Point Cloud Library (PCL)
1.14.1-dev
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NormalDistributionsTransform2D provides an implementation of the Normal Distributions Transform algorithm for scan matching. More...
#include <pcl/registration/ndt_2d.h>
Public Member Functions | |
NormalDistributionsTransform2D () | |
Empty constructor. More... | |
~NormalDistributionsTransform2D () override=default | |
Empty destructor. More... | |
virtual void | setGridCentre (const Eigen::Vector2f ¢re) |
centre of the ndt grid (target coordinate system) More... | |
virtual void | setGridStep (const Eigen::Vector2f &step) |
Grid spacing (step) of the NDT grid. More... | |
virtual void | setGridExtent (const Eigen::Vector2f &extent) |
NDT Grid extent (in either direction from the grid centre) More... | |
virtual void | setOptimizationStepSize (const double &lambda) |
NDT Newton optimisation step size parameter. More... | |
virtual void | setOptimizationStepSize (const Eigen::Vector3d &lambda) |
NDT Newton optimisation step size parameter. More... | |
Public Member Functions inherited from pcl::Registration< PointSource, PointTarget, Scalar > | |
Registration () | |
Empty constructor. More... | |
~Registration () override=default | |
destructor. More... | |
void | setTransformationEstimation (const TransformationEstimationPtr &te) |
Provide a pointer to the transformation estimation object. More... | |
void | setCorrespondenceEstimation (const CorrespondenceEstimationPtr &ce) |
Provide a pointer to the correspondence estimation object. More... | |
virtual void | setInputSource (const PointCloudSourceConstPtr &cloud) |
Provide a pointer to the input source (e.g., the point cloud that we want to align to the target) More... | |
PointCloudSourceConstPtr const | getInputSource () |
Get a pointer to the input point cloud dataset target. More... | |
virtual void | setInputTarget (const PointCloudTargetConstPtr &cloud) |
Provide a pointer to the input target (e.g., the point cloud that we want to align the input source to) More... | |
PointCloudTargetConstPtr const | getInputTarget () |
Get a pointer to the input point cloud dataset target. More... | |
void | setSearchMethodTarget (const KdTreePtr &tree, bool force_no_recompute=false) |
Provide a pointer to the search object used to find correspondences in the target cloud. More... | |
KdTreePtr | getSearchMethodTarget () const |
Get a pointer to the search method used to find correspondences in the target cloud. More... | |
void | setSearchMethodSource (const KdTreeReciprocalPtr &tree, bool force_no_recompute=false) |
Provide a pointer to the search object used to find correspondences in the source cloud (usually used by reciprocal correspondence finding). More... | |
KdTreeReciprocalPtr | getSearchMethodSource () const |
Get a pointer to the search method used to find correspondences in the source cloud. More... | |
Matrix4 | getFinalTransformation () |
Get the final transformation matrix estimated by the registration method. More... | |
Matrix4 | getLastIncrementalTransformation () |
Get the last incremental transformation matrix estimated by the registration method. More... | |
void | setMaximumIterations (int nr_iterations) |
Set the maximum number of iterations the internal optimization should run for. More... | |
int | getMaximumIterations () |
Get the maximum number of iterations the internal optimization should run for, as set by the user. More... | |
void | setRANSACIterations (int ransac_iterations) |
Set the number of iterations RANSAC should run for. More... | |
double | getRANSACIterations () |
Get the number of iterations RANSAC should run for, as set by the user. More... | |
void | setRANSACOutlierRejectionThreshold (double inlier_threshold) |
Set the inlier distance threshold for the internal RANSAC outlier rejection loop. More... | |
double | getRANSACOutlierRejectionThreshold () |
Get the inlier distance threshold for the internal outlier rejection loop as set by the user. More... | |
void | setMaxCorrespondenceDistance (double distance_threshold) |
Set the maximum distance threshold between two correspondent points in source <-> target. More... | |
double | getMaxCorrespondenceDistance () |
Get the maximum distance threshold between two correspondent points in source <-> target. More... | |
void | setTransformationEpsilon (double epsilon) |
Set the transformation epsilon (maximum allowable translation squared difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution. More... | |
double | getTransformationEpsilon () |
Get the transformation epsilon (maximum allowable translation squared difference between two consecutive transformations) as set by the user. More... | |
void | setTransformationRotationEpsilon (double epsilon) |
Set the transformation rotation epsilon (maximum allowable rotation difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution. More... | |
double | getTransformationRotationEpsilon () |
Get the transformation rotation epsilon (maximum allowable difference between two consecutive transformations) as set by the user (epsilon is the cos(angle) in a axis-angle representation). More... | |
void | setEuclideanFitnessEpsilon (double epsilon) |
Set the maximum allowed Euclidean error between two consecutive steps in the ICP loop, before the algorithm is considered to have converged. More... | |
double | getEuclideanFitnessEpsilon () |
Get the maximum allowed distance error before the algorithm will be considered to have converged, as set by the user. More... | |
void | setPointRepresentation (const PointRepresentationConstPtr &point_representation) |
Provide a boost shared pointer to the PointRepresentation to be used when comparing points. More... | |
bool | registerVisualizationCallback (std::function< UpdateVisualizerCallbackSignature > &visualizerCallback) |
Register the user callback function which will be called from registration thread in order to update point cloud obtained after each iteration. More... | |
double | getFitnessScore (double max_range=std::numeric_limits< double >::max()) |
Obtain the Euclidean fitness score (e.g., mean of squared distances from the source to the target) More... | |
double | getFitnessScore (const std::vector< float > &distances_a, const std::vector< float > &distances_b) |
Obtain the Euclidean fitness score (e.g., mean of squared distances from the source to the target) from two sets of correspondence distances (distances between source and target points) More... | |
bool | hasConverged () const |
Return the state of convergence after the last align run. More... | |
void | align (PointCloudSource &output) |
Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output. More... | |
void | align (PointCloudSource &output, const Matrix4 &guess) |
Call the registration algorithm which estimates the transformation and returns the transformed source (input) as output. More... | |
const std::string & | getClassName () const |
Abstract class get name method. More... | |
bool | initCompute () |
Internal computation initialization. More... | |
bool | initComputeReciprocal () |
Internal computation when reciprocal lookup is needed. More... | |
void | addCorrespondenceRejector (const CorrespondenceRejectorPtr &rejector) |
Add a new correspondence rejector to the list. More... | |
std::vector< CorrespondenceRejectorPtr > | getCorrespondenceRejectors () |
Get the list of correspondence rejectors. More... | |
bool | removeCorrespondenceRejector (unsigned int i) |
Remove the i-th correspondence rejector in the list. More... | |
void | clearCorrespondenceRejectors () |
Clear the list of correspondence rejectors. More... | |
Public Member Functions inherited from pcl::PCLBase< PointSource > | |
PCLBase () | |
Empty constructor. More... | |
PCLBase (const PCLBase &base) | |
Copy constructor. More... | |
virtual | ~PCLBase ()=default |
Destructor. More... | |
virtual void | setInputCloud (const PointCloudConstPtr &cloud) |
Provide a pointer to the input dataset. More... | |
PointCloudConstPtr const | getInputCloud () const |
Get a pointer to the input point cloud dataset. More... | |
virtual void | setIndices (const IndicesPtr &indices) |
Provide a pointer to the vector of indices that represents the input data. More... | |
virtual void | setIndices (const IndicesConstPtr &indices) |
Provide a pointer to the vector of indices that represents the input data. More... | |
virtual void | setIndices (const PointIndicesConstPtr &indices) |
Provide a pointer to the vector of indices that represents the input data. More... | |
virtual void | setIndices (std::size_t row_start, std::size_t col_start, std::size_t nb_rows, std::size_t nb_cols) |
Set the indices for the points laying within an interest region of the point cloud. More... | |
IndicesPtr | getIndices () |
Get a pointer to the vector of indices used. More... | |
IndicesConstPtr const | getIndices () const |
Get a pointer to the vector of indices used. More... | |
const PointSource & | operator[] (std::size_t pos) const |
Override PointCloud operator[] to shorten code. More... | |
Protected Member Functions | |
void | computeTransformation (PointCloudSource &output, const Eigen::Matrix4f &guess) override |
Rigid transformation computation method with initial guess. More... | |
Protected Member Functions inherited from pcl::Registration< PointSource, PointTarget, Scalar > | |
bool | searchForNeighbors (const PointCloudSource &cloud, int index, pcl::Indices &indices, std::vector< float > &distances) |
Search for the closest nearest neighbor of a given point. More... | |
virtual void | computeTransformation (PointCloudSource &output, const Matrix4 &guess)=0 |
Abstract transformation computation method with initial guess. More... | |
Protected Member Functions inherited from pcl::PCLBase< PointSource > | |
bool | initCompute () |
This method should get called before starting the actual computation. More... | |
bool | deinitCompute () |
This method should get called after finishing the actual computation. More... | |
Protected Attributes | |
Eigen::Vector2f | grid_centre_ |
Eigen::Vector2f | grid_step_ |
Eigen::Vector2f | grid_extent_ |
Eigen::Vector3d | newton_lambda_ |
Protected Attributes inherited from pcl::Registration< PointSource, PointTarget, Scalar > | |
std::string | reg_name_ |
The registration method name. More... | |
KdTreePtr | tree_ |
A pointer to the spatial search object. More... | |
KdTreeReciprocalPtr | tree_reciprocal_ |
A pointer to the spatial search object of the source. More... | |
int | nr_iterations_ {0} |
The number of iterations the internal optimization ran for (used internally). More... | |
int | max_iterations_ {10} |
The maximum number of iterations the internal optimization should run for. More... | |
int | ransac_iterations_ {0} |
The number of iterations RANSAC should run for. More... | |
PointCloudTargetConstPtr | target_ |
The input point cloud dataset target. More... | |
Matrix4 | final_transformation_ |
The final transformation matrix estimated by the registration method after N iterations. More... | |
Matrix4 | transformation_ |
The transformation matrix estimated by the registration method. More... | |
Matrix4 | previous_transformation_ |
The previous transformation matrix estimated by the registration method (used internally). More... | |
double | transformation_epsilon_ {0.0} |
The maximum difference between two consecutive transformations in order to consider convergence (user defined). More... | |
double | transformation_rotation_epsilon_ {0.0} |
The maximum rotation difference between two consecutive transformations in order to consider convergence (user defined). More... | |
double | euclidean_fitness_epsilon_ |
The maximum allowed Euclidean error between two consecutive steps in the ICP loop, before the algorithm is considered to have converged. More... | |
double | corr_dist_threshold_ |
The maximum distance threshold between two correspondent points in source <-> target. More... | |
double | inlier_threshold_ {0.05} |
The inlier distance threshold for the internal RANSAC outlier rejection loop. More... | |
bool | converged_ {false} |
Holds internal convergence state, given user parameters. More... | |
unsigned int | min_number_correspondences_ {3} |
The minimum number of correspondences that the algorithm needs before attempting to estimate the transformation. More... | |
CorrespondencesPtr | correspondences_ |
The set of correspondences determined at this ICP step. More... | |
TransformationEstimationPtr | transformation_estimation_ |
A TransformationEstimation object, used to calculate the 4x4 rigid transformation. More... | |
CorrespondenceEstimationPtr | correspondence_estimation_ |
A CorrespondenceEstimation object, used to estimate correspondences between the source and the target cloud. More... | |
std::vector< CorrespondenceRejectorPtr > | correspondence_rejectors_ |
The list of correspondence rejectors to use. More... | |
bool | target_cloud_updated_ {true} |
Variable that stores whether we have a new target cloud, meaning we need to pre-process it again. More... | |
bool | source_cloud_updated_ {true} |
Variable that stores whether we have a new source cloud, meaning we need to pre-process it again. More... | |
bool | force_no_recompute_ {false} |
A flag which, if set, means the tree operating on the target cloud will never be recomputed. More... | |
bool | force_no_recompute_reciprocal_ {false} |
A flag which, if set, means the tree operating on the source cloud will never be recomputed. More... | |
std::function< UpdateVisualizerCallbackSignature > | update_visualizer_ |
Callback function to update intermediate source point cloud position during it's registration to the target point cloud. More... | |
Protected Attributes inherited from pcl::PCLBase< PointSource > | |
PointCloudConstPtr | input_ |
The input point cloud dataset. More... | |
IndicesPtr | indices_ |
A pointer to the vector of point indices to use. More... | |
bool | use_indices_ |
Set to true if point indices are used. More... | |
bool | fake_indices_ |
If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. More... | |
NormalDistributionsTransform2D provides an implementation of the Normal Distributions Transform algorithm for scan matching.
This implementation is intended to match the definition: Peter Biber and Wolfgang Straßer. The normal distributions transform: A new approach to laser scan matching. In Proceedings of the IEEE In- ternational Conference on Intelligent Robots and Systems (IROS), pages 2743–2748, Las Vegas, USA, October 2003.
using pcl::NormalDistributionsTransform2D< PointSource, PointTarget >::ConstPtr = shared_ptr<const NormalDistributionsTransform2D<PointSource, PointTarget> > |
using pcl::NormalDistributionsTransform2D< PointSource, PointTarget >::Ptr = shared_ptr<NormalDistributionsTransform2D<PointSource, PointTarget> > |
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inline |
Empty constructor.
Definition at line 78 of file ndt_2d.h.
References pcl::Registration< PointSource, PointTarget, Scalar >::reg_name_.
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overridedefault |
Empty destructor.
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overrideprotected |
Rigid transformation computation method with initial guess.
[out] | output | the transformed input point cloud dataset using the rigid transformation found |
[in] | guess | the initial guess of the transformation to compute |
Definition at line 392 of file ndt_2d.hpp.
References pcl::ndt2d::ValueAndDerivatives< N, T >::grad, pcl::ndt2d::ValueAndDerivatives< N, T >::hessian, pcl::ndt2d::NDT2D< PointT >::test(), pcl::transformPointCloud(), pcl::ndt2d::ValueAndDerivatives< N, T >::value, and pcl::ndt2d::ValueAndDerivatives< N, T >::Zero().
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inlinevirtual |
centre of the ndt grid (target coordinate system)
centre | value to set |
Definition at line 95 of file ndt_2d.h.
References pcl::NormalDistributionsTransform2D< PointSource, PointTarget >::grid_centre_.
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inlinevirtual |
NDT Grid extent (in either direction from the grid centre)
[in] | extent | value to set |
Definition at line 113 of file ndt_2d.h.
References pcl::NormalDistributionsTransform2D< PointSource, PointTarget >::grid_extent_.
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inlinevirtual |
Grid spacing (step) of the NDT grid.
[in] | step | value to set |
Definition at line 104 of file ndt_2d.h.
References pcl::NormalDistributionsTransform2D< PointSource, PointTarget >::grid_step_.
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inlinevirtual |
NDT Newton optimisation step size parameter.
[in] | lambda | step size: 1 is simple newton optimisation, smaller values may improve convergence |
Definition at line 123 of file ndt_2d.h.
References pcl::NormalDistributionsTransform2D< PointSource, PointTarget >::newton_lambda_.
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inlinevirtual |
NDT Newton optimisation step size parameter.
[in] | lambda | step size: (1,1,1) is simple newton optimisation, smaller values may improve convergence, or elements may be set to zero to prevent optimisation over some parameters |
This overload allows control of updates to the individual (x, y, theta) free parameters in the optimisation. If, for example, theta is believed to be close to the correct value a small value of lambda[2] should be used.
Definition at line 139 of file ndt_2d.h.
References pcl::NormalDistributionsTransform2D< PointSource, PointTarget >::newton_lambda_.
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Definition at line 167 of file ndt_2d.h.
Referenced by pcl::NormalDistributionsTransform2D< PointSource, PointTarget >::setGridCentre().
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Definition at line 169 of file ndt_2d.h.
Referenced by pcl::NormalDistributionsTransform2D< PointSource, PointTarget >::setGridExtent().
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Definition at line 168 of file ndt_2d.h.
Referenced by pcl::NormalDistributionsTransform2D< PointSource, PointTarget >::setGridStep().
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protected |
Definition at line 170 of file ndt_2d.h.
Referenced by pcl::NormalDistributionsTransform2D< PointSource, PointTarget >::setOptimizationStepSize().