1 Commits

Author SHA1 Message Date
c6b8a2c2fc added branch 2019-04-03 06:51:18 +00:00
41 changed files with 466 additions and 4880 deletions

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@ -1,16 +0,0 @@
{
"configurations": [
{
"name": "Linux",
"includePath": [
"${workspaceFolder}/**"
],
"defines": [],
"compilerPath": "/usr/bin/gcc",
"cStandard": "c11",
"cppStandard": "c++14",
"intelliSenseMode": "clang-x64"
}
],
"version": 4
}

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@ -1,6 +0,0 @@
{
"files.associations": {
"core": "cpp",
"sparsecore": "cpp"
}
}

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@ -24,7 +24,6 @@ find_package(catkin REQUIRED COMPONENTS
pcl_conversions pcl_conversions
pcl_ros pcl_ros
std_srvs std_srvs
visualization_msgs
) )
## System dependencies are found with CMake's conventions ## System dependencies are found with CMake's conventions
@ -80,7 +79,6 @@ include_directories(
add_library(msckf_vio add_library(msckf_vio
src/msckf_vio.cpp src/msckf_vio.cpp
src/utils.cpp src/utils.cpp
src/image_handler.cpp
) )
add_dependencies(msckf_vio add_dependencies(msckf_vio
${${PROJECT_NAME}_EXPORTED_TARGETS} ${${PROJECT_NAME}_EXPORTED_TARGETS}
@ -89,7 +87,6 @@ add_dependencies(msckf_vio
target_link_libraries(msckf_vio target_link_libraries(msckf_vio
${catkin_LIBRARIES} ${catkin_LIBRARIES}
${SUITESPARSE_LIBRARIES} ${SUITESPARSE_LIBRARIES}
${OpenCV_LIBRARIES}
) )
# Msckf Vio nodelet # Msckf Vio nodelet
@ -109,7 +106,6 @@ target_link_libraries(msckf_vio_nodelet
add_library(image_processor add_library(image_processor
src/image_processor.cpp src/image_processor.cpp
src/utils.cpp src/utils.cpp
src/image_handler.cpp
) )
add_dependencies(image_processor add_dependencies(image_processor
${${PROJECT_NAME}_EXPORTED_TARGETS} ${${PROJECT_NAME}_EXPORTED_TARGETS}

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@ -9,7 +9,7 @@ cam0:
0, 0, 0, 1.000000000000000] 0, 0, 0, 1.000000000000000]
camera_model: pinhole camera_model: pinhole
distortion_coeffs: [-0.28340811, 0.07395907, 0.00019359, 1.76187114e-05] distortion_coeffs: [-0.28340811, 0.07395907, 0.00019359, 1.76187114e-05]
distortion_model: pre-radtan distortion_model: radtan
intrinsics: [458.654, 457.296, 367.215, 248.375] intrinsics: [458.654, 457.296, 367.215, 248.375]
resolution: [752, 480] resolution: [752, 480]
timeshift_cam_imu: 0.0 timeshift_cam_imu: 0.0
@ -26,7 +26,7 @@ cam1:
0, 0, 0, 1.000000000000000] 0, 0, 0, 1.000000000000000]
camera_model: pinhole camera_model: pinhole
distortion_coeffs: [-0.28368365, 0.07451284, -0.00010473, -3.55590700e-05] distortion_coeffs: [-0.28368365, 0.07451284, -0.00010473, -3.55590700e-05]
distortion_model: pre-radtan distortion_model: radtan
intrinsics: [457.587, 456.134, 379.999, 255.238] intrinsics: [457.587, 456.134, 379.999, 255.238]
resolution: [752, 480] resolution: [752, 480]
timeshift_cam_imu: 0.0 timeshift_cam_imu: 0.0

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@ -1,36 +0,0 @@
cam0:
T_cam_imu:
[-0.9995378259923383, 0.02917807204183088, -0.008530798463872679, 0.047094247958417004,
0.007526588843243184, -0.03435493139706542, -0.9993813532126198, -0.04788273017221637,
-0.029453096117288798, -0.9989836729399656, 0.034119442089241274, -0.0697294754693238,
0.0, 0.0, 0.0, 1.0]
camera_model: pinhole
distortion_coeffs: [0.0034823894022493434, 0.0007150348452162257, -0.0020532361418706202,
0.00020293673591811182]
distortion_model: pre-equidistant
intrinsics: [190.97847715128717, 190.9733070521226, 254.93170605935475, 256.8974428996504]
resolution: [512, 512]
rostopic: /cam0/image_raw
cam1:
T_cam_imu:
[-0.9995240747493029, 0.02986739485347808, -0.007717688852024281, -0.05374086123613335,
0.008095979457928231, 0.01256553460985914, -0.9998882749870535, -0.04648588412432889,
-0.02976708103202316, -0.9994748851595197, -0.0128013601698453, -0.07333210787623645,
0.0, 0.0, 0.0, 1.0]
T_cn_cnm1:
[0.9999994317488622, -0.0008361847221513937, -0.0006612844045898121, -0.10092123225528335,
0.0008042457277382264, 0.9988989443471681, -0.04690684567228134, -0.001964540595211977,
0.0006997790813734836, 0.04690628718225568, 0.9988990492196964, -0.0014663556043866572,
0.0, 0.0, 0.0, 1.0]
camera_model: pinhole
distortion_coeffs: [0.0034003170790442797, 0.001766278153469831, -0.00266312569781606,
0.0003299517423931039]
distortion_model: pre-equidistant
intrinsics: [190.44236969414825, 190.4344384721956, 252.59949716835982, 254.91723064636983]
resolution: [512, 512]
rostopic: /cam1/image_raw
T_imu_body:
[1.0000, 0.0000, 0.0000, 0.0000,
0.0000, 1.0000, 0.0000, 0.0000,
0.0000, 0.0000, 1.0000, 0.0000,
0.0000, 0.0000, 0.0000, 1.0000]

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@ -1,36 +0,0 @@
cam0:
T_cam_imu:
[-0.9995378259923383, 0.02917807204183088, -0.008530798463872679, 0.047094247958417004,
0.007526588843243184, -0.03435493139706542, -0.9993813532126198, -0.04788273017221637,
-0.029453096117288798, -0.9989836729399656, 0.034119442089241274, -0.0697294754693238,
0.0, 0.0, 0.0, 1.0]
camera_model: pinhole
distortion_coeffs: [0.010171079892421483, -0.010816440029919381, 0.005942781769412756,
-0.001662284667857643]
distortion_model: equidistant
intrinsics: [380.81042871360756, 380.81194179427075, 510.29465304840727, 514.3304630538506]
resolution: [1024, 1024]
rostopic: /cam0/image_raw
cam1:
T_cam_imu:
[-0.9995240747493029, 0.02986739485347808, -0.007717688852024281, -0.05374086123613335,
0.008095979457928231, 0.01256553460985914, -0.9998882749870535, -0.04648588412432889,
-0.02976708103202316, -0.9994748851595197, -0.0128013601698453, -0.07333210787623645,
0.0, 0.0, 0.0, 1.0]
T_cn_cnm1:
[0.9999994317488622, -0.0008361847221513937, -0.0006612844045898121, -0.10092123225528335,
0.0008042457277382264, 0.9988989443471681, -0.04690684567228134, -0.001964540595211977,
0.0006997790813734836, 0.04690628718225568, 0.9988990492196964, -0.0014663556043866572,
0.0, 0.0, 0.0, 1.0]
camera_model: pinhole
distortion_coeffs: [0.01371679169245271, -0.015567360615942622, 0.00905043103315326,
-0.002347858896562788]
distortion_model: equidistant
intrinsics: [379.2869884263036, 379.26583742214524, 505.5666703237407, 510.2840961765407]
resolution: [1024, 1024]
rostopic: /cam1/image_raw
T_imu_body:
[1.0000, 0.0000, 0.0000, 0.0000,
0.0000, 1.0000, 0.0000, 0.0000,
0.0000, 0.0000, 1.0000, 0.0000,
0.0000, 0.0000, 0.0000, 1.0000]

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@ -15,37 +15,6 @@
#include "imu_state.h" #include "imu_state.h"
namespace msckf_vio { namespace msckf_vio {
struct Frame{
cv::Mat image;
cv::Mat dximage;
cv::Mat dyimage;
double exposureTime_ms;
};
typedef std::map<StateIDType, Frame, std::less<StateIDType>,
Eigen::aligned_allocator<
std::pair<StateIDType, Frame> > > movingWindow;
struct IlluminationParameter{
double frame_bias;
double frame_gain;
double feature_bias;
double feature_gain;
};
struct CameraCalibration{
std::string distortion_model;
cv::Vec2i resolution;
cv::Vec4d intrinsics;
cv::Vec4d distortion_coeffs;
movingWindow moving_window;
cv::Mat featureVisu;
int id;
};
/* /*
* @brief CAMState Stored camera state in order to * @brief CAMState Stored camera state in order to
* form measurement model. * form measurement model.
@ -66,9 +35,6 @@ struct CAMState {
// Position of the camera frame in the world frame. // Position of the camera frame in the world frame.
Eigen::Vector3d position; Eigen::Vector3d position;
// Illumination Information of the frame
IlluminationParameter illumination;
// These two variables should have the same physical // These two variables should have the same physical
// interpretation with `orientation` and `position`. // interpretation with `orientation` and `position`.
// There two variables are used to modify the measurement // There two variables are used to modify the measurement

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@ -1,61 +0,0 @@
#ifndef MSCKF_VIO_IMAGE_HANDLER_H
#define MSCKF_VIO_IMAGE_HANDLER_H
#include <vector>
#include <boost/shared_ptr.hpp>
#include <opencv2/opencv.hpp>
#include <opencv2/video.hpp>
#include <ros/ros.h>
#include <cv_bridge/cv_bridge.h>
namespace msckf_vio {
/*
* @brief utilities for msckf_vio
*/
namespace image_handler {
cv::Point2f pinholeDownProject(const cv::Point2f& p_in, const cv::Vec4d& intrinsics);
cv::Point2f pinholeUpProject(const cv::Point2f& p_in, const cv::Vec4d& intrinsics);
void undistortImage(
cv::InputArray src,
cv::OutputArray dst,
const std::string& distortion_model,
const cv::Vec4d& intrinsics,
const cv::Vec4d& distortion_coeffs);
void undistortPoints(
const std::vector<cv::Point2f>& pts_in,
const cv::Vec4d& intrinsics,
const std::string& distortion_model,
const cv::Vec4d& distortion_coeffs,
std::vector<cv::Point2f>& pts_out,
const cv::Matx33d &rectification_matrix = cv::Matx33d::eye(),
const cv::Vec4d &new_intrinsics = cv::Vec4d(1,1,0,0));
std::vector<cv::Point2f> distortPoints(
const std::vector<cv::Point2f>& pts_in,
const cv::Vec4d& intrinsics,
const std::string& distortion_model,
const cv::Vec4d& distortion_coeffs);
cv::Point2f distortPoint(
const cv::Point2f& pt_in,
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

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@ -14,6 +14,10 @@
#include <opencv2/opencv.hpp> #include <opencv2/opencv.hpp>
#include <opencv2/video.hpp> #include <opencv2/video.hpp>
#include <opencv2/cudaoptflow.hpp>
#include <opencv2/cudaimgproc.hpp>
#include <opencv2/cudaarithm.hpp>
#include <ros/ros.h> #include <ros/ros.h>
#include <cv_bridge/cv_bridge.h> #include <cv_bridge/cv_bridge.h>
#include <image_transport/image_transport.h> #include <image_transport/image_transport.h>
@ -22,8 +26,6 @@
#include <message_filters/subscriber.h> #include <message_filters/subscriber.h>
#include <message_filters/time_synchronizer.h> #include <message_filters/time_synchronizer.h>
#include "cam_state.h"
namespace msckf_vio { namespace msckf_vio {
/* /*
@ -310,7 +312,7 @@ private:
const std::vector<unsigned char>& markers, const std::vector<unsigned char>& markers,
std::vector<T>& refined_vec) { std::vector<T>& refined_vec) {
if (raw_vec.size() != markers.size()) { if (raw_vec.size() != markers.size()) {
ROS_WARN("The input size of raw_vec(%lu) and markers(%lu) does not match...", ROS_WARN("The input size of raw_vec(%i) and markers(%i) does not match...",
raw_vec.size(), markers.size()); raw_vec.size(), markers.size());
} }
for (int i = 0; i < markers.size(); ++i) { for (int i = 0; i < markers.size(); ++i) {
@ -320,8 +322,6 @@ private:
return; return;
} }
bool STREAMPAUSE;
// Indicate if this is the first image message. // Indicate if this is the first image message.
bool is_first_img; bool is_first_img;
@ -336,8 +336,15 @@ private:
std::vector<sensor_msgs::Imu> imu_msg_buffer; std::vector<sensor_msgs::Imu> imu_msg_buffer;
// Camera calibration parameters // Camera calibration parameters
CameraCalibration cam0; std::string cam0_distortion_model;
CameraCalibration cam1; cv::Vec2i cam0_resolution;
cv::Vec4d cam0_intrinsics;
cv::Vec4d cam0_distortion_coeffs;
std::string cam1_distortion_model;
cv::Vec2i cam1_resolution;
cv::Vec4d cam1_intrinsics;
cv::Vec4d cam1_distortion_coeffs;
// Take a vector from cam0 frame to the IMU frame. // Take a vector from cam0 frame to the IMU frame.
cv::Matx33d R_cam0_imu; cv::Matx33d R_cam0_imu;
@ -360,6 +367,13 @@ private:
boost::shared_ptr<GridFeatures> prev_features_ptr; boost::shared_ptr<GridFeatures> prev_features_ptr;
boost::shared_ptr<GridFeatures> curr_features_ptr; boost::shared_ptr<GridFeatures> curr_features_ptr;
cv::Ptr<cv::cuda::SparsePyrLKOpticalFlow> d_pyrLK_sparse;
cv::cuda::GpuMat cam0_curr_img;
cv::cuda::GpuMat cam1_curr_img;
cv::cuda::GpuMat cam0_points_gpu;
cv::cuda::GpuMat cam1_points_gpu;
// Number of features after each outlier removal step. // Number of features after each outlier removal step.
int before_tracking; int before_tracking;
int after_tracking; int after_tracking;

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@ -43,50 +43,6 @@ inline void quaternionNormalize(Eigen::Vector4d& q) {
return; return;
} }
/*
* @brief invert rotation of passed quaternion through conjugation
* and return conjugation
*/
inline Eigen::Vector4d quaternionConjugate(Eigen::Vector4d& q)
{
Eigen::Vector4d p;
p(0) = -q(0);
p(1) = -q(1);
p(2) = -q(2);
p(3) = q(3);
quaternionNormalize(p);
return p;
}
/*
* @brief converts a vector4 to a vector3, dropping (3)
* this is typically used to get the vector part of a quaternion
for eq small angle approximation
*/
inline Eigen::Vector3d v4tov3(const Eigen::Vector4d& q)
{
Eigen::Vector3d p;
p(0) = q(0);
p(1) = q(1);
p(2) = q(2);
return p;
}
/*
* @brief Perform q1 * q2
*/
inline Eigen::Vector4d QtoV(const Eigen::Quaterniond& q)
{
Eigen::Vector4d p;
p(0) = q.x();
p(1) = q.y();
p(2) = q.z();
p(3) = q.w();
return p;
}
/* /*
* @brief Perform q1 * q2 * @brief Perform q1 * q2
*/ */

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@ -14,17 +14,11 @@
#include <string> #include <string>
#include <Eigen/Dense> #include <Eigen/Dense>
#include <Eigen/Geometry> #include <Eigen/Geometry>
#include <math.h>
#include <boost/shared_ptr.hpp> #include <boost/shared_ptr.hpp>
#include <opencv2/opencv.hpp>
#include <opencv2/video.hpp>
#include <ros/ros.h> #include <ros/ros.h>
#include <sensor_msgs/Imu.h> #include <sensor_msgs/Imu.h>
#include <sensor_msgs/Image.h>
#include <sensor_msgs/PointCloud.h>
#include <nav_msgs/Odometry.h> #include <nav_msgs/Odometry.h>
#include <std_msgs/Float64.h>
#include <tf/transform_broadcaster.h> #include <tf/transform_broadcaster.h>
#include <std_srvs/Trigger.h> #include <std_srvs/Trigger.h>
@ -33,13 +27,6 @@
#include "feature.hpp" #include "feature.hpp"
#include <msckf_vio/CameraMeasurement.h> #include <msckf_vio/CameraMeasurement.h>
#include <cv_bridge/cv_bridge.h>
#include <image_transport/image_transport.h>
#include <message_filters/subscriber.h>
#include <message_filters/time_synchronizer.h>
#define PI 3.14159265
namespace msckf_vio { namespace msckf_vio {
/* /*
* @brief MsckfVio Implements the algorithm in * @brief MsckfVio Implements the algorithm in
@ -110,27 +97,11 @@ class MsckfVio {
void imuCallback(const sensor_msgs::ImuConstPtr& msg); void imuCallback(const sensor_msgs::ImuConstPtr& msg);
/* /*
* @brief truthCallback * @brief featureCallback
* Callback function for ground truth navigation information * Callback function for feature measurements.
* @param TransformStamped msg * @param msg Stereo feature measurements.
*/
void truthCallback(
const geometry_msgs::TransformStampedPtr& msg);
/*
* @brief imageCallback
* Callback function for feature measurements
* Triggers measurement update
* @param msg
* Camera 0 Image
* Camera 1 Image
* Stereo feature measurements.
*/ */
void imageCallback ( void featureCallback(const CameraMeasurementConstPtr& msg);
const sensor_msgs::ImageConstPtr& cam0_img,
const sensor_msgs::ImageConstPtr& cam1_img,
const CameraMeasurementConstPtr& feature_msg);
/* /*
* @brief publish Publish the results of VIO. * @brief publish Publish the results of VIO.
@ -155,26 +126,6 @@ class MsckfVio {
bool resetCallback(std_srvs::Trigger::Request& req, bool resetCallback(std_srvs::Trigger::Request& req,
std_srvs::Trigger::Response& res); std_srvs::Trigger::Response& res);
// Saves the exposure time and the camera measurementes
void manageMovingWindow(
const sensor_msgs::ImageConstPtr& cam0_img,
const sensor_msgs::ImageConstPtr& cam1_img,
const CameraMeasurementConstPtr& feature_msg);
void calcErrorState();
// Debug related Functions
// Propagate the true state
void batchTruthProcessing(
const double& time_bound);
void processTruthtoIMU(const double& time,
const Eigen::Vector4d& m_rot,
const Eigen::Vector3d& m_trans);
// Filter related functions // Filter related functions
// Propogate the state // Propogate the state
void batchImuProcessing( void batchImuProcessing(
@ -186,12 +137,8 @@ class MsckfVio {
const Eigen::Vector3d& gyro, const Eigen::Vector3d& gyro,
const Eigen::Vector3d& acc); const Eigen::Vector3d& acc);
// groundtruth state augmentation
void truePhotometricStateAugmentation(const double& time);
// Measurement update // Measurement update
void stateAugmentation(const double& time); void stateAugmentation(const double& time);
void PhotometricStateAugmentation(const double& time);
void addFeatureObservations(const CameraMeasurementConstPtr& msg); void addFeatureObservations(const CameraMeasurementConstPtr& msg);
// This function is used to compute the measurement Jacobian // This function is used to compute the measurement Jacobian
// for a single feature observed at a single camera frame. // for a single feature observed at a single camera frame.
@ -202,118 +149,25 @@ class MsckfVio {
Eigen::Vector4d& r); Eigen::Vector4d& r);
// This function computes the Jacobian of all measurements viewed // This function computes the Jacobian of all measurements viewed
// in the given camera states of this feature. // in the given camera states of this feature.
bool featureJacobian( void featureJacobian(const FeatureIDType& feature_id,
const FeatureIDType& feature_id,
const std::vector<StateIDType>& cam_state_ids, const std::vector<StateIDType>& cam_state_ids,
Eigen::MatrixXd& H_x, Eigen::VectorXd& r); Eigen::MatrixXd& H_x, Eigen::VectorXd& r);
void twodotMeasurementJacobian(
const StateIDType& cam_state_id,
const FeatureIDType& feature_id,
Eigen::MatrixXd& H_x, Eigen::MatrixXd& H_y, Eigen::VectorXd& r);
bool 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);
bool PhotometricPatchPointResidual(
const StateIDType& cam_state_id,
const Feature& feature,
Eigen::VectorXd& r);
bool PhotometricPatchPointJacobian(
const CAMState& cam_state,
const StateIDType& cam_state_id,
const Feature& feature,
Eigen::Vector3d point,
int count,
Eigen::Matrix<double, 2, 1>& H_rhoj,
Eigen::Matrix<double, 2, 6>& H_plj,
Eigen::Matrix<double, 2, 6>& H_pAj,
Eigen::Matrix<double, 2, 4>& dI_dhj);
bool PhotometricMeasurementJacobian(
const StateIDType& cam_state_id,
const FeatureIDType& feature_id,
Eigen::MatrixXd& H_x,
Eigen::MatrixXd& H_y,
Eigen::VectorXd& r);
bool twodotFeatureJacobian(
const FeatureIDType& feature_id,
const std::vector<StateIDType>& cam_state_ids,
Eigen::MatrixXd& H_x, Eigen::VectorXd& r);
bool PhotometricFeatureJacobian(
const FeatureIDType& feature_id,
const std::vector<StateIDType>& cam_state_ids,
Eigen::MatrixXd& H_x, Eigen::VectorXd& r);
void photometricMeasurementUpdate(const Eigen::MatrixXd& H, const Eigen::VectorXd& r);
void measurementUpdate(const Eigen::MatrixXd& H, void measurementUpdate(const Eigen::MatrixXd& H,
const Eigen::VectorXd& r); const Eigen::VectorXd& r);
void twoMeasurementUpdate(const Eigen::MatrixXd& H, const Eigen::VectorXd& r);
bool gatingTest(const Eigen::MatrixXd& H, bool gatingTest(const Eigen::MatrixXd& H,
const Eigen::VectorXd&r, const int& dof, int filter=0); const Eigen::VectorXd&r, const int& dof);
void removeLostFeatures(); void removeLostFeatures();
void findRedundantCamStates( void findRedundantCamStates(
std::vector<StateIDType>& rm_cam_state_ids); std::vector<StateIDType>& rm_cam_state_ids);
void pruneLastCamStateBuffer();
void pruneCamStateBuffer(); void pruneCamStateBuffer();
// Reset the system online if the uncertainty is too large. // Reset the system online if the uncertainty is too large.
void onlineReset(); void onlineReset();
// Photometry flag
int FILTER;
// debug flag
bool STREAMPAUSE;
bool PRINTIMAGES;
bool GROUNDTRUTH;
bool nan_flag;
bool play;
double last_time_bound;
double time_offset;
// Patch size for Photometry
int N;
// Image rescale
int SCALE;
// Chi squared test table. // Chi squared test table.
static std::map<int, double> chi_squared_test_table; static std::map<int, double> chi_squared_test_table;
double eval_time;
IMUState timed_old_imu_state;
IMUState timed_old_true_state;
IMUState old_imu_state;
IMUState old_true_state;
// change in position
Eigen::Vector3d delta_position;
Eigen::Vector3d delta_orientation;
// State vector // State vector
StateServer state_server; StateServer state_server;
StateServer photometric_state_server;
// Ground truth state vector
StateServer true_state_server;
// error state based on ground truth
StateServer err_state_server;
// Maximum number of camera states // Maximum number of camera states
int max_cam_state_size; int max_cam_state_size;
@ -325,22 +179,6 @@ class MsckfVio {
// transfer delay between IMU and Image messages. // transfer delay between IMU and Image messages.
std::vector<sensor_msgs::Imu> imu_msg_buffer; std::vector<sensor_msgs::Imu> imu_msg_buffer;
// Ground Truth message data
std::vector<geometry_msgs::TransformStamped> truth_msg_buffer;
// Moving Window buffer
movingWindow cam0_moving_window;
movingWindow cam1_moving_window;
// Camera calibration parameters
CameraCalibration cam0;
CameraCalibration cam1;
// covariance data
double irradiance_frame_bias;
ros::Time image_save_time;
// Indicate if the gravity vector is set. // Indicate if the gravity vector is set.
bool is_gravity_set; bool is_gravity_set;
@ -368,21 +206,12 @@ class MsckfVio {
// Subscribers and publishers // Subscribers and publishers
ros::Subscriber imu_sub; ros::Subscriber imu_sub;
ros::Subscriber truth_sub; ros::Subscriber feature_sub;
ros::Publisher truth_odom_pub;
ros::Publisher odom_pub; ros::Publisher odom_pub;
ros::Publisher marker_pub;
ros::Publisher feature_pub; ros::Publisher feature_pub;
tf::TransformBroadcaster tf_pub; tf::TransformBroadcaster tf_pub;
ros::ServiceServer reset_srv; ros::ServiceServer reset_srv;
message_filters::Subscriber<sensor_msgs::Image> cam0_img_sub;
message_filters::Subscriber<sensor_msgs::Image> cam1_img_sub;
message_filters::Subscriber<CameraMeasurement> feature_sub;
message_filters::TimeSynchronizer<sensor_msgs::Image, sensor_msgs::Image, CameraMeasurement> image_sub;
// Frame id // Frame id
std::string fixed_frame_id; std::string fixed_frame_id;
std::string child_frame_id; std::string child_frame_id;
@ -403,9 +232,6 @@ class MsckfVio {
ros::Publisher mocap_odom_pub; ros::Publisher mocap_odom_pub;
geometry_msgs::TransformStamped raw_mocap_odom_msg; geometry_msgs::TransformStamped raw_mocap_odom_msg;
Eigen::Isometry3d mocap_initial_frame; Eigen::Isometry3d mocap_initial_frame;
Eigen::Vector4d mocap_initial_orientation;
Eigen::Vector3d mocap_initial_position;
}; };
typedef MsckfVio::Ptr MsckfVioPtr; typedef MsckfVio::Ptr MsckfVioPtr;

View File

@ -11,6 +11,9 @@
#include <ros/ros.h> #include <ros/ros.h>
#include <string> #include <string>
#include <opencv2/core/core.hpp> #include <opencv2/core/core.hpp>
#include <opencv2/cudaoptflow.hpp>
#include <opencv2/cudaimgproc.hpp>
#include <opencv2/cudaarithm.hpp>
#include <Eigen/Geometry> #include <Eigen/Geometry>
namespace msckf_vio { namespace msckf_vio {
@ -18,6 +21,10 @@ namespace msckf_vio {
* @brief utilities for msckf_vio * @brief utilities for msckf_vio
*/ */
namespace utils { namespace utils {
void download(const cv::cuda::GpuMat& d_mat, std::vector<uchar>& vec);
void download(const cv::cuda::GpuMat& d_mat, std::vector<cv::Point2f>& vec);
Eigen::Isometry3d getTransformEigen(const ros::NodeHandle &nh, Eigen::Isometry3d getTransformEigen(const ros::NodeHandle &nh,
const std::string &field); const std::string &field);

View File

@ -8,8 +8,7 @@
<group ns="$(arg robot)"> <group ns="$(arg robot)">
<node pkg="nodelet" type="nodelet" name="image_processor" <node pkg="nodelet" type="nodelet" name="image_processor"
args="standalone msckf_vio/ImageProcessorNodelet" args="standalone msckf_vio/ImageProcessorNodelet"
output="screen" output="screen">
>
<rosparam command="load" file="$(arg calibration_file)"/> <rosparam command="load" file="$(arg calibration_file)"/>
<param name="grid_row" value="4"/> <param name="grid_row" value="4"/>

View File

@ -1,33 +0,0 @@
<launch>
<arg name="robot" default="firefly_sbx"/>
<arg name="calibration_file"
default="$(find msckf_vio)/config/camchain-imucam-mynt.yaml"/>
<!-- Image Processor Nodelet -->
<group ns="$(arg robot)">
<node pkg="nodelet" type="nodelet" name="image_processor"
args="standalone msckf_vio/ImageProcessorNodelet"
output="screen">
<rosparam command="load" file="$(arg calibration_file)"/>
<param name="grid_row" value="4"/>
<param name="grid_col" value="5"/>
<param name="grid_min_feature_num" value="3"/>
<param name="grid_max_feature_num" value="4"/>
<param name="pyramid_levels" value="3"/>
<param name="patch_size" value="15"/>
<param name="fast_threshold" value="10"/>
<param name="max_iteration" value="30"/>
<param name="track_precision" value="0.01"/>
<param name="ransac_threshold" value="3"/>
<param name="stereo_threshold" value="5"/>
<remap from="~imu" to="/imu0"/>
<remap from="~cam0_image" to="/mynteye/left/image_raw"/>
<remap from="~cam1_image" to="/mynteye/right/image_raw"/>
</node>
</group>
</launch>

View File

@ -1,38 +0,0 @@
<launch>
<arg name="robot" default="firefly_sbx"/>
<arg name="calibration_file"
default="$(find msckf_vio)/config/camchain-imucam-tum-scaled.yaml"/>
<!-- Image Processor Nodelet -->
<group ns="$(arg robot)">
<node pkg="nodelet" type="nodelet" name="image_processor"
args="standalone msckf_vio/ImageProcessorNodelet"
output="screen"
>
<!-- Debugging Flaggs -->
<param name="StreamPause" value="true"/>
<rosparam command="load" file="$(arg calibration_file)"/>
<param name="grid_row" value="4"/>
<param name="grid_col" value="4"/>
<param name="grid_min_feature_num" value="3"/>
<param name="grid_max_feature_num" value="5"/>
<param name="pyramid_levels" value="3"/>
<param name="patch_size" value="15"/>
<param name="fast_threshold" value="10"/>
<param name="max_iteration" value="30"/>
<param name="track_precision" value="0.01"/>
<param name="ransac_threshold" value="3"/>
<param name="stereo_threshold" value="5"/>
<remap from="~imu" to="/imu0"/>
<remap from="~cam0_image" to="/cam0/image_raw"/>
<remap from="~cam1_image" to="/cam1/image_raw"/>
</node>
</group>
</launch>

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@ -1,37 +0,0 @@
<launch>
<arg name="robot" default="firefly_sbx"/>
<arg name="calibration_file"
default="$(find msckf_vio)/config/camchain-imucam-tum.yaml"/>
<!-- Image Processor Nodelet -->
<group ns="$(arg robot)">
<node pkg="nodelet" type="nodelet" name="image_processor"
args="standalone msckf_vio/ImageProcessorNodelet"
output="screen"
>
<!-- Debugging Flaggs -->
<param name="StreamPause" value="true"/>
<rosparam command="load" file="$(arg calibration_file)"/>
<param name="grid_row" value="4"/>
<param name="grid_col" value="4"/>
<param name="grid_min_feature_num" value="3"/>
<param name="grid_max_feature_num" value="4"/>
<param name="pyramid_levels" value="3"/>
<param name="patch_size" value="15"/>
<param name="fast_threshold" value="10"/>
<param name="max_iteration" value="30"/>
<param name="track_precision" value="0.01"/>
<param name="ransac_threshold" value="3"/>
<param name="stereo_threshold" value="5"/>
<remap from="~imu" to="/imu0"/>
<remap from="~cam0_image" to="/cam0/image_raw"/>
<remap from="~cam1_image" to="/cam1/image_raw"/>
</node>
</group>
</launch>

View File

@ -1,75 +0,0 @@
<launch>
<arg name="robot" default="firefly_sbx"/>
<arg name="fixed_frame_id" default="world"/>
<arg name="calibration_file"
default="$(find msckf_vio)/config/camchain-imucam-tum.yaml"/>
<!-- Image Processor Nodelet -->
<include file="$(find msckf_vio)/launch/image_processor_tum.launch">
<arg name="robot" value="$(arg robot)"/>
<arg name="calibration_file" value="$(arg calibration_file)"/>
</include>
<!-- Msckf Vio Nodelet -->
<group ns="$(arg robot)">
<node pkg="nodelet" type="nodelet" name="vio"
args='standalone msckf_vio/MsckfVioNodelet'
output="screen"
launch-prefix="xterm -e gdb --args">
<!-- Photometry Flag-->
<param name="PHOTOMETRIC" value="true"/>
<!-- Debugging Flaggs -->
<param name="PrintImages" value="true"/>
<param name="GroundTruth" value="false"/>
<param name="patch_size_n" value="3"/>
<!-- Calibration parameters -->
<rosparam command="load" file="$(arg calibration_file)"/>
<param name="publish_tf" value="true"/>
<param name="frame_rate" value="20"/>
<param name="fixed_frame_id" value="$(arg fixed_frame_id)"/>
<param name="child_frame_id" value="odom"/>
<param name="max_cam_state_size" value="20"/>
<param name="position_std_threshold" value="8.0"/>
<param name="rotation_threshold" value="0.2618"/>
<param name="translation_threshold" value="0.4"/>
<param name="tracking_rate_threshold" value="0.5"/>
<!-- Feature optimization config -->
<param name="feature/config/translation_threshold" value="-1.0"/>
<!-- These values should be standard deviation -->
<param name="noise/gyro" value="0.005"/>
<param name="noise/acc" value="0.05"/>
<param name="noise/gyro_bias" value="0.001"/>
<param name="noise/acc_bias" value="0.01"/>
<param name="noise/feature" value="0.035"/>
<param name="initial_state/velocity/x" value="0.0"/>
<param name="initial_state/velocity/y" value="0.0"/>
<param name="initial_state/velocity/z" value="0.0"/>
<!-- These values should be covariance -->
<param name="initial_covariance/velocity" value="0.25"/>
<param name="initial_covariance/gyro_bias" value="0.01"/>
<param name="initial_covariance/acc_bias" value="0.01"/>
<param name="initial_covariance/extrinsic_rotation_cov" value="3.0462e-4"/>
<param name="initial_covariance/extrinsic_translation_cov" value="2.5e-5"/>
<param name="initial_covariance/irradiance_frame_bias" value="0.1"/>
<remap from="~imu" to="/imu0"/>
<remap from="~cam0_image" to="/cam0/image_raw"/>
<remap from="~cam1_image" to="/cam1/image_raw"/>
<remap from="~features" to="image_processor/features"/>
</node>
</group>
</launch>

View File

@ -17,18 +17,6 @@
args='standalone msckf_vio/MsckfVioNodelet' args='standalone msckf_vio/MsckfVioNodelet'
output="screen"> output="screen">
<!-- Filter Flag, 0 = msckf, 1 = photometric, 2 = two -->
<param name="FILTER" value="1"/>
<!-- Debugging Flaggs -->
<param name="StreamPause" value="true"/>
<param name="PrintImages" value="true"/>
<param name="GroundTruth" value="false"/>
<param name="patch_size_n" value="5"/>
<param name="image_scale" value ="1"/>
<!-- Calibration parameters --> <!-- Calibration parameters -->
<rosparam command="load" file="$(arg calibration_file)"/> <rosparam command="load" file="$(arg calibration_file)"/>
@ -65,9 +53,6 @@
<param name="initial_covariance/extrinsic_translation_cov" value="2.5e-5"/> <param name="initial_covariance/extrinsic_translation_cov" value="2.5e-5"/>
<remap from="~imu" to="/imu0"/> <remap from="~imu" to="/imu0"/>
<remap from="~cam0_image" to="/cam0/image_raw"/>
<remap from="~cam1_image" to="/cam1/image_raw"/>
<remap from="~features" to="image_processor/features"/> <remap from="~features" to="image_processor/features"/>
</node> </node>

View File

@ -1,61 +0,0 @@
<launch>
<arg name="robot" default="firefly_sbx"/>
<arg name="fixed_frame_id" default="world"/>
<arg name="calibration_file"
default="$(find msckf_vio)/config/camchain-imucam-mynt.yaml"/>
<!-- Image Processor Nodelet -->
<include file="$(find msckf_vio)/launch/image_processor_mynt.launch">
<arg name="robot" value="$(arg robot)"/>
<arg name="calibration_file" value="$(arg calibration_file)"/>
</include>
<!-- Msckf Vio Nodelet -->
<group ns="$(arg robot)">
<node pkg="nodelet" type="nodelet" name="vio"
args='standalone msckf_vio/MsckfVioNodelet'
output="screen">
<!-- Calibration parameters -->
<rosparam command="load" file="$(arg calibration_file)"/>
<param name="publish_tf" value="true"/>
<param name="frame_rate" value="20"/>
<param name="fixed_frame_id" value="$(arg fixed_frame_id)"/>
<param name="child_frame_id" value="odom"/>
<param name="max_cam_state_size" value="20"/>
<param name="position_std_threshold" value="8.0"/>
<param name="rotation_threshold" value="0.2618"/>
<param name="translation_threshold" value="0.4"/>
<param name="tracking_rate_threshold" value="0.5"/>
<!-- Feature optimization config -->
<param name="feature/config/translation_threshold" value="-1.0"/>
<!-- These values should be standard deviation -->
<param name="noise/gyro" value="0.005"/>
<param name="noise/acc" value="0.05"/>
<param name="noise/gyro_bias" value="0.001"/>
<param name="noise/acc_bias" value="0.01"/>
<param name="noise/feature" value="0.035"/>
<param name="initial_state/velocity/x" value="0.0"/>
<param name="initial_state/velocity/y" value="0.0"/>
<param name="initial_state/velocity/z" value="0.0"/>
<!-- These values should be covariance -->
<param name="initial_covariance/velocity" value="0.25"/>
<param name="initial_covariance/gyro_bias" value="0.01"/>
<param name="initial_covariance/acc_bias" value="0.01"/>
<param name="initial_covariance/extrinsic_rotation_cov" value="3.0462e-4"/>
<param name="initial_covariance/extrinsic_translation_cov" value="2.5e-5"/>
<remap from="~imu" to="/mynteye/imu/data_raw"/>
<remap from="~features" to="image_processor/features"/>
</node>
</group>
</launch>

View File

@ -1,77 +0,0 @@
<launch>
<arg name="robot" default="firefly_sbx"/>
<arg name="fixed_frame_id" default="world"/>
<arg name="calibration_file"
default="$(find msckf_vio)/config/camchain-imucam-tum-scaled.yaml"/>
<!-- Image Processor Nodelet -->
<include file="$(find msckf_vio)/launch/image_processor_tinytum.launch">
<arg name="robot" value="$(arg robot)"/>
<arg name="calibration_file" value="$(arg calibration_file)"/>
</include>
<!-- Msckf Vio Nodelet -->
<group ns="$(arg robot)">
<node pkg="nodelet" type="nodelet" name="vio"
args='standalone msckf_vio/MsckfVioNodelet'
output="screen">
<param name="FILTER" value="0"/>
<!-- Debugging Flaggs -->
<param name="StreamPause" value="true"/>
<param name="PrintImages" value="false"/>
<param name="GroundTruth" value="false"/>
<param name="patch_size_n" value="3"/>
<param name="image_scale" value ="1"/>
<!-- Calibration parameters -->
<rosparam command="load" file="$(arg calibration_file)"/>
<param name="publish_tf" value="true"/>
<param name="frame_rate" value="20"/>
<param name="fixed_frame_id" value="$(arg fixed_frame_id)"/>
<param name="child_frame_id" value="odom"/>
<param name="max_cam_state_size" value="12"/>
<param name="position_std_threshold" value="8.0"/>
<param name="rotation_threshold" value="0.2618"/>
<param name="translation_threshold" value="0.4"/>
<param name="tracking_rate_threshold" value="0.5"/>
<!-- Feature optimization config -->
<param name="feature/config/translation_threshold" value="-1.0"/>
<!-- These values should be standard deviation -->
<param name="noise/gyro" value="0.005"/>
<param name="noise/acc" value="0.05"/>
<param name="noise/gyro_bias" value="0.001"/>
<param name="noise/acc_bias" value="0.01"/>
<param name="noise/feature" value="0.035"/>
<param name="initial_state/velocity/x" value="0.0"/>
<param name="initial_state/velocity/y" value="0.0"/>
<param name="initial_state/velocity/z" value="0.0"/>
<!-- These values should be covariance -->
<param name="initial_covariance/velocity" value="0.25"/>
<param name="initial_covariance/gyro_bias" value="0.01"/>
<param name="initial_covariance/acc_bias" value="0.01"/>
<param name="initial_covariance/extrinsic_rotation_cov" value="3.0462e-4"/>
<param name="initial_covariance/extrinsic_translation_cov" value="2.5e-5"/>
<param name="initial_covariance/irradiance_frame_bias" value="0.1"/>
<remap from="~imu" to="/imu0"/>
<remap from="~ground_truth" to="/vrpn_client/raw_transform"/>
<remap from="~cam0_image" to="/cam0/image_raw"/>
<remap from="~cam1_image" to="/cam1/image_raw"/>
<remap from="~features" to="image_processor/features"/>
</node>
</group>
</launch>

View File

@ -1,78 +0,0 @@
<launch>
<arg name="robot" default="firefly_sbx"/>
<arg name="fixed_frame_id" default="world"/>
<arg name="calibration_file"
default="$(find msckf_vio)/config/camchain-imucam-tum.yaml"/>
<!-- Image Processor Nodelet -->
<include file="$(find msckf_vio)/launch/image_processor_tum.launch">
<arg name="robot" value="$(arg robot)"/>
<arg name="calibration_file" value="$(arg calibration_file)"/>
</include>
<!-- Msckf Vio Nodelet -->
<group ns="$(arg robot)">
<node pkg="nodelet" type="nodelet" name="vio"
args='standalone msckf_vio/MsckfVioNodelet'
output="screen">
<!-- Filter Flag, 0 = msckf, 1 = photometric, 2 = two -->
<param name="FILTER" value="1"/>
<!-- Debugging Flaggs -->
<param name="StreamPause" value="true"/>
<param name="PrintImages" value="false"/>
<param name="GroundTruth" value="false"/>
<param name="patch_size_n" value="3"/>
<!-- Calibration parameters -->
<rosparam command="load" file="$(arg calibration_file)"/>
<param name="publish_tf" value="true"/>
<param name="frame_rate" value="20"/>
<param name="fixed_frame_id" value="$(arg fixed_frame_id)"/>
<param name="child_frame_id" value="odom"/>
<param name="max_cam_state_size" value="20"/>
<param name="position_std_threshold" value="8.0"/>
<param name="rotation_threshold" value="0.2618"/>
<param name="translation_threshold" value="0.4"/>
<param name="tracking_rate_threshold" value="0.5"/>
<!-- Feature optimization config -->
<param name="feature/config/translation_threshold" value="-1.0"/>
<!-- These values should be standard deviation -->
<param name="noise/gyro" value="0.005"/>
<param name="noise/acc" value="0.05"/>
<param name="noise/gyro_bias" value="0.001"/>
<param name="noise/acc_bias" value="0.01"/>
<param name="noise/feature" value="0.035"/>
<param name="initial_state/velocity/x" value="0.0"/>
<param name="initial_state/velocity/y" value="0.0"/>
<param name="initial_state/velocity/z" value="0.0"/>
<!-- These values should be covariance -->
<param name="initial_covariance/velocity" value="0.25"/>
<param name="initial_covariance/gyro_bias" value="0.01"/>
<param name="initial_covariance/acc_bias" value="0.01"/>
<param name="initial_covariance/extrinsic_rotation_cov" value="3.0462e-4"/>
<param name="initial_covariance/extrinsic_translation_cov" value="2.5e-5"/>
<param name="initial_covariance/irradiance_frame_bias" value="0.1"/>
<remap from="~imu" to="/imu0"/>
<remap from="~ground_truth" to="/vrpn_client/raw_transform"/>
<remap from="~cam0_image" to="/cam0/image_raw"/>
<remap from="~cam1_image" to="/cam1/image_raw"/>
<remap from="~features" to="image_processor/features"/>
</node>
</group>
<!--node name="player" pkg="bagcontrol" type="control.py" /-->
</launch>

73
log
View File

@ -1,73 +0,0 @@
# Created by Octave 3.8.1, Wed Jun 12 14:36:37 2019 CEST <raphael@raphael-desktop>
# name: Hx
# type: matrix
# rows: 18
# columns: 49
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0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 441.06 -94.50069999999999 174.424 -53.7653 204.822 120.248 0 -441.685 90.1101 -175.657 53.7653 -204.822 -120.248 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 225.35 -54.5629 77.60599999999999 -21.1425 105.886 60.3706 0 -225.756 52.3373 -78.2406 21.1425 -105.886 -60.3706 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 175.128 20.6203 175.127 -79.63939999999999 73.245 62.1868 0 -174.573 -22.5235 -175.576 79.63939999999999 -73.245 -62.1868 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 296.962 43.5469 311.307 -143.667 123.399 108.355 0 -295.905 -46.7952 -312.063 143.667 -123.399 -108.355 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 126.283 117.889 311.864 -161.264 38.8521 71.8019 0 -124.464 -119.541 -312.118 161.264 -38.8521 -71.8019 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 49.2502 63.7166 155.071 -80.81950000000001 12.7732 32.1826 0 -48.2934 -64.4113 -155.157 80.81950000000001 -12.7732 -32.1826 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 69.59699999999999 154.579 335.384 -179.355 9.212580000000001 62.0364 0 -67.35599999999999 -155.735 -335.462 179.355 -9.212580000000001 -62.0364 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -66.6965 304.947 500.218 -285.589 -71.31010000000001 55.5058 0 70.8009 -305.077 -499.831 285.589 71.31010000000001 -55.5058 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 323.404 -62.2043 141.092 -46.6015 148.737 89.1108 0 0 0 0 0 0 0 0 -324.336 57.8552 -141.991 46.6015 -148.737 -89.1108 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 454.208 -99.3095 175.986 -53.4094 211.276 123.174 0 0 0 0 0 0 0 0 -455.779 93.0992 -177.158 53.4094 -211.276 -123.174 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 231.884 -57.0266 78.2559 -20.8926 109.118 61.8183 0 0 0 0 0 0 0 0 -232.824 53.8025 -78.80719999999999 20.8926 -109.118 -61.8183 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 181.715 18.8525 177.045 -80.08499999999999 76.3716 63.8254 0 0 0 0 0 0 0 0 -181.07 -20.839 -177.959 80.08499999999999 -76.3716 -63.8254 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 308.249 40.5812 314.711 -144.494 128.766 111.207 0 0 0 0 0 0 0 0 -306.972 -43.8825 -316.328 144.494 -128.766 -111.207 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 133.309 116.865 315.474 -162.598 42.0763 73.8353 0 0 0 0 0 0 0 0 -130.603 -117.454 -316.931 162.598 -42.0763 -73.8353 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 52.4426 63.3607 156.902 -81.5288 14.2139 33.1222 0 0 0 0 0 0 0 0 -50.9976 -63.4393 -157.607 81.5288 -14.2139 -33.1222 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 75.5508 154.234 339.369 -180.995 11.859 63.8956 0 0 0 0 0 0 0 0 -72.1041 -153.816 -340.865 180.995 -11.859 -63.8956 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -62.0551 306.357 506.351 -288.542 -69.50409999999999 57.4562 0 0 0 0 0 0 0 0 68.6262 -303.028 -508.423 288.542 69.50409999999999 -57.4562 1 0 0 0 0 0 0 0
# name: Hy
# type: matrix
# rows: 18
# columns: 14
1.56267 0 0 0 0 0 0 0 0 0 0.252873 0 0 0.110387
0 1.56267 0 0 0 0 0 0 0 0 0.453168 0 0 0.162961
0 0 1.56267 0 0 0 0 0 0 0 0.638441 0 0 0.0873758
0 0 0 1.56267 0 0 0 0 0 0 0.21031 0 0 0.0321517
0 0 0 0 1.56267 0 0 0 0 0 0.375554 0 0 0.0505151
0 0 0 0 0 1.56267 0 0 0 0 0.638441 0 0 -0.0336034
0 0 0 0 0 0 1.56267 0 0 0 0.157733 0 0 -0.0232704
0 0 0 0 0 0 0 1.56267 0 0 0.212814 0 0 -0.0688343
0 0 0 0 0 0 0 0 1.56267 0 0.360532 0 0 -0.187745
1.56267 0 0 0 0 0 0 0 0 0 0 0.252873 0 0.322811
0 1.56267 0 0 0 0 0 0 0 0 0 0.453168 0 0.467319
0 0 1.56267 0 0 0 0 0 0 0 0 0.638441 0 0.245907
0 0 0 1.56267 0 0 0 0 0 0 0 0.21031 0 0.135725
0 0 0 0 1.56267 0 0 0 0 0 0 0.375554 0 0.225277
0 0 0 0 0 1.56267 0 0 0 0 0 0.638441 0 0.012926
0 0 0 0 0 0 1.56267 0 0 0 0 0.157733 0 -0.0108962
0 0 0 0 0 0 0 1.56267 0 0 0 0.212814 0 -0.06974909999999999
0 0 0 0 0 0 0 0 1.56267 0 0 0.360532 0 -0.318846
# name: r
# type: matrix
# rows: 18
# columns: 1
0.0354809
0.0153183
0.0570191
-0.0372801
0.0878601
0.06811780000000001
-0.00426164
5.162985999041026e-321
6.927779999999998e-310
0
2.121999999910509e-314
0
0
0
3.6073900000086e-313
4.446590812571219e-323
3.952525166729972e-323
3.952525166729972e-323

View File

@ -1,4 +1,4 @@
Header header std_msgs/Header header
# All features on the current image, # All features on the current image,
# including tracked ones and newly detected ones. # including tracked ones and newly detected ones.
FeatureMeasurement[] features FeatureMeasurement[] features

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@ -3,12 +3,13 @@
<name>msckf_vio</name> <name>msckf_vio</name>
<version>0.0.1</version> <version>0.0.1</version>
<description>Multi-State Constraint Kalman Filter - Photometric expansion</description> <description>Multi-State Constraint Kalman Filter for Vision-aided Inertial Navigation</description>
<maintainer email="raphael@maenle.net">Raphael Maenle</maintainer> <maintainer email="sunke.polyu@gmail.com">Ke Sun</maintainer>
<license>Penn Software License</license> <license>Penn Software License</license>
<author email="raphael@maenle.net">Raphael Maenle</author> <author email="sunke.polyu@gmail.com">Ke Sun</author>
<author email="kartikmohta@gmail.com">Kartik Mohta</author>
<buildtool_depend>catkin</buildtool_depend> <buildtool_depend>catkin</buildtool_depend>
@ -18,7 +19,6 @@
<depend>nav_msgs</depend> <depend>nav_msgs</depend>
<depend>sensor_msgs</depend> <depend>sensor_msgs</depend>
<depend>geometry_msgs</depend> <depend>geometry_msgs</depend>
<depend>visualization_msgs</depend>
<depend>eigen_conversions</depend> <depend>eigen_conversions</depend>
<depend>tf_conversions</depend> <depend>tf_conversions</depend>
<depend>random_numbers</depend> <depend>random_numbers</depend>

View File

@ -1,97 +0,0 @@
stereo callback()
create image pyramids
_Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK._
.
if first Frame:
*initialize first Frame ()
else:
*track Features ()
*addnewFeatures ()
*pruneGridFeatures()
_removes worst features from any overflowing grid_
publish features (u1, v1, u2, v2)
_undistorts them beforehand_
addnewFeatures()
*mask existing features
*detect new fast features
*collect in a grid, keep only best n per grid
*stereomatch()
*save inliers into a new feature with u,v on cam0 and cam1
track Features()
*integrateIMUData ()
_uses existing IMU data between two frames to calc. rotation between the two frames_
*predictFeatureTracking()
_compensates the rotation between consecutive frames - rotates previous camera frame features to current camera rotation_
*calcOpticalFlowPyrLK()
_measures the change between the features in the previous frame and in the current frame (using the predicted features)_
*remove points outside of image region
_how does this even happen?_
*stereo match()
_find tracked features from optical flow in the camera 1 image_
_remove all features that could not be matched_
*twoPointRansac(cam0)
*twoPointRansac(cam1)
_remove any features outside best found ransac model_
twoPointRansac()
*mark all points as inliers
*compensate rotation between frames
*normalize points
*calculate difference bewteen previous and current points
*mark large distances (over 50 pixels currently)
*calculate mean points distance
*return if inliers (non marked) < 3
*return if motion smaller than norm pixel unit
*ransac
*optimize with found inlier after random sample
*set inlier markers
initialize first Frame()
features = FastFeatureDetector detect ()
*stereo match ()
group features into grid
- according to position in the image
- sorting them by response
- save the top responses
- save the top responses
stereo match ()
*undistort cam0 Points
*project cam0 Points to cam1 to initialize points in cam1
*calculate lk optical flow
_used because camera calibrations not perfect enough_
_also, calculation more efficient, because LK calculated anyway_
*compute relative trans/rot between cam0 and cam1*
*remove outliers based on essential matrix
_essential matrix relates points in stereo image (pinhole model)_
for every point:
- calculate epipolar line of point in cam0
- calculate error of cam1 to epipolar line
- remove if to big

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@ -1,82 +0,0 @@
featureCallback
propagate IMU state()
state Augmentation()
add Feature Observations()
#the following possibly trigger ekf update step:
remove Lost Features ()
prune Camera State Buffer ()
remove Lost Features()
every feature that does not have a current observation:
*just delete if not enough features
check Motion of Feature ()
_calculation here makes no sense - he uses pixel position as direction vector for feature?_
*initialize Position ()
caculate feature Jakobian and Residual()
*for every observation in this feature
- calculate u and v in camera frames, based on estimated feature position
- input results into jakobi d(measurement)/d(camera 0/1)
- input results into jakobi d(camera 0/1)/d(state) and jakobi d(camera 0/1)/d(feature position)
- project both jakobis to nullspace of feature position jakobi
- calculate residual: measurement - u and v of camera frames
- project residual onto nullspace of feature position jakobi
- stack residual and jakobians
gating Test()
*measurementUpdate()
_use calculated residuals and jakobians to calculate change in error_
measurementUpdate():
- QR reduce the stacked Measurment Jakobis
- calcualte Kalman Gain based on Measurement Jakobian, Error-State Covariance and Noise
_does some fancy shit here_
- calculate estimated error after observation: delta_x = KalmanGain * residual
- add estimated error to state (imu states and cam states)
initialize Position ():
* create initial guess for global feature position ()
_uses first feature measurement on left camera and last feature measurement of right camera_
- transform first measurement to plane of last measurement
- calcualte least square point between rays
* get position approximation using measured feature positions
_using Levenberg Marqhart iterative search_
add Feature Observations()
* if feature not in map, add feature to map
_and add u0, v0, u1, v1 as first observation
* if feature in map, add new observation u0,v0,u1,v1
state Augmentation()
* Add estimated cam position to state
* Update P with Jakobian of cam Position
propagate IMU state ()
_uses IMU process model for every saved IMU state_
for every buffered imu state:
*remove bias
*Compute F and G matrix (continuous transition and noise cov.)
_using current orientation, gyro and acc. reading_
* approximate phi: phi = 1 + Fdt + ...
* calculate new state propagating through runge kutta
* modify transition matrix to have a propper null space?
* calculate Q = Phi*G*Q_noise*GT*PhiT
* calculate P = Phi*P*PhiT + Q
stateAugmentation ()
_save current IMU state as camera position_

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@ -1,64 +0,0 @@
#!/usr/bin/env python
import rosbag
import rospy
from sensor_msgs.msg import Imu, Image
from geometry_msgs.msg import TransformStamped
import time
import signal
import sys
def signal_handler(sig, frame):
print('gracefully exiting the program.')
bag.close()
sys.exit(0)
def main():
global bag
cam0_topic = '/cam0/image_raw'
cam1_topic = '/cam1/image_raw'
imu0_topic = '/imu0'
grnd_topic = '/vrpn_client/raw_transform'
rospy.init_node('controlbag')
rospy.set_param('play_bag', False)
cam0_pub = rospy.Publisher(cam0_topic, Image, queue_size=10)
cam1_pub = rospy.Publisher(cam1_topic, Image, queue_size=10)
imu0_pub = rospy.Publisher(imu0_topic, Imu, queue_size=10)
grnd_pub = rospy.Publisher(grnd_topic, TransformStamped, queue_size=10)
signal.signal(signal.SIGINT, signal_handler)
bag = rosbag.Bag('/home/raphael/dev/MSCKF_ws/bag/TUM/dataset-corridor1_1024_16.bag')
for topic, msg, t in bag.read_messages(topics=[cam0_topic, cam1_topic, imu0_topic, grnd_topic]):
# pause if parameter set to false
flag = False
while not rospy.get_param('/play_bag'):
time.sleep(0.01)
if not flag:
print("stopped playback")
flag = not flag
if flag:
print("resume playback")
if topic == cam0_topic:
cam0_pub.publish(msg)
elif topic == cam1_topic:
cam1_pub.publish(msg)
elif topic == imu0_topic:
imu0_pub.publish(msg)
elif topic ==grnd_topic:
grnd_pub.publish(msg)
#print msg
bag.close()
if __name__== "__main__":
main()

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@ -1,64 +0,0 @@
#!/usr/bin/env python
import rosbag
import rospy
from sensor_msgs.msg import Imu, Image
from geometry_msgs.msg import TransformStamped
import time
import signal
import sys
def signal_handler(sig, frame):
print('gracefully exiting the program.')
bag.close()
sys.exit(0)
def main():
global bag
cam0_topic = '/cam0/image_raw'
cam1_topic = '/cam1/image_raw'
imu0_topic = '/imu0'
grnd_topic = '/vrpn_client/raw_transform'
rospy.init_node('controlbag')
rospy.set_param('play_bag', False)
cam0_pub = rospy.Publisher(cam0_topic, Image, queue_size=10)
cam1_pub = rospy.Publisher(cam1_topic, Image, queue_size=10)
imu0_pub = rospy.Publisher(imu0_topic, Imu, queue_size=10)
grnd_pub = rospy.Publisher(grnd_topic, TransformStamped, queue_size=10)
signal.signal(signal.SIGINT, signal_handler)
bag = rosbag.Bag('/home/raphael/dev/MSCKF_ws/bag/TUM/dataset-corridor1_1024_16.bag')
for topic, msg, t in bag.read_messages(topics=[cam0_topic, cam1_topic, imu0_topic, grnd_topic]):
# pause if parameter set to false
flag = False
while not rospy.get_param('/play_bag'):
time.sleep(0.01)
if not flag:
print("stopped playback")
flag = not flag
if flag:
print("resume playback")
if topic == cam0_topic:
cam0_pub.publish(msg)
elif topic == cam1_topic:
cam1_pub.publish(msg)
elif topic == imu0_topic:
imu0_pub.publish(msg)
elif topic ==grnd_topic:
grnd_pub.publish(msg)
#print msg
bag.close()
if __name__== "__main__":
main()

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@ -1,293 +0,0 @@
#include <iostream>
#include <algorithm>
#include <set>
#include <Eigen/Dense>
#include <sensor_msgs/image_encodings.h>
#include <random_numbers/random_numbers.h>
#include <msckf_vio/CameraMeasurement.h>
#include <msckf_vio/TrackingInfo.h>
#include <msckf_vio/image_processor.h>
namespace msckf_vio {
namespace image_handler {
cv::Point2f pinholeDownProject(const cv::Point2f& p_in, const cv::Vec4d& intrinsics)
{
return cv::Point2f(p_in.x * intrinsics[0] + intrinsics[2], p_in.y * intrinsics[1] + intrinsics[3]);
}
cv::Point2f pinholeUpProject(const cv::Point2f& p_in, const cv::Vec4d& intrinsics)
{
return cv::Point2f((p_in.x - intrinsics[2])/intrinsics[0], (p_in.y - intrinsics[3])/intrinsics[1]);
}
void undistortImage(
cv::InputArray src,
cv::OutputArray dst,
const std::string& distortion_model,
const cv::Vec4d& intrinsics,
const cv::Vec4d& distortion_coeffs)
{
const cv::Matx33d K(intrinsics[0], 0.0, intrinsics[2],
0.0, intrinsics[1], intrinsics[3],
0.0, 0.0, 1.0);
if (distortion_model == "pre-equidistant")
cv::fisheye::undistortImage(src, dst, K, distortion_coeffs, K);
else if (distortion_model == "equidistant")
src.copyTo(dst);
else if (distortion_model == "pre-radtan")
cv::undistort(src, dst, K, distortion_coeffs, K);
else if (distortion_model == "radtan")
src.copyTo(dst);
}
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);
}
// equidistant
else if (distortion_model == "equidistant") {
cv::fisheye::undistortPoints(pts_in, pts_out, K, distortion_coeffs,
rectification_matrix, K_new);
}
// fov
else if (distortion_model == "fov") {
for(int i = 0; i < pts_in.size(); i++)
{
float omega = distortion_coeffs[0];
float rd = sqrt(pts_in[i].x * pts_in[i].x + pts_in[i].y * pts_in[i].y);
float ru = tan(rd * omega)/(2 * tan(omega / 2));
cv::Point2f newPoint(
((pts_in[i].x - intrinsics[2]) / intrinsics[0]) * (ru / rd),
((pts_in[i].y - intrinsics[3]) / intrinsics[1]) * (ru / rd));
pts_out.push_back(newPoint);
}
}
else if (distortion_model == "pre-equidistant" or distortion_model == "pre-radtan")
{
std::vector<cv::Point2f> temp_pts_out;
for(int i = 0; i < pts_in.size(); i++)
temp_pts_out.push_back(pinholeUpProject(pts_in[i], intrinsics));
pts_out = temp_pts_out;
}
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,
const std::string& distortion_model,
const cv::Vec4d& distortion_coeffs,
std::vector<cv::Point2f>& pts_out,
const cv::Matx33d &rectification_matrix,
const cv::Vec4d &new_intrinsics) {
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 if (distortion_model == "fov") {
for(int i = 0; i < pts_in.size(); i++)
{
float omega = distortion_coeffs[0];
float rd = sqrt(pts_in[i].x * pts_in[i].x + pts_in[i].y * pts_in[i].y);
float ru = tan(rd * omega)/(2 * tan(omega / 2));
cv::Point2f newPoint(
((pts_in[i].x - intrinsics[2]) / intrinsics[0]) * (ru / rd),
((pts_in[i].y - intrinsics[3]) / intrinsics[1]) * (ru / rd));
pts_out.push_back(newPoint);
}
}
else if (distortion_model == "pre-equidistant" or distortion_model == "pre-radtan")
{
std::vector<cv::Point2f> temp_pts_out;
for(int i = 0; i < pts_in.size(); i++)
temp_pts_out.push_back(pinholeUpProject(pts_in[i], intrinsics));
pts_out = temp_pts_out;
}
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);
}
return;
}
std::vector<cv::Point2f> distortPoints(
const std::vector<cv::Point2f>& pts_in,
const cv::Vec4d& intrinsics,
const std::string& distortion_model,
const cv::Vec4d& distortion_coeffs) {
const cv::Matx33d K(intrinsics[0], 0.0, intrinsics[2],
0.0, intrinsics[1], intrinsics[3],
0.0, 0.0, 1.0);
std::vector<cv::Point2f> pts_out;
if (distortion_model == "radtan") {
std::vector<cv::Point3f> homogenous_pts;
cv::convertPointsToHomogeneous(pts_in, homogenous_pts);
cv::projectPoints(homogenous_pts, cv::Vec3d::zeros(), cv::Vec3d::zeros(), K,
distortion_coeffs, pts_out);
} else if (distortion_model == "equidistant") {
cv::fisheye::distortPoints(pts_in, pts_out, K, distortion_coeffs);
}
else if (distortion_model == "fov") {
for(int i = 0; i < pts_in.size(); i++)
{
// based on 'straight lines have to be straight'
float ru = sqrt(pts_in[i].x * pts_in[i].x + pts_in[i].y * pts_in[i].y);
float omega = distortion_coeffs[0];
float rd = 1 / (omega)*atan(2*ru*tan(omega / 2));
cv::Point2f newPoint(
pts_in[i].x * (rd/ru) * intrinsics[0] + intrinsics[2],
pts_in[i].y * (rd/ru) * intrinsics[1] + intrinsics[3]);
pts_out.push_back(newPoint);
}
}
else if (distortion_model == "pre-equidistant" or distortion_model == "pre-radtan")
{
std::vector<cv::Point2f> temp_pts_out;
for(int i = 0; i < pts_in.size(); i++)
temp_pts_out.push_back(pinholeDownProject(pts_in[i], intrinsics));
pts_out = temp_pts_out;
}
else {
ROS_WARN_ONCE("The model %s is unrecognized, using radtan instead...",
distortion_model.c_str());
std::vector<cv::Point3f> homogenous_pts;
cv::convertPointsToHomogeneous(pts_in, homogenous_pts);
cv::projectPoints(homogenous_pts, cv::Vec3d::zeros(), cv::Vec3d::zeros(), K,
distortion_coeffs, pts_out);
}
return pts_out;
}
cv::Point2f distortPoint(
const cv::Point2f& pt_in,
const cv::Vec4d& intrinsics,
const std::string& distortion_model,
const cv::Vec4d& distortion_coeffs) {
std::vector<cv::Point2f> pts_in;
pts_in.push_back(pt_in);
const cv::Matx33d K(intrinsics[0], 0.0, intrinsics[2],
0.0, intrinsics[1], intrinsics[3],
0.0, 0.0, 1.0);
std::vector<cv::Point2f> pts_out;
if (distortion_model == "radtan") {
std::vector<cv::Point3f> homogenous_pts;
cv::convertPointsToHomogeneous(pts_in, homogenous_pts);
cv::projectPoints(homogenous_pts, cv::Vec3d::zeros(), cv::Vec3d::zeros(), K,
distortion_coeffs, pts_out);
} else if (distortion_model == "equidistant") {
cv::fisheye::distortPoints(pts_in, pts_out, K, distortion_coeffs);
}
else if (distortion_model == "fov") {
for(int i = 0; i < pts_in.size(); i++)
{
// based on 'straight lines have to be straight'
float ru = sqrt(pts_in[i].x * pts_in[i].x + pts_in[i].y * pts_in[i].y);
float omega = distortion_coeffs[0];
float rd = 1 / (omega)*atan(2*ru*tan(omega / 2));
cv::Point2f newPoint(
pts_in[i].x * (rd/ru) * intrinsics[0] + intrinsics[2],
pts_in[i].y * (rd/ru) * intrinsics[1] + intrinsics[3]);
pts_out.push_back(newPoint);
}
}
else if (distortion_model == "pre-equidistant" or distortion_model == "pre-radtan")
{
std::vector<cv::Point2f> temp_pts_out;
for(int i = 0; i < pts_in.size(); i++)
pts_out.push_back(pinholeDownProject(pts_in[i], intrinsics));
pts_out = temp_pts_out;
}
else {
ROS_WARN_ONCE("The model %s is unrecognized, using radtan instead...",
distortion_model.c_str());
std::vector<cv::Point3f> homogenous_pts;
cv::convertPointsToHomogeneous(pts_in, homogenous_pts);
cv::projectPoints(homogenous_pts, cv::Vec3d::zeros(), cv::Vec3d::zeros(), K,
distortion_coeffs, pts_out);
}
return pts_out[0];
}
} // namespace image_handler
} // namespace msckf_vio

View File

@ -17,7 +17,6 @@
#include <msckf_vio/TrackingInfo.h> #include <msckf_vio/TrackingInfo.h>
#include <msckf_vio/image_processor.h> #include <msckf_vio/image_processor.h>
#include <msckf_vio/utils.h> #include <msckf_vio/utils.h>
#include <msckf_vio/image_handler.h>
using namespace std; using namespace std;
using namespace cv; using namespace cv;
@ -42,54 +41,51 @@ ImageProcessor::~ImageProcessor() {
} }
bool ImageProcessor::loadParameters() { bool ImageProcessor::loadParameters() {
// debug parameters
nh.param<bool>("StreamPause", STREAMPAUSE, false);
// Camera calibration parameters // Camera calibration parameters
nh.param<string>("cam0/distortion_model", nh.param<string>("cam0/distortion_model",
cam0.distortion_model, string("radtan")); cam0_distortion_model, string("radtan"));
nh.param<string>("cam1/distortion_model", nh.param<string>("cam1/distortion_model",
cam1.distortion_model, string("radtan")); cam1_distortion_model, string("radtan"));
vector<int> cam0_resolution_temp(2); vector<int> cam0_resolution_temp(2);
nh.getParam("cam0/resolution", cam0_resolution_temp); nh.getParam("cam0/resolution", cam0_resolution_temp);
cam0.resolution[0] = cam0_resolution_temp[0]; cam0_resolution[0] = cam0_resolution_temp[0];
cam0.resolution[1] = cam0_resolution_temp[1]; cam0_resolution[1] = cam0_resolution_temp[1];
vector<int> cam1_resolution_temp(2); vector<int> cam1_resolution_temp(2);
nh.getParam("cam1/resolution", cam1_resolution_temp); nh.getParam("cam1/resolution", cam1_resolution_temp);
cam1.resolution[0] = cam1_resolution_temp[0]; cam1_resolution[0] = cam1_resolution_temp[0];
cam1.resolution[1] = cam1_resolution_temp[1]; cam1_resolution[1] = cam1_resolution_temp[1];
vector<double> cam0_intrinsics_temp(4); vector<double> cam0_intrinsics_temp(4);
nh.getParam("cam0/intrinsics", cam0_intrinsics_temp); nh.getParam("cam0/intrinsics", cam0_intrinsics_temp);
cam0.intrinsics[0] = cam0_intrinsics_temp[0]; cam0_intrinsics[0] = cam0_intrinsics_temp[0];
cam0.intrinsics[1] = cam0_intrinsics_temp[1]; cam0_intrinsics[1] = cam0_intrinsics_temp[1];
cam0.intrinsics[2] = cam0_intrinsics_temp[2]; cam0_intrinsics[2] = cam0_intrinsics_temp[2];
cam0.intrinsics[3] = cam0_intrinsics_temp[3]; cam0_intrinsics[3] = cam0_intrinsics_temp[3];
vector<double> cam1_intrinsics_temp(4); vector<double> cam1_intrinsics_temp(4);
nh.getParam("cam1/intrinsics", cam1_intrinsics_temp); nh.getParam("cam1/intrinsics", cam1_intrinsics_temp);
cam1.intrinsics[0] = cam1_intrinsics_temp[0]; cam1_intrinsics[0] = cam1_intrinsics_temp[0];
cam1.intrinsics[1] = cam1_intrinsics_temp[1]; cam1_intrinsics[1] = cam1_intrinsics_temp[1];
cam1.intrinsics[2] = cam1_intrinsics_temp[2]; cam1_intrinsics[2] = cam1_intrinsics_temp[2];
cam1.intrinsics[3] = cam1_intrinsics_temp[3]; cam1_intrinsics[3] = cam1_intrinsics_temp[3];
vector<double> cam0_distortion_coeffs_temp(4); vector<double> cam0_distortion_coeffs_temp(4);
nh.getParam("cam0/distortion_coeffs", nh.getParam("cam0/distortion_coeffs",
cam0_distortion_coeffs_temp); cam0_distortion_coeffs_temp);
cam0.distortion_coeffs[0] = cam0_distortion_coeffs_temp[0]; cam0_distortion_coeffs[0] = cam0_distortion_coeffs_temp[0];
cam0.distortion_coeffs[1] = cam0_distortion_coeffs_temp[1]; cam0_distortion_coeffs[1] = cam0_distortion_coeffs_temp[1];
cam0.distortion_coeffs[2] = cam0_distortion_coeffs_temp[2]; cam0_distortion_coeffs[2] = cam0_distortion_coeffs_temp[2];
cam0.distortion_coeffs[3] = cam0_distortion_coeffs_temp[3]; cam0_distortion_coeffs[3] = cam0_distortion_coeffs_temp[3];
vector<double> cam1_distortion_coeffs_temp(4); vector<double> cam1_distortion_coeffs_temp(4);
nh.getParam("cam1/distortion_coeffs", nh.getParam("cam1/distortion_coeffs",
cam1_distortion_coeffs_temp); cam1_distortion_coeffs_temp);
cam1.distortion_coeffs[0] = cam1_distortion_coeffs_temp[0]; cam1_distortion_coeffs[0] = cam1_distortion_coeffs_temp[0];
cam1.distortion_coeffs[1] = cam1_distortion_coeffs_temp[1]; cam1_distortion_coeffs[1] = cam1_distortion_coeffs_temp[1];
cam1.distortion_coeffs[2] = cam1_distortion_coeffs_temp[2]; cam1_distortion_coeffs[2] = cam1_distortion_coeffs_temp[2];
cam1.distortion_coeffs[3] = cam1_distortion_coeffs_temp[3]; cam1_distortion_coeffs[3] = cam1_distortion_coeffs_temp[3];
cv::Mat T_imu_cam0 = utils::getTransformCV(nh, "cam0/T_cam_imu"); cv::Mat T_imu_cam0 = utils::getTransformCV(nh, "cam0/T_cam_imu");
cv::Matx33d R_imu_cam0(T_imu_cam0(cv::Rect(0,0,3,3))); cv::Matx33d R_imu_cam0(T_imu_cam0(cv::Rect(0,0,3,3)));
@ -127,27 +123,27 @@ bool ImageProcessor::loadParameters() {
processor_config.stereo_threshold, 3); processor_config.stereo_threshold, 3);
ROS_INFO("==========================================="); ROS_INFO("===========================================");
ROS_INFO("cam0.resolution: %d, %d", ROS_INFO("cam0_resolution: %d, %d",
cam0.resolution[0], cam0.resolution[1]); cam0_resolution[0], cam0_resolution[1]);
ROS_INFO("cam0_intrinscs: %f, %f, %f, %f", ROS_INFO("cam0_intrinscs: %f, %f, %f, %f",
cam0.intrinsics[0], cam0.intrinsics[1], cam0_intrinsics[0], cam0_intrinsics[1],
cam0.intrinsics[2], cam0.intrinsics[3]); cam0_intrinsics[2], cam0_intrinsics[3]);
ROS_INFO("cam0.distortion_model: %s", ROS_INFO("cam0_distortion_model: %s",
cam0.distortion_model.c_str()); cam0_distortion_model.c_str());
ROS_INFO("cam0_distortion_coefficients: %f, %f, %f, %f", ROS_INFO("cam0_distortion_coefficients: %f, %f, %f, %f",
cam0.distortion_coeffs[0], cam0.distortion_coeffs[1], cam0_distortion_coeffs[0], cam0_distortion_coeffs[1],
cam0.distortion_coeffs[2], cam0.distortion_coeffs[3]); cam0_distortion_coeffs[2], cam0_distortion_coeffs[3]);
ROS_INFO("cam1.resolution: %d, %d", ROS_INFO("cam1_resolution: %d, %d",
cam1.resolution[0], cam1.resolution[1]); cam1_resolution[0], cam1_resolution[1]);
ROS_INFO("cam1_intrinscs: %f, %f, %f, %f", ROS_INFO("cam1_intrinscs: %f, %f, %f, %f",
cam1.intrinsics[0], cam1.intrinsics[1], cam1_intrinsics[0], cam1_intrinsics[1],
cam1.intrinsics[2], cam1.intrinsics[3]); cam1_intrinsics[2], cam1_intrinsics[3]);
ROS_INFO("cam1.distortion_model: %s", ROS_INFO("cam1_distortion_model: %s",
cam1.distortion_model.c_str()); cam1_distortion_model.c_str());
ROS_INFO("cam1_distortion_coefficients: %f, %f, %f, %f", ROS_INFO("cam1_distortion_coefficients: %f, %f, %f, %f",
cam1.distortion_coeffs[0], cam1.distortion_coeffs[1], cam1_distortion_coeffs[0], cam1_distortion_coeffs[1],
cam1.distortion_coeffs[2], cam1.distortion_coeffs[3]); cam1_distortion_coeffs[2], cam1_distortion_coeffs[3]);
cout << R_imu_cam0 << endl; cout << R_imu_cam0 << endl;
cout << t_imu_cam0.t() << endl; cout << t_imu_cam0.t() << endl;
@ -174,6 +170,10 @@ bool ImageProcessor::loadParameters() {
processor_config.ransac_threshold); processor_config.ransac_threshold);
ROS_INFO("stereo_threshold: %f", ROS_INFO("stereo_threshold: %f",
processor_config.stereo_threshold); processor_config.stereo_threshold);
ROS_INFO("OpenCV Major Version: %d",
CV_MAJOR_VERSION);
ROS_INFO("OpenCV Minor Version: %d",
CV_MINOR_VERSION);
ROS_INFO("==========================================="); ROS_INFO("===========================================");
return true; return true;
} }
@ -204,6 +204,13 @@ bool ImageProcessor::initialize() {
detector_ptr = FastFeatureDetector::create( detector_ptr = FastFeatureDetector::create(
processor_config.fast_threshold); processor_config.fast_threshold);
//create gpu optical flow lk
d_pyrLK_sparse = cuda::SparsePyrLKOpticalFlow::create(
Size(processor_config.patch_size, processor_config.patch_size),
processor_config.pyramid_levels,
processor_config.max_iteration,
true);
if (!createRosIO()) return false; if (!createRosIO()) return false;
ROS_INFO("Finish creating ROS IO..."); ROS_INFO("Finish creating ROS IO...");
@ -214,9 +221,7 @@ void ImageProcessor::stereoCallback(
const sensor_msgs::ImageConstPtr& cam0_img, const sensor_msgs::ImageConstPtr& cam0_img,
const sensor_msgs::ImageConstPtr& cam1_img) { const sensor_msgs::ImageConstPtr& cam1_img) {
// stop playing bagfile if printing images //cout << "==================================" << endl;
//if(STREAMPAUSE)
// nh.setParam("/play_bag_image", false);
// Get the current image. // Get the current image.
cam0_curr_img_ptr = cv_bridge::toCvShare(cam0_img, cam0_curr_img_ptr = cv_bridge::toCvShare(cam0_img,
@ -224,27 +229,14 @@ void ImageProcessor::stereoCallback(
cam1_curr_img_ptr = cv_bridge::toCvShare(cam1_img, cam1_curr_img_ptr = cv_bridge::toCvShare(cam1_img,
sensor_msgs::image_encodings::MONO8); sensor_msgs::image_encodings::MONO8);
ros::Time start_time = ros::Time::now();
cv::Mat new_cam0;
cv::Mat new_cam1;
image_handler::undistortImage(cam0_curr_img_ptr->image, new_cam0, cam0.distortion_model, cam0.intrinsics, cam0.distortion_coeffs);
image_handler::undistortImage(cam1_curr_img_ptr->image, new_cam1, cam1.distortion_model, cam1.intrinsics, cam1.distortion_coeffs);
new_cam0.copyTo(cam0_curr_img_ptr->image);
new_cam1.copyTo(cam1_curr_img_ptr->image);
//ROS_INFO("Publishing: %f",
// (ros::Time::now()-start_time).toSec());
// Build the image pyramids once since they're used at multiple places // Build the image pyramids once since they're used at multiple places
createImagePyramids();
// removed due to alternate cuda construct
//createImagePyramids();
// Detect features in the first frame. // Detect features in the first frame.
if (is_first_img) { if (is_first_img) {
start_time = ros::Time::now(); ros::Time start_time = ros::Time::now();
initializeFirstFrame(); initializeFirstFrame();
//ROS_INFO("Detection time: %f", //ROS_INFO("Detection time: %f",
// (ros::Time::now()-start_time).toSec()); // (ros::Time::now()-start_time).toSec());
@ -257,7 +249,7 @@ void ImageProcessor::stereoCallback(
// (ros::Time::now()-start_time).toSec()); // (ros::Time::now()-start_time).toSec());
} else { } else {
// Track the feature in the previous image. // Track the feature in the previous image.
start_time = ros::Time::now(); ros::Time start_time = ros::Time::now();
trackFeatures(); trackFeatures();
//ROS_INFO("Tracking time: %f", //ROS_INFO("Tracking time: %f",
// (ros::Time::now()-start_time).toSec()); // (ros::Time::now()-start_time).toSec());
@ -265,7 +257,6 @@ void ImageProcessor::stereoCallback(
// Add new features into the current image. // Add new features into the current image.
start_time = ros::Time::now(); start_time = ros::Time::now();
addNewFeatures(); addNewFeatures();
//ROS_INFO("Addition time: %f", //ROS_INFO("Addition time: %f",
// (ros::Time::now()-start_time).toSec()); // (ros::Time::now()-start_time).toSec());
@ -288,18 +279,16 @@ void ImageProcessor::stereoCallback(
// (ros::Time::now()-start_time).toSec()); // (ros::Time::now()-start_time).toSec());
// Publish features in the current image. // Publish features in the current image.
start_time = ros::Time::now(); ros::Time start_time = ros::Time::now();
publish(); publish();
//ROS_INFO("Publishing: %f", //ROS_INFO("Publishing: %f",
// (ros::Time::now()-start_time).toSec()); // (ros::Time::now()-start_time).toSec());
// Update the previous image and previous features. // Update the previous image and previous features.
cam0_prev_img_ptr = cam0_curr_img_ptr; cam0_prev_img_ptr = cam0_curr_img_ptr;
prev_features_ptr = curr_features_ptr; prev_features_ptr = curr_features_ptr;
std::swap(prev_cam0_pyramid_, curr_cam0_pyramid_); std::swap(prev_cam0_pyramid_, curr_cam0_pyramid_);
// Initialize the current features to empty vectors. // Initialize the current features to empty vectors.
curr_features_ptr.reset(new GridFeatures()); curr_features_ptr.reset(new GridFeatures());
for (int code = 0; code < for (int code = 0; code <
@ -307,10 +296,6 @@ void ImageProcessor::stereoCallback(
(*curr_features_ptr)[code] = vector<FeatureMetaData>(0); (*curr_features_ptr)[code] = vector<FeatureMetaData>(0);
} }
// stop playing bagfile if printing images
//if(STREAMPAUSE)
// nh.setParam("/play_bag_image", true);
return; return;
} }
@ -324,6 +309,7 @@ void ImageProcessor::imuCallback(
void ImageProcessor::createImagePyramids() { void ImageProcessor::createImagePyramids() {
const Mat& curr_cam0_img = cam0_curr_img_ptr->image; const Mat& curr_cam0_img = cam0_curr_img_ptr->image;
// TODO: build cuda optical flow
buildOpticalFlowPyramid( buildOpticalFlowPyramid(
curr_cam0_img, curr_cam0_pyramid_, curr_cam0_img, curr_cam0_pyramid_,
Size(processor_config.patch_size, processor_config.patch_size), Size(processor_config.patch_size, processor_config.patch_size),
@ -331,6 +317,7 @@ void ImageProcessor::createImagePyramids() {
BORDER_CONSTANT, false); BORDER_CONSTANT, false);
const Mat& curr_cam1_img = cam1_curr_img_ptr->image; const Mat& curr_cam1_img = cam1_curr_img_ptr->image;
// TODO: build cuda optical flow
buildOpticalFlowPyramid( buildOpticalFlowPyramid(
curr_cam1_img, curr_cam1_pyramid_, curr_cam1_img, curr_cam1_pyramid_,
Size(processor_config.patch_size, processor_config.patch_size), Size(processor_config.patch_size, processor_config.patch_size),
@ -417,6 +404,7 @@ void ImageProcessor::predictFeatureTracking(
const cv::Matx33f& R_p_c, const cv::Matx33f& R_p_c,
const cv::Vec4d& intrinsics, const cv::Vec4d& intrinsics,
vector<cv::Point2f>& compensated_pts) { vector<cv::Point2f>& compensated_pts) {
// Return directly if there are no input features. // Return directly if there are no input features.
if (input_pts.size() == 0) { if (input_pts.size() == 0) {
compensated_pts.clear(); compensated_pts.clear();
@ -447,6 +435,7 @@ void ImageProcessor::trackFeatures() {
cam0_curr_img_ptr->image.rows / processor_config.grid_row; cam0_curr_img_ptr->image.rows / processor_config.grid_row;
static int grid_width = static int grid_width =
cam0_curr_img_ptr->image.cols / processor_config.grid_col; cam0_curr_img_ptr->image.cols / processor_config.grid_col;
// Compute a rough relative rotation which takes a vector // Compute a rough relative rotation which takes a vector
// from the previous frame to the current frame. // from the previous frame to the current frame.
Matx33f cam0_R_p_c; Matx33f cam0_R_p_c;
@ -480,8 +469,10 @@ void ImageProcessor::trackFeatures() {
vector<unsigned char> track_inliers(0); vector<unsigned char> track_inliers(0);
predictFeatureTracking(prev_cam0_points, predictFeatureTracking(prev_cam0_points,
cam0_R_p_c, cam0.intrinsics, curr_cam0_points); cam0_R_p_c, cam0_intrinsics, curr_cam0_points);
//TODO: test change to sparse
/*
calcOpticalFlowPyrLK( calcOpticalFlowPyrLK(
prev_cam0_pyramid_, curr_cam0_pyramid_, prev_cam0_pyramid_, curr_cam0_pyramid_,
prev_cam0_points, curr_cam0_points, prev_cam0_points, curr_cam0_points,
@ -492,6 +483,25 @@ void ImageProcessor::trackFeatures() {
processor_config.max_iteration, processor_config.max_iteration,
processor_config.track_precision), processor_config.track_precision),
cv::OPTFLOW_USE_INITIAL_FLOW); cv::OPTFLOW_USE_INITIAL_FLOW);
*/
cam0_curr_img = cv::cuda::GpuMat(cam0_curr_img_ptr->image);
cam1_curr_img = cv::cuda::GpuMat(cam1_curr_img_ptr->image);
cam0_points_gpu = cv::cuda::GpuMat(prev_cam0_points);
cam1_points_gpu = cv::cuda::GpuMat(curr_cam0_points);
cv::cuda::GpuMat inlier_markers_gpu;
d_pyrLK_sparse->calc(cam0_curr_img,
cam1_curr_img,
cam0_points_gpu,
cam1_points_gpu,
inlier_markers_gpu,
noArray());
utils::download(cam1_points_gpu, curr_cam0_points);
utils::download(inlier_markers_gpu, track_inliers);
// Mark those tracked points out of the image region // Mark those tracked points out of the image region
// as untracked. // as untracked.
@ -575,14 +585,14 @@ void ImageProcessor::trackFeatures() {
// Step 2 and 3: RANSAC on temporal image pairs of cam0 and cam1. // Step 2 and 3: RANSAC on temporal image pairs of cam0 and cam1.
vector<int> cam0_ransac_inliers(0); vector<int> cam0_ransac_inliers(0);
twoPointRansac(prev_matched_cam0_points, curr_matched_cam0_points, twoPointRansac(prev_matched_cam0_points, curr_matched_cam0_points,
cam0_R_p_c, cam0.intrinsics, cam0.distortion_model, cam0_R_p_c, cam0_intrinsics, cam0_distortion_model,
cam0.distortion_coeffs, processor_config.ransac_threshold, cam0_distortion_coeffs, processor_config.ransac_threshold,
0.99, cam0_ransac_inliers); 0.99, cam0_ransac_inliers);
vector<int> cam1_ransac_inliers(0); vector<int> cam1_ransac_inliers(0);
twoPointRansac(prev_matched_cam1_points, curr_matched_cam1_points, twoPointRansac(prev_matched_cam1_points, curr_matched_cam1_points,
cam1_R_p_c, cam1.intrinsics, cam1.distortion_model, cam1_R_p_c, cam1_intrinsics, cam1_distortion_model,
cam1.distortion_coeffs, processor_config.ransac_threshold, cam1_distortion_coeffs, processor_config.ransac_threshold,
0.99, cam1_ransac_inliers); 0.99, cam1_ransac_inliers);
// Number of features after ransac. // Number of features after ransac.
@ -607,7 +617,6 @@ void ImageProcessor::trackFeatures() {
++after_ransac; ++after_ransac;
} }
// Compute the tracking rate. // Compute the tracking rate.
int prev_feature_num = 0; int prev_feature_num = 0;
for (const auto& item : *prev_features_ptr) for (const auto& item : *prev_features_ptr)
@ -637,6 +646,7 @@ void ImageProcessor::stereoMatch(
const vector<cv::Point2f>& cam0_points, const vector<cv::Point2f>& cam0_points,
vector<cv::Point2f>& cam1_points, vector<cv::Point2f>& cam1_points,
vector<unsigned char>& inlier_markers) { vector<unsigned char>& inlier_markers) {
if (cam0_points.size() == 0) return; if (cam0_points.size() == 0) return;
if(cam1_points.size() == 0) { if(cam1_points.size() == 0) {
@ -644,15 +654,31 @@ void ImageProcessor::stereoMatch(
// rotation from stereo extrinsics // rotation from stereo extrinsics
const cv::Matx33d R_cam0_cam1 = R_cam1_imu.t() * R_cam0_imu; const cv::Matx33d R_cam0_cam1 = R_cam1_imu.t() * R_cam0_imu;
vector<cv::Point2f> cam0_points_undistorted; vector<cv::Point2f> cam0_points_undistorted;
image_handler::undistortPoints(cam0_points, cam0.intrinsics, cam0.distortion_model, undistortPoints(cam0_points, cam0_intrinsics, cam0_distortion_model,
cam0.distortion_coeffs, cam0_points_undistorted, cam0_distortion_coeffs, cam0_points_undistorted,
R_cam0_cam1); R_cam0_cam1);
cam1_points = distortPoints(cam0_points_undistorted, cam1_intrinsics,
cam1_points = image_handler::distortPoints(cam0_points_undistorted, cam1.intrinsics, cam1_distortion_model, cam1_distortion_coeffs);
cam1.distortion_model, cam1.distortion_coeffs);
} }
cam0_curr_img = cv::cuda::GpuMat(cam0_curr_img_ptr->image);
cam1_curr_img = cv::cuda::GpuMat(cam1_curr_img_ptr->image);
cam0_points_gpu = cv::cuda::GpuMat(cam0_points);
cam1_points_gpu = cv::cuda::GpuMat(cam1_points);
cv::cuda::GpuMat inlier_markers_gpu;
d_pyrLK_sparse->calc(cam0_curr_img,
cam1_curr_img,
cam0_points_gpu,
cam1_points_gpu,
inlier_markers_gpu,
noArray());
utils::download(cam1_points_gpu, cam1_points);
utils::download(inlier_markers_gpu, inlier_markers);
// Track features using LK optical flow method. // Track features using LK optical flow method.
/*
calcOpticalFlowPyrLK(curr_cam0_pyramid_, curr_cam1_pyramid_, calcOpticalFlowPyrLK(curr_cam0_pyramid_, curr_cam1_pyramid_,
cam0_points, cam1_points, cam0_points, cam1_points,
inlier_markers, noArray(), inlier_markers, noArray(),
@ -662,7 +688,7 @@ void ImageProcessor::stereoMatch(
processor_config.max_iteration, processor_config.max_iteration,
processor_config.track_precision), processor_config.track_precision),
cv::OPTFLOW_USE_INITIAL_FLOW); cv::OPTFLOW_USE_INITIAL_FLOW);
*/
// Mark those tracked points out of the image region // Mark those tracked points out of the image region
// as untracked. // as untracked.
for (int i = 0; i < cam1_points.size(); ++i) { for (int i = 0; i < cam1_points.size(); ++i) {
@ -687,21 +713,18 @@ void ImageProcessor::stereoMatch(
// Further remove outliers based on the known // Further remove outliers based on the known
// essential matrix. // essential matrix.
vector<cv::Point2f> cam0_points_undistorted(0); vector<cv::Point2f> cam0_points_undistorted(0);
vector<cv::Point2f> cam1_points_undistorted(0); vector<cv::Point2f> cam1_points_undistorted(0);
image_handler::undistortPoints( undistortPoints(
cam0_points, cam0.intrinsics, cam0.distortion_model, cam0_points, cam0_intrinsics, cam0_distortion_model,
cam0.distortion_coeffs, cam0_points_undistorted); cam0_distortion_coeffs, cam0_points_undistorted);
image_handler::undistortPoints( undistortPoints(
cam1_points, cam1.intrinsics, cam1.distortion_model, cam1_points, cam1_intrinsics, cam1_distortion_model,
cam1.distortion_coeffs, cam1_points_undistorted); cam1_distortion_coeffs, cam1_points_undistorted);
double norm_pixel_unit = 4.0 / ( double norm_pixel_unit = 4.0 / (
cam0.intrinsics[0]+cam0.intrinsics[1]+ cam0_intrinsics[0]+cam0_intrinsics[1]+
cam1.intrinsics[0]+cam1.intrinsics[1]); cam1_intrinsics[0]+cam1_intrinsics[1]);
for (int i = 0; i < cam0_points_undistorted.size(); ++i) { for (int i = 0; i < cam0_points_undistorted.size(); ++i) {
if (inlier_markers[i] == 0) continue; if (inlier_markers[i] == 0) continue;
@ -728,8 +751,8 @@ void ImageProcessor::addNewFeatures() {
cam0_curr_img_ptr->image.rows / processor_config.grid_row; cam0_curr_img_ptr->image.rows / processor_config.grid_row;
static int grid_width = static int grid_width =
cam0_curr_img_ptr->image.cols / processor_config.grid_col; cam0_curr_img_ptr->image.cols / processor_config.grid_col;
// Create a mask to avoid redetecting existing features.
// Create a mask to avoid redetecting existing features.
Mat mask(curr_img.rows, curr_img.cols, CV_8U, Scalar(1)); Mat mask(curr_img.rows, curr_img.cols, CV_8U, Scalar(1));
for (const auto& features : *curr_features_ptr) { for (const auto& features : *curr_features_ptr) {
@ -749,6 +772,7 @@ void ImageProcessor::addNewFeatures() {
mask(row_range, col_range) = 0; mask(row_range, col_range) = 0;
} }
} }
// Detect new features. // Detect new features.
vector<KeyPoint> new_features(0); vector<KeyPoint> new_features(0);
detector_ptr->detect(curr_img, new_features, mask); detector_ptr->detect(curr_img, new_features, mask);
@ -763,6 +787,7 @@ void ImageProcessor::addNewFeatures() {
new_feature_sieve[ new_feature_sieve[
row*processor_config.grid_col+col].push_back(feature); row*processor_config.grid_col+col].push_back(feature);
} }
new_features.clear(); new_features.clear();
for (auto& item : new_feature_sieve) { for (auto& item : new_feature_sieve) {
if (item.size() > processor_config.grid_max_feature_num) { if (item.size() > processor_config.grid_max_feature_num) {
@ -775,6 +800,7 @@ void ImageProcessor::addNewFeatures() {
} }
int detected_new_features = new_features.size(); int detected_new_features = new_features.size();
// Find the stereo matched points for the newly // Find the stereo matched points for the newly
// detected features. // detected features.
vector<cv::Point2f> cam0_points(new_features.size()); vector<cv::Point2f> cam0_points(new_features.size());
@ -802,6 +828,7 @@ void ImageProcessor::addNewFeatures() {
static_cast<double>(detected_new_features) < 0.1) static_cast<double>(detected_new_features) < 0.1)
ROS_WARN("Images at [%f] seems unsynced...", ROS_WARN("Images at [%f] seems unsynced...",
cam0_curr_img_ptr->header.stamp.toSec()); cam0_curr_img_ptr->header.stamp.toSec());
// Group the features into grids // Group the features into grids
GridFeatures grid_new_features; GridFeatures grid_new_features;
for (int code = 0; code < for (int code = 0; code <
@ -823,6 +850,7 @@ void ImageProcessor::addNewFeatures() {
new_feature.cam1_point = cam1_point; new_feature.cam1_point = cam1_point;
grid_new_features[code].push_back(new_feature); grid_new_features[code].push_back(new_feature);
} }
// Sort the new features in each grid based on its response. // Sort the new features in each grid based on its response.
for (auto& item : grid_new_features) for (auto& item : grid_new_features)
std::sort(item.second.begin(), item.second.end(), std::sort(item.second.begin(), item.second.end(),
@ -872,6 +900,73 @@ void ImageProcessor::pruneGridFeatures() {
return; return;
} }
void ImageProcessor::undistortPoints(
const vector<cv::Point2f>& pts_in,
const cv::Vec4d& intrinsics,
const string& distortion_model,
const cv::Vec4d& distortion_coeffs,
vector<cv::Point2f>& pts_out,
const cv::Matx33d &rectification_matrix,
const cv::Vec4d &new_intrinsics) {
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);
}
return;
}
vector<cv::Point2f> ImageProcessor::distortPoints(
const vector<cv::Point2f>& pts_in,
const cv::Vec4d& intrinsics,
const string& distortion_model,
const cv::Vec4d& distortion_coeffs) {
const cv::Matx33d K(intrinsics[0], 0.0, intrinsics[2],
0.0, intrinsics[1], intrinsics[3],
0.0, 0.0, 1.0);
vector<cv::Point2f> pts_out;
if (distortion_model == "radtan") {
vector<cv::Point3f> homogenous_pts;
cv::convertPointsToHomogeneous(pts_in, homogenous_pts);
cv::projectPoints(homogenous_pts, cv::Vec3d::zeros(), cv::Vec3d::zeros(), K,
distortion_coeffs, pts_out);
} else if (distortion_model == "equidistant") {
cv::fisheye::distortPoints(pts_in, pts_out, K, distortion_coeffs);
} else {
ROS_WARN_ONCE("The model %s is unrecognized, using radtan instead...",
distortion_model.c_str());
vector<cv::Point3f> homogenous_pts;
cv::convertPointsToHomogeneous(pts_in, homogenous_pts);
cv::projectPoints(homogenous_pts, cv::Vec3d::zeros(), cv::Vec3d::zeros(), K,
distortion_coeffs, pts_out);
}
return pts_out;
}
void ImageProcessor::integrateImuData( void ImageProcessor::integrateImuData(
Matx33f& cam0_R_p_c, Matx33f& cam1_R_p_c) { Matx33f& cam0_R_p_c, Matx33f& cam1_R_p_c) {
// Find the start and the end limit within the imu msg buffer. // Find the start and the end limit within the imu msg buffer.
@ -923,6 +1018,7 @@ void ImageProcessor::integrateImuData(
void ImageProcessor::rescalePoints( void ImageProcessor::rescalePoints(
vector<Point2f>& pts1, vector<Point2f>& pts2, vector<Point2f>& pts1, vector<Point2f>& pts2,
float& scaling_factor) { float& scaling_factor) {
scaling_factor = 0.0f; scaling_factor = 0.0f;
for (int i = 0; i < pts1.size(); ++i) { for (int i = 0; i < pts1.size(); ++i) {
@ -952,7 +1048,7 @@ void ImageProcessor::twoPointRansac(
// Check the size of input point size. // Check the size of input point size.
if (pts1.size() != pts2.size()) if (pts1.size() != pts2.size())
ROS_ERROR("Sets of different size (%lu and %lu) are used...", ROS_ERROR("Sets of different size (%i and %i) are used...",
pts1.size(), pts2.size()); pts1.size(), pts2.size());
double norm_pixel_unit = 2.0 / (intrinsics[0]+intrinsics[1]); double norm_pixel_unit = 2.0 / (intrinsics[0]+intrinsics[1]);
@ -966,10 +1062,10 @@ void ImageProcessor::twoPointRansac(
// Undistort all the points. // Undistort all the points.
vector<Point2f> pts1_undistorted(pts1.size()); vector<Point2f> pts1_undistorted(pts1.size());
vector<Point2f> pts2_undistorted(pts2.size()); vector<Point2f> pts2_undistorted(pts2.size());
image_handler::undistortPoints( undistortPoints(
pts1, intrinsics, distortion_model, pts1, intrinsics, distortion_model,
distortion_coeffs, pts1_undistorted); distortion_coeffs, pts1_undistorted);
image_handler::undistortPoints( undistortPoints(
pts2, intrinsics, distortion_model, pts2, intrinsics, distortion_model,
distortion_coeffs, pts2_undistorted); distortion_coeffs, pts2_undistorted);
@ -1187,6 +1283,7 @@ void ImageProcessor::twoPointRansac(
} }
void ImageProcessor::publish() { void ImageProcessor::publish() {
// Publish features. // Publish features.
CameraMeasurementPtr feature_msg_ptr(new CameraMeasurement); CameraMeasurementPtr feature_msg_ptr(new CameraMeasurement);
feature_msg_ptr->header.stamp = cam0_curr_img_ptr->header.stamp; feature_msg_ptr->header.stamp = cam0_curr_img_ptr->header.stamp;
@ -1206,12 +1303,12 @@ void ImageProcessor::publish() {
vector<Point2f> curr_cam0_points_undistorted(0); vector<Point2f> curr_cam0_points_undistorted(0);
vector<Point2f> curr_cam1_points_undistorted(0); vector<Point2f> curr_cam1_points_undistorted(0);
image_handler::undistortPoints( undistortPoints(
curr_cam0_points, cam0.intrinsics, cam0.distortion_model, curr_cam0_points, cam0_intrinsics, cam0_distortion_model,
cam0.distortion_coeffs, curr_cam0_points_undistorted); cam0_distortion_coeffs, curr_cam0_points_undistorted);
image_handler::undistortPoints( undistortPoints(
curr_cam1_points, cam1.intrinsics, cam1.distortion_model, curr_cam1_points, cam1_intrinsics, cam1_distortion_model,
cam1.distortion_coeffs, curr_cam1_points_undistorted); cam1_distortion_coeffs, curr_cam1_points_undistorted);
for (int i = 0; i < curr_ids.size(); ++i) { for (int i = 0; i < curr_ids.size(); ++i) {
feature_msg_ptr->features.push_back(FeatureMeasurement()); feature_msg_ptr->features.push_back(FeatureMeasurement());

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@ -1,75 +0,0 @@
#!/usr/bin/env python
from __future__ import print_function
import sys
import rospy
import cv2
from std_msgs.msg import String
from sensor_msgs.msg import Image
from cv_bridge import CvBridge, CvBridgeError
class image_converter:
def __init__(self):
self.image0_pub = rospy.Publisher("/cam0/new_image_raw",Image, queue_size=10)
self.image1_pub = rospy.Publisher("/cam1/new_image_raw",Image, queue_size=10)
self.bridge = CvBridge()
self.image0_sub = rospy.Subscriber("/cam0/image_raw",Image,self.callback_cam0)
self.image1_sub = rospy.Subscriber("/cam1/image_raw",Image,self.callback_cam1)
def callback_cam0(self,data):
try:
cv_image = self.bridge.imgmsg_to_cv2(data, "bgr8")
except CvBridgeError as e:
print(e)
imgScale = 0.25
newX,newY = cv_image.shape[1]*imgScale, cv_image.shape[0]*imgScale
newimg = cv2.resize(cv_image,(int(newX),int(newY)))
newpub = self.bridge.cv2_to_imgmsg(newimg, "bgr8")
newdata = data
newdata.height = newpub.height
newdata.width = newpub.width
newdata.step = newpub.step
newdata.data = newpub.data
try:
self.image0_pub.publish(newdata)
except CvBridgeError as e:
print(e)
def callback_cam1(self,data):
try:
cv_image = self.bridge.imgmsg_to_cv2(data, "bgr8")
except CvBridgeError as e:
print(e)
imgScale = 0.25
newX,newY = cv_image.shape[1]*imgScale, cv_image.shape[0]*imgScale
newimg = cv2.resize(cv_image,(int(newX),int(newY)))
newpub = self.bridge.cv2_to_imgmsg(newimg, "bgr8")
newdata = data
newdata.height = newpub.height
newdata.width = newpub.width
newdata.step = newpub.step
newdata.data = newpub.data
try:
self.image1_pub.publish(newdata)
except CvBridgeError as e:
print(e)
def main(args):
ic = image_converter()
rospy.init_node('image_converter', anonymous=True)
try:
rospy.spin()
except KeyboardInterrupt:
print("Shutting down")
cv2.destroyAllWindows()
if __name__ == '__main__':
main(sys.argv)

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@ -11,6 +11,20 @@
namespace msckf_vio { namespace msckf_vio {
namespace utils { namespace utils {
void download(const cv::cuda::GpuMat& d_mat, std::vector<cv::Point2f>& vec)
{
vec.resize(d_mat.cols);
cv::Mat mat(1, d_mat.cols, CV_32FC2, (void*)&vec[0]);
d_mat.download(mat);
}
void download(const cv::cuda::GpuMat& d_mat, std::vector<uchar>& vec)
{
vec.resize(d_mat.cols);
cv::Mat mat(1, d_mat.cols, CV_8UC1, (void*)&vec[0]);
d_mat.download(mat);
}
Eigen::Isometry3d getTransformEigen(const ros::NodeHandle &nh, Eigen::Isometry3d getTransformEigen(const ros::NodeHandle &nh,
const std::string &field) { const std::string &field) {
Eigen::Isometry3d T; Eigen::Isometry3d T;