27 Commits

Author SHA1 Message Date
6e151510cf calculate average of jacobis and residual to reduce to single point in caclualtion - does not produce desired result 2019-05-29 10:38:40 +02:00
8bebf99c37 corrected pixel distance calcualtion 2019-05-24 09:49:47 +02:00
82cd2c6771 fixed Irradiance jacobain calculation, now division by pixel distance 2019-05-23 18:34:57 +02:00
0be7047928 cache 2019-05-23 09:17:05 +02:00
2f130685c8 removed merge conflicts 2 2019-05-22 11:34:26 +02:00
8ff0e9d816 removed merge conflicts 2019-05-22 11:34:00 +02:00
976108bffe changed anchor feature position calculation 2019-05-22 11:24:53 +02:00
2aef2089aa added undistort point 2019-05-21 14:26:26 +02:00
0f96c916f1 minor output changes, added arrows for gradient and residual visualization 2019-05-21 13:34:58 +02:00
05d277c4f4 reformulated irradiance to be: irradiance arround measured feature - irradiance at projection 2019-05-17 15:00:56 +02:00
9c7f67d2fd minor print changes 2019-05-16 13:56:37 +02:00
2ee7c248c1 alterations at nullspaceing, jakobi changes 2019-05-14 16:03:24 +02:00
44de215518 lots of additional debugging tools implemented to check parts of the algorithm. still no good 2019-05-10 17:19:29 +02:00
ad2f464716 added 3d visualization and stepping through bag file - minor edits in jakobi 2019-05-09 12:14:12 +02:00
53b26f7613 minor changes to visualization, jakobi tests 2019-05-03 16:42:27 +02:00
ee40dff740 added minor visualization changes 2019-05-02 17:02:44 +02:00
acbcf79417 fixed some typos in jacobian 2019-04-30 18:25:05 +02:00
cf40ce8afb added visualization with a ros flag, which shows feature with projection and residual (the features apparent movement) 2019-04-30 17:02:22 +02:00
750d8ecfb1 sublime folding changes 2019-04-26 14:42:31 +02:00
e3ac604dbf changed structure for sublime folding 2019-04-26 10:45:10 +02:00
e8489dbd06 removed resizing not correcting for photometric info, added N as global variable 2019-04-26 09:44:19 +02:00
e2e936ff01 fixed non 0 filling of new state covariance 2019-04-25 19:13:22 +02:00
de07296d31 added minor changes to nullspace 2019-04-25 13:44:21 +02:00
6ba26d782d added flag to switch to original, using right null space matrix for calculation now and existing eigen function, gating restult still way to high 2019-04-25 11:16:44 +02:00
821d9d6f71 added debug launch file, added state augmentation, added jakobi concat; resulting jakobis do not pass gating test 2019-04-24 19:36:38 +02:00
1ffc4fb37f Jakobi Calculation done 2019-04-24 15:30:25 +02:00
5958adb57c added jakobi x calculation, y calculation (of photometric update) still missing 2019-04-23 19:16:46 +02:00
10 changed files with 1567 additions and 296 deletions

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@ -24,6 +24,7 @@ find_package(catkin REQUIRED COMPONENTS
pcl_conversions
pcl_ros
std_srvs
visualization_msgs
)
## System dependencies are found with CMake's conventions

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@ -15,6 +15,10 @@
#include <Eigen/Dense>
#include <Eigen/Geometry>
#include <Eigen/StdVector>
#include <math.h>
#include <visualization_msgs/Marker.h>
#include <visualization_msgs/MarkerArray.h>
#include <geometry_msgs/Point.h>
#include "image_handler.h"
@ -22,6 +26,7 @@
#include "imu_state.h"
#include "cam_state.h"
namespace msckf_vio {
/*
@ -116,6 +121,15 @@ struct Feature {
inline bool checkMotion(
const CamStateServer& cam_states) const;
/*
* @brief AnchorPixelToPosition projects an undistorted point in the
* anchor frame back into the real world using the rho calculated
* based on featur position
*/
inline Eigen::Vector3d AnchorPixelToPosition(cv::Point2f in_p, const CameraCalibration& cam);
/*
* @brief InitializeAnchor generates the NxN patch around the
* feature in the Anchor image
@ -126,7 +140,7 @@ struct Feature {
*/
bool initializeAnchor(
const CameraCalibration& cam);
const CameraCalibration& cam, int N);
/*
@ -143,6 +157,14 @@ struct Feature {
inline bool initializePosition(
const CamStateServer& cam_states);
cv::Point2f pixelDistanceAt(
const CAMState& cam_state,
const StateIDType& cam_state_id,
const CameraCalibration& cam,
Eigen::Vector3d& in_p) const;
/*
* @brief project PositionToCamera Takes a 3d position in a world frame
* and projects it into the passed camera frame using pinhole projection
@ -165,20 +187,31 @@ struct Feature {
const CAMState& cam_state,
const StateIDType& cam_state_id,
CameraCalibration& cam0,
std::vector<float>& anchorPatch_estimate) const;
std::vector<double>& anchorPatch_estimate,
IlluminationParameter& estimatedIllumination) const;
bool FrameIrradiance(
bool MarkerGeneration(
ros::Publisher& marker_pub,
const CamStateServer& cam_states) const;
bool VisualizePatch(
const CAMState& cam_state,
const StateIDType& cam_state_id,
CameraCalibration& cam0,
std::vector<float>& anchorPatch_measurement) const;
const std::vector<double> photo_r,
std::stringstream& ss) const;
/*
* @brief projectPixelToPosition uses the calcualted pixels
* of the anchor patch to generate 3D positions of all of em
/* @brief takes a pure pixel position (1m from image)
* converts to actual pixel value and returns patch irradiance
* around this pixel
*/
inline Eigen::Vector3d projectPixelToPosition(cv::Point2f in_p,
const CameraCalibration& cam);
void PatchAroundPurePixel(cv::Point2f p,
int N,
const CameraCalibration& cam,
const StateIDType& cam_state_id,
std::vector<float>& return_i) const;
/*
* @brief Irradiance returns irradiance value of a pixel
@ -203,8 +236,10 @@ inline Eigen::Vector3d projectPixelToPosition(cv::Point2f in_p,
// NxN Patch of Anchor Image
std::vector<double> anchorPatch;
std::vector<cv::Point2f> anchorPatch_ideal;
std::vector<cv::Point2f> anchorPatch_real;
// Position of NxN Patch in 3D space
// Position of NxN Patch in 3D space in anchor camera frame
std::vector<Eigen::Vector3d> anchorPatch_3d;
// Anchor Isometry
@ -239,7 +274,8 @@ typedef std::map<FeatureIDType, Feature, std::less<int>,
void Feature::cost(const Eigen::Isometry3d& T_c0_ci,
const Eigen::Vector3d& x, const Eigen::Vector2d& z,
double& e) const {
double& e) const
{
// Compute hi1, hi2, and hi3 as Equation (37).
const double& alpha = x(0);
const double& beta = x(1);
@ -262,7 +298,8 @@ void Feature::cost(const Eigen::Isometry3d& T_c0_ci,
void Feature::jacobian(const Eigen::Isometry3d& T_c0_ci,
const Eigen::Vector3d& x, const Eigen::Vector2d& z,
Eigen::Matrix<double, 2, 3>& J, Eigen::Vector2d& r,
double& w) const {
double& w) const
{
// Compute hi1, hi2, and hi3 as Equation (37).
const double& alpha = x(0);
@ -299,7 +336,8 @@ void Feature::jacobian(const Eigen::Isometry3d& T_c0_ci,
void Feature::generateInitialGuess(
const Eigen::Isometry3d& T_c1_c2, const Eigen::Vector2d& z1,
const Eigen::Vector2d& z2, Eigen::Vector3d& p) const {
const Eigen::Vector2d& z2, Eigen::Vector3d& p) const
{
// Construct a least square problem to solve the depth.
Eigen::Vector3d m = T_c1_c2.linear() * Eigen::Vector3d(z1(0), z1(1), 1.0);
@ -319,8 +357,8 @@ void Feature::generateInitialGuess(
return;
}
bool Feature::checkMotion(
const CamStateServer& cam_states) const {
bool Feature::checkMotion(const CamStateServer& cam_states) const
{
const StateIDType& first_cam_id = observations.begin()->first;
const StateIDType& last_cam_id = (--observations.end())->first;
@ -366,7 +404,8 @@ bool Feature::estimate_FrameIrradiance(
const CAMState& cam_state,
const StateIDType& cam_state_id,
CameraCalibration& cam0,
std::vector<float>& anchorPatch_estimate) const
std::vector<double>& anchorPatch_estimate,
IlluminationParameter& estimated_illumination) const
{
// get irradiance of patch in anchor frame
// subtract estimated b and divide by a of anchor frame
@ -374,77 +413,404 @@ bool Feature::estimate_FrameIrradiance(
auto anchor = observations.begin();
if(cam0.moving_window.find(anchor->first) == cam0.moving_window.end())
{
std::cout << "anchor not in buffer anymore!" << std::endl;
return false;
}
double anchorExposureTime_ms = cam0.moving_window.find(anchor->first)->second.exposureTime_ms;
double frameExposureTime_ms = cam0.moving_window.find(cam_state_id)->second.exposureTime_ms;
double a_A = anchorExposureTime_ms;
double b_A = 0;
double a_l =frameExposureTime_ms;
double a_l = frameExposureTime_ms;
double b_l = 0;
estimated_illumination.frame_gain = a_l;
estimated_illumination.frame_bias = b_l;
estimated_illumination.feature_gain = 1;
estimated_illumination.feature_bias = 0;
//printf("frames: %lld, %lld\n", anchor->first, cam_state_id);
//printf("exposure: %f, %f\n", a_A, a_l);
for (double anchorPixel : anchorPatch)
{
float irradiance = ((anchorPixel - b_A) / a_A ) * a_l - b_l;
float irradiance = (anchorPixel - b_A) / a_A ;
anchorPatch_estimate.push_back(irradiance);
}
}
bool Feature::FrameIrradiance(
// generates markers for every camera position/observation
// and estimated feature/path position
bool Feature::MarkerGeneration(
ros::Publisher& marker_pub,
const CamStateServer& cam_states) const
{
visualization_msgs::MarkerArray ma;
// add all camera states used for estimation
int count = 0;
for(auto observation : observations)
{
visualization_msgs::Marker marker;
marker.header.frame_id = "world";
marker.header.stamp = ros::Time::now();
marker.ns = "cameras";
marker.id = count++;
marker.type = visualization_msgs::Marker::ARROW;
marker.action = visualization_msgs::Marker::ADD;
marker.pose.position.x = cam_states.find(observation.first)->second.position(0);
marker.pose.position.y = cam_states.find(observation.first)->second.position(1);
marker.pose.position.z = cam_states.find(observation.first)->second.position(2);
// rotate form x to z axis
Eigen::Vector4d q = quaternionMultiplication(Eigen::Vector4d(0, -0.707, 0, 0.707), cam_states.find(observation.first)->second.orientation);
marker.pose.orientation.x = q(0);
marker.pose.orientation.y = q(1);
marker.pose.orientation.z = q(2);
marker.pose.orientation.w = q(3);
marker.scale.x = 0.15;
marker.scale.y = 0.05;
marker.scale.z = 0.05;
if(count == 1)
{
marker.color.r = 0.0f;
marker.color.g = 0.0f;
marker.color.b = 1.0f;
}
else
{
marker.color.r = 0.0f;
marker.color.g = 1.0f;
marker.color.b = 0.0f;
}
marker.color.a = 1.0;
marker.lifetime = ros::Duration(0);
ma.markers.push_back(marker);
}
// 'delete' any existing cameras (make invisible)
for(int i = count; i < 20; i++)
{
visualization_msgs::Marker marker;
marker.header.frame_id = "world";
marker.header.stamp = ros::Time::now();
marker.ns = "cameras";
marker.id = i;
marker.type = visualization_msgs::Marker::ARROW;
marker.action = visualization_msgs::Marker::ADD;
marker.pose.orientation.w = 1;
marker.color.a = 0.0;
marker.lifetime = ros::Duration(1);
ma.markers.push_back(marker);
}
//generate feature patch points position
visualization_msgs::Marker marker;
marker.header.frame_id = "world";
marker.header.stamp = ros::Time::now();
marker.ns = "patch";
marker.id = 0;
marker.type = visualization_msgs::Marker::POINTS;
marker.action = visualization_msgs::Marker::ADD;
marker.pose.orientation.w = 1;
marker.scale.x = 0.02;
marker.scale.y = 0.02;
marker.color.r = 1.0f;
marker.color.g = 0.0f;
marker.color.b = 0.0f;
marker.color.a = 1.0;
for(auto point : anchorPatch_3d)
{
geometry_msgs::Point p;
p.x = point(0);
p.y = point(1);
p.z = point(2);
marker.points.push_back(p);
}
ma.markers.push_back(marker);
marker_pub.publish(ma);
}
bool Feature::VisualizePatch(
const CAMState& cam_state,
const StateIDType& cam_state_id,
CameraCalibration& cam0,
std::vector<float>& anchorPatch_measurement) const
const std::vector<double> photo_r,
std::stringstream& ss) const
{
// visu - feature
/*cv::Mat current_image = cam0.moving_window.find(cam_state_id)->second.image;
cv::Mat dottedFrame(current_image.size(), CV_8UC3);
cv::cvtColor(current_image, dottedFrame, CV_GRAY2RGB);
*/
double rescale = 1;
// project every point in anchorPatch_3d.
for (auto point : anchorPatch_3d)
//visu - anchor
auto anchor = observations.begin();
cv::Mat anchorImage = cam0.moving_window.find(anchor->first)->second.image;
cv::Mat dottedFrame(anchorImage.size(), CV_8UC3);
cv::cvtColor(anchorImage, dottedFrame, CV_GRAY2RGB);
// visualize the true anchor points (the surrounding of the original measurements)
for(auto point : anchorPatch_real)
{
cv::Point2f p_in_c0 = projectPositionToCamera(cam_state, cam_state_id, cam0, point);
// visu - feature
/*cv::Point xs(p_in_c0.x, p_in_c0.y);
cv::Point xs(point.x, point.y);
cv::Point ys(point.x, point.y);
cv::rectangle(dottedFrame, xs, ys, cv::Scalar(0,255,255));
}
cam0.featureVisu = dottedFrame.clone();
// visu - feature
cv::Mat current_image = cam0.moving_window.find(cam_state_id)->second.image;
cv::cvtColor(current_image, dottedFrame, CV_GRAY2RGB);
// set position in frame
// save irradiance of projection
std::vector<double> projectionPatch;
for(auto point : anchorPatch_3d)
{
cv::Point2f p_in_c0 = projectPositionToCamera(cam_state, cam_state_id, cam0, point);
projectionPatch.push_back(PixelIrradiance(p_in_c0, current_image));
// visu - feature
cv::Point xs(p_in_c0.x, p_in_c0.y);
cv::Point ys(p_in_c0.x, p_in_c0.y);
cv::rectangle(dottedFrame, xs, ys, cv::Scalar(0,255,0));
*/
float irradiance = PixelIrradiance(p_in_c0, cam0.moving_window.find(cam_state_id)->second.image);
anchorPatch_measurement.push_back(irradiance);
// testing
//if(cam_state_id == observations.begin()->first)
//if(count++ == 4)
//printf("dist:\n \tpos: %f, %f\n\ttrue pos: %f, %f\n\n", p_in_c0.x, p_in_c0.y, anchor_center_pos.x, anchor_center_pos.y);
}
cv::hconcat(cam0.featureVisu, dottedFrame, cam0.featureVisu);
// patches visualization
int N = sqrt(anchorPatch_3d.size());
int scale = 30;
cv::Mat irradianceFrame(anchorImage.size(), CV_8UC3, cv::Scalar(255, 240, 255));
cv::resize(irradianceFrame, irradianceFrame, cv::Size(), rescale, rescale);
// irradiance grid anchor
std::stringstream namer;
namer << "anchor";
cv::putText(irradianceFrame, namer.str() , cvPoint(30, 25),
cv::FONT_HERSHEY_COMPLEX_SMALL, 0.8, cvScalar(0,0,0), 1, CV_AA);
for(int i = 0; i<N; i++)
for(int j = 0; j<N; j++)
cv::rectangle(irradianceFrame,
cv::Point(30+scale*(i+1), 30+scale*j),
cv::Point(30+scale*i, 30+scale*(j+1)),
cv::Scalar(anchorPatch[i*N+j]*255, anchorPatch[i*N+j]*255, anchorPatch[i*N+j]*255),
CV_FILLED);
// irradiance grid projection
namer.str(std::string());
namer << "projection";
cv::putText(irradianceFrame, namer.str(), cvPoint(30, 45+scale*N),
cv::FONT_HERSHEY_COMPLEX_SMALL, 0.8, cvScalar(0,0,0), 1, CV_AA);
for(int i = 0; i<N; i++)
for(int j = 0; j<N ; j++)
cv::rectangle(irradianceFrame,
cv::Point(30+scale*(i+1), 50+scale*(N+j)),
cv::Point(30+scale*(i), 50+scale*(N+j+1)),
cv::Scalar(projectionPatch[i*N+j]*255, projectionPatch[i*N+j]*255, projectionPatch[i*N+j]*255),
CV_FILLED);
// true irradiance at feature
// get current observation
namer.str(std::string());
namer << "feature";
cv::putText(irradianceFrame, namer.str() , cvPoint(30, 65+scale*2*N),
cv::FONT_HERSHEY_COMPLEX_SMALL, 0.8, cvScalar(0,0,0), 1, CV_AA);
cv::Point2f p_f(observations.find(cam_state_id)->second(0),observations.find(cam_state_id)->second(1));
// move to real pixels
p_f = image_handler::distortPoint(p_f, cam0.intrinsics, cam0.distortion_model, cam0.distortion_coeffs);
for(int i = 0; i<N; i++)
{
for(int j = 0; j<N ; j++)
{
float irr = PixelIrradiance(cv::Point2f(p_f.x + (i-(N-1)/2), p_f.y + (j-(N-1)/2)), current_image);
cv::rectangle(irradianceFrame,
cv::Point(30+scale*(i+1), 70+scale*(2*N+j)),
cv::Point(30+scale*(i), 70+scale*(2*N+j+1)),
cv::Scalar(irr*255, irr*255, irr*255),
CV_FILLED);
}
}
// visu - feature
//cv::resize(dottedFrame, dottedFrame, cv::Size(dottedFrame.cols*0.2, dottedFrame.rows*0.2));
/*if(cam0.featureVisu.empty())
cam0.featureVisu = dottedFrame.clone();
else
cv::hconcat(cam0.featureVisu, dottedFrame, cam0.featureVisu);
// residual grid projection, positive - red, negative - blue colored
namer.str(std::string());
namer << "residual";
cv::putText(irradianceFrame, namer.str() , cvPoint(30+scale*N, scale*N/2-5),
cv::FONT_HERSHEY_COMPLEX_SMALL, 0.8, cvScalar(0,0,0), 1, CV_AA);
for(int i = 0; i<N; i++)
for(int j = 0; j<N; j++)
if(photo_r[i*N+j]>0)
cv::rectangle(irradianceFrame,
cv::Point(40+scale*(N+i+1), 15+scale*(N/2+j)),
cv::Point(40+scale*(N+i), 15+scale*(N/2+j+1)),
cv::Scalar(255 - photo_r[i*N+j]*255, 255 - photo_r[i*N+j]*255, 255),
CV_FILLED);
else
cv::rectangle(irradianceFrame,
cv::Point(40+scale*(N+i+1), 15+scale*(N/2+j)),
cv::Point(40+scale*(N+i), 15+scale*(N/2+j+1)),
cv::Scalar(255, 255 + photo_r[i*N+j]*255, 255 + photo_r[i*N+j]*255),
CV_FILLED);
// gradient arrow
/*
cv::arrowedLine(irradianceFrame,
cv::Point(30+scale*(N/2 +0.5), 50+scale*(N+(N/2)+0.5)),
cv::Point(30+scale*(N/2+0.5)+scale*gradientVector.x, 50+scale*(N+(N/2)+0.5)+scale*gradientVector.y),
cv::Scalar(100, 0, 255),
1);
// residual gradient direction
cv::arrowedLine(irradianceFrame,
cv::Point(40+scale*(N+N/2+0.5), 15+scale*((N-0.5))),
cv::Point(40+scale*(N+N/2+0.5)+scale*residualVector.x, 15+scale*(N-0.5)+scale*residualVector.y),
cv::Scalar(0, 255, 175),
3);
*/
cv::hconcat(cam0.featureVisu, irradianceFrame, cam0.featureVisu);
// visualize position of used observations and resulting feature position
/*
cv::Mat positionFrame(anchorImage.size(), CV_8UC3, cv::Scalar(255, 240, 255));
cv::resize(positionFrame, positionFrame, cv::Size(), rescale, rescale);
// draw world zero
cv::line(positionFrame,
cv::Point(20,20),
cv::Point(20,30),
cv::Scalar(0,0,255),
CV_FILLED);
cv::line(positionFrame,
cv::Point(20,20),
cv::Point(30,20),
cv::Scalar(255,0,0),
CV_FILLED);
// for every observation, get cam state
for(auto obs : observations)
{
cv::line(positionFrame,
cv::Point(20,20),
cv::Point(30,20),
cv::Scalar(255,0,0),
CV_FILLED);
}
// draw, x y position and arrow with direction - write z next to it
cv::resize(cam0.featureVisu, cam0.featureVisu, cv::Size(), rescale, rescale);
cv::hconcat(cam0.featureVisu, positionFrame, cam0.featureVisu);
*/
// write feature position
std::stringstream pos_s;
pos_s << "u: " << observations.begin()->second(0) << " v: " << observations.begin()->second(1);
cv::putText(cam0.featureVisu, ss.str() , cvPoint(anchorImage.rows + 100, anchorImage.cols - 30),
cv::FONT_HERSHEY_COMPLEX_SMALL, 0.8, cvScalar(200,200,250), 1, CV_AA);
// create line?
//save image
std::stringstream loc;
// loc << "/home/raphael/dev/MSCKF_ws/img/feature_" << std::to_string(ros::Time::now().toSec()) << ".jpg";
//cv::imwrite(loc.str(), cam0.featureVisu);
cv::imshow("patch", cam0.featureVisu);
cvWaitKey(0);
}
void Feature::PatchAroundPurePixel(cv::Point2f p,
int N,
const CameraCalibration& cam,
const StateIDType& cam_state_id,
std::vector<float>& return_i) const
{
int n = (int)(N-1)/2;
cv::Mat image = cam.moving_window.find(cam_state_id)->second.image;
cv::Point2f img_p = image_handler::distortPoint(p,
cam.intrinsics,
cam.distortion_model,
cam.distortion_coeffs);
for(double u_run = -n; u_run <= n; u_run++)
for(double v_run = -n; v_run <= n; v_run++)
return_i.push_back(PixelIrradiance(cv::Point2f(img_p.x+u_run, img_p.y+v_run), image));
}
float Feature::PixelIrradiance(cv::Point2f pose, cv::Mat image) const
{
return (float)image.at<uint8_t>(pose.x, pose.y);
return ((float)image.at<uint8_t>(pose.y, pose.x))/255;
}
cv::Point2f Feature::pixelDistanceAt(
const CAMState& cam_state,
const StateIDType& cam_state_id,
const CameraCalibration& cam,
Eigen::Vector3d& in_p) const
{
cv::Point2f cam_p = projectPositionToCamera(cam_state, cam_state_id, cam, in_p);
// create vector of patch in pixel plane
std::vector<cv::Point2f> surroundingPoints;
surroundingPoints.push_back(cv::Point2f(cam_p.x+1, cam_p.y));
surroundingPoints.push_back(cv::Point2f(cam_p.x-1, cam_p.y));
surroundingPoints.push_back(cv::Point2f(cam_p.x, cam_p.y+1));
surroundingPoints.push_back(cv::Point2f(cam_p.x, cam_p.y-1));
std::vector<cv::Point2f> pure;
image_handler::undistortPoints(surroundingPoints,
cam.intrinsics,
cam.distortion_model,
cam.distortion_coeffs,
pure);
// returns the absolute pixel distance at pixels one metres away
cv::Point2f distance(fabs(pure[0].x - pure[1].x), fabs(pure[2].y - pure[3].y));
return distance;
}
cv::Point2f Feature::projectPositionToCamera(
const CAMState& cam_state,
const StateIDType& cam_state_id,
@ -477,27 +843,23 @@ cv::Point2f Feature::projectPositionToCamera(
return my_p;
}
Eigen::Vector3d Feature::projectPixelToPosition(cv::Point2f in_p,
const CameraCalibration& cam)
Eigen::Vector3d Feature::AnchorPixelToPosition(cv::Point2f in_p, const CameraCalibration& cam)
{
// use undistorted position of point of interest
// project it back into 3D space using pinhole model
// save resulting NxN positions for this feature
Eigen::Vector3d PositionInCamera(in_p.x/anchor_rho, in_p.y/anchor_rho, 1/anchor_rho);
Eigen::Vector3d PositionInWorld= T_anchor_w.linear()*PositionInCamera + T_anchor_w.translation();
Eigen::Vector3d PositionInWorld = T_anchor_w.linear()*PositionInCamera + T_anchor_w.translation();
return PositionInWorld;
//printf("%f, %f, %f\n",PositionInWorld[0], PositionInWorld[1], PositionInWorld[2]);
}
//@test center projection must always be initial feature projection
bool Feature::initializeAnchor(
const CameraCalibration& cam)
bool Feature::initializeAnchor(const CameraCalibration& cam, int N)
{
//initialize patch Size
//TODO make N size a ros parameter
int N = 3;
int n = (int)(N-1)/2;
auto anchor = observations.begin();
@ -516,52 +878,45 @@ bool Feature::initializeAnchor(
int count = 0;
// get feature in undistorted pixel space
// this only reverts from 'pure' space into undistorted pixel space using camera matrix
cv::Point2f und_pix_p = image_handler::distortPoint(cv::Point2f(u, v),
cam.intrinsics,
cam.distortion_model,
0);
cam.distortion_coeffs);
// create vector of patch in pixel plane
std::vector<cv::Point2f> und_pix_v;
for(double u_run = -n; u_run <= n; u_run++)
for(double v_run = -n; v_run <= n; v_run++)
und_pix_v.push_back(cv::Point2f(und_pix_p.x-u_run, und_pix_p.y-v_run));
anchorPatch_real.push_back(cv::Point2f(und_pix_p.x+u_run, und_pix_p.y+v_run));
//create undistorted pure points
std::vector<cv::Point2f> und_v;
image_handler::undistortPoints(und_pix_v,
image_handler::undistortPoints(anchorPatch_real,
cam.intrinsics,
cam.distortion_model,
0,
und_v);
//create distorted pixel points
std::vector<cv::Point2f> vec = image_handler::distortPoints(und_v,
cam.intrinsics,
cam.distortion_model,
cam.distortion_coeffs);
cam.distortion_coeffs,
anchorPatch_ideal);
// save anchor position for later visualisaztion
anchor_center_pos = vec[4];
for(auto point : vec)
{
anchor_center_pos = anchorPatch_real[(N*N-1)/2];
// save true pixel Patch position
for(auto point : anchorPatch_real)
if(point.x - n < 0 || point.x + n >= cam.resolution(0) || point.y - n < 0 || point.y + n >= cam.resolution(1))
return false;
}
for(auto point : vec)
anchorPatch.push_back((double)anchorImage.at<uint8_t>((int)point.x,(int)point.y));
// project patch pixel to 3D space
for(auto point : und_v)
anchorPatch_3d.push_back(projectPixelToPosition(point, cam));
for(auto point : anchorPatch_real)
anchorPatch.push_back(PixelIrradiance(point, anchorImage));
// project patch pixel to 3D space in camera coordinate system
for(auto point : anchorPatch_ideal)
anchorPatch_3d.push_back(AnchorPixelToPosition(point, cam));
is_anchored = true;
return true;
}
bool Feature::initializePosition(
const CamStateServer& cam_states) {
/*
bool Feature::initializeRho(const CamStateServer& cam_states) {
// Organize camera poses and feature observations properly.
std::vector<Eigen::Isometry3d,
@ -710,6 +1065,157 @@ bool Feature::initializePosition(
return is_valid_solution;
}
*/
bool Feature::initializePosition(const CamStateServer& cam_states) {
// Organize camera poses and feature observations properly.
std::vector<Eigen::Isometry3d,
Eigen::aligned_allocator<Eigen::Isometry3d> > cam_poses(0);
std::vector<Eigen::Vector2d,
Eigen::aligned_allocator<Eigen::Vector2d> > measurements(0);
for (auto& m : observations) {
// TODO: This should be handled properly. Normally, the
// required camera states should all be available in
// the input cam_states buffer.
auto cam_state_iter = cam_states.find(m.first);
if (cam_state_iter == cam_states.end()) continue;
// Add the measurement.
measurements.push_back(m.second.head<2>());
measurements.push_back(m.second.tail<2>());
// This camera pose will take a vector from this camera frame
// to the world frame.
Eigen::Isometry3d cam0_pose;
cam0_pose.linear() = quaternionToRotation(
cam_state_iter->second.orientation).transpose();
cam0_pose.translation() = cam_state_iter->second.position;
Eigen::Isometry3d cam1_pose;
cam1_pose = cam0_pose * CAMState::T_cam0_cam1.inverse();
cam_poses.push_back(cam0_pose);
cam_poses.push_back(cam1_pose);
}
// All camera poses should be modified such that it takes a
// vector from the first camera frame in the buffer to this
// camera frame.
Eigen::Isometry3d T_c0_w = cam_poses[0];
T_anchor_w = T_c0_w;
for (auto& pose : cam_poses)
pose = pose.inverse() * T_c0_w;
// Generate initial guess
Eigen::Vector3d initial_position(0.0, 0.0, 0.0);
generateInitialGuess(cam_poses[cam_poses.size()-1], measurements[0],
measurements[measurements.size()-1], initial_position);
Eigen::Vector3d solution(
initial_position(0)/initial_position(2),
initial_position(1)/initial_position(2),
1.0/initial_position(2));
// Apply Levenberg-Marquart method to solve for the 3d position.
double lambda = optimization_config.initial_damping;
int inner_loop_cntr = 0;
int outer_loop_cntr = 0;
bool is_cost_reduced = false;
double delta_norm = 0;
// Compute the initial cost.
double total_cost = 0.0;
for (int i = 0; i < cam_poses.size(); ++i) {
double this_cost = 0.0;
cost(cam_poses[i], solution, measurements[i], this_cost);
total_cost += this_cost;
}
// Outer loop.
do {
Eigen::Matrix3d A = Eigen::Matrix3d::Zero();
Eigen::Vector3d b = Eigen::Vector3d::Zero();
for (int i = 0; i < cam_poses.size(); ++i) {
Eigen::Matrix<double, 2, 3> J;
Eigen::Vector2d r;
double w;
jacobian(cam_poses[i], solution, measurements[i], J, r, w);
if (w == 1) {
A += J.transpose() * J;
b += J.transpose() * r;
} else {
double w_square = w * w;
A += w_square * J.transpose() * J;
b += w_square * J.transpose() * r;
}
}
// Inner loop.
// Solve for the delta that can reduce the total cost.
do {
Eigen::Matrix3d damper = lambda * Eigen::Matrix3d::Identity();
Eigen::Vector3d delta = (A+damper).ldlt().solve(b);
Eigen::Vector3d new_solution = solution - delta;
delta_norm = delta.norm();
double new_cost = 0.0;
for (int i = 0; i < cam_poses.size(); ++i) {
double this_cost = 0.0;
cost(cam_poses[i], new_solution, measurements[i], this_cost);
new_cost += this_cost;
}
if (new_cost < total_cost) {
is_cost_reduced = true;
solution = new_solution;
total_cost = new_cost;
lambda = lambda/10 > 1e-10 ? lambda/10 : 1e-10;
} else {
is_cost_reduced = false;
lambda = lambda*10 < 1e12 ? lambda*10 : 1e12;
}
} while (inner_loop_cntr++ <
optimization_config.inner_loop_max_iteration && !is_cost_reduced);
inner_loop_cntr = 0;
} while (outer_loop_cntr++ <
optimization_config.outer_loop_max_iteration &&
delta_norm > optimization_config.estimation_precision);
// Covert the feature position from inverse depth
// representation to its 3d coordinate.
Eigen::Vector3d final_position(solution(0)/solution(2),
solution(1)/solution(2), 1.0/solution(2));
// Check if the solution is valid. Make sure the feature
// is in front of every camera frame observing it.
bool is_valid_solution = true;
for (const auto& pose : cam_poses) {
Eigen::Vector3d position =
pose.linear()*final_position + pose.translation();
if (position(2) <= 0) {
is_valid_solution = false;
break;
}
}
//save inverse depth distance from camera
anchor_rho = solution(2);
// Convert the feature position to the world frame.
position = T_c0_w.linear()*final_position + T_c0_w.translation();
if (is_valid_solution)
is_initialized = true;
return is_valid_solution;
}
} // namespace msckf_vio
#endif // MSCKF_VIO_FEATURE_H

View File

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

View File

@ -13,6 +13,13 @@
namespace msckf_vio {
inline double absoluted(double a){
if(a>0)
return a;
else return -a;
}
/*
* @brief Create a skew-symmetric matrix from a 3-element vector.
* @note Performs the operation:
@ -43,6 +50,50 @@ inline void quaternionNormalize(Eigen::Vector4d& q) {
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
*/

View File

@ -14,7 +14,7 @@
#include <string>
#include <Eigen/Dense>
#include <Eigen/Geometry>
#include <math.h>
#include <boost/shared_ptr.hpp>
#include <opencv2/opencv.hpp>
#include <opencv2/video.hpp>
@ -38,6 +38,8 @@
#include <message_filters/subscriber.h>
#include <message_filters/time_synchronizer.h>
#define PI 3.14159265
namespace msckf_vio {
/*
* @brief MsckfVio Implements the algorithm in
@ -107,6 +109,15 @@ class MsckfVio {
*/
void imuCallback(const sensor_msgs::ImuConstPtr& msg);
/*
* @brief truthCallback
* Callback function for ground truth navigation information
* @param TransformStamped msg
*/
void truthCallback(
const geometry_msgs::TransformStampedPtr& msg);
/*
* @brief imageCallback
* Callback function for feature measurements
@ -144,11 +155,26 @@ class MsckfVio {
bool resetCallback(std_srvs::Trigger::Request& req,
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
// Propogate the state
void batchImuProcessing(
@ -160,8 +186,12 @@ class MsckfVio {
const Eigen::Vector3d& gyro,
const Eigen::Vector3d& acc);
// groundtruth state augmentation
void truePhotometricStateAugmentation(const double& time);
// Measurement update
void stateAugmentation(const double& time);
void PhotometricStateAugmentation(const double& time);
void addFeatureObservations(const CameraMeasurementConstPtr& msg);
// This function is used to compute the measurement Jacobian
// for a single feature observed at a single camera frame.
@ -180,9 +210,9 @@ class MsckfVio {
void PhotometricMeasurementJacobian(
const StateIDType& cam_state_id,
const FeatureIDType& feature_id,
Eigen::Matrix<double, 4, 6>& H_x,
Eigen::Matrix<double, 4, 3>& H_f,
Eigen::Vector4d& r);
Eigen::MatrixXd& H_x,
Eigen::MatrixXd& H_y,
Eigen::VectorXd& r);
void PhotometricFeatureJacobian(
const FeatureIDType& feature_id,
@ -200,11 +230,32 @@ class MsckfVio {
// Reset the system online if the uncertainty is too large.
void onlineReset();
// Photometry flag
bool PHOTOMETRIC;
// debug flag
bool PRINTIMAGES;
bool GROUNDTRUTH;
bool nan_flag;
bool play;
double last_time_bound;
// Patch size for Photometry
int N;
// Chi squared test table.
static std::map<int, double> chi_squared_test_table;
// State vector
StateServer 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
int max_cam_state_size;
@ -216,6 +267,8 @@ class MsckfVio {
// transfer delay between IMU and Image messages.
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;
@ -224,6 +277,8 @@ class MsckfVio {
CameraCalibration cam0;
CameraCalibration cam1;
// covariance data
double irradiance_frame_bias;
ros::Time image_save_time;
@ -255,7 +310,9 @@ class MsckfVio {
// Subscribers and publishers
ros::Subscriber imu_sub;
ros::Subscriber truth_sub;
ros::Publisher odom_pub;
ros::Publisher marker_pub;
ros::Publisher feature_pub;
tf::TransformBroadcaster tf_pub;
ros::ServiceServer reset_srv;
@ -287,6 +344,9 @@ class MsckfVio {
ros::Publisher mocap_odom_pub;
geometry_msgs::TransformStamped raw_mocap_odom_msg;
Eigen::Isometry3d mocap_initial_frame;
Eigen::Vector4d mocap_initial_orientation;
Eigen::Vector3d mocap_initial_position;
};
typedef MsckfVio::Ptr MsckfVioPtr;

View File

@ -0,0 +1,75 @@
<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="$(arg robot)">
<node pkg="nodelet" type="nodelet" name="vio"
args='standalone msckf_vio/MsckfVioNodelet'
output="screen"
launch-prefix="xterm -e gdb --args">
<!-- Photometry Flag-->
<param name="PHOTOMETRIC" value="true"/>
<!-- Debugging Flaggs -->
<param name="PrintImages" value="false"/>
<param name="GroundTruth" value="false"/>
<param name="patch_size_n" value="7"/>
<!-- Calibration parameters -->
<rosparam command="load" file="$(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

@ -17,6 +17,14 @@
args='standalone msckf_vio/MsckfVioNodelet'
output="screen">
<!-- 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="7"/>
<!-- Calibration parameters -->
<rosparam command="load" file="$(arg calibration_file)"/>
@ -51,8 +59,10 @@
<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"/>

View File

@ -18,6 +18,7 @@
<depend>nav_msgs</depend>
<depend>sensor_msgs</depend>
<depend>geometry_msgs</depend>
<depend>visualization_msgs</depend>
<depend>eigen_conversions</depend>
<depend>tf_conversions</depend>
<depend>random_numbers</depend>

View File

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

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