185 lines
7.3 KiB
C
185 lines
7.3 KiB
C
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/*
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* Software License Agreement (BSD License)
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*
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* Point Cloud Library (PCL) - www.pointclouds.org
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* Copyright (c) 2010-2012, Willow Garage, Inc.
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*
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above
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* copyright notice, this list of conditions and the following
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* disclaimer in the documentation and/or other materials provided
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* with the distribution.
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* * Neither the name of Willow Garage, Inc. nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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* $Id$
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*
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*/
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/*
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* trimmed_icp.h
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*
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* Created on: Mar 10, 2013
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* Author: papazov
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*/
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#pragma once
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#include <pcl/registration/transformation_estimation_svd.h>
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#include <pcl/kdtree/kdtree_flann.h>
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#include <pcl/correspondence.h>
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#include <pcl/point_cloud.h>
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#include <pcl/pcl_exports.h>
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#include <limits>
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#include <pcl/recognition/ransac_based/auxiliary.h>
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namespace pcl
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{
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namespace recognition
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{
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template<typename PointT, typename Scalar>
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class PCL_EXPORTS TrimmedICP: public pcl::registration::TransformationEstimationSVD<PointT, PointT, Scalar>
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{
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public:
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using PointCloud = pcl::PointCloud<PointT>;
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using PointCloudConstPtr = typename PointCloud::ConstPtr;
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using Matrix4 = typename Eigen::Matrix<Scalar, 4, 4>;
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public:
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TrimmedICP ()
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: new_to_old_energy_ratio_ (0.99f)
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{}
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~TrimmedICP ()
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{}
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/** \brief Call this method before calling align().
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*
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* \param[in] target is target point cloud. The method builds a kd-tree based on 'target' for performing fast closest point search.
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* The source point cloud will be registered to 'target' (see align() method).
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* */
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inline void
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init (const PointCloudConstPtr& target)
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{
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target_points_ = target;
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kdtree_.setInputCloud (target);
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}
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/** \brief The method performs trimmed ICP, i.e., it rigidly registers the source to the target (passed to the init() method).
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*
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* \param[in] source_points is the point cloud to be registered to the target.
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* \param[in] num_source_points_to_use gives the number of closest source points taken into account for registration. By closest
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* source points we mean the source points closest to the target. These points are computed anew at each iteration.
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* \param[in,out] guess_and_result is the estimated rigid transform. IMPORTANT: this matrix is also taken as the initial guess
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* for the alignment. If there is no guess, set the matrix to identity!
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* */
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inline void
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align (const PointCloud& source_points, int num_source_points_to_use, Matrix4& guess_and_result) const
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{
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int num_trimmed_source_points = num_source_points_to_use, num_source_points = static_cast<int> (source_points.size ());
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if ( num_trimmed_source_points >= num_source_points )
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{
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printf ("WARNING in 'TrimmedICP::%s()': the user-defined number of source points of interest is greater or equal to "
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"the total number of source points. Trimmed ICP will work correctly but won't be very efficient. Either set "
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"the number of source points to use to a lower value or use standard ICP.\n", __func__);
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num_trimmed_source_points = num_source_points;
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}
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// These are vectors containing source to target correspondences
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pcl::Correspondences full_src_to_tgt (num_source_points), trimmed_src_to_tgt (num_trimmed_source_points);
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// Some variables for the closest point search
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pcl::PointXYZ transformed_source_point;
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pcl::Indices target_index (1);
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std::vector<float> sqr_dist_to_target (1);
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float old_energy, energy = std::numeric_limits<float>::max ();
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// printf ("\nalign\n");
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do
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{
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// Update the correspondences
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for ( int i = 0 ; i < num_source_points ; ++i )
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{
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// Transform the i-th source point based on the current transform matrix
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aux::transform (guess_and_result, source_points[i], transformed_source_point);
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// Perform the closest point search
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kdtree_.nearestKSearch (transformed_source_point, 1, target_index, sqr_dist_to_target);
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// Update the i-th correspondence
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full_src_to_tgt[i].index_query = i;
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full_src_to_tgt[i].index_match = target_index[0];
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full_src_to_tgt[i].distance = sqr_dist_to_target[0];
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}
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// Sort in ascending order according to the squared distance
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std::sort (full_src_to_tgt.begin (), full_src_to_tgt.end (), TrimmedICP::compareCorrespondences);
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old_energy = energy;
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energy = 0.0f;
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// Now, setup the trimmed correspondences used for the transform estimation
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for ( int i = 0 ; i < num_trimmed_source_points ; ++i )
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{
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trimmed_src_to_tgt[i].index_query = full_src_to_tgt[i].index_query;
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trimmed_src_to_tgt[i].index_match = full_src_to_tgt[i].index_match;
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energy += full_src_to_tgt[i].distance;
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}
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this->estimateRigidTransformation (source_points, *target_points_, trimmed_src_to_tgt, guess_and_result);
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// printf ("energy = %f, energy diff. = %f, ratio = %f\n", energy, old_energy - energy, energy/old_energy);
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}
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while ( energy/old_energy < new_to_old_energy_ratio_ ); // iterate if enough progress
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// printf ("\n");
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}
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inline void
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setNewToOldEnergyRatio (float ratio)
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{
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if ( ratio >= 1 )
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new_to_old_energy_ratio_ = 0.99f;
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else
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new_to_old_energy_ratio_ = ratio;
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}
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protected:
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static inline bool
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compareCorrespondences (const pcl::Correspondence& a, const pcl::Correspondence& b)
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{
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return a.distance < b.distance;
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}
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protected:
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PointCloudConstPtr target_points_;
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pcl::KdTreeFLANN<PointT> kdtree_;
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float new_to_old_energy_ratio_;
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};
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} // namespace recognition
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} // namespace pcl
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