148 lines
6.0 KiB
C++
148 lines
6.0 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 matlab.h
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* @brief Contains *generic* global functions designed particularly for the matlab interface
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* @author Stephen Williams
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*/
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#pragma once
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#include <gtsam/slam/ProjectionFactor.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/nonlinear/NonlinearFactor.h>
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#include <gtsam/nonlinear/Values.h>
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#include <gtsam/geometry/Point2.h>
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#include <gtsam/geometry/Point3.h>
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#include <gtsam/geometry/Pose2.h>
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#include <gtsam/geometry/Pose3.h>
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#include <gtsam/geometry/Cal3_S2.h>
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#include <gtsam/geometry/SimpleCamera.h>
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#include <exception>
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namespace gtsam {
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namespace utilities {
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/// Extract all Point2 values into a single matrix [x y]
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Matrix extractPoint2(const Values& values) {
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size_t j=0;
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Values::ConstFiltered<Point2> points = values.filter<Point2>();
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Matrix result(points.size(),2);
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BOOST_FOREACH(const Values::ConstFiltered<Point2>::KeyValuePair& key_value, points)
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result.row(j++) = key_value.value.vector();
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return result;
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}
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/// Extract all Point3 values into a single matrix [x y z]
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Matrix extractPoint3(const Values& values) {
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Values::ConstFiltered<Point3> points = values.filter<Point3>();
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Matrix result(points.size(),3);
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size_t j=0;
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BOOST_FOREACH(const Values::ConstFiltered<Point3>::KeyValuePair& key_value, points)
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result.row(j++) = key_value.value.vector();
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return result;
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}
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/// Extract all Pose2 values into a single matrix [x y theta]
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Matrix extractPose2(const Values& values) {
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Values::ConstFiltered<Pose2> poses = values.filter<Pose2>();
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Matrix result(poses.size(),3);
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size_t j=0;
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BOOST_FOREACH(const Values::ConstFiltered<Pose2>::KeyValuePair& key_value, poses)
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result.row(j++) << key_value.value.x(), key_value.value.y(), key_value.value.theta();
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return result;
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}
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/// Extract all Pose3 values
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Values allPose3s(const Values& values) {
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return values.filter<Pose3>();
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}
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/// Extract all Pose3 values into a single matrix [r11 r12 r13 r21 r22 r23 r31 r32 r33 x y z]
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Matrix extractPose3(const Values& values) {
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Values::ConstFiltered<Pose3> poses = values.filter<Pose3>();
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Matrix result(poses.size(),12);
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size_t j=0;
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BOOST_FOREACH(const Values::ConstFiltered<Pose3>::KeyValuePair& key_value, poses) {
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result.row(j).segment(0, 3) << key_value.value.rotation().matrix().row(0);
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result.row(j).segment(3, 3) << key_value.value.rotation().matrix().row(1);
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result.row(j).segment(6, 3) << key_value.value.rotation().matrix().row(2);
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result.row(j).tail(3) = key_value.value.translation().vector();
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j++;
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}
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return result;
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}
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/// perturb all Point2 using normally distributed noise
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void perturbPoint2(Values& values, double sigma, int32_t seed = 42u) {
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noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(2,sigma);
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Sampler sampler(model, seed);
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BOOST_FOREACH(const Values::ConstFiltered<Point2>::KeyValuePair& key_value, values.filter<Point2>()) {
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values.update(key_value.key, key_value.value.retract(sampler.sample()));
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}
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}
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/// perturb all Point3 using normally distributed noise
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void perturbPoint3(Values& values, double sigma, int32_t seed = 42u) {
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noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(3,sigma);
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Sampler sampler(model, seed);
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BOOST_FOREACH(const Values::ConstFiltered<Point3>::KeyValuePair& key_value, values.filter<Point3>()) {
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values.update(key_value.key, key_value.value.retract(sampler.sample()));
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}
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}
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/// insert a number of initial point values by backprojecting
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void insertBackprojections(Values& values, const SimpleCamera& camera, const Vector& J, const Matrix& Z, double depth) {
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if (Z.rows() != 2) throw std::invalid_argument("insertBackProjections: Z must be 2*K");
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if (Z.cols() != J.size()) throw std::invalid_argument("insertBackProjections: J and Z must have same number of entries");
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for(int k=0;k<Z.cols();k++) {
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Point2 p(Z(0,k),Z(1,k));
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Point3 P = camera.backproject(p, depth);
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values.insert(J(k), P);
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}
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}
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/// insert multiple projection factors for a single pose key
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void insertProjectionFactors(NonlinearFactorGraph& graph, Key i, const Vector& J, const Matrix& Z,
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const SharedNoiseModel& model, const Cal3_S2::shared_ptr K, const Pose3& body_P_sensor = Pose3()) {
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if (Z.rows() != 2) throw std::invalid_argument("addMeasurements: Z must be 2*K");
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if (Z.cols() != J.size()) throw std::invalid_argument(
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"addMeasurements: J and Z must have same number of entries");
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for (int k = 0; k < Z.cols(); k++) {
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graph.push_back(
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boost::make_shared<GenericProjectionFactor<Pose3, Point3> >
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(Point2(Z(0, k), Z(1, k)), model, i, Key(J(k)), K, body_P_sensor));
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}
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}
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/// calculate the errors of all projection factors in a graph
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Matrix reprojectionErrors(const NonlinearFactorGraph& graph, const Values& values) {
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// first count
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size_t K = 0, k=0;
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BOOST_FOREACH(const NonlinearFactor::shared_ptr& f, graph)
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if (boost::dynamic_pointer_cast<const GenericProjectionFactor<Pose3, Point3> >(f)) ++K;
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// now fill
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Matrix errors(2,K);
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BOOST_FOREACH(const NonlinearFactor::shared_ptr& f, graph) {
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boost::shared_ptr<const GenericProjectionFactor<Pose3, Point3> > p = boost::dynamic_pointer_cast<const GenericProjectionFactor<Pose3, Point3> >(f);
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if (p) errors.col(k++) = p->unwhitenedError(values);
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}
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return errors;
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}
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}
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}
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