121 lines
4.3 KiB
C++
121 lines
4.3 KiB
C++
/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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* @file StereoVOExample_large.cpp
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* @brief A stereo visual odometry example
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* @date May 25, 2014
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* @author Stephen Camp
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*/
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/**
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* A 3D stereo visual odometry example
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* - robot starts at origin
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* -moves forward, taking periodic stereo measurements
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* -takes stereo readings of many landmarks
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*/
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#include <gtsam/geometry/Pose3.h>
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#include <gtsam/geometry/Cal3_S2Stereo.h>
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#include <gtsam/nonlinear/Values.h>
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#include <gtsam/nonlinear/NonlinearEquality.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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#include <gtsam/inference/Symbol.h>
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#include <gtsam/slam/StereoFactor.h>
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#include <gtsam/slam/dataset.h>
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#include <string>
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#include <fstream>
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#include <iostream>
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using namespace std;
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using namespace gtsam;
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int main(int argc, char** argv) {
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Values initial_estimate;
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NonlinearFactorGraph graph;
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const auto model = noiseModel::Isotropic::Sigma(3, 1);
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string calibration_loc = findExampleDataFile("VO_calibration.txt");
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string pose_loc = findExampleDataFile("VO_camera_poses_large.txt");
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string factor_loc = findExampleDataFile("VO_stereo_factors_large.txt");
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// read camera calibration info from file
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// focal lengths fx, fy, skew s, principal point u0, v0, baseline b
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double fx, fy, s, u0, v0, b;
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ifstream calibration_file(calibration_loc.c_str());
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cout << "Reading calibration info" << endl;
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calibration_file >> fx >> fy >> s >> u0 >> v0 >> b;
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// create stereo camera calibration object
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const Cal3_S2Stereo::shared_ptr K(new Cal3_S2Stereo(fx, fy, s, u0, v0, b));
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ifstream pose_file(pose_loc.c_str());
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cout << "Reading camera poses" << endl;
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int pose_id;
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MatrixRowMajor m(4, 4);
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// read camera pose parameters and use to make initial estimates of camera
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// poses
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while (pose_file >> pose_id) {
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for (int i = 0; i < 16; i++) {
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pose_file >> m.data()[i];
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}
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initial_estimate.insert(Symbol('x', pose_id), Pose3(m));
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}
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// camera and landmark keys
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size_t x, l;
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// pixel coordinates uL, uR, v (same for left/right images due to
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// rectification) landmark coordinates X, Y, Z in camera frame, resulting from
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// triangulation
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double uL, uR, v, X, Y, Z;
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ifstream factor_file(factor_loc.c_str());
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cout << "Reading stereo factors" << endl;
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// read stereo measurement details from file and use to create and add
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// GenericStereoFactor objects to the graph representation
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while (factor_file >> x >> l >> uL >> uR >> v >> X >> Y >> Z) {
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graph.emplace_shared<GenericStereoFactor<Pose3, Point3> >(
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StereoPoint2(uL, uR, v), model, Symbol('x', x), Symbol('l', l), K);
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// if the landmark variable included in this factor has not yet been added
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// to the initial variable value estimate, add it
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if (!initial_estimate.exists(Symbol('l', l))) {
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Pose3 camPose = initial_estimate.at<Pose3>(Symbol('x', x));
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// transformFrom() transforms the input Point3 from the camera pose space,
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// camPose, to the global space
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Point3 worldPoint = camPose.transformFrom(Point3(X, Y, Z));
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initial_estimate.insert(Symbol('l', l), worldPoint);
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}
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}
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Pose3 first_pose = initial_estimate.at<Pose3>(Symbol('x', 1));
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// constrain the first pose such that it cannot change from its original value
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// during optimization
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// NOTE: NonlinearEquality forces the optimizer to use QR rather than Cholesky
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// QR is much slower than Cholesky, but numerically more stable
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graph.emplace_shared<NonlinearEquality<Pose3> >(Symbol('x', 1), first_pose);
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cout << "Optimizing" << endl;
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// create Levenberg-Marquardt optimizer to optimize the factor graph
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LevenbergMarquardtParams params;
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params.orderingType = Ordering::METIS;
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LevenbergMarquardtOptimizer optimizer(graph, initial_estimate, params);
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Values result = optimizer.optimize();
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cout << "Final result sample:" << endl;
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Values pose_values = result.filter<Pose3>();
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pose_values.print("Final camera poses:\n");
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return 0;
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}
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