement = _lastOdom.inverse() * currentOdom;
  SE2 currEst = _lastVertex->estimate() * displacement;

  v->setEstimate(currEst);
  v->setId(++_runningVertexId + idRobot() * baseId());
  //Add covariance information
  //VertexEllipse *ellipse = new VertexEllipse;
  //Matrix3f cov = Matrix3f::Zero(); //last vertex has zero covariance
  //ellipse->setCovariance(cov);
  //v->setUserData(ellipse);
  v->addUserData(laser);

  std::cout << endl << 
    "Current vertex: " << v->id() << 
    " Estimate: "<< v->estimate().translation().x() << 
    " " << v->estimate().translation().y() << 
    " " << v->estimate().rotation().angle() << std::endl;

  _graph->addVertex(v);

  //Add current odometry edge
  EdgeSE2 *e = new EdgeSE2;
  e->setId(++_runningEdgeId + idRobot() * baseId());
  e->vertices()[0] = _lastVertex;
  e->vertices()[1] = v;
      

  OptimizableGraph::VertexSet vset;
  vset.insert(_lastVertex);
  int j = 1;
  int gap = 5;
  while (j <= gap){
    VertexSE2 *vj =  dynamic_cast<VertexSE2 *>(graph()->vertex(_lastVertex->id()-j));
    if (vj)
      vset.insert(vj);
    else
      break;
    j++;
  }

  SE2 transf;
  bool shouldIAdd = _closeMatcher.closeScanMatching(vset, _lastVertex, v,  &transf, maxScore);

  if (shouldIAdd){
    e->setMeasurement(transf);
    e->setInformation(_SMinf);
  }else{ //Trust the odometry
    e->setMeasurement(displacement);
    // Vector3d dis = displacement.toVector();
    // dis.x() = fabs(dis.x());
    // dis.y() = fabs(dis.y());
    // dis.z() = fabs(dis.z());
    // dis += Vector3d(1e-3,1e-3,1e-2);  
    // Matrix3d dis2 = dis*dis.transpose();
    // Matrix3d newcov = dis2.cwiseProduct(_odomK);
    // e->setInformation(newcov.inverse());

    e->setInformation(_odominf);
  }

  _graph->addEdge(e);

  _lastOdom = currentOdom;
  _lastVertex = v;
}

//.........这里部分代码省略.........
    }

    HyperGraph::VertexSet fixedSet;

    // off diagonal for each edge
    for (SparseOptimizer::EdgeContainer::const_iterator it = _optimizer->activeEdges().begin(); it != _optimizer->activeEdges().end(); ++it) {
#    ifndef NDEBUG
      EdgeSE2* e = dynamic_cast<EdgeSE2*>(*it);
      assert(e && "Active edges contain non-odometry edge"); //
#    else
      EdgeSE2* e = static_cast<EdgeSE2*>(*it);
#    endif
      OptimizableGraph::Vertex* from = static_cast<OptimizableGraph::Vertex*>(e->vertices()[0]);
      OptimizableGraph::Vertex* to   = static_cast<OptimizableGraph::Vertex*>(e->vertices()[1]);

      int ind1 = from->hessianIndex();
      int ind2 = to->hessianIndex();
      if (ind1 == -1 || ind2 == -1) {
        if (ind1 == -1) fixedSet.insert(from); // collect the fixed vertices
        if (ind2 == -1) fixedSet.insert(to);
        continue;
      }

      bool transposedBlock = ind1 > ind2;
      if (transposedBlock){ // make sure, we allocate the upper triangle block
        std::swap(ind1, ind2);
      }

      ScalarMatrix* m = H.block(ind1, ind2, true);
      m->setZero();
    }

    // walk along the Minimal Spanning Tree to compute the guess for the robot orientation
    assert(fixedSet.size() == 1);
    VertexSE2* root = static_cast<VertexSE2*>(*fixedSet.begin());
    VectorXD thetaGuess;
    thetaGuess.setZero(_optimizer->indexMapping().size());
    UniformCostFunction uniformCost;
    HyperDijkstra hyperDijkstra(_optimizer);
    hyperDijkstra.shortestPaths(root, &uniformCost);

    HyperDijkstra::computeTree(hyperDijkstra.adjacencyMap());
    ThetaTreeAction thetaTreeAction(thetaGuess.data());
    HyperDijkstra::visitAdjacencyMap(hyperDijkstra.adjacencyMap(), &thetaTreeAction);

    // construct for the orientation
    for (SparseOptimizer::EdgeContainer::const_iterator it = _optimizer->activeEdges().begin(); it != _optimizer->activeEdges().end(); ++it) {
      EdgeSE2* e = static_cast<EdgeSE2*>(*it);
      VertexSE2* from = static_cast<VertexSE2*>(e->vertices()[0]);
      VertexSE2* to   = static_cast<VertexSE2*>(e->vertices()[1]);

      double omega = e->information()(2,2);

      double fromThetaGuess = from->hessianIndex() < 0 ? 0. : thetaGuess[from->hessianIndex()];
      double toThetaGuess   = to->hessianIndex() < 0 ? 0. : thetaGuess[to->hessianIndex()];
      double error          = normalize_theta(-e->measurement().rotation().angle() + toThetaGuess - fromThetaGuess);

      bool fromNotFixed = !(from->fixed());
      bool toNotFixed   = !(to->fixed());

      if (fromNotFixed || toNotFixed) {
        double omega_r = - omega * error;
        if (fromNotFixed) {
          b(from->hessianIndex()) -= omega_r;
          (*H.block(from->hessianIndex(), from->hessianIndex()))(0,0) += omega;
          if (toNotFixed) {
            if (from->hessianIndex() > to->hessianIndex())
              (*H.block(to->hessianIndex(), from->hessianIndex()))(0,0) -= omega;
            else
              (*H.block(from->hessianIndex(), to->hessianIndex()))(0,0) -= omega;
          }
        } 
        if (toNotFixed ) {
          b(to->hessianIndex()) += omega_r;
          (*H.block(to->hessianIndex(), to->hessianIndex()))(0,0) += omega;
        }
      }
    }

    // solve orientation
    typedef LinearSolverCSparse<ScalarMatrix> SystemSolver;
    SystemSolver linearSystemSolver;
    linearSystemSolver.init();
    bool ok = linearSystemSolver.solve(H, x.data(), b.data());
    if (!ok) {
      cerr << __PRETTY_FUNCTION__ << "Failure while solving linear system" << endl;
      return false;
    }

    // update the orientation of the 2D poses and set translation to 0, GN shall solve that
    root->setToOrigin();
    for (size_t i = 0; i < _optimizer->indexMapping().size(); ++i) {
      VertexSE2* v = static_cast<VertexSE2*>(_optimizer->indexMapping()[i]);
      int poseIdx = v->hessianIndex();
      SE2 poseUpdate(0, 0, normalize_theta(thetaGuess(poseIdx) + x(poseIdx)));
      v->setEstimate(poseUpdate);
    }

    return true;
  }