removed merge conflicts

include/msckf_vio/feature.hpp

@@ -15,7 +15,7 @@
 #include <Eigen/Dense>
 #include <Eigen/Geometry>
 #include <Eigen/StdVector>
-
+#include <math.h>
 #include <visualization_msgs/Marker.h>
 #include <visualization_msgs/MarkerArray.h>
 #include <geometry_msgs/Point.h>
@@ -191,7 +191,9 @@ struct Feature {
                   const StateIDType& cam_state_id,
                   CameraCalibration& cam0,
                   const std::vector<double> photo_r,
-                  std::stringstream& ss) const;
+                  std::stringstream& ss,
+                  cv::Point2f gradientVector,
+                  cv::Point2f residualVector) const;
 
 
   /* @brief takes a pure pixel position (1m from image)
@@ -203,11 +205,12 @@ struct Feature {
                                const CameraCalibration& cam, 
                                const StateIDType& cam_state_id,
                                std::vector<float>& return_i) const;
+
   /*
-  * @brief projectPixelToPosition uses the calcualted pixels
+  * @brief AnchorPixelToPosition uses the calcualted pixels
   *     of the anchor patch to generate 3D positions of all of em
   */
-inline Eigen::Vector3d projectPixelToPosition(cv::Point2f in_p,
+inline Eigen::Vector3d AnchorPixelToPosition(cv::Point2f in_p,
           const CameraCalibration& cam);
 
   /*
@@ -553,7 +556,9 @@ bool Feature::VisualizePatch(
                   const StateIDType& cam_state_id,
                   CameraCalibration& cam0,
                   const std::vector<double> photo_r,
-                  std::stringstream& ss) const
+                  std::stringstream& ss,
+                  cv::Point2f gradientVector,
+                  cv::Point2f residualVector) const
 {
 
   double rescale = 1;
@@ -593,45 +598,107 @@ bool Feature::VisualizePatch(
 
   cv::hconcat(cam0.featureVisu, dottedFrame, cam0.featureVisu);
 
-  // irradiance grid anchor
+
+  // patches visualization
   int N = sqrt(anchorPatch_3d.size());
-  int scale = 20;
+  int scale = 30;
   cv::Mat irradianceFrame(anchorImage.size(), CV_8UC3, cv::Scalar(255, 240, 255));
   cv::resize(irradianceFrame, irradianceFrame, cv::Size(), rescale, rescale);
+  
+  // irradiance grid anchor
+  std::stringstream namer;
+  namer << "anchor";
+  cv::putText(irradianceFrame, namer.str() , cvPoint(30, 25), 
+    cv::FONT_HERSHEY_COMPLEX_SMALL, 0.8, cvScalar(0,0,0), 1, CV_AA);
+
+
   for(int i = 0; i<N; i++)
     for(int j = 0; j<N; j++)
       cv::rectangle(irradianceFrame, 
-                    cv::Point(10+scale*(i+1), 10+scale*j), 
+                    cv::Point(30+scale*(i+1), 30+scale*j), 
-                    cv::Point(10+scale*i, 10+scale*(j+1)), 
+                    cv::Point(30+scale*i, 30+scale*(j+1)), 
                     cv::Scalar(anchorPatch[i*N+j]*255, anchorPatch[i*N+j]*255, anchorPatch[i*N+j]*255),  
                     CV_FILLED);
 
   // irradiance grid projection
+
+  namer.str(std::string());
+  namer << "projection";
+  cv::putText(irradianceFrame, namer.str() , cvPoint(30, 45+scale*N), 
+    cv::FONT_HERSHEY_COMPLEX_SMALL, 0.8, cvScalar(0,0,0), 1, CV_AA);
+
   for(int i = 0; i<N; i++)
     for(int j = 0; j<N ; j++)
       cv::rectangle(irradianceFrame, 
-                    cv::Point(10+scale*(i+1), 20+scale*(N+j)), 
+                    cv::Point(30+scale*(i+1), 50+scale*(N+j)), 
-                    cv::Point(10+scale*(i), 20+scale*(N+j+1)), 
+                    cv::Point(30+scale*(i), 50+scale*(N+j+1)), 
                     cv::Scalar(projectionPatch[i*N+j]*255, projectionPatch[i*N+j]*255, projectionPatch[i*N+j]*255),  
                     CV_FILLED);
 
+  // true irradiance at feature
+  // get current observation
+
+  namer.str(std::string());
+  namer << "feature";
+  cv::putText(irradianceFrame, namer.str() , cvPoint(30, 65+scale*2*N), 
+    cv::FONT_HERSHEY_COMPLEX_SMALL, 0.8, cvScalar(0,0,0), 1, CV_AA);
+
+  cv::Point2f p_f(observations.find(cam_state_id)->second(0),observations.find(cam_state_id)->second(1));
+  // move to real pixels
+  p_f = image_handler::distortPoint(p_f, cam0.intrinsics, cam0.distortion_model, cam0.distortion_coeffs);
+
+  for(int i = 0; i<N; i++)
+  {
+    for(int j = 0; j<N ; j++)
+    {
+      float irr = PixelIrradiance(cv::Point2f(p_f.x + (i-(N-1)/2), p_f.y + (j-(N-1)/2)), current_image);
+      cv::rectangle(irradianceFrame, 
+                    cv::Point(30+scale*(i+1), 70+scale*(2*N+j)), 
+                    cv::Point(30+scale*(i), 70+scale*(2*N+j+1)), 
+                    cv::Scalar(irr*255, irr*255, irr*255),  
+                    CV_FILLED);
+    }
+  }
+
   // residual grid projection, positive - red, negative - blue colored 
+  namer.str(std::string());
+  namer << "residual";
+  cv::putText(irradianceFrame, namer.str() , cvPoint(30+scale*N, scale*N/2-5), 
+    cv::FONT_HERSHEY_COMPLEX_SMALL, 0.8, cvScalar(0,0,0), 1, CV_AA);
+
   for(int i = 0; i<N; i++)
     for(int j = 0; j<N; j++)
       if(photo_r[i*N+j]>0)
         cv::rectangle(irradianceFrame, 
-                      cv::Point(20+scale*(N+i+1), 15+scale*(N/2+j)), 
+                      cv::Point(40+scale*(N+i+1), 15+scale*(N/2+j)), 
-                      cv::Point(20+scale*(N+i), 15+scale*(N/2+j+1)), 
+                      cv::Point(40+scale*(N+i), 15+scale*(N/2+j+1)), 
                       cv::Scalar(255 - photo_r[i*N+j]*255, 255 - photo_r[i*N+j]*255, 255),  
                       CV_FILLED);
       else
         cv::rectangle(irradianceFrame, 
-                      cv::Point(20+scale*(N+i+1), 15+scale*(N/2+j)), 
+                      cv::Point(40+scale*(N+i+1), 15+scale*(N/2+j)), 
-                      cv::Point(20+scale*(N+i), 15+scale*(N/2+j+1)), 
+                      cv::Point(40+scale*(N+i), 15+scale*(N/2+j+1)), 
                       cv::Scalar(255, 255 + photo_r[i*N+j]*255, 255 + photo_r[i*N+j]*255), 
                       CV_FILLED);
 
-      cv::hconcat(cam0.featureVisu, irradianceFrame, cam0.featureVisu);
+  // gradient arrow
+  /*
+  cv::arrowedLine(irradianceFrame,
+                  cv::Point(30+scale*(N/2 +0.5), 50+scale*(N+(N/2)+0.5)),
+                  cv::Point(30+scale*(N/2+0.5)+scale*gradientVector.x, 50+scale*(N+(N/2)+0.5)+scale*gradientVector.y),
+                  cv::Scalar(100, 0, 255),
+                  1);
+  */
+
+  // residual gradient direction
+  cv::arrowedLine(irradianceFrame,
+                  cv::Point(40+scale*(N+N/2+0.5), 15+scale*((N-0.5))),
+                  cv::Point(40+scale*(N+N/2+0.5)+scale*residualVector.x, 15+scale*(N-0.5)+scale*residualVector.y),
+                  cv::Scalar(0, 255, 175),
+                  3);
+                  
+
+  cv::hconcat(cam0.featureVisu, irradianceFrame, cam0.featureVisu);
       
 /*
   // visualize position of used observations and resulting feature position
@@ -742,7 +809,7 @@ cv::Point2f Feature::projectPositionToCamera(
   return my_p;
 }
 
-Eigen::Vector3d Feature::projectPixelToPosition(cv::Point2f in_p, const CameraCalibration& cam)
+Eigen::Vector3d Feature::AnchorPixelToPosition(cv::Point2f in_p, const CameraCalibration& cam)
 {
   // use undistorted position of point of interest
   // project it back into 3D space using pinhole model

include/msckf_vio/image_handler.h

@@ -36,6 +36,16 @@ cv::Point2f distortPoint(
     const cv::Vec4d& intrinsics,
     const std::string& distortion_model,
     const cv::Vec4d& distortion_coeffs);
+
+void undistortPoint(
+    const cv::Point2f& pt_in,
+    const cv::Vec4d& intrinsics,
+    const std::string& distortion_model,
+    const cv::Vec4d& distortion_coeffs,
+    cv::Point2f& pt_out,
+    const cv::Matx33d &rectification_matrix = cv::Matx33d::eye(),
+    const cv::Vec4d &new_intrinsics = cv::Vec4d(1,1,0,0));
+
 }
 }
 #endif

include/msckf_vio/msckf_vio.h

@@ -14,7 +14,7 @@
 #include <string>
 #include <Eigen/Dense>
 #include <Eigen/Geometry>
-
+#include <math.h>
 #include <boost/shared_ptr.hpp>
 #include <opencv2/opencv.hpp>
 #include <opencv2/video.hpp>
@@ -38,6 +38,8 @@
 #include <message_filters/subscriber.h>
 #include <message_filters/time_synchronizer.h>
 
+#define PI 3.14159265
+
 namespace msckf_vio {
 /*
  * @brief MsckfVio Implements the algorithm in

launch/msckf_vio_tum.launch

@@ -24,7 +24,7 @@
       <param name="PrintImages" value="true"/>
       <param name="GroundTruth" value="false"/>
 
-      <param name="patch_size_n" value="7"/>
+      <param name="patch_size_n" value="5"/>
       <!-- Calibration parameters -->
       <rosparam command="load" file="$(arg calibration_file)"/>
 

src/image_handler.cpp

@@ -14,6 +14,47 @@ namespace msckf_vio {
 namespace image_handler {
 
 
+void undistortPoint(
+    const cv::Point2f& pt_in,
+    const cv::Vec4d& intrinsics,
+    const std::string& distortion_model,
+    const cv::Vec4d& distortion_coeffs,
+    cv::Point2f& pt_out,
+    const cv::Matx33d &rectification_matrix,
+    const cv::Vec4d &new_intrinsics) {
+
+
+  std::vector<cv::Point2f> pts_in;
+  std::vector<cv::Point2f> pts_out;
+  pts_in.push_back(pt_in);
+  if (pts_in.size() == 0) return;
+
+  const cv::Matx33d K(
+      intrinsics[0], 0.0, intrinsics[2],
+      0.0, intrinsics[1], intrinsics[3],
+      0.0, 0.0, 1.0);
+
+  const cv::Matx33d K_new(
+      new_intrinsics[0], 0.0, new_intrinsics[2],
+      0.0, new_intrinsics[1], new_intrinsics[3],
+      0.0, 0.0, 1.0);
+
+  if (distortion_model == "radtan") {
+    cv::undistortPoints(pts_in, pts_out, K, distortion_coeffs,
+                        rectification_matrix, K_new);
+  } else if (distortion_model == "equidistant") {
+    cv::fisheye::undistortPoints(pts_in, pts_out, K, distortion_coeffs,
+                                 rectification_matrix, K_new);
+  } else {
+    ROS_WARN_ONCE("The model %s is unrecognized, use radtan instead...",
+                  distortion_model.c_str());
+    cv::undistortPoints(pts_in, pts_out, K, distortion_coeffs,
+                        rectification_matrix, K_new);
+  }
+  pt_out = pts_out[0];
+  return;
+}
+
 void undistortPoints(
     const std::vector<cv::Point2f>& pts_in,
     const cv::Vec4d& intrinsics,

src/msckf_vio.cpp

@@ -1238,10 +1238,31 @@ void MsckfVio::PhotometricMeasurementJacobian(
 
   auto frame = cam0.moving_window.find(cam_state_id)->second.image;
 
+  //observation
+  const Vector4d& z = feature.observations.find(cam_state_id)->second;
+
+  //estimate photometric measurement
+  std::vector<double> estimate_irradiance;
+  std::vector<double> estimate_photo_z;
+  IlluminationParameter estimated_illumination;
+  feature.estimate_FrameIrradiance(cam_state, cam_state_id, cam0, estimate_irradiance, estimated_illumination);
+  
+  // calculated here, because we need true 'estimate_irradiance' later for jacobi
+  for (auto& estimate_irradiance_j : estimate_irradiance)
+            estimate_photo_z.push_back (estimate_irradiance_j * 
+                    estimated_illumination.frame_gain * estimated_illumination.feature_gain +
+                    estimated_illumination.frame_bias + estimated_illumination.feature_bias);
+
   int count = 0;
   double dx, dy;
 
   std::vector<float> z_irr_est;
+  // gradient visualization parameters
+  cv::Point2f gradientVector(0,0);
+
+  // residual change visualization
+  cv::Point2f residualVector(0,0);
+  double res_sum = 0;
 
   for (auto point : feature.anchorPatch_3d)
   {
@@ -1251,6 +1272,10 @@ void MsckfVio::PhotometricMeasurementJacobian(
     z_irr_est.push_back(feature.PixelIrradiance(p_in_c0, frame));
 
     Matrix<double, 1, 2> dI_dhj = Matrix<double, 1, 2>::Zero();
+      //calculate photom. residual
+    photo_r.push_back(photo_z[count] - estimate_photo_z[count]);
+
+    // add jacobians
 
     // frame derivative calculated convoluting with kernel [-1, 0, 1]
     dx = feature.PixelIrradiance(cv::Point2f(p_in_c0.x+1, p_in_c0.y), frame) - feature.PixelIrradiance(cv::Point2f(p_in_c0.x-1, p_in_c0.y), frame);
@@ -1276,6 +1301,41 @@ void MsckfVio::PhotometricMeasurementJacobian(
     H_xi = dI_dhj*dz_dpc0*dpc0_dxc;
     H_fi = dI_dhj*dz_dpc0*dpc0_dpg;
 
+    gradientVector.x += dx;
+    gradientVector.y += dy; 
+    
+    residualVector.x += dx * photo_r[count];
+    residualVector.y += dy * photo_r[count];
+    res_sum += photo_r[count];
+
+    //dh / d{}^Cp_{ij}
+    dh_dCpij(0, 0) = 1 / p_c0(2);
+    dh_dCpij(1, 1) = 1 / p_c0(2);
+    dh_dCpij(0, 2) = -(p_c0(0))/(p_c0(2)*p_c0(2));
+    dh_dCpij(1, 2) = -(p_c0(1))/(p_c0(2)*p_c0(2));
+
+    dCpij_dGpij = quaternionToRotation(cam_state.orientation);
+
+    //orientation takes camera frame to world frame, we wa
+    dh_dGpij = dh_dCpij * dCpij_dGpij;
+
+    //dh / d X_{pl}
+    dCpij_dCGtheta = skewSymmetric(p_c0);
+    dCpij_dGpC = -quaternionToRotation(cam_state.orientation);
+    dh_dXplj.block<2, 3>(0, 0) = dh_dCpij * dCpij_dCGtheta;
+    dh_dXplj.block<2, 3>(0, 3) = dh_dCpij * dCpij_dGpC;
+
+    //d{}^Gp_P{ij} / \rho_i
+    double rho = feature.anchor_rho;
+    // Isometry T_anchor_w takes a vector in anchor frame to world frame
+    dGpj_drhoj = -feature.T_anchor_w.linear() * Eigen::Vector3d(feature.anchorPatch_ideal[count].x/(rho*rho), feature.anchorPatch_ideal[count].y/(rho*rho), 1/(rho*rho));
+
+    dGpj_XpAj.block<3, 3>(0, 0) = - feature.T_anchor_w.linear()
+                                 * skewSymmetric(Eigen::Vector3d(feature.anchorPatch_ideal[count].x/(rho), 
+                                                   feature.anchorPatch_ideal[count].y/(rho), 
+                                                   1/(rho)));
+    dGpj_XpAj.block<3, 3>(0, 3) = Matrix<double, 3, 3>::Identity();
+
     H_xl.block<1, 6>(count, 0) = H_xi;
     H_yl.block<1, 3>(count, 0) = H_fi;
 
@@ -1296,7 +1356,23 @@ void MsckfVio::PhotometricMeasurementJacobian(
   r = r_l;
   H_x = H_xl;
   H_y = H_yl;
+<<<<<<< HEAD
   // calculate residual
+=======
+
+  //TODO make this more fluent as well
+  count = 0; 
+  for(auto data : photo_r)
+    r[count++] = data;
+
+  std::stringstream ss;
+  ss << "INFO:" << " anchor: " << cam_state_cntr_anchor << "  frame: " << cam_state_cntr;
+  if(PRINTIMAGES)
+  {  
+    feature.MarkerGeneration(marker_pub, state_server.cam_states);
+    feature.VisualizePatch(cam_state, cam_state_id, cam0, photo_r, ss, gradientVector, residualVector);
+  }
+>>>>>>> photometry-jakobi
 
   return;
 }
@@ -1392,14 +1468,12 @@ void MsckfVio::PhotometricFeatureJacobian(
   H_x = A_null_space.transpose() * H_xi;
   r = A_null_space.transpose() * r_i;
 
-  
   ofstream myfile;
   myfile.open ("/home/raphael/dev/MSCKF_ws/log.txt");
-  myfile << "-- residual -- \n" << r << "\n---- H ----\n" << H_x << "\n---- state cov ----\n" << state_server.state_cov <<endl;
+  myfile << "Hx\n" << H_x << "r\n" << r << "from residual estimated error state: " << H_x. * r << endl;
   myfile.close();
   cout << "---------- LOGGED -------- " << endl; 
 
-
   if(PRINTIMAGES)
   {
     std::cout << "resume playback" << std::endl;
@@ -1551,13 +1625,11 @@ void MsckfVio::featureJacobian(
   
   ofstream myfile;
   myfile.open ("/home/raphael/dev/MSCKF_ws/log.txt");
-  myfile << "-- residual -- \n" << r << "\n---- H ----\n" << H_x << "\n---- state cov ----\n" << state_server.state_cov <<endl;
+  myfile << "Hx\n" << H_x << "r\n" << r << "from residual estimated error state: " << H_x.ldlt().solve(r) << endl;
   myfile.close();
   cout << "---------- LOGGED -------- " << endl; 
-  
-  nh.setParam("/play_bag", false);
-
   return;
+
 }
 
 void MsckfVio::measurementUpdate(const MatrixXd& H, const VectorXd& r) {
@@ -1568,7 +1640,11 @@ void MsckfVio::measurementUpdate(const MatrixXd& H, const VectorXd& r) {
   // complexity as in Equation (28), (29).
   MatrixXd H_thin;
   VectorXd r_thin;
+  int augmentationSize = 6;
+  if(PHOTOMETRIC)
+    augmentationSize = 7;
 
+  /*
   if (H.rows() > H.cols()) {
     // Convert H to a sparse matrix.
     SparseMatrix<double> H_sparse = H.sparseView();
@@ -1583,8 +1659,8 @@ void MsckfVio::measurementUpdate(const MatrixXd& H, const VectorXd& r) {
     (spqr_helper.matrixQ().transpose() * H).evalTo(H_temp);
     (spqr_helper.matrixQ().transpose() * r).evalTo(r_temp);
 
-    H_thin = H_temp.topRows(21+state_server.cam_states.size()*6);
+    H_thin = H_temp.topRows(21+state_server.cam_states.size()*augmentationSize);
-    r_thin = r_temp.head(21+state_server.cam_states.size()*6);
+    r_thin = r_temp.head(21+state_server.cam_states.size()*augmentationSize);
 
     //HouseholderQR<MatrixXd> qr_helper(H);
     //MatrixXd Q = qr_helper.householderQ();
@@ -1596,18 +1672,19 @@ void MsckfVio::measurementUpdate(const MatrixXd& H, const VectorXd& r) {
     H_thin = H;
     r_thin = r;
   }
+  */
 
   // Compute the Kalman gain.
   const MatrixXd& P = state_server.state_cov;
-  MatrixXd S = H_thin*P*H_thin.transpose() +
+  MatrixXd S = H*P*H.transpose() +
       Feature::observation_noise*MatrixXd::Identity(
-        H_thin.rows(), H_thin.rows());
+        H.rows(), H.rows());
-  //MatrixXd K_transpose = S.fullPivHouseholderQr().solve(H_thin*P);
+  //MatrixXd K_transpose = S.fullPivHouseholderQr().solve(H*P);
-  MatrixXd K_transpose = S.ldlt().solve(H_thin*P);
+  MatrixXd K_transpose = S.ldlt().solve(H*P);
   MatrixXd K = K_transpose.transpose();
 
   // Compute the error of the state.
-  VectorXd delta_x = K * r_thin;
+  VectorXd delta_x = K * r;
 
   // Update the IMU state.
   const VectorXd& delta_x_imu = delta_x.head<21>();
@@ -1642,7 +1719,7 @@ void MsckfVio::measurementUpdate(const MatrixXd& H, const VectorXd& r) {
   auto cam_state_iter = state_server.cam_states.begin();
   for (int i = 0; i < state_server.cam_states.size();
       ++i, ++cam_state_iter) {
-    const VectorXd& delta_x_cam = delta_x.segment<6>(21+i*6);
+    const VectorXd& delta_x_cam = delta_x.segment(21+i*augmentationSize, augmentationSize);
     const Vector4d dq_cam = smallAngleQuaternion(delta_x_cam.head<3>());
     cam_state_iter->second.orientation = quaternionMultiplication(
         dq_cam, cam_state_iter->second.orientation);
@@ -1650,7 +1727,7 @@ void MsckfVio::measurementUpdate(const MatrixXd& H, const VectorXd& r) {
   }
 
   // Update state covariance.
-  MatrixXd I_KH = MatrixXd::Identity(K.rows(), H_thin.cols()) - K*H_thin;
+  MatrixXd I_KH = MatrixXd::Identity(K.rows(), H.cols()) - K*H;
   //state_server.state_cov = I_KH*state_server.state_cov*I_KH.transpose() +
   //  K*K.transpose()*Feature::observation_noise;
   state_server.state_cov = I_KH*state_server.state_cov;
@@ -1664,7 +1741,7 @@ void MsckfVio::measurementUpdate(const MatrixXd& H, const VectorXd& r) {
 }
 
 bool MsckfVio::gatingTest(const MatrixXd& H, const VectorXd& r, const int& dof) {
-
+  return true;
   MatrixXd P1 = H * state_server.state_cov * H.transpose();