122 lines
		
	
	
		
			4.3 KiB
		
	
	
	
		
			C++
		
	
	
			
		
		
	
	
			122 lines
		
	
	
		
			4.3 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 StereoVOExample_large.cpp
 | 
						|
* @brief A stereo visual odometry example
 | 
						|
* @date May 25, 2014
 | 
						|
* @author Stephen Camp
 | 
						|
*/
 | 
						|
 | 
						|
 | 
						|
/**
 | 
						|
 * A 3D stereo visual odometry example
 | 
						|
 *  - robot starts at origin
 | 
						|
 *  -moves forward, taking periodic stereo measurements
 | 
						|
 *  -takes stereo readings of many landmarks
 | 
						|
 */
 | 
						|
 | 
						|
#include <gtsam/geometry/Pose3.h>
 | 
						|
#include <gtsam/geometry/Cal3_S2Stereo.h>
 | 
						|
#include <gtsam/nonlinear/Values.h>
 | 
						|
#include <gtsam/nonlinear/utilities.h>
 | 
						|
#include <gtsam/nonlinear/NonlinearEquality.h>
 | 
						|
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
 | 
						|
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
 | 
						|
#include <gtsam/inference/Symbol.h>
 | 
						|
#include <gtsam/slam/StereoFactor.h>
 | 
						|
#include <gtsam/slam/dataset.h>
 | 
						|
 | 
						|
#include <string>
 | 
						|
#include <fstream>
 | 
						|
#include <iostream>
 | 
						|
 | 
						|
using namespace std;
 | 
						|
using namespace gtsam;
 | 
						|
 | 
						|
int main(int argc, char** argv) {
 | 
						|
  Values initial_estimate;
 | 
						|
  NonlinearFactorGraph graph;
 | 
						|
  const auto model = noiseModel::Isotropic::Sigma(3, 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
 | 
						|
  double fx, fy, s, u0, v0, b;
 | 
						|
  ifstream calibration_file(calibration_loc.c_str());
 | 
						|
  cout << "Reading calibration info" << endl;
 | 
						|
  calibration_file >> fx >> fy >> s >> u0 >> v0 >> b;
 | 
						|
 | 
						|
  // create stereo camera calibration object
 | 
						|
  const Cal3_S2Stereo::shared_ptr K(new Cal3_S2Stereo(fx, fy, s, u0, v0, b));
 | 
						|
 | 
						|
  ifstream pose_file(pose_loc.c_str());
 | 
						|
  cout << "Reading camera poses" << endl;
 | 
						|
  int pose_id;
 | 
						|
  MatrixRowMajor m(4, 4);
 | 
						|
  // read camera pose parameters and use to make initial estimates of camera
 | 
						|
  // poses
 | 
						|
  while (pose_file >> pose_id) {
 | 
						|
    for (int i = 0; i < 16; i++) {
 | 
						|
      pose_file >> m.data()[i];
 | 
						|
    }
 | 
						|
    initial_estimate.insert(Symbol('x', pose_id), Pose3(m));
 | 
						|
  }
 | 
						|
 | 
						|
  // camera and landmark keys
 | 
						|
  size_t x, l;
 | 
						|
 | 
						|
  // 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 measurement details from file and use to create and add
 | 
						|
  // GenericStereoFactor objects to the graph representation
 | 
						|
  while (factor_file >> x >> l >> uL >> uR >> v >> X >> Y >> Z) {
 | 
						|
    graph.emplace_shared<GenericStereoFactor<Pose3, Point3> >(
 | 
						|
        StereoPoint2(uL, uR, v), model, Symbol('x', x), Symbol('l', l), K);
 | 
						|
    // if the landmark variable included in this factor has not yet been added
 | 
						|
    // to the initial variable value estimate, add it
 | 
						|
    if (!initial_estimate.exists(Symbol('l', l))) {
 | 
						|
      Pose3 camPose = initial_estimate.at<Pose3>(Symbol('x', x));
 | 
						|
      // transformFrom() transforms the input Point3 from the camera pose space,
 | 
						|
      // camPose, to the global space
 | 
						|
      Point3 worldPoint = camPose.transformFrom(Point3(X, Y, Z));
 | 
						|
      initial_estimate.insert(Symbol('l', l), worldPoint);
 | 
						|
    }
 | 
						|
  }
 | 
						|
 | 
						|
  Pose3 first_pose = initial_estimate.at<Pose3>(Symbol('x', 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> >(Symbol('x', 1), first_pose);
 | 
						|
 | 
						|
  cout << "Optimizing" << endl;
 | 
						|
  // create Levenberg-Marquardt optimizer to optimize the factor graph
 | 
						|
  LevenbergMarquardtParams params;
 | 
						|
  params.orderingType = Ordering::METIS;
 | 
						|
  LevenbergMarquardtOptimizer optimizer(graph, initial_estimate, params);
 | 
						|
  Values result = optimizer.optimize();
 | 
						|
 | 
						|
  cout << "Final result sample:" << endl;
 | 
						|
  Values pose_values = utilities::allPose3s(result);
 | 
						|
  pose_values.print("Final camera poses:\n");
 | 
						|
 | 
						|
  return 0;
 | 
						|
}
 |