gtsam/matlab.h

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