Exemplo n.º 1
0
  void ViewerState::processCommands(){
    _meHasNewFrame = false;
    refreshFlags();
    updateDrawableParameters();
    if(!wasInitialGuess && !newCloudAdded && drawableFrameVector.size() > 1 && *initialGuessViewer) {
      initialGuessSelected();
      continuousMode = false;
    } else if(newCloudAdded && drawableFrameVector.size() > 1 && *optimizeViewer && !(*stepByStepViewer)) {
      optimizeSelected();
      continuousMode = false;
    }
    // Add cloud was pressed.
    else if(*addCloud) {
      addCloudSelected();
      continuousMode = false;
    }
    // clear buttons pressed.
    else if(*clearAll) {
      clear();
      *clearAll = 0;
      continuousMode = false;
    }
    else if(*clearLast) {
      clearLastSelected();
      continuousMode = false;
    } 
    else if(continuousMode){
      addNextAndOptimizeSelected();
    }
    // To avoid memorized commands to be managed.
    *initialGuessViewer = 0;
    *optimizeViewer = 0;
    *addCloud = 0; 
    *clearAll = 0;
    *clearLast = 0;

    if (0 && drawableFrameVector.size()){
      Eigen::Isometry3f globalT = drawableFrameVector.front()->transformation();
      qglviewer::Vec robotPose(globalT.translation().x(), globalT.translation().y(), globalT.translation().z());
      qglviewer::Vec robotAxisX(globalT.linear()(0,0), globalT.linear()(1,0), globalT.linear()(2,0));
      qglviewer::Vec robotAxisZ(globalT.linear()(0,2), globalT.linear()(1,2), globalT.linear()(2,2));
      pwnGMW->viewer_3d->camera()->setPosition(robotPose+.5*robotAxisZ+.5*robotAxisX);
      pwnGMW->viewer_3d->camera()->setUpVector(robotAxisX+robotAxisZ);
      pwnGMW->viewer_3d->camera()->setViewDirection(robotPose+.5*robotAxisZ+.5*robotAxisX);
    }


    pwnGMW->viewer_3d->updateGL();
  }
Exemplo n.º 2
0
  void DrawableCloud::draw() {
    if(_parameter->show() && _cloud) {
      glPushMatrix();
      glMultMatrixf(_transformation.data());
      if(_drawablePoints)
	_drawablePoints->draw();
      if(_drawableNormals)
	_drawableNormals->draw();
      if(_drawableCovariances)
	_drawableCovariances->draw();
      if(_drawableCorrespondences)
	_drawableCorrespondences->draw();

      glPushMatrix();
      Eigen::Isometry3f sensorOffset;
      sensorOffset.translation() = Eigen::Vector3f(0.0f, 0.0f, 0.0f);
      Eigen::Quaternionf quaternion = Eigen::Quaternionf(-.5f, -0.5f, 0.5f, 0.5f);
      sensorOffset.linear() = quaternion.toRotationMatrix();
      sensorOffset.matrix().row(3) << 0.0f, 0.0f, 0.0f, 1.0f;
      glMultMatrixf(sensorOffset.data());
      glColor4f(1,0,0,0.5);
      glPopMatrix();

      glPopMatrix();
    }
  }
Exemplo n.º 3
0
  bool extractAbsolutePrior(Eigen::Isometry3f& priorMean, Matrix6f& priorInfo, 
			    const DrawableFrame* current){
    VertexSE3* currentVertex =current->_vertex;
    ImuData* imuData = 0;
    OptimizableGraph::Data* d = currentVertex->userData();
    while(d) {
      ImuData* imuData_ = dynamic_cast<ImuData*>(d);
      if (imuData_){
	imuData = imuData_;
      }
      d=d->next();
    }
	
    if (imuData){
      Eigen::Matrix3d R=imuData->getOrientation().matrix();
      Eigen::Matrix3d Omega = imuData->getOrientationCovariance().inverse();
      priorMean.setIdentity();
      priorInfo.setZero();
      for (int c = 0; c<3; c++)
	for (int r = 0; r<3; r++)
	  priorMean.linear()(r,c)=R(r,c);
      
      for (int c = 0; c<3; c++)
	for (int r = 0; r<3; r++)
	  priorInfo(r+3,c+3)=Omega(r,c);
      return true;
    }
    return false;
  }
  void DrawableTransformCovariance::updateCovarianceDrawList() {
    GLParameterTransformCovariance *covarianceParameter = dynamic_cast<GLParameterTransformCovariance*>(_parameter);
    glNewList(_covarianceDrawList, GL_COMPILE); 
    if(_covariance != Eigen::Matrix3f::Zero() && 
       covarianceParameter && 
       covarianceParameter->show() && 
       covarianceParameter->scale() > 0.0f) {
      float scale = covarianceParameter->scale();
      Eigen::Vector4f color = covarianceParameter->color();
      
      Eigen::SelfAdjointEigenSolver<Eigen::Matrix3f> eigenSolver;
      eigenSolver.computeDirect(_covariance, Eigen::ComputeEigenvectors);

      Eigen::Vector3f lambda = eigenSolver.eigenvalues();      
      Eigen::Isometry3f I = Eigen::Isometry3f::Identity();
      I.linear() = eigenSolver.eigenvectors();
      I.translation() = Eigen::Vector3f(_mean.x(), _mean.y(), _mean.z());
      
      float sx = sqrt(lambda[0]) * scale;
      float sy = sqrt(lambda[1]) * scale;
      float sz = sqrt(lambda[2]) * scale;
      
      glPushMatrix();
      glMultMatrixf(I.data());
      glColor4f(color[0], color[1], color[2], color[3]);
      glScalef(sx, sy, sz);
      glCallList(_sphereDrawList);
      glPopMatrix();	    
    }
    glEndList();
  }
Exemplo n.º 5
0
  void DrawableUncertainty::updateCovarianceDrawList() {
    GLParameterUncertainty *uncertaintyParameter = dynamic_cast<GLParameterUncertainty*>(_parameter);
    glNewList(_covarianceDrawList, GL_COMPILE); 
    if(_covarianceDrawList &&
       _covariances && 
       uncertaintyParameter && 
       uncertaintyParameter->ellipsoidScale() > 0.0f) {
      uncertaintyParameter->applyGLParameter();
      Eigen::SelfAdjointEigenSolver<Eigen::Matrix3f> eigenSolver;
      float ellipsoidScale = uncertaintyParameter->ellipsoidScale();
      for(size_t i = 0; i < _covariances->size(); i += uncertaintyParameter->step()) {
	Gaussian3f &gaussian3f = _covariances->at(i);
	Eigen::Matrix3f covariance = gaussian3f.covarianceMatrix();
	Eigen::Vector3f mean = gaussian3f.mean();
	eigenSolver.computeDirect(covariance, Eigen::ComputeEigenvectors);
	Eigen::Vector3f eigenValues = eigenSolver.eigenvalues();      
	Eigen::Isometry3f I = Eigen::Isometry3f::Identity();
	I.linear() = eigenSolver.eigenvectors();
	I.translation() = mean;
	float sx = sqrt(eigenValues[0]) * ellipsoidScale;
	float sy = sqrt(eigenValues[1]) * ellipsoidScale;
	float sz = sqrt(eigenValues[2]) * ellipsoidScale;
	glPushMatrix();
	glMultMatrixf(I.data());	
	sx = sx;
	sy = sy;
	sz = sz;
	glScalef(sx, sy, sz);
	glCallList(_sphereDrawList);
	glPopMatrix();	    
      }   
    }
    glEndList();
  }
Exemplo n.º 6
0
bool LcmTranslator::
fromLcm(const drc::map_scan_t& iMessage, LidarScan& oScan) {
  const auto& msg = iMessage;

  // basic info
  oScan.setTimestamp(msg.utime);
  oScan.setAngles(msg.theta_min, msg.theta_step);

  // poses
  Eigen::Isometry3f startPose = Eigen::Isometry3f::Identity();
  Eigen::Isometry3f endPose = Eigen::Isometry3f::Identity();
  for (int k = 0; k < 3; ++k) startPose(k,3) = msg.translation_start[k];
  for (int k = 0; k < 3; ++k) endPose(k,3) = msg.translation_end[k];
  Eigen::Quaternionf startQuat, endQuat;
  for (int k = 0; k < 4; ++k) startQuat.coeffs()[k] =
                                msg.quaternion_start[(k+1)%4];
  for (int k = 0; k < 4; ++k) endQuat.coeffs()[k] = msg.quaternion_end[(k+1)%4];
  startPose.linear() = startQuat.matrix();
  endPose.linear() = endQuat.matrix();
  oScan.setPoses(startPose, endPose);

  // ranges
  DataBlob blob;
  if (!fromLcm(msg.range_blob, blob)) return false;
  blob.convertTo(DataBlob::CompressionTypeNone, DataBlob::DataTypeFloat32);
  float* raw = (float*)(&blob.getBytes()[0]);
  std::vector<float> ranges(raw, raw+blob.getBytes().size()/sizeof(float));
  for (auto& r : ranges) r *= msg.range_scale;
  oScan.setRanges(ranges);

  // intensities
  if (fromLcm(msg.intensity_blob, blob)) {
    blob.convertTo(DataBlob::CompressionTypeNone, DataBlob::DataTypeFloat32);
    raw = (float*)blob.getBytes().data();
    std::vector<float> intensities
      (raw, raw+blob.getBytes().size()/sizeof(float));
    if (intensities.size() == ranges.size()) {
      for (auto& val : intensities) val *= msg.intensity_scale;
      oScan.setIntensities(intensities);
    }
  }

  return true;
}
Exemplo n.º 7
0
  void draw(const std::shared_ptr<maps::ViewBase>& iView,
            const std::shared_ptr<MeshRenderer>& iMeshRenderer) {
    if (!mVisible) return;

    // set mesh properties
    iMeshRenderer->setRangeOrigin(mLatestTransform.translation());
    iMeshRenderer->setScaleRange(mAttributes.mMinZ, mAttributes.mMaxZ);
    iMeshRenderer->setPointSize(mAttributes.mPointSize);
    Eigen::Projective3f worldToMap = mUseTransform ? iView->getTransform() :
      Eigen::Projective3f::Identity();
    Eigen::Projective3f mapToWorld = worldToMap.inverse();
    Eigen::Matrix3f calib;
    Eigen::Isometry3f pose;
    bool ortho;
    maps::Utils::factorViewMatrix(worldToMap, calib, pose, ortho);
    iMeshRenderer->setNormalZero(-pose.linear().col(2));

    // see whether we need to (and can) get a mesh representation
    bool usePoints = false;
    maps::TriangleMesh::Ptr mesh;
    if (mAttributes.mMeshMode == MeshRenderer::MeshModePoints) {
      usePoints = true;
    }
    else {
      mesh = iView->getAsMesh(!mUseTransform);
      if (mesh == NULL) usePoints = true;
    }

    // just a point cloud
    if (usePoints) {
      mesh.reset(new maps::TriangleMesh());
      maps::PointCloud::Ptr cloud = iView->getAsPointCloud(!mUseTransform);
      mesh->mVertices.reserve(cloud->size());
      for (size_t i = 0; i < cloud->size(); ++i) {
        mesh->mVertices.push_back((*cloud)[i].getVector3fMap());
      }
    }

    // set up mesh renderer
    iMeshRenderer->setColor(mAttributes.mColor[0],
                            mAttributes.mColor[1],
                            mAttributes.mColor[2]);
    iMeshRenderer->setColorMode
      ((MeshRenderer::ColorMode)mAttributes.mColorMode);
    iMeshRenderer->setMeshMode
      ((MeshRenderer::MeshMode)mAttributes.mMeshMode);
    if (usePoints) iMeshRenderer->setMeshMode(MeshRenderer::MeshModePoints);
    iMeshRenderer->setData(mesh->mVertices, mesh->mNormals,
                           mesh->mFaces, mapToWorld);

    // draw this view's data
    iMeshRenderer->draw();
    drawBounds();
  }
 void PinholePointProjector::_updateMatrices() {
   Eigen::Isometry3f t =_transform.inverse();
   t.matrix().block<1, 4>(3, 0) << 0.0f, 0.0f, 0.0f, 1.0f;
   _iK = _cameraMatrix.inverse();
   _KR = _cameraMatrix * t.linear();
   _Kt = _cameraMatrix * t.translation();
   _iKR = _transform.linear() * _iK;
   _iKt = _transform.translation();
   _KRt.setIdentity();
   _iKRt.setIdentity();
   _KRt.block<3, 3>(0, 0) = _KR; 
   _KRt.block<3, 1>(0, 3) = _Kt;
   _iKRt.block<3, 3>(0, 0) = _iKR; 
   _iKRt.block<3, 1>(0, 3) = _iKt;
 }
Exemplo n.º 9
0
  void NICPQGLViewer::updateCameraPosition(Eigen::Isometry3f pose) {
    qglviewer::Camera *oldcam = camera();
    qglviewer::Camera *cam = new StandardCamera();
    setCamera(cam);

    Eigen::Vector3f position = pose*Vector3f(-2.0f, 0.0f, 1.0f);
    cam->setPosition(qglviewer::Vec(position[0], position[1], position[2]));
    Eigen::Vector3f upVector = pose.linear()*Vector3f(0.0f, 0.0f, 0.5f);
    upVector.normalize();
    cam->setUpVector(qglviewer::Vec(upVector[0], upVector[1], upVector[2]), true);
  
    Eigen::Vector3f lookAt = pose*Vector3f(4.0f, 0.0f, 0.0f);  
    cam->lookAt(qglviewer::Vec(lookAt[0], lookAt[1], lookAt[2]));  

    delete oldcam;
  }
Exemplo n.º 10
0
  void DrawableCovariances::updateCovarianceDrawList() {
    GLParameterCovariances *covariancesParameter = dynamic_cast<GLParameterCovariances*>(_parameter);
    glNewList(_covarianceDrawList, GL_COMPILE); 
    if(_covariances && 
       covariancesParameter && 
       covariancesParameter->show() && 
       covariancesParameter->ellipsoidScale() > 0.0f) {
      float ellipsoidScale = covariancesParameter->ellipsoidScale();
      Eigen::Vector4f colorLowCurvature = covariancesParameter->colorLowCurvature();
      Eigen::Vector4f colorHighCurvature = covariancesParameter->colorHighCurvature();
      float curvatureThreshold = covariancesParameter->curvatureThreshold();
      for(size_t i = 0; i < _covariances->size(); i += covariancesParameter->step()) {
	Stats cov = _covariances->at(i);
	Eigen::Vector3f lambda = cov.eigenValues();
	Eigen::Isometry3f I = Eigen::Isometry3f::Identity();
	I.linear() = cov.eigenVectors();
	if(cov.n() == 0 )
	  continue;
	I.translation() = Eigen::Vector3f(cov.mean()[0], cov.mean()[1], cov.mean()[2]);
	float sx = sqrt(lambda[0]) * ellipsoidScale;
	float sy = sqrt(lambda[1]) * ellipsoidScale;
	float sz = sqrt(lambda[2]) * ellipsoidScale;
	float curvature = cov.curvature();
	glPushMatrix();
	glMultMatrixf(I.data());
	if(curvature > curvatureThreshold) {
	  glColor4f(colorHighCurvature[0] - curvature, colorHighCurvature[1], colorHighCurvature[2], colorHighCurvature[3]);
	  sx = ellipsoidScale;
	  sy = ellipsoidScale;
	  sz = ellipsoidScale;
	}
	else {
	  glColor4f(colorLowCurvature[0], colorLowCurvature[1] - curvature, colorLowCurvature[2], colorLowCurvature[3]);
	  sx = 1e-03;
	  sy = ellipsoidScale;
	  sz = ellipsoidScale;
	}

	glScalef(sx, sy, sz);
	glCallList(_sphereDrawList);
	glPopMatrix();	    
      }   
    }
    glEndList();
  }
Exemplo n.º 11
0
  void ViewerState::addCloudSelected(){
    if(listItem) {
      cerr << "adding a frame" << endl;
      int index = pwnGMW->listWidget->row(listItem);
      cerr << "index: " << endl;
      std::string fname = listAssociations[index]->baseFilename()+"_depth.pgm";
      DepthImage depthImage;
      if (!depthImage.load(fname.c_str(), true)){
      	cerr << " skipping " << fname << endl;
      	newCloudAdded = false;
      	*addCloud = 0;
      	return;
      }
      DepthImage scaledDepthImage;
      DepthImage::scale(scaledDepthImage, depthImage, reduction);
      imageRows = scaledDepthImage.rows();
      imageCols = scaledDepthImage.cols();
      correspondenceFinder->setSize(imageRows, imageCols);
      Frame * frame=new Frame();
      converter->compute(*frame, scaledDepthImage, sensorOffset);
      OptimizableGraph::DataContainer* dc =listAssociations[index]->dataContainer();
      cerr << "datacontainer: " << dc << endl;
      VertexSE3* v = dynamic_cast<VertexSE3*>(dc);
      cerr << "vertex of the frame: " << v->id() << endl;

      DrawableFrame* drawableFrame = new DrawableFrame(globalT, drawableFrameParameters, frame);
      drawableFrame->_vertex = v;
      
      Eigen::Isometry3f priorMean;
      Matrix6f priorInfo;
      bool hasImu =extractAbsolutePrior(priorMean, priorInfo, drawableFrame);
      if (hasImu && drawableFrameVector.size()==0){
        	globalT.linear() = priorMean.linear();
        	cerr << "!!!! i found an imu for the first vertex, me happy" << endl;
        	drawableFrame->setTransformation(globalT);
      }
      drawableFrameVector.push_back(drawableFrame);
      pwnGMW->viewer_3d->addDrawable(drawableFrame);
    }
    newCloudAdded = true;
    *addCloud = 0;
    _meHasNewFrame = true;
  }
Exemplo n.º 12
0
void computeSensorOffsetAndK(Eigen::Isometry3f &sensorOffset, Eigen::Matrix3f &cameraMatrix, ParameterCamera *cameraParam, int reduction) {
  sensorOffset = Isometry3f::Identity();
  cameraMatrix.setZero();
      
  int cmax = 4;
  int rmax = 3;
  for (int c=0; c<cmax; c++){
    for (int r=0; r<rmax; r++){
      sensorOffset.matrix()(r, c) = cameraParam->offset()(r, c);
      if (c<3)
	cameraMatrix(r,c) = cameraParam->Kcam()(r, c);
    }
  }
  sensorOffset.translation() = Vector3f(0.15f, 0.0f, 0.05f);
  Quaternionf quat = Quaternionf(0.5, -0.5, 0.5, -0.5);
  sensorOffset.linear() = quat.toRotationMatrix();
  sensorOffset.matrix().block<1, 4>(3, 0) << 0.0f, 0.0f, 0.0f, 1.0f;
	
  float scale = 1./reduction;
  cameraMatrix *= scale;
  cameraMatrix(2,2) = 1;
}
Exemplo n.º 13
0
bool Utils::
factorViewMatrix(const Eigen::Projective3f& iMatrix,
                 Eigen::Matrix3f& oCalib, Eigen::Isometry3f& oPose,
                 bool& oIsOrthographic) {
  oIsOrthographic = isOrthographic(iMatrix.matrix());

  // get appropriate rows
  std::vector<int> rows = {0,1,2};
  if (!oIsOrthographic) rows[2] = 3;

  // get A matrix (upper left 3x3) and t vector
  Eigen::Matrix3f A;
  Eigen::Vector3f t;
  for (int i = 0; i < 3; ++i) {
    for (int j = 0; j < 3; ++j) {
      A(i,j) = iMatrix(rows[i],j);
    }
    t[i] = iMatrix(rows[i],3);
  }

  // determine translation vector
  oPose.setIdentity();
  oPose.translation() = -(A.inverse()*t);

  // determine calibration matrix
  Eigen::Matrix3f AAtrans = A*A.transpose();
  AAtrans.col(0).swap(AAtrans.col(2));
  AAtrans.row(0).swap(AAtrans.row(2));
  Eigen::LLT<Eigen::Matrix3f, Eigen::Upper> llt(AAtrans);
  oCalib = llt.matrixU();
  oCalib.col(0).swap(oCalib.col(2));
  oCalib.row(0).swap(oCalib.row(2));
  oCalib.transposeInPlace();

  // compute rotation matrix
  oPose.linear() = (oCalib.inverse()*A).transpose();

  return true;
}
  void ImageMessageListener::imageCallback(const sensor_msgs::ImageConstPtr& in_msg) {
    static int counter = 0;     // counter to add periodic line breaks
    _image_deque.push_back(*in_msg);
    if (_image_deque.size()<_deque_length){
      return;
    }
    sensor_msgs::Image msg = _image_deque.front();
    _image_deque.pop_front();
    
    
    if (_listener) {
      tf::StampedTransform transform;
      try{
        _listener->waitForTransform(_odom_frame_id, 
                                    _base_link_frame_id, 
                                    msg.header.stamp, 
                                    ros::Duration(0.5) );
        _listener->lookupTransform (_odom_frame_id, 
                                    _base_link_frame_id, 
                                    msg.header.stamp, 
                                    transform);
      }
      catch (tf::TransformException ex){
        ROS_ERROR("%s",ex.what());
      }
      Eigen::Quaternionf q;
      q.x() = transform.getRotation().x();
      q.y() = transform.getRotation().y();
      q.z() = transform.getRotation().z();
      q.w() = transform.getRotation().w();
      _odom_pose.linear()=q.toRotationMatrix();
      _odom_pose.translation()=Eigen::Vector3f(transform.getOrigin().x(),
                                               transform.getOrigin().y(),
                                               transform.getOrigin().z());
    }      


    cv_bridge::CvImageConstPtr bridge;
    bridge = cv_bridge::toCvCopy(msg,msg.encoding);

  
    if (! _has_camera_matrix){
      cerr << "received: " << _image_topic << " waiting for camera matrix" << endl;
      return;
    }
    _cv_image = bridge->image.clone();
 
  
    PinholeImageMessage* img_msg = new PinholeImageMessage(_image_topic, msg.header.frame_id,  msg.header.seq, msg.header.stamp.toSec());
    img_msg->setImage(_cv_image);
    img_msg->setOffset(_camera_offset);
    img_msg->setCameraMatrix(_K);
    img_msg->setDepthScale(_depth_scale);
  
    if (_imu_interpolator && _listener) {
      Eigen::Isometry3f imu = Eigen::Isometry3f::Identity();
      Eigen::Quaternionf q_imu;
      if (!_imu_interpolator->getOrientation(q_imu, msg.header.stamp.toSec()))
        return;
      imu.linear() = q_imu.toRotationMatrix();
      if (_verbose) {
        cerr << "i";
        counter++;
        if( counter % 1024 == 0 )
          cerr << endl;
      }
      img_msg->setImu(imu);
    } else if (_listener) {
      img_msg->setOdometry(_odom_pose);
      if (_verbose)
        cerr << "o";
        counter++;
        if( counter % 1024 == 0 )
          cerr << endl;
    } else {
      if (_verbose)
        cerr << "x";
        counter++;
        if( counter % 1024 == 0 )
          cerr << endl;
    }
    _sorter->insertMessage(img_msg);
  }
Exemplo n.º 15
0
BlockFitter::Result BlockFitter::
go() {
  Result result;
  result.mSuccess = false;

  if (mCloud->size() < 100) return result;

  // voxelize
  LabeledCloud::Ptr cloud(new LabeledCloud());
  pcl::VoxelGrid<pcl::PointXYZL> voxelGrid;
  voxelGrid.setInputCloud(mCloud);
  voxelGrid.setLeafSize(mDownsampleResolution, mDownsampleResolution,
                        mDownsampleResolution);
  voxelGrid.filter(*cloud);
  for (int i = 0; i < (int)cloud->size(); ++i) cloud->points[i].label = i;

  if (mDebug) {
    std::cout << "Original cloud size " << mCloud->size() << std::endl;
    std::cout << "Voxelized cloud size " << cloud->size() << std::endl;
    pcl::io::savePCDFileBinary("cloud_full.pcd", *cloud);
  }

  if (cloud->size() < 100) return result;

  // pose
  cloud->sensor_origin_.head<3>() = mOrigin;
  cloud->sensor_origin_[3] = 1;
  Eigen::Vector3f rz = mLookDir;
  Eigen::Vector3f rx = rz.cross(Eigen::Vector3f::UnitZ());
  Eigen::Vector3f ry = rz.cross(rx);
  Eigen::Matrix3f rotation;
  rotation.col(0) = rx.normalized();
  rotation.col(1) = ry.normalized();
  rotation.col(2) = rz.normalized();
  Eigen::Isometry3f pose = Eigen::Isometry3f::Identity();
  pose.linear() = rotation;
  pose.translation() = mOrigin;

  // ground removal
  if (mRemoveGround) {
    Eigen::Vector4f groundPlane;

    // filter points
    float minZ = mMinGroundZ;
    float maxZ = mMaxGroundZ;
    if ((minZ > 10000) && (maxZ > 10000)) {
      std::vector<float> zVals(cloud->size());
      for (int i = 0; i < (int)cloud->size(); ++i) {
        zVals[i] = cloud->points[i].z;
      }
      std::sort(zVals.begin(), zVals.end());
      minZ = zVals[0]-0.1;
      maxZ = minZ + 0.5;
    }
    LabeledCloud::Ptr tempCloud(new LabeledCloud());
    for (int i = 0; i < (int)cloud->size(); ++i) {
      const Eigen::Vector3f& p = cloud->points[i].getVector3fMap();
      if ((p[2] < minZ) || (p[2] > maxZ)) continue;
      tempCloud->push_back(cloud->points[i]);
    }

    // downsample
    voxelGrid.setInputCloud(tempCloud);
    voxelGrid.setLeafSize(0.1, 0.1, 0.1);
    voxelGrid.filter(*tempCloud);

    if (tempCloud->size() < 100) return result;

    // find ground plane
    std::vector<Eigen::Vector3f> pts(tempCloud->size());
    for (int i = 0; i < (int)tempCloud->size(); ++i) {
      pts[i] = tempCloud->points[i].getVector3fMap();
    }
    const float kGroundPlaneDistanceThresh = 0.01; // TODO: param
    PlaneFitter planeFitter;
    planeFitter.setMaxDistance(kGroundPlaneDistanceThresh);
    planeFitter.setRefineUsingInliers(true);
    auto res = planeFitter.go(pts);
    groundPlane = res.mPlane;
    if (groundPlane[2] < 0) groundPlane = -groundPlane;
    if (mDebug) {
      std::cout << "dominant plane: " << groundPlane.transpose() << std::endl;
      std::cout << "  inliers: " << res.mInliers.size() << std::endl;
    }

    if (std::acos(groundPlane[2]) > 30*M_PI/180) {
      std::cout << "error: ground plane not found!" << std::endl;
      std::cout << "proceeding with full segmentation (may take a while)..." <<
        std::endl;
    }

    else {
      // compute convex hull
      result.mGroundPlane = groundPlane;
      {
        tempCloud.reset(new LabeledCloud());
        for (int i = 0; i < (int)cloud->size(); ++i) {
          Eigen::Vector3f p = cloud->points[i].getVector3fMap();
          float dist = groundPlane.head<3>().dot(p) + groundPlane[3];
          if (std::abs(dist) > kGroundPlaneDistanceThresh) continue;
          p -= (groundPlane.head<3>()*dist);
          pcl::PointXYZL cloudPt;
          cloudPt.getVector3fMap() = p;
          tempCloud->push_back(cloudPt);
        }
        pcl::ConvexHull<pcl::PointXYZL> chull;
        pcl::PointCloud<pcl::PointXYZL> hull;
        chull.setInputCloud(tempCloud);
        chull.reconstruct(hull);
        result.mGroundPolygon.resize(hull.size());
        for (int i = 0; i < (int)hull.size(); ++i) {
          result.mGroundPolygon[i] = hull[i].getVector3fMap();
        }
      }

      // remove points below or near ground
      tempCloud.reset(new LabeledCloud());
      for (int i = 0; i < (int)cloud->size(); ++i) {
        Eigen::Vector3f p = cloud->points[i].getVector3fMap();
        float dist = p.dot(groundPlane.head<3>()) + groundPlane[3];
        if ((dist < mMinHeightAboveGround) ||
            (dist > mMaxHeightAboveGround)) continue;
        float range = (p-mOrigin).norm();
        if (range > mMaxRange) continue;
        tempCloud->push_back(cloud->points[i]);
      }
      std::swap(tempCloud, cloud);
      if (mDebug) {
        std::cout << "Filtered cloud size " << cloud->size() << std::endl;
      }
    }
  }

  // normal estimation
  auto t0 = std::chrono::high_resolution_clock::now();
  if (mDebug) {
    std::cout << "computing normals..." << std::flush;
  }
  RobustNormalEstimator normalEstimator;
  normalEstimator.setMaxEstimationError(0.01);
  normalEstimator.setRadius(0.1);
  normalEstimator.setMaxCenterError(0.02);
  normalEstimator.setMaxIterations(100);
  NormalCloud::Ptr normals(new NormalCloud());
  normalEstimator.go(cloud, *normals);
  if (mDebug) {
    auto t1 = std::chrono::high_resolution_clock::now();
    auto dt = std::chrono::duration_cast<std::chrono::milliseconds>(t1-t0);
    std::cout << "finished in " << dt.count()/1e3 << " sec" << std::endl;
  }

  // filter non-horizontal points
  const float maxNormalAngle = mMaxAngleFromHorizontal*M_PI/180;
  LabeledCloud::Ptr tempCloud(new LabeledCloud());
  NormalCloud::Ptr tempNormals(new NormalCloud());
  for (int i = 0; i < (int)normals->size(); ++i) {
    const auto& norm = normals->points[i];
    Eigen::Vector3f normal(norm.normal_x, norm.normal_y, norm.normal_z);
    float angle = std::acos(normal[2]);
    if (angle > maxNormalAngle) continue;
    tempCloud->push_back(cloud->points[i]);
    tempNormals->push_back(normals->points[i]);
  }
  std::swap(tempCloud, cloud);
  std::swap(tempNormals, normals);

  if (mDebug) {
    std::cout << "Horizontal points remaining " << cloud->size() << std::endl;
    pcl::io::savePCDFileBinary("cloud.pcd", *cloud);
    pcl::io::savePCDFileBinary("robust_normals.pcd", *normals);
  }

  // plane segmentation
  t0 = std::chrono::high_resolution_clock::now();
  if (mDebug) {
    std::cout << "segmenting planes..." << std::flush;
  }
  PlaneSegmenter segmenter;
  segmenter.setData(cloud, normals);
  segmenter.setMaxError(0.05);
  segmenter.setMaxAngle(5);
  segmenter.setMinPoints(100);
  PlaneSegmenter::Result segmenterResult = segmenter.go();
  if (mDebug) {
    auto t1 = std::chrono::high_resolution_clock::now();
    auto dt = std::chrono::duration_cast<std::chrono::milliseconds>(t1-t0);
    std::cout << "finished in " << dt.count()/1e3 << " sec" << std::endl;

    std::ofstream ofs("labels.txt");
    for (const int lab : segmenterResult.mLabels) {
      ofs << lab << std::endl;
    }
    ofs.close();

    ofs.open("planes.txt");
    for (auto it : segmenterResult.mPlanes) {
      auto& plane = it.second;
      ofs << it.first << " " << plane.transpose() << std::endl;
    }
    ofs.close();
  }

  // create point clouds
  std::unordered_map<int,std::vector<Eigen::Vector3f>> cloudMap;
  for (int i = 0; i < (int)segmenterResult.mLabels.size(); ++i) {
    int label = segmenterResult.mLabels[i];
    if (label <= 0) continue;
    cloudMap[label].push_back(cloud->points[i].getVector3fMap());
  }
  struct Plane {
    MatrixX3f mPoints;
    Eigen::Vector4f mPlane;
  };
  std::vector<Plane> planes;
  planes.reserve(cloudMap.size());
  for (auto it : cloudMap) {
    int n = it.second.size();
    Plane plane;
    plane.mPoints.resize(n,3);
    for (int i = 0; i < n; ++i) plane.mPoints.row(i) = it.second[i];
    plane.mPlane = segmenterResult.mPlanes[it.first];
    planes.push_back(plane);
  }

  std::vector<RectangleFitter::Result> results;
  for (auto& plane : planes) {
    RectangleFitter fitter;
    fitter.setDimensions(mBlockDimensions.head<2>());
    fitter.setAlgorithm((RectangleFitter::Algorithm)mRectangleFitAlgorithm);
    fitter.setData(plane.mPoints, plane.mPlane);
    auto result = fitter.go();
    results.push_back(result);
  }

  if (mDebug) {
    std::ofstream ofs("boxes.txt");
    for (int i = 0; i < (int)results.size(); ++i) {
      auto& res = results[i];
      for (auto& p : res.mPolygon) {
        ofs << i << " " << p.transpose() << std::endl;
      }
    }
    ofs.close();

    ofs.open("hulls.txt");
    for (int i = 0; i < (int)results.size(); ++i) {
      auto& res = results[i];
      for (auto& p : res.mConvexHull) {
        ofs << i << " " << p.transpose() << std::endl;
      }
    }
    ofs.close();

    ofs.open("poses.txt");
    for (int i = 0; i < (int)results.size(); ++i) {
      auto& res = results[i];
      auto transform = res.mPose;
      ofs << transform.matrix() << std::endl;
    }
    ofs.close();
  }

  for (int i = 0; i < (int)results.size(); ++i) {
    const auto& res = results[i];
    if (mBlockDimensions.head<2>().norm() > 1e-5) {
      float areaRatio = mBlockDimensions.head<2>().prod()/res.mConvexArea;
      if ((areaRatio < mAreaThreshMin) ||
          (areaRatio > mAreaThreshMax)) continue;
    }

    Block block;
    block.mSize << res.mSize[0], res.mSize[1], mBlockDimensions[2];
    block.mPose = res.mPose;
    block.mPose.translation() -=
      block.mPose.rotation().col(2)*mBlockDimensions[2]/2;
    block.mHull = res.mConvexHull;
    result.mBlocks.push_back(block);
  }
  if (mDebug) {
    std::cout << "Surviving blocks: " << result.mBlocks.size() << std::endl;
  }

  result.mSuccess = true;
  return result;
}
Exemplo n.º 16
0
gtsam::Pose3 Convert(const Eigen::Isometry3f& iso)
{
    gtsam::Matrix3 mat = iso.linear().cast<double>();
    Eigen::Vector3d trans = iso.translation().cast<double>();
    return gtsam::Pose3(mat, gtsam::Point3(trans));
}