124 lines
4.1 KiB
C++
124 lines
4.1 KiB
C++
/* ----------------------------------------------------------------------------
|
|
|
|
* GTSAM Copyright 2010, Georgia Tech Research Corporation,
|
|
* Atlanta, Georgia 30332-0415
|
|
* All Rights Reserved
|
|
* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
|
|
|
|
* See LICENSE for the license information
|
|
|
|
* -------------------------------------------------------------------------- */
|
|
|
|
/**
|
|
* @file SmartProjectionFactorExample.cpp
|
|
* @brief A stereo visual odometry example
|
|
* @date May 30, 2014
|
|
* @author Stephen Camp
|
|
* @author Chris Beall
|
|
*/
|
|
|
|
|
|
/**
|
|
* A smart projection factor example based on stereo data, throwing away the
|
|
* measurement from the right camera
|
|
* -robot starts at origin
|
|
* -moves forward, taking periodic stereo measurements
|
|
* -makes monocular observations of many landmarks
|
|
*/
|
|
|
|
#include <gtsam/slam/SmartProjectionPoseFactor.h>
|
|
#include <gtsam/slam/dataset.h>
|
|
#include <gtsam/geometry/Cal3_S2Stereo.h>
|
|
#include <gtsam/nonlinear/Values.h>
|
|
#include <gtsam/nonlinear/NonlinearEquality.h>
|
|
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
|
|
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
|
|
#include <gtsam/inference/Symbol.h>
|
|
|
|
#include <string>
|
|
#include <fstream>
|
|
#include <iostream>
|
|
|
|
using namespace std;
|
|
using namespace gtsam;
|
|
|
|
int main(int argc, char** argv){
|
|
|
|
typedef PinholePose<Cal3_S2> Camera;
|
|
typedef SmartProjectionPoseFactor<Cal3_S2> SmartFactor;
|
|
|
|
Values initial_estimate;
|
|
NonlinearFactorGraph graph;
|
|
const noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(2,1);
|
|
|
|
string calibration_loc = findExampleDataFile("VO_calibration.txt");
|
|
string pose_loc = findExampleDataFile("VO_camera_poses_large.txt");
|
|
string factor_loc = findExampleDataFile("VO_stereo_factors_large.txt");
|
|
|
|
//read camera calibration info from file
|
|
// focal lengths fx, fy, skew s, principal point u0, v0, baseline b
|
|
cout << "Reading calibration info" << endl;
|
|
ifstream calibration_file(calibration_loc.c_str());
|
|
|
|
double fx, fy, s, u0, v0, b;
|
|
calibration_file >> fx >> fy >> s >> u0 >> v0 >> b;
|
|
const Cal3_S2::shared_ptr K(new Cal3_S2(fx, fy, s, u0, v0));
|
|
|
|
cout << "Reading camera poses" << endl;
|
|
ifstream pose_file(pose_loc.c_str());
|
|
|
|
int pose_index;
|
|
MatrixRowMajor m(4,4);
|
|
//read camera pose parameters and use to make initial estimates of camera poses
|
|
while (pose_file >> pose_index) {
|
|
for (int i = 0; i < 16; i++)
|
|
pose_file >> m.data()[i];
|
|
initial_estimate.insert(pose_index, Pose3(m));
|
|
}
|
|
|
|
// landmark keys
|
|
size_t landmark_key;
|
|
|
|
// pixel coordinates uL, uR, v (same for left/right images due to rectification)
|
|
// landmark coordinates X, Y, Z in camera frame, resulting from triangulation
|
|
double uL, uR, v, X, Y, Z;
|
|
ifstream factor_file(factor_loc.c_str());
|
|
cout << "Reading stereo factors" << endl;
|
|
|
|
//read stereo measurements and construct smart factors
|
|
|
|
SmartFactor::shared_ptr factor(new SmartFactor(model, K));
|
|
size_t current_l = 3; // hardcoded landmark ID from first measurement
|
|
|
|
while (factor_file >> pose_index >> landmark_key >> uL >> uR >> v >> X >> Y >> Z) {
|
|
|
|
if(current_l != landmark_key) {
|
|
graph.push_back(factor);
|
|
factor = SmartFactor::shared_ptr(new SmartFactor(model, K));
|
|
current_l = landmark_key;
|
|
}
|
|
factor->add(Point2(uL,v), pose_index);
|
|
}
|
|
|
|
Pose3 firstPose = initial_estimate.at<Pose3>(1);
|
|
//constrain the first pose such that it cannot change from its original value during optimization
|
|
// NOTE: NonlinearEquality forces the optimizer to use QR rather than Cholesky
|
|
// QR is much slower than Cholesky, but numerically more stable
|
|
graph.emplace_shared<NonlinearEquality<Pose3> >(1,firstPose);
|
|
|
|
LevenbergMarquardtParams params;
|
|
params.verbosityLM = LevenbergMarquardtParams::TRYLAMBDA;
|
|
params.verbosity = NonlinearOptimizerParams::ERROR;
|
|
|
|
cout << "Optimizing" << endl;
|
|
//create Levenberg-Marquardt optimizer to optimize the factor graph
|
|
LevenbergMarquardtOptimizer optimizer(graph, initial_estimate, params);
|
|
Values result = optimizer.optimize();
|
|
|
|
cout << "Final result sample:" << endl;
|
|
Values pose_values = result.filter<Pose3>();
|
|
pose_values.print("Final camera poses:\n");
|
|
|
|
return 0;
|
|
}
|