PointToPlaneWithCov.cpp
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4 
5 Copyright (c) 2010--2012,
6 Fran├žois Pomerleau and Stephane Magnenat, ASL, ETHZ, Switzerland
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8 <stephane at magnenat dot net>
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35 
36 #include <iostream>
37 
38 #include "Eigen/SVD"
39 
40 #include "ErrorMinimizersImpl.h"
41 #include "PointMatcherPrivate.h"
42 #include "Functions.h"
43 
44 using namespace Eigen;
45 using namespace std;
46 
52 
53 template<typename T>
56  sensorStdDev(Parametrizable::get<T>("sensorStdDev"))
57 {
58 }
59 
60 template<typename T>
62 {
63  ErrorElements mPts = mPts_const;
65 
66  this->covMatrix = this->estimateCovariance(mPts, out);
67 
68  return out;
69 }
70 
71 template<typename T>
74 {
75  const int max_nbr_point = mPts.reading.getNbPoints();
76 
77  Matrix covariance(Matrix::Zero(6,6));
78  Matrix J_hessian(Matrix::Zero(6,6));
79  Matrix d2J_dReadingdX(Matrix::Zero(6, max_nbr_point));
80  Matrix d2J_dReferencedX(Matrix::Zero(6, max_nbr_point));
81 
82  Vector reading_point(Vector::Zero(3));
83  Vector reference_point(Vector::Zero(3));
84  Vector normal(3);
85  Vector reading_direction(Vector::Zero(3));
86  Vector reference_direction(Vector::Zero(3));
87 
88  //TODO: should be constView
89  Matrix normals = mPts.reference.getDescriptorViewByName("normals");
90 
91  if (normals.rows() < 3) // Make sure there are normals in DataPoints
92  return std::numeric_limits<T>::max() * Matrix::Identity(6,6);
93 
94  T beta = -asin(transformation(2,0));
95  T alpha = atan2(transformation(2,1), transformation(2,2));
96  T gamma = atan2(transformation(1,0)/cos(beta), transformation(0,0)/cos(beta));
97  T t_x = transformation(0,3);
98  T t_y = transformation(1,3);
99  T t_z = transformation(2,3);
100 
101  Vector tmp_vector_6(Vector::Zero(6));
102 
103  int valid_points_count = 0;
104 
105  //TODO: add missing const
106  for(int i = 0; i < max_nbr_point; ++i)
107  {
108  //if (outlierWeights(0,i) > 0.0)
109  {
110  reading_point = mPts.reading.features.block(0,i,3,1);
111  //int reference_idx = matches.ids(0,i);
112  reference_point = mPts.reference.features.block(0,i,3,1);
113 
114  normal = normals.block(0,i,3,1);
115 
116  T reading_range = reading_point.norm();
117  reading_direction = reading_point / reading_range;
118  T reference_range = reference_point.norm();
119  reference_direction = reference_point / reference_range;
120 
121  T n_alpha = normal(2)*reading_direction(1) - normal(1)*reading_direction(2);
122  T n_beta = normal(0)*reading_direction(2) - normal(2)*reading_direction(0);
123  T n_gamma = normal(1)*reading_direction(0) - normal(0)*reading_direction(1);
124 
125  T E = normal(0)*(reading_point(0) - gamma*reading_point(1) + beta*reading_point(2) + t_x - reference_point(0));
126  E += normal(1)*(gamma*reading_point(0) + reading_point(1) - alpha*reading_point(2) + t_y - reference_point(1));
127  E += normal(2)*(-beta*reading_point(0) + alpha*reading_point(1) + reading_point(2) + t_z - reference_point(2));
128 
129  T N_reading = normal(0)*(reading_direction(0) - gamma*reading_direction(1) + beta*reading_direction(2));
130  N_reading += normal(1)*(gamma*reading_direction(0) + reading_direction(1) - alpha*reading_direction(2));
131  N_reading += normal(2)*(-beta*reading_direction(0) + alpha*reading_direction(1) + reading_direction(2));
132 
133  T N_reference = -(normal(0)*reference_direction(0) + normal(1)*reference_direction(1) + normal(2)*reference_direction(2));
134 
135  // update the hessian and d2J/dzdx
136  tmp_vector_6 << normal(0), normal(1), normal(2), reading_range * n_alpha, reading_range * n_beta, reading_range * n_gamma;
137 
138  J_hessian += tmp_vector_6 * tmp_vector_6.transpose();
139 
140  tmp_vector_6 << normal(0) * N_reading, normal(1) * N_reading, normal(2) * N_reading, n_alpha * (E + reading_range * N_reading), n_beta * (E + reading_range * N_reading), n_gamma * (E + reading_range * N_reading);
141 
142  d2J_dReadingdX.block(0,valid_points_count,6,1) = tmp_vector_6;
143 
144  tmp_vector_6 << normal(0) * N_reference, normal(1) * N_reference, normal(2) * N_reference, reference_range * n_alpha * N_reference, reference_range * n_beta * N_reference, reference_range * n_gamma * N_reference;
145 
146  d2J_dReferencedX.block(0,valid_points_count,6,1) = tmp_vector_6;
147 
148  valid_points_count++;
149  } // if (outlierWeights(0,i) > 0.0)
150  }
151 
152  Matrix d2J_dZdX(Matrix::Zero(6, 2 * valid_points_count));
153  d2J_dZdX.block(0,0,6,valid_points_count) = d2J_dReadingdX.block(0,0,6,valid_points_count);
154  d2J_dZdX.block(0,valid_points_count,6,valid_points_count) = d2J_dReferencedX.block(0,0,6,valid_points_count);
155 
156  Matrix inv_J_hessian = J_hessian.inverse();
157 
158  covariance = d2J_dZdX * d2J_dZdX.transpose();
159  covariance = inv_J_hessian * covariance * inv_J_hessian;
160 
161  return (sensorStdDev * sensorStdDev) * covariance;
162 }
163 
164 
165 template<typename T>
167 {
168  return covMatrix;
169 }
170 
PointToPlaneWithCovErrorMinimizer::compute
virtual TransformationParameters compute(const ErrorElements &mPts)
Find the transformation that minimizes the error given matched pair of points. This function most be ...
Definition: PointToPlaneWithCov.cpp:61
PointToPlaneErrorMinimizer::Vector
PointMatcher< T >::Vector Vector
Definition: PointToPlane.h:56
PointToPlaneWithCovErrorMinimizer::getCovariance
virtual Matrix getCovariance() const
If not redefined by child class, return zero matrix.
Definition: PointToPlaneWithCov.cpp:166
build_map.T
T
Definition: build_map.py:34
PointToPlaneErrorMinimizer::TransformationParameters
PointMatcher< T >::TransformationParameters TransformationParameters
Definition: PointToPlane.h:55
PointMatcherPrivate.h
PointToPlaneWithCovErrorMinimizer::PointToPlaneWithCovErrorMinimizer
PointToPlaneWithCovErrorMinimizer(const Parameters &params=Parameters())
Definition: PointToPlaneWithCov.cpp:54
ParametersDoc
Parametrizable::ParametersDoc ParametersDoc
Definition: PointToPlaneWithCov.cpp:51
PointToPlaneErrorMinimizer::Matrix
PointMatcher< T >::Matrix Matrix
Definition: PointToPlane.h:57
ErrorMinimizersImpl.h
PointToPlaneWithCovErrorMinimizer::estimateCovariance
Matrix estimateCovariance(const ErrorElements &mPts, const TransformationParameters &transformation)
Definition: PointToPlaneWithCov.cpp:73
Parameters
Parametrizable::Parameters Parameters
Definition: PointToPlaneWithCov.cpp:49
PointMatcher::ErrorMinimizer::ErrorElements
A structure holding data ready for minimization. The data are "normalized", for instance there are no...
Definition: PointMatcher.h:534
ParameterDoc
Parametrizable::ParameterDoc ParameterDoc
Definition: PointToPlaneWithCov.cpp:50
PointMatcherSupport::Parametrizable::ParametersDoc
std::vector< ParameterDoc > ParametersDoc
The documentation of all parameters.
Definition: Parametrizable.h:187
PointToPlaneErrorMinimizer
Definition: PointToPlane.h:42
align_sequence.params
params
Definition: align_sequence.py:13
PointMatcher::Matrix
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > Matrix
A dense matrix over ScalarType.
Definition: PointMatcher.h:169
PointMatcher::ErrorMinimizer::ErrorElements::reading
DataPoints reading
reading point cloud
Definition: PointMatcher.h:536
PointMatcher::DataPoints::getNbPoints
unsigned getNbPoints() const
Return the number of points contained in the point cloud.
Definition: pointmatcher/DataPoints.cpp:158
PointMatcher::DataPoints::features
Matrix features
features of points in the cloud
Definition: PointMatcher.h:331
PointMatcher::ErrorMinimizer::ErrorElements::reference
DataPoints reference
reference point cloud
Definition: PointMatcher.h:537
PointToPlaneWithCovErrorMinimizer
Definition: PointToPlaneWithCov.h:43
PointToPlaneErrorMinimizer::Parameters
Parametrizable::Parameters Parameters
Definition: PointToPlane.h:46
PointToPlaneErrorMinimizer::compute_in_place
TransformationParameters compute_in_place(ErrorElements &mPts)
Definition: PointToPlane.cpp:172
PointMatcherSupport::Parametrizable
The superclass of classes that are constructed using generic parameters. This class provides the para...
Definition: Parametrizable.h:141
std
PointMatcherSupport::get
const M::mapped_type & get(const M &m, const typename M::key_type &k)
Definition: Bibliography.cpp:57
PointMatcherSupport::Parametrizable::ParameterDoc
The documentation of a parameter.
Definition: Parametrizable.h:160
build_map.transformation
transformation
Definition: build_map.py:37
Functions.h
Parametrizable
PointMatcherSupport::Parametrizable Parametrizable
Definition: PointToPlaneWithCov.cpp:47
PointMatcher::DataPoints::getDescriptorViewByName
ConstView getDescriptorViewByName(const std::string &name) const
Get a const view on a descriptor by name, throw an exception if it does not exist.
Definition: pointmatcher/DataPoints.cpp:555
P
PointMatcherSupport::Parametrizable P
Definition: PointToPlaneWithCov.cpp:48
PointMatcherSupport::Parametrizable::Parameters
std::map< std::string, Parameter > Parameters
Parameters stored as a map of string->string.
Definition: Parametrizable.h:199
PointMatcher::TransformationParameters
Matrix TransformationParameters
A matrix holding the parameters a transformation.
Definition: PointMatcher.h:182


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