Point Cloud Library (PCL) 1.14.0
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ndt_2d.h
1/*
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4 * Point Cloud Library (PCL) - www.pointclouds.org
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40
41#pragma once
42
43#include <pcl/registration/registration.h>
44#include <pcl/memory.h>
45
46namespace pcl {
47/** \brief @b NormalDistributionsTransform2D provides an implementation of the
48 * Normal Distributions Transform algorithm for scan matching.
49 *
50 * This implementation is intended to match the definition:
51 * Peter Biber and Wolfgang Straßer. The normal distributions transform: A
52 * new approach to laser scan matching. In Proceedings of the IEEE In-
53 * ternational Conference on Intelligent Robots and Systems (IROS), pages
54 * 2743–2748, Las Vegas, USA, October 2003.
55 *
56 * \author James Crosby
57 * \ingroup registration
58 */
59template <typename PointSource, typename PointTarget>
60class NormalDistributionsTransform2D : public Registration<PointSource, PointTarget> {
61 using PointCloudSource =
63 using PointCloudSourcePtr = typename PointCloudSource::Ptr;
64 using PointCloudSourceConstPtr = typename PointCloudSource::ConstPtr;
65
66 using PointCloudTarget =
68
69 using PointIndicesPtr = PointIndices::Ptr;
70 using PointIndicesConstPtr = PointIndices::ConstPtr;
71
72public:
73 using Ptr = shared_ptr<NormalDistributionsTransform2D<PointSource, PointTarget>>;
74 using ConstPtr =
75 shared_ptr<const NormalDistributionsTransform2D<PointSource, PointTarget>>;
76
77 /** \brief Empty constructor. */
79 : Registration<PointSource, PointTarget>()
80 , grid_centre_(0, 0)
81 , grid_step_(1, 1)
82 , grid_extent_(20, 20)
83 , newton_lambda_(1, 1, 1)
84 {
85 reg_name_ = "NormalDistributionsTransform2D";
86 }
87
88 /** \brief Empty destructor */
89 ~NormalDistributionsTransform2D() override = default;
90
91 /** \brief centre of the ndt grid (target coordinate system)
92 * \param centre value to set
93 */
94 virtual void
95 setGridCentre(const Eigen::Vector2f& centre)
96 {
97 grid_centre_ = centre;
98 }
99
100 /** \brief Grid spacing (step) of the NDT grid
101 * \param[in] step value to set
102 */
103 virtual void
104 setGridStep(const Eigen::Vector2f& step)
105 {
106 grid_step_ = step;
107 }
108
109 /** \brief NDT Grid extent (in either direction from the grid centre)
110 * \param[in] extent value to set
111 */
112 virtual void
113 setGridExtent(const Eigen::Vector2f& extent)
114 {
115 grid_extent_ = extent;
116 }
117
118 /** \brief NDT Newton optimisation step size parameter
119 * \param[in] lambda step size: 1 is simple newton optimisation, smaller values may
120 * improve convergence
121 */
122 virtual void
123 setOptimizationStepSize(const double& lambda)
124 {
125 newton_lambda_ = Eigen::Vector3d(lambda, lambda, lambda);
126 }
127
128 /** \brief NDT Newton optimisation step size parameter
129 * \param[in] lambda step size: (1,1,1) is simple newton optimisation,
130 * smaller values may improve convergence, or elements may be set to
131 * zero to prevent optimisation over some parameters
132 *
133 * This overload allows control of updates to the individual (x, y,
134 * theta) free parameters in the optimisation. If, for example, theta is
135 * believed to be close to the correct value a small value of lambda[2]
136 * should be used.
137 */
138 virtual void
139 setOptimizationStepSize(const Eigen::Vector3d& lambda)
140 {
141 newton_lambda_ = lambda;
142 }
143
144protected:
145 /** \brief Rigid transformation computation method with initial guess.
146 * \param[out] output the transformed input point cloud dataset using the rigid
147 * transformation found \param[in] guess the initial guess of the transformation to
148 * compute
149 */
150 void
151 computeTransformation(PointCloudSource& output,
152 const Eigen::Matrix4f& guess) override;
153
154 using Registration<PointSource, PointTarget>::reg_name_;
155 using Registration<PointSource, PointTarget>::target_;
156 using Registration<PointSource, PointTarget>::converged_;
157 using Registration<PointSource, PointTarget>::nr_iterations_;
158 using Registration<PointSource, PointTarget>::max_iterations_;
159 using Registration<PointSource, PointTarget>::transformation_epsilon_;
160 using Registration<PointSource, PointTarget>::transformation_rotation_epsilon_;
161 using Registration<PointSource, PointTarget>::transformation_;
162 using Registration<PointSource, PointTarget>::previous_transformation_;
163 using Registration<PointSource, PointTarget>::final_transformation_;
164 using Registration<PointSource, PointTarget>::update_visualizer_;
165 using Registration<PointSource, PointTarget>::indices_;
166
167 Eigen::Vector2f grid_centre_;
168 Eigen::Vector2f grid_step_;
169 Eigen::Vector2f grid_extent_;
170 Eigen::Vector3d newton_lambda_;
171
172public:
174};
175
176} // namespace pcl
177
178#include <pcl/registration/impl/ndt_2d.hpp>
NormalDistributionsTransform2D provides an implementation of the Normal Distributions Transform algor...
Definition ndt_2d.h:60
virtual void setOptimizationStepSize(const double &lambda)
NDT Newton optimisation step size parameter.
Definition ndt_2d.h:123
virtual void setOptimizationStepSize(const Eigen::Vector3d &lambda)
NDT Newton optimisation step size parameter.
Definition ndt_2d.h:139
~NormalDistributionsTransform2D() override=default
Empty destructor.
virtual void setGridStep(const Eigen::Vector2f &step)
Grid spacing (step) of the NDT grid.
Definition ndt_2d.h:104
virtual void setGridExtent(const Eigen::Vector2f &extent)
NDT Grid extent (in either direction from the grid centre)
Definition ndt_2d.h:113
virtual void setGridCentre(const Eigen::Vector2f &centre)
centre of the ndt grid (target coordinate system)
Definition ndt_2d.h:95
NormalDistributionsTransform2D()
Empty constructor.
Definition ndt_2d.h:78
void computeTransformation(PointCloudSource &output, const Eigen::Matrix4f &guess) override
Rigid transformation computation method with initial guess.
Definition ndt_2d.hpp:392
shared_ptr< NormalDistributionsTransform2D< PointSource, PointTarget > > Ptr
Definition ndt_2d.h:73
shared_ptr< const NormalDistributionsTransform2D< PointSource, PointTarget > > ConstPtr
Definition ndt_2d.h:75
IndicesPtr indices_
A pointer to the vector of point indices to use.
Definition pcl_base.h:150
Registration represents the base registration class for general purpose, ICP-like methods.
Matrix4 final_transformation_
The final transformation matrix estimated by the registration method after N iterations.
std::function< UpdateVisualizerCallbackSignature > update_visualizer_
Callback function to update intermediate source point cloud position during it's registration to the ...
std::string reg_name_
The registration method name.
Matrix4 transformation_
The transformation matrix estimated by the registration method.
int nr_iterations_
The number of iterations the internal optimization ran for (used internally).
Matrix4 previous_transformation_
The previous transformation matrix estimated by the registration method (used internally).
bool converged_
Holds internal convergence state, given user parameters.
int max_iterations_
The maximum number of iterations the internal optimization should run for.
double transformation_rotation_epsilon_
The maximum rotation difference between two consecutive transformations in order to consider converge...
double transformation_epsilon_
The maximum difference between two consecutive transformations in order to consider convergence (user...
PointCloudTargetConstPtr target_
The input point cloud dataset target.
#define PCL_MAKE_ALIGNED_OPERATOR_NEW
Macro to signal a class requires a custom allocator.
Definition memory.h:63
Defines functions, macros and traits for allocating and using memory.
shared_ptr< ::pcl::PointIndices > Ptr
shared_ptr< const ::pcl::PointIndices > ConstPtr