102 lines
3.6 KiB
C++
102 lines
3.6 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 SFMExampleExpressions.cpp
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* @brief A structure-from-motion example done with Expressions
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* @author Frank Dellaert
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* @author Duy-Nguyen Ta
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* @date October 1, 2014
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*/
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/**
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* This is the Expression version of SFMExample
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* See detailed description of headers there, this focuses on explaining the AD part
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*/
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// The two new headers that allow using our Automatic Differentiation Expression framework
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#include <gtsam/slam/expressions.h>
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#include <gtsam/nonlinear/ExpressionFactorGraph.h>
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// Header order is close to far
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#include "SFMdata.h"
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#include <gtsam/geometry/Point2.h>
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#include <gtsam/nonlinear/DoglegOptimizer.h>
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#include <gtsam/nonlinear/Values.h>
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#include <gtsam/inference/Symbol.h>
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#include <vector>
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using namespace std;
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using namespace gtsam;
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using namespace noiseModel;
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/* ************************************************************************* */
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int main(int argc, char* argv[]) {
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Cal3_S2 K(50.0, 50.0, 0.0, 50.0, 50.0);
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Isotropic::shared_ptr measurementNoise = Isotropic::Sigma(2, 1.0); // one pixel in u and v
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// Create the set of ground-truth landmarks and poses
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vector<Point3> points = createPoints();
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vector<Pose3> poses = createPoses();
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// Create a factor graph
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ExpressionFactorGraph graph;
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// Specify uncertainty on first pose prior
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Vector6 sigmas; sigmas << Vector3(0.3,0.3,0.3), Vector3(0.1,0.1,0.1);
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Diagonal::shared_ptr poseNoise = Diagonal::Sigmas(sigmas);
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// Here we don't use a PriorFactor but directly the ExpressionFactor class
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// x0 is an Expression, and we create a factor wanting it to be equal to poses[0]
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Pose3_ x0('x',0);
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graph.addExpressionFactor(x0, poses[0], poseNoise);
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// We create a constant Expression for the calibration here
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Cal3_S2_ cK(K);
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// Simulated measurements from each camera pose, adding them to the factor graph
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for (size_t i = 0; i < poses.size(); ++i) {
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Pose3_ x('x', i);
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PinholeCamera<Cal3_S2> camera(poses[i], K);
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for (size_t j = 0; j < points.size(); ++j) {
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Point2 measurement = camera.project(points[j]);
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// Below an expression for the prediction of the measurement:
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Point3_ p('l', j);
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Point2_ prediction = uncalibrate(cK, project(transformTo(x, p)));
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// Again, here we use an ExpressionFactor
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graph.addExpressionFactor(prediction, measurement, measurementNoise);
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}
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}
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// Add prior on first point to constrain scale, again with ExpressionFactor
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Isotropic::shared_ptr pointNoise = Isotropic::Sigma(3, 0.1);
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graph.addExpressionFactor(Point3_('l', 0), points[0], pointNoise);
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// Create perturbed initial
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Values initial;
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Pose3 delta(Rot3::Rodrigues(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20));
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for (size_t i = 0; i < poses.size(); ++i)
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initial.insert(Symbol('x', i), poses[i].compose(delta));
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for (size_t j = 0; j < points.size(); ++j)
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initial.insert<Point3>(Symbol('l', j), points[j] + Point3(-0.25, 0.20, 0.15));
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cout << "initial error = " << graph.error(initial) << endl;
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/* Optimize the graph and print results */
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Values result = DoglegOptimizer(graph, initial).optimize();
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cout << "final error = " << graph.error(result) << endl;
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return 0;
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}
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/* ************************************************************************* */
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