restructured calcualtion of patches in code
This commit is contained in:
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58fe991647
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737c23f32a
@ -202,7 +202,8 @@ class MsckfVio {
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Eigen::Vector4d& r);
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// This function computes the Jacobian of all measurements viewed
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// in the given camera states of this feature.
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void featureJacobian(const FeatureIDType& feature_id,
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void featureJacobian(
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const FeatureIDType& feature_id,
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const std::vector<StateIDType>& cam_state_ids,
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Eigen::MatrixXd& H_x, Eigen::VectorXd& r);
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@ -212,6 +213,29 @@ class MsckfVio {
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const FeatureIDType& feature_id,
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Eigen::MatrixXd& H_x, Eigen::MatrixXd& H_y, Eigen::VectorXd& r);
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bool ConstructJacobians(
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Eigen::MatrixXd& H_rho,
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Eigen::MatrixXd& H_pl,
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Eigen::MatrixXd& H_pA,
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const Feature& feature,
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const StateIDType& cam_state_id,
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Eigen::MatrixXd& H_xl,
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Eigen::MatrixXd& H_yl);
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bool PhotometricPatchPointResidual(
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const StateIDType& cam_state_id,
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const Feature& feature,
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Eigen::VectorXd& r);
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bool PhotometricPatchPointJacobian(
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const CAMState& cam_state,
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const Feature& feature,
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Eigen::Vector3d point,
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int count,
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Eigen::Matrix<double, 1, 1>& H_rhoj,
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Eigen::Matrix<double, 1, 6>& H_plj,
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Eigen::Matrix<double, 1, 6>& H_pAj);
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bool PhotometricMeasurementJacobian(
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const StateIDType& cam_state_id,
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const FeatureIDType& feature_id,
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@ -263,6 +287,13 @@ class MsckfVio {
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// Chi squared test table.
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static std::map<int, double> chi_squared_test_table;
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double eval_time;
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IMUState timed_old_imu_state;
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IMUState timed_old_true_state;
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IMUState old_imu_state;
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IMUState old_true_state;
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// change in position
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Eigen::Vector3d delta_position;
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@ -18,14 +18,14 @@
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output="screen">
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<!-- Filter Flag, 0 = msckf, 1 = photometric, 2 = two -->
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<param name="FILTER" value="1"/>
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<param name="FILTER" value="0"/>
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<!-- Debugging Flaggs -->
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<param name="StreamPause" value="true"/>
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<param name="PrintImages" value="false"/>
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<param name="GroundTruth" value="false"/>
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<param name="patch_size_n" value="5"/>
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<param name="patch_size_n" value="3"/>
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<!-- Calibration parameters -->
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<rosparam command="load" file="$(arg calibration_file)"/>
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@ -223,8 +223,8 @@ void ImageProcessor::stereoCallback(
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image_handler::undistortImage(cam0_curr_img_ptr->image, cam0_curr_img_ptr->image, cam0.distortion_model, cam0.intrinsics, cam0.distortion_coeffs);
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image_handler::undistortImage(cam1_curr_img_ptr->image, cam1_curr_img_ptr->image, cam1.distortion_model, cam1.intrinsics, cam1.distortion_coeffs);
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ROS_INFO("Publishing: %f",
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(ros::Time::now()-start_time).toSec());
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//ROS_INFO("Publishing: %f",
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// (ros::Time::now()-start_time).toSec());
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// Build the image pyramids once since they're used at multiple places
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createImagePyramids();
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@ -260,6 +260,7 @@ bool MsckfVio::createRosIO() {
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// activating bag playing parameter, for debugging
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nh.setParam("/play_bag", true);
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eval_time = 0;
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odom_pub = nh.advertise<nav_msgs::Odometry>("odom", 10);
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truth_odom_pub = nh.advertise<nav_msgs::Odometry>("true_odom", 10);
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feature_pub = nh.advertise<sensor_msgs::PointCloud2>(
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@ -412,6 +413,10 @@ void MsckfVio::imageCallback(
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return;
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}
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old_imu_state = state_server.imu_state;
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old_true_state = true_state_server.imu_state;
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// Start the system if the first image is received.
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// The frame where the first image is received will be
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// the origin.
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@ -419,7 +424,6 @@ void MsckfVio::imageCallback(
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is_first_img = false;
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state_server.imu_state.time = feature_msg->header.stamp.toSec();
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}
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static double max_processing_time = 0.0;
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static int critical_time_cntr = 0;
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double processing_start_time = ros::Time::now().toSec();
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@ -428,23 +432,13 @@ void MsckfVio::imageCallback(
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// that are received before the image feature_msg.
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ros::Time start_time = ros::Time::now();
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nh.param<int>("FILTER", FILTER, 0);
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batchImuProcessing(feature_msg->header.stamp.toSec());
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if(GROUNDTRUTH)
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{
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state_server.imu_state.position = true_state_server.imu_state.position;
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state_server.imu_state.orientation = true_state_server.imu_state.orientation;
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state_server.imu_state.position_null = true_state_server.imu_state.position_null;
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state_server.imu_state.orientation_null = true_state_server.imu_state.orientation_null;
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state_server.imu_state.R_imu_cam0 = true_state_server.imu_state.R_imu_cam0;
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state_server.imu_state.t_cam0_imu = true_state_server.imu_state.t_cam0_imu;
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}
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double imu_processing_time = (
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ros::Time::now()-start_time).toSec();
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cout << "1" << endl;
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// Augment the state vector.
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start_time = ros::Time::now();
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//truePhotometricStateAugmentation(feature_msg->header.stamp.toSec());
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@ -453,7 +447,7 @@ void MsckfVio::imageCallback(
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ros::Time::now()-start_time).toSec();
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cout << "2" << endl;
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// cout << "2" << endl;
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// Add new observations for existing features or new
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// features in the map server.
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start_time = ros::Time::now();
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@ -462,7 +456,7 @@ void MsckfVio::imageCallback(
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ros::Time::now()-start_time).toSec();
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cout << "3" << endl;
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// cout << "3" << endl;
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// Add new images to moving window
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start_time = ros::Time::now();
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manageMovingWindow(cam0_img, cam1_img, feature_msg);
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@ -470,14 +464,14 @@ void MsckfVio::imageCallback(
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ros::Time::now()-start_time).toSec();
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cout << "4" << endl;
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// cout << "4" << endl;
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// Perform measurement update if necessary.
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start_time = ros::Time::now();
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removeLostFeatures();
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double remove_lost_features_time = (
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ros::Time::now()-start_time).toSec();
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cout << "5" << endl;
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// cout << "5" << endl;
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start_time = ros::Time::now();
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pruneLastCamStateBuffer();
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double prune_cam_states_time = (
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@ -487,7 +481,7 @@ void MsckfVio::imageCallback(
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batchTruthProcessing(feature_msg->header.stamp.toSec());
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cout << "6" << endl;
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// cout << "6" << endl;
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// Publish the odometry.
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start_time = ros::Time::now();
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publish(feature_msg->header.stamp);
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@ -504,18 +498,18 @@ void MsckfVio::imageCallback(
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++critical_time_cntr;
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ROS_INFO("\033[1;31mTotal processing time %f/%d...\033[0m",
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processing_time, critical_time_cntr);
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printf("IMU processing time: %f/%f\n",
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imu_processing_time, imu_processing_time/processing_time);
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printf("State augmentation time: %f/%f\n",
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state_augmentation_time, state_augmentation_time/processing_time);
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printf("Add observations time: %f/%f\n",
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add_observations_time, add_observations_time/processing_time);
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printf("Remove lost features time: %f/%f\n",
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remove_lost_features_time, remove_lost_features_time/processing_time);
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printf("Remove camera states time: %f/%f\n",
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prune_cam_states_time, prune_cam_states_time/processing_time);
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printf("Publish time: %f/%f\n",
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publish_time, publish_time/processing_time);
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//printf("IMU processing time: %f/%f\n",
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// imu_processing_time, imu_processing_time/processing_time);
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//printf("State augmentation time: %f/%f\n",
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// state_augmentation_time, state_augmentation_time/processing_time);
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//printf("Add observations time: %f/%f\n",
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// add_observations_time, add_observations_time/processing_time);
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//printf("Remove lost features time: %f/%f\n",
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// remove_lost_features_time, remove_lost_features_time/processing_time);
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//printf("Remove camera states time: %f/%f\n",
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// prune_cam_states_time, prune_cam_states_time/processing_time);
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//printf("Publish time: %f/%f\n",
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// publish_time, publish_time/processing_time);
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}
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if(STREAMPAUSE)
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@ -806,8 +800,6 @@ void MsckfVio::batchTruthProcessing(const double& time_bound) {
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// Counter how many IMU msgs in the buffer are used.
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int used_truth_msg_cntr = 0;
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const IMUState old_true_state = true_state_server.imu_state;
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for (const auto& truth_msg : truth_msg_buffer) {
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double truth_time = truth_msg.header.stamp.toSec();
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if (truth_time < true_state_server.imu_state.time) {
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@ -839,22 +831,76 @@ void MsckfVio::batchTruthProcessing(const double& time_bound) {
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truth_msg_buffer.erase(truth_msg_buffer.begin(),
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truth_msg_buffer.begin()+used_truth_msg_cntr);
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/*
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// calculate change
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delta_position = state_server.imu_state.position - old_imu_state.position;
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Eigen::Vector4d delta_orientation_quaternion = quaternionMultiplication(quaternionConjugate(state_server.imu_state.orientation), old_imu_state.orientation);
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delta_orientation = Eigen::Vector3d(delta_orientation_quaternion[0]*2, delta_orientation_quaternion[1]*2, delta_orientation_quaternion[2]*2);
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// calculate error in position
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// calculate error in change
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// calculate change
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Eigen::Vector3d delta_true_position = true_state_server.imu_state.position - old_true_state.position;
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Eigen::Vector4d delta_true_orientation = quaternionMultiplication(quaternionConjugate(true_state_server.imu_state.orientation), old_true_state.orientation);
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Eigen::Vector3d delta_smallangle_true_orientation = Eigen::Vector3d(delta_true_orientation[0]*2, delta_true_orientation[1]*2, delta_true_orientation[2]*2);
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Eigen::Vector3d error_delta_position = delta_true_position - delta_position;
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Eigen::Vector3d error_delta_orientation = delta_smallangle_true_orientation - delta_orientation;
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double dx = (error_delta_position[0]/delta_true_position[0]);
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double dy = (error_delta_position[1]/delta_true_position[1]);
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double dz = (error_delta_position[2]/delta_true_position[2]);
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cout << "relative pos error: " << sqrt(dx*dx + dy*dy + dz*dz) * 100 << "%" << endl;
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Eigen::Vector3d error_position = true_state_server.imu_state.position - state_server.imu_state.position;
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Eigen::Vector4d error_orientation_q = quaternionMultiplication(quaternionConjugate(true_state_server.imu_state.orientation), state_server.imu_state.orientation);
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Eigen::Vector3d error_orientation = Eigen::Vector3d(error_orientation_q[0]*2, error_orientation_q[1]*2, error_orientation_q[2]*2);
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double relerr = (sqrt(error_delta_position[0]*error_delta_position[0] + error_delta_position[1]*error_delta_position[1] + error_delta_position[2]*error_delta_position[2])/
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sqrt(delta_true_position[0]*delta_true_position[0] + delta_true_position[1]*delta_true_position[1] + delta_true_position[2]*delta_true_position[2]));
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double relOerr = (sqrt(error_delta_orientation[0]*error_delta_orientation[0] + error_delta_orientation[1]*error_delta_orientation[1] + error_delta_orientation[2]*error_delta_orientation[2])/
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sqrt(delta_smallangle_true_orientation[0]*delta_smallangle_true_orientation[0] + delta_smallangle_true_orientation[1]*delta_smallangle_true_orientation[1] + delta_smallangle_true_orientation[2]*delta_smallangle_true_orientation[2]));
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double abserr = (sqrt(error_delta_position[0]*error_delta_position[0] + error_delta_position[1]*error_delta_position[1] + error_delta_position[2]*error_delta_position[2])/
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sqrt(delta_true_position[0]*delta_true_position[0] + delta_true_position[1]*delta_true_position[1] + delta_true_position[2]*delta_true_position[2]));
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cout << "relative pos error: " << relerr * 100 << "%" << endl;
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cout << "relative ori error: " << relOerr * 100 << "%" << endl;
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//cout << "absolute pos error: " <<
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*/
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if (eval_time + 1 < ros::Time::now().toSec())
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{
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// calculate change
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delta_position = state_server.imu_state.position - timed_old_imu_state.position;
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Eigen::Vector4d delta_orientation_quaternion = quaternionMultiplication(quaternionConjugate(state_server.imu_state.orientation), timed_old_imu_state.orientation);
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delta_orientation = Eigen::Vector3d(delta_orientation_quaternion[0]*2, delta_orientation_quaternion[1]*2, delta_orientation_quaternion[2]*2);
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// calculate error in position
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// calculate error in change
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Eigen::Vector3d delta_true_position = true_state_server.imu_state.position - timed_old_true_state.position;
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Eigen::Vector4d delta_true_orientation = quaternionMultiplication(quaternionConjugate(true_state_server.imu_state.orientation), timed_old_true_state.orientation);
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Eigen::Vector3d delta_smallangle_true_orientation = Eigen::Vector3d(delta_true_orientation[0]*2, delta_true_orientation[1]*2, delta_true_orientation[2]*2);
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Eigen::Vector3d error_delta_position = delta_true_position - delta_position;
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Eigen::Vector3d error_delta_orientation = delta_smallangle_true_orientation - delta_orientation;
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Eigen::Vector3d error_position = true_state_server.imu_state.position - state_server.imu_state.position;
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Eigen::Vector4d error_orientation_q = quaternionMultiplication(quaternionConjugate(true_state_server.imu_state.orientation), state_server.imu_state.orientation);
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Eigen::Vector3d error_orientation = Eigen::Vector3d(error_orientation_q[0]*2, error_orientation_q[1]*2, error_orientation_q[2]*2);
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double relerr = (sqrt(error_delta_position[0]*error_delta_position[0] + error_delta_position[1]*error_delta_position[1] + error_delta_position[2]*error_delta_position[2])/
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sqrt(delta_true_position[0]*delta_true_position[0] + delta_true_position[1]*delta_true_position[1] + delta_true_position[2]*delta_true_position[2]));
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double relOerr = (sqrt(error_delta_orientation[0]*error_delta_orientation[0] + error_delta_orientation[1]*error_delta_orientation[1] + error_delta_orientation[2]*error_delta_orientation[2])/
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sqrt(delta_smallangle_true_orientation[0]*delta_smallangle_true_orientation[0] + delta_smallangle_true_orientation[1]*delta_smallangle_true_orientation[1] + delta_smallangle_true_orientation[2]*delta_smallangle_true_orientation[2]));
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double abserr = (sqrt(error_delta_position[0]*error_delta_position[0] + error_delta_position[1]*error_delta_position[1] + error_delta_position[2]*error_delta_position[2])/
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sqrt(delta_true_position[0]*delta_true_position[0] + delta_true_position[1]*delta_true_position[1] + delta_true_position[2]*delta_true_position[2]));
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// cout << "relative pos error: " << relerr * 100 << "%" << endl;
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// cout << "relative ori error: " << relOerr * 100 << "%" << endl;
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timed_old_imu_state = state_server.imu_state;
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timed_old_true_state = true_state_server.imu_state;
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eval_time = ros::Time::now().toSec();
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}
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}
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void MsckfVio::processTruthtoIMU(const double& time,
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@ -1477,17 +1523,60 @@ void MsckfVio::twodotFeatureJacobian(
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return;
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}
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bool MsckfVio::PhotometricMeasurementJacobian(
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bool MsckfVio::PhotometricPatchPointResidual(
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const StateIDType& cam_state_id,
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const FeatureIDType& feature_id,
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MatrixXd& H_x, MatrixXd& H_y, VectorXd& r)
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const Feature& feature,
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VectorXd& r)
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{
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// Prepare all the required data.
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VectorXd r_photo = VectorXd::Zero(N*N);
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int count = 0;
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auto frame = cam0.moving_window.find(cam_state_id)->second.image;
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const CAMState& cam_state = state_server.cam_states[cam_state_id];
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const Feature& feature = map_server[feature_id];
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//estimate photometric measurement
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std::vector<double> estimate_irradiance;
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std::vector<double> estimate_photo_z;
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std::vector<double> photo_z;
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IlluminationParameter estimated_illumination;
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feature.estimate_FrameIrradiance(cam_state, cam_state_id, cam0, estimate_irradiance, estimated_illumination);
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for (auto& estimate_irradiance_j : estimate_irradiance)
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estimate_photo_z.push_back (estimate_irradiance_j *
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estimated_illumination.frame_gain * estimated_illumination.feature_gain +
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estimated_illumination.frame_bias + estimated_illumination.feature_bias);
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for(auto point : feature.anchorPatch_3d)
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{
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cv::Point2f p_in_c0 = feature.projectPositionToCamera(cam_state, cam_state_id, cam0, point);
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// test if projection is inside frame
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if(p_in_c0.x < 0 or p_in_c0.x > frame.cols-1 or p_in_c0.y < 0 or p_in_c0.y > frame.rows-1)
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return false;
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//add observation
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photo_z.push_back(feature.PixelIrradiance(p_in_c0, frame));
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//calculate photom. residual
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r_photo(count) = photo_z[count] - estimate_photo_z[count];
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count++;
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}
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r = r_photo;
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return true;
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}
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// generates the jacobian of one patch point regarding rho, anchor and current frame
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bool MsckfVio::PhotometricPatchPointJacobian(
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const CAMState& cam_state,
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const Feature& feature,
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Eigen::Vector3d point,
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int count,
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Eigen::Matrix<double, 1, 1>& H_rhoj,
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Eigen::Matrix<double, 1, 6>& H_plj,
|
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Eigen::Matrix<double, 1, 6>& H_pAj)
|
||||
{
|
||||
|
||||
const StateIDType anchor_state_id = feature.observations.begin()->first;
|
||||
const CAMState anchor_state = state_server.cam_states[anchor_state_id];
|
||||
@ -1502,9 +1591,6 @@ bool MsckfVio::PhotometricMeasurementJacobian(
|
||||
Vector3d t_c1_w = t_c0_w - R_w_c1.transpose()*CAMState::T_cam0_cam1.translation();
|
||||
|
||||
|
||||
//photometric observation
|
||||
std::vector<double> photo_z;
|
||||
VectorXd r_photo = VectorXd::Zero(N*N);
|
||||
// individual Jacobians
|
||||
Matrix<double, 1, 2> dI_dhj = Matrix<double, 1, 2>::Zero();
|
||||
Matrix<double, 2, 3> dh_dCpij = Matrix<double, 2, 3>::Zero();
|
||||
@ -1517,64 +1603,17 @@ bool MsckfVio::PhotometricMeasurementJacobian(
|
||||
Matrix<double, 3, 3> dCpij_dCGtheta = Matrix<double, 3, 3>::Zero();
|
||||
Matrix<double, 3, 3> dCpij_dGpC = Matrix<double, 3, 3>::Zero();
|
||||
|
||||
// one line of the NxN Jacobians
|
||||
Eigen::Matrix<double, 1, 1> H_rhoj;
|
||||
Eigen::Matrix<double, 1, 6> H_plj;
|
||||
Eigen::Matrix<double, 1, 6> H_pAj;
|
||||
|
||||
// combined Jacobians
|
||||
Eigen::MatrixXd H_rho(N*N, 1);
|
||||
Eigen::MatrixXd H_pl(N*N, 6);
|
||||
Eigen::MatrixXd H_pA(N*N, 6);
|
||||
|
||||
auto frame = cam0.moving_window.find(cam_state_id)->second.image;
|
||||
auto anchor_frame = cam0.moving_window.find(anchor_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;
|
||||
|
||||
for (auto point : feature.anchorPatch_3d)
|
||||
{
|
||||
//cout << "____feature-measurement_____\n" << endl;
|
||||
Eigen::Vector3d p_c0 = R_w_c0 * (point-t_c0_w);
|
||||
cv::Point2f p_in_c0 = feature.projectPositionToCamera(cam_state, cam_state_id, cam0, point);
|
||||
cv::Point2f p_in_anchor = feature.projectPositionToCamera(anchor_state, anchor_state_id, cam0, point);
|
||||
|
||||
if(p_in_c0.x < 0 or p_in_c0.x > frame.cols-1 or p_in_c0.y < 0 or p_in_c0.y > frame.rows-1)
|
||||
{
|
||||
cout << "skipped" << endl;
|
||||
return false;
|
||||
}
|
||||
//add observation
|
||||
photo_z.push_back(feature.PixelIrradiance(p_in_c0, frame));
|
||||
|
||||
//calculate photom. residual
|
||||
r_photo(count) = photo_z[count] - estimate_photo_z[count];
|
||||
//cout << "residual: " << photo_r.back() << endl;
|
||||
|
||||
// calculate derivation for anchor frame, use position for derivation calculation
|
||||
// frame derivative calculated convoluting with kernel [-1, 0, 1]
|
||||
|
||||
dx = feature.cvKernel(p_in_anchor, "Sobel_x");
|
||||
dy = feature.cvKernel(p_in_anchor, "Sobel_y");
|
||||
|
||||
// dx = feature.PixelIrradiance(cv::Point2f(p_in_anchor.x+1, p_in_anchor.y), anchor_frame) - feature.PixelIrradiance(cv::Point2f(p_in_anchor.x-1, p_in_anchor.y), anchor_frame);
|
||||
// dy = feature.PixelIrradiance(cv::Point2f(p_in_anchor.x, p_in_anchor.y+1), anchor_frame) - feature.PixelIrradiance(cv::Point2f(p_in_anchor.x, p_in_anchor.y-1), anchor_frame);
|
||||
|
||||
dI_dhj(0, 0) = dx * cam0.intrinsics[0];
|
||||
dI_dhj(0, 1) = dy * cam0.intrinsics[1];
|
||||
|
||||
@ -1611,6 +1650,45 @@ bool MsckfVio::PhotometricMeasurementJacobian(
|
||||
H_plj = dI_dhj * dh_dXplj; // 1 x 6
|
||||
H_pAj = dI_dhj * dh_dGpij * dGpj_XpAj; // 1 x 6
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
bool MsckfVio::PhotometricMeasurementJacobian(
|
||||
const StateIDType& cam_state_id,
|
||||
const FeatureIDType& feature_id,
|
||||
MatrixXd& H_x, MatrixXd& H_y, VectorXd& r)
|
||||
{
|
||||
|
||||
// Prepare all the required data.
|
||||
const CAMState& cam_state = state_server.cam_states[cam_state_id];
|
||||
const Feature& feature = map_server[feature_id];
|
||||
|
||||
//photometric observation
|
||||
VectorXd r_photo = VectorXd::Zero(N*N);
|
||||
|
||||
// one line of the NxN Jacobians
|
||||
Eigen::Matrix<double, 1, 1> H_rhoj;
|
||||
Eigen::Matrix<double, 1, 6> H_plj;
|
||||
Eigen::Matrix<double, 1, 6> H_pAj;
|
||||
|
||||
// combined Jacobians
|
||||
Eigen::MatrixXd H_rho(N*N, 1);
|
||||
Eigen::MatrixXd H_pl(N*N, 6);
|
||||
Eigen::MatrixXd H_pA(N*N, 6);
|
||||
|
||||
auto frame = cam0.moving_window.find(cam_state_id)->second.image;
|
||||
|
||||
// calcualte residual of patch
|
||||
PhotometricPatchPointResidual(cam_state_id, feature, r_photo);
|
||||
|
||||
// calculate jacobian for patch
|
||||
int count = 0;
|
||||
for (auto point : feature.anchorPatch_3d)
|
||||
{
|
||||
// get jacobi of single point in patch
|
||||
PhotometricPatchPointJacobian(cam_state, feature, point, count, H_rhoj, H_plj, H_pAj);
|
||||
|
||||
// stack point into entire jacobi
|
||||
H_rho.block<1, 1>(count, 0) = H_rhoj;
|
||||
H_pl.block<1, 6>(count, 0) = H_plj;
|
||||
H_pA.block<1, 6>(count, 0) = H_pAj;
|
||||
@ -1618,22 +1696,58 @@ bool MsckfVio::PhotometricMeasurementJacobian(
|
||||
count++;
|
||||
}
|
||||
|
||||
cout << "done" << endl;
|
||||
// construct the jacobian structure needed for nullspacing
|
||||
MatrixXd H_xl = MatrixXd::Zero(N*N, 21+state_server.cam_states.size()*7);
|
||||
MatrixXd H_yl = MatrixXd::Zero(N*N, N*N+1);
|
||||
|
||||
// set anchor Jakobi
|
||||
// get position of anchor in cam states
|
||||
ConstructJacobians(H_rho, H_pl, H_pA, feature, cam_state_id, H_xl, H_yl);
|
||||
|
||||
|
||||
// set to return values
|
||||
H_x = H_xl;
|
||||
H_y = H_yl;
|
||||
r = r_photo;
|
||||
|
||||
if(PRINTIMAGES)
|
||||
{
|
||||
// pregenerating information for visualization
|
||||
std::stringstream ss;
|
||||
auto cam_state_anchor = state_server.cam_states.find(feature.observations.begin()->first);
|
||||
int cam_state_cntr_anchor = std::distance(state_server.cam_states.begin(), cam_state_anchor);
|
||||
H_xl.block(0, 21+cam_state_cntr_anchor*7, N*N, 6) = -H_pA;
|
||||
|
||||
// set frame Jakobi
|
||||
//get position of current frame in cam states
|
||||
auto cam_state_iter = state_server.cam_states.find(cam_state_id);
|
||||
int cam_state_cntr = std::distance(state_server.cam_states.begin(), cam_state_iter);
|
||||
|
||||
ss << "INFO:" << " anchor: " << cam_state_cntr_anchor << " frame: " << cam_state_cntr;
|
||||
|
||||
// visualizing functions
|
||||
feature.MarkerGeneration(marker_pub, state_server.cam_states);
|
||||
feature.VisualizePatch(cam_state, cam_state_id, cam0, r_photo, ss);
|
||||
//feature.VisualizeKernel(cam_state, cam_state_id, cam0);
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
bool MsckfVio::ConstructJacobians(Eigen::MatrixXd& H_rho,
|
||||
Eigen::MatrixXd& H_pl,
|
||||
Eigen::MatrixXd& H_pA,
|
||||
const Feature& feature,
|
||||
const StateIDType& cam_state_id,
|
||||
Eigen::MatrixXd& H_xl,
|
||||
Eigen::MatrixXd& H_yl)
|
||||
{
|
||||
// get position of anchor in cam states
|
||||
auto cam_state_anchor = state_server.cam_states.find(feature.observations.begin()->first);
|
||||
int cam_state_cntr_anchor = std::distance(state_server.cam_states.begin(), cam_state_anchor);
|
||||
// set anchor Jakobi
|
||||
H_xl.block(0, 21+cam_state_cntr_anchor*7, N*N, 6) = -H_pA;
|
||||
|
||||
//get position of current frame in cam states
|
||||
auto cam_state_iter = state_server.cam_states.find(cam_state_id);
|
||||
// set frame Jakobi
|
||||
int cam_state_cntr = std::distance(state_server.cam_states.begin(), cam_state_iter);
|
||||
|
||||
// set jakobi of state
|
||||
H_xl.block(0, 21+cam_state_cntr*7, N*N, 6) = -H_pl;
|
||||
|
||||
@ -1643,7 +1757,6 @@ bool MsckfVio::PhotometricMeasurementJacobian(
|
||||
// set irradiance error Block
|
||||
H_yl.block(0, 0,N*N, N*N) = /* estimated_illumination.feature_gain * estimated_illumination.frame_gain * */ Eigen::MatrixXd::Identity(N*N, N*N);
|
||||
|
||||
// TODO make this calculation more fluent
|
||||
|
||||
/*for(int i = 0; i< N*N; i++)
|
||||
H_yl(i, N*N+cam_state_cntr) = estimate_irradiance[i];
|
||||
@ -1651,21 +1764,6 @@ bool MsckfVio::PhotometricMeasurementJacobian(
|
||||
|
||||
H_yl.block(0, N*N, N*N, 1) = -H_rho;
|
||||
|
||||
H_x = H_xl;
|
||||
H_y = H_yl;
|
||||
|
||||
r = r_photo;
|
||||
|
||||
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, r_photo, ss);
|
||||
//feature.VisualizeKernel(cam_state, cam_state_id, cam0);
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
|
||||
@ -1717,11 +1815,9 @@ bool MsckfVio::PhotometricFeatureJacobian(
|
||||
r_i.segment(stack_cntr, N*N) = r_l;
|
||||
stack_cntr += N*N;
|
||||
}
|
||||
if(stack_cntr == 0)
|
||||
{
|
||||
cout << "skip feature" << endl;
|
||||
if(stack_cntr < 2*N*N)
|
||||
return false;
|
||||
}
|
||||
|
||||
// Project the residual and Jacobians onto the nullspace
|
||||
// of H_yj.
|
||||
|
||||
@ -2027,8 +2123,8 @@ void MsckfVio::measurementUpdate(const MatrixXd& H, const VectorXd& r) {
|
||||
VectorXd delta_x = K * r;
|
||||
|
||||
|
||||
cout << "reg rotate: " << delta_x[0] << ", " << delta_x[1] << ", " << delta_x[2] << endl;
|
||||
cout << "reg update: " << delta_x[12] << ", " << delta_x[13] << ", " << delta_x[14] << endl;
|
||||
// cout << "reg rotate: " << delta_x[0] << ", " << delta_x[1] << ", " << delta_x[2] << endl;
|
||||
cout << "reg: " << delta_x[12] << ", " << delta_x[13] << ", " << delta_x[14] << endl;
|
||||
|
||||
if(FILTER != 0) return;
|
||||
|
||||
@ -2053,9 +2149,6 @@ void MsckfVio::measurementUpdate(const MatrixXd& H, const VectorXd& r) {
|
||||
|
||||
myfile.close();
|
||||
}
|
||||
delta_position = Eigen::Vector3d(delta_x[12], delta_x[13], delta_x[14]);
|
||||
delta_orientation = Eigen::Vector3d(delta_x[0], delta_x[1], delta_x[2]);
|
||||
|
||||
// Update the IMU state.
|
||||
|
||||
const VectorXd& delta_x_imu = delta_x.head<21>();
|
||||
@ -2239,10 +2332,13 @@ void MsckfVio::photometricMeasurementUpdate(const MatrixXd& H, const VectorXd& r
|
||||
// Perform QR decompostion on H_sparse.
|
||||
SPQR<SparseMatrix<double> > spqr_helper;
|
||||
spqr_helper.setSPQROrdering(SPQR_ORDERING_NATURAL);
|
||||
spqr_helper.compute(H_sparse);
|
||||
|
||||
cout << "comp" << endl;
|
||||
spqr_helper.compute(H_sparse);
|
||||
cout << "done" << endl;
|
||||
MatrixXd H_temp;
|
||||
VectorXd r_temp;
|
||||
|
||||
(spqr_helper.matrixQ().transpose() * H).evalTo(H_temp);
|
||||
(spqr_helper.matrixQ().transpose() * r).evalTo(r_temp);
|
||||
|
||||
@ -2261,6 +2357,7 @@ void MsckfVio::photometricMeasurementUpdate(const MatrixXd& H, const VectorXd& r
|
||||
Feature::observation_noise*MatrixXd::Identity(
|
||||
H_thin.rows(), H_thin.rows());
|
||||
//MatrixXd K_transpose = S.fullPivHouseholderQr().solve(H*P);
|
||||
|
||||
MatrixXd K_transpose = S.ldlt().solve(H_thin*P);
|
||||
MatrixXd K = K_transpose.transpose();
|
||||
// Compute the error of the state.
|
||||
@ -2291,8 +2388,7 @@ void MsckfVio::photometricMeasurementUpdate(const MatrixXd& H, const VectorXd& r
|
||||
myfile.close();
|
||||
}
|
||||
|
||||
delta_position = Eigen::Vector3d(delta_x[12], delta_x[13], delta_x[14]);
|
||||
delta_orientation = Eigen::Vector3d(delta_x[0], delta_x[1], delta_x[2]);
|
||||
cout << "pho: " << delta_x[12] << ", " << delta_x[13] << ", " << delta_x[14] << endl;
|
||||
|
||||
const VectorXd& delta_x_imu = delta_x.head<21>();
|
||||
|
||||
@ -2349,8 +2445,8 @@ void MsckfVio::photometricMeasurementUpdate(const MatrixXd& H, const VectorXd& r
|
||||
|
||||
|
||||
bool MsckfVio::gatingTest(const MatrixXd& H, const VectorXd& r, const int& dof) {
|
||||
MatrixXd P1 = H * state_server.state_cov * H.transpose();
|
||||
|
||||
MatrixXd P1 = H * state_server.state_cov * H.transpose();
|
||||
|
||||
MatrixXd P2 = Feature::observation_noise *
|
||||
MatrixXd::Identity(H.rows(), H.rows());
|
||||
@ -2466,15 +2562,14 @@ void MsckfVio::removeLostFeatures() {
|
||||
MatrixXd twoH_xj;
|
||||
VectorXd twor_j;
|
||||
|
||||
/*
|
||||
if(PhotometricFeatureJacobian(feature.id, cam_state_ids, pH_xj, pr_j) == true);
|
||||
if(PhotometricFeatureJacobian(feature.id, cam_state_ids, pH_xj, pr_j) == true)
|
||||
{
|
||||
if (gatingTest(pH_xj, pr_j, pr_j.size())) { //, cam_state_ids.size()-1)) {
|
||||
pH_x.block(pstack_cntr, 0, pH_xj.rows(), pH_xj.cols()) = pH_xj;
|
||||
pr.segment(pstack_cntr, pr_j.rows()) = pr_j;
|
||||
pstack_cntr += pH_xj.rows();
|
||||
}
|
||||
}*/
|
||||
}
|
||||
|
||||
featureJacobian(feature.id, cam_state_ids, H_xj, r_j);
|
||||
twodotFeatureJacobian(feature.id, cam_state_ids, twoH_xj, twor_j);
|
||||
@ -2503,6 +2598,7 @@ void MsckfVio::removeLostFeatures() {
|
||||
photometricMeasurementUpdate(pH_x, pr);
|
||||
}
|
||||
|
||||
|
||||
H_x.conservativeResize(stack_cntr, H_x.cols());
|
||||
r.conservativeResize(stack_cntr);
|
||||
|
||||
@ -2648,17 +2744,15 @@ void MsckfVio::pruneLastCamStateBuffer()
|
||||
for (const auto& cam_state : state_server.cam_states)
|
||||
involved_cam_state_ids.push_back(cam_state.first);
|
||||
|
||||
/*
|
||||
if(PhotometricFeatureJacobian(feature.id, involved_cam_state_ids, pH_xj, pr_j) == true);
|
||||
{
|
||||
|
||||
if(PhotometricFeatureJacobian(feature.id, involved_cam_state_ids, pH_xj, pr_j) == true)
|
||||
{
|
||||
if (gatingTest(pH_xj, pr_j, pr_j.size())) { //, cam_state_ids.size()-1)) {
|
||||
pH_x.block(pstack_cntr, 0, pH_xj.rows(), pH_xj.cols()) = pH_xj;
|
||||
pr.segment(pstack_cntr, pr_j.rows()) = pr_j;
|
||||
pstack_cntr += pH_xj.rows();
|
||||
}
|
||||
}*/
|
||||
|
||||
}
|
||||
|
||||
featureJacobian(feature.id, involved_cam_state_ids, H_xj, r_j);
|
||||
twodotFeatureJacobian(feature.id, involved_cam_state_ids, twoH_xj, twor_j);
|
||||
@ -2679,6 +2773,7 @@ void MsckfVio::pruneLastCamStateBuffer()
|
||||
feature.observations.erase(cam_id);
|
||||
}
|
||||
|
||||
|
||||
if(pstack_cntr)
|
||||
{
|
||||
pH_x.conservativeResize(pstack_cntr, pH_x.cols());
|
||||
@ -2690,15 +2785,14 @@ void MsckfVio::pruneLastCamStateBuffer()
|
||||
|
||||
H_x.conservativeResize(stack_cntr, H_x.cols());
|
||||
r.conservativeResize(stack_cntr);
|
||||
// Perform measurement update.
|
||||
|
||||
twoH_x.conservativeResize(twostack_cntr, twoH_x.cols());
|
||||
twor.conservativeResize(twostack_cntr);
|
||||
// Perform measurement update.
|
||||
|
||||
|
||||
// Perform the measurement update step.
|
||||
measurementUpdate(H_x, r);
|
||||
twoMeasurementUpdate(twoH_x, twor);
|
||||
|
||||
//reduction
|
||||
int cam_sequence = std::distance(state_server.cam_states.begin(),
|
||||
state_server.cam_states.find(rm_cam_state_id));
|
||||
@ -2831,7 +2925,7 @@ void MsckfVio::pruneCamStateBuffer() {
|
||||
|
||||
if (involved_cam_state_ids.size() == 0) continue;
|
||||
|
||||
/*
|
||||
|
||||
if(PhotometricFeatureJacobian(feature.id, involved_cam_state_ids, pH_xj, pr_j) == true)
|
||||
{
|
||||
if (gatingTest(pH_xj, pr_j, pr_j.size())) {// involved_cam_state_ids.size())) {
|
||||
@ -2839,7 +2933,8 @@ void MsckfVio::pruneCamStateBuffer() {
|
||||
pr.segment(pstack_cntr, pr_j.rows()) = pr_j;
|
||||
pstack_cntr += pH_xj.rows();
|
||||
}
|
||||
}*/
|
||||
}
|
||||
|
||||
featureJacobian(feature.id, involved_cam_state_ids, H_xj, r_j);
|
||||
twodotFeatureJacobian(feature.id, involved_cam_state_ids, twoH_xj, twor_j);
|
||||
|
||||
@ -2860,11 +2955,11 @@ void MsckfVio::pruneCamStateBuffer() {
|
||||
}
|
||||
|
||||
|
||||
if(pstack_cntr > 0)
|
||||
|
||||
if(pstack_cntr)
|
||||
{
|
||||
pH_x.conservativeResize(pstack_cntr, pH_x.cols());
|
||||
pr.conservativeResize(pstack_cntr);
|
||||
|
||||
photometricMeasurementUpdate(pH_x, pr);
|
||||
}
|
||||
|
||||
@ -2874,9 +2969,10 @@ void MsckfVio::pruneCamStateBuffer() {
|
||||
twoH_x.conservativeResize(twostack_cntr, twoH_x.cols());
|
||||
twor.conservativeResize(twostack_cntr);
|
||||
|
||||
// Perform measurement update.
|
||||
// Perform the measurement update step.
|
||||
measurementUpdate(H_x, r);
|
||||
twoMeasurementUpdate(twoH_x, twor);
|
||||
|
||||
//reduction
|
||||
for (const auto& cam_id : rm_cam_state_ids) {
|
||||
int cam_sequence = std::distance(state_server.cam_states.begin(),
|
||||
|
||||
Loading…
Reference in New Issue
Block a user