Skip to content

Add alignment unit test for IterativeClosestPointWithNormals #6454

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
mvieth merged 1 commit into from
Aug 10, 2026
+37 −0
Merged

Add alignment unit test for IterativeClosestPointWithNormals #6454

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
37 changes: 37 additions & 0 deletions test/registration/test_registration.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -269,6 +269,39 @@ TEST (PCL, IterativeClosestPoint)
EXPECT_EQ (transformation (3, 3), 1);
}

template <typename Scalar> void
runICPWithNormals ()
{
using PointT = PointNormal;
PointCloud<PointT>::Ptr src (new PointCloud<PointT>);
copyPointCloud (cloud_source, *src);
PointCloud<PointT>::Ptr tgt (new PointCloud<PointT>);
copyPointCloud (cloud_target, *tgt);
PointCloud<PointT> output;

// IterativeClosestPointWithNormals needs normals on both clouds
NormalEstimation<PointT, PointT> norm_est;
norm_est.setSearchMethod (search::KdTree<PointT>::Ptr (new search::KdTree<PointT>));
norm_est.setKSearch (10);
norm_est.setInputCloud (src);
norm_est.compute (*src);
norm_est.setInputCloud (tgt);
norm_est.compute (*tgt);

IterativeClosestPointWithNormals<PointT, PointT, Scalar> reg;
reg.setInputSource (src);
reg.setInputTarget (tgt);
reg.setMaximumIterations (50);
reg.setTransformationEpsilon (1e-8);
reg.setMaxCorrespondenceDistance (0.05);

// Register and check that the alignment succeeded
reg.align (output);
EXPECT_EQ (output.size (), cloud_source.size ());
EXPECT_TRUE (reg.hasConverged ());
EXPECT_LT (reg.getFitnessScore (), 0.001);
}

TEST (PCL, IterativeClosestPointWithNormals)
{
IterativeClosestPointWithNormals<PointNormal, PointNormal, float> reg_float;
Expand All @@ -278,6 +311,10 @@ TEST (PCL, IterativeClosestPointWithNormals)
IterativeClosestPointWithNormals<PointNormal, PointNormal, double> reg_double;
reg_double.setUseSymmetricObjective(true);
EXPECT_TRUE(reg_double.getUseSymmetricObjective());

// Test the actual alignment for both float and double precision
runICPWithNormals<float> ();
runICPWithNormals<double> ();
}

////////////////////////////////////////////////////////////////////////////////////////////////////////
Expand Down
Loading