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fix(autoware_ndt_scan_matcher): fix cppcheck unusedFunction #9275

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Nov 11, 2024
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fix(autoware_ndt_scan_matcher): fix cppcheck unusedFunction #9275

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8 changes: 0 additions & 8 deletions ...toware_ndt_scan_matcher/include/autoware/ndt_scan_matcher/ndt_omp/estimate_covariance.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -48,14 +48,6 @@ ResultOfMultiNdtCovarianceEstimation estimate_xy_covariance_by_multi_ndt_score(
pclomp::MultiGridNormalDistributionsTransform<pcl::PointXYZ, pcl::PointXYZ>> & ndt_ptr,
const std::vector<Eigen::Matrix4f> & poses_to_search, const double temperature);

/** \brief Find rotation matrix aligning covariance to principal axes
* (1) Compute eigenvalues and eigenvectors
* (2) Compute angle for first eigenvector
* (3) Return rotation matrix
*/
Eigen::Matrix2d find_rotation_matrix_aligning_covariance_to_principal_axes(
const Eigen::Matrix2d & matrix);

/** \brief Propose poses to search.
* (1) Compute covariance by Laplace approximation
* (2) Find rotation matrix aligning covariance to principal axes
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21 changes: 0 additions & 21 deletions localization/autoware_ndt_scan_matcher/src/ndt_omp/estimate_covariance.cpp
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Expand Up @@ -103,34 +103,13 @@ ResultOfMultiNdtCovarianceEstimation estimate_xy_covariance_by_multi_ndt_score(
return {mean, covariance, poses_to_search, ndt_results};
}

Eigen::Matrix2d find_rotation_matrix_aligning_covariance_to_principal_axes(
const Eigen::Matrix2d & matrix)
{
const Eigen::SelfAdjointEigenSolver<Eigen::Matrix2d> eigensolver(matrix);
if (eigensolver.info() == Eigen::Success) {
const Eigen::Vector2d eigen_vec = eigensolver.eigenvectors().col(0);
const double th = std::atan2(eigen_vec.y(), eigen_vec.x());
return Eigen::Rotation2Dd(th).toRotationMatrix();
}
throw std::runtime_error("Eigen solver failed. Return output_pose_covariance value.");
}

std::vector<Eigen::Matrix4f> propose_poses_to_search(
const NdtResult & ndt_result, const std::vector<double> & offset_x,
const std::vector<double> & offset_y)
{
assert(offset_x.size() == offset_y.size());
const Eigen::Matrix4f & center_pose = ndt_result.pose;

// (1) calculate rot by pose (default)
const Eigen::Matrix2d rot = ndt_result.pose.topLeftCorner<2, 2>().cast<double>();

// (2) calculate rot by covariance (alternative)
// const Eigen::Matrix<double, 6, 6> & hessian = ndt_result.hessian;
// const Eigen::Matrix2d covariance = estimate_xy_covariance_by_Laplace_approximation(hessian);
// const Eigen::Matrix2d rot =
// find_rotation_matrix_aligning_covariance_to_principal_axes(-covariance);

std::vector<Eigen::Matrix4f> poses_to_search;
for (int i = 0; i < static_cast<int>(offset_x.size()); i++) {
const Eigen::Vector2d pose_offset(offset_x[i], offset_y[i]);
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