161 lines
8.4 KiB
C
161 lines
8.4 KiB
C
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// ----------------------------------------------------------------------------
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// - Open3D: www.open3d.org -
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// ----------------------------------------------------------------------------
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// Copyright (c) 2018-2023 www.open3d.org
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// SPDX-License-Identifier: MIT
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// ----------------------------------------------------------------------------
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#pragma once
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#include "open3d/core/Tensor.h"
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#include "open3d/t/pipelines/registration/Registration.h"
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#include "open3d/t/pipelines/registration/RobustKernel.h"
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namespace open3d {
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namespace t {
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namespace pipelines {
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namespace kernel {
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/// \brief Computes pose for point to plane registration method.
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///
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/// \param source_positions source point positions of Float32 or Float64 dtype.
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/// \param target_positions target point positions of same dtype as source point
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/// positions.
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/// \param target_normals target point normals of same dtype as source point
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/// positions.
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/// \param correspondence_indices Tensor of type Int64 containing indices of
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/// corresponding target positions, where the value is the target index and the
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/// index of the value itself is the source index. It contains -1 as value at
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/// index with no correspondence.
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/// \param kernel statistical robust kernel for outlier rejection.
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/// \return Pose [alpha beta gamma, tx, ty, tz], a shape {6} tensor of dtype
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/// Float64, where alpha, beta, gamma are the Euler angles in the ZYX order.
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core::Tensor ComputePosePointToPlane(const core::Tensor &source_positions,
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const core::Tensor &target_positions,
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const core::Tensor &target_normals,
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const core::Tensor &correspondence_indices,
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const registration::RobustKernel &kernel);
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/// \brief Computes pose for colored-icp registration method.
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///
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/// \param source_positions source point positions of Float32 or Float64 dtype.
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/// \param source_colors source point colors of same dtype as source point
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/// positions.
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/// \param target_positions target point positions of same dtype as source point
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/// positions.
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/// \param target_normals target point normals of same dtype as source point
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/// positions.
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/// \param target_colors target point colors of same dtype as source point
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/// positions.
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/// \param target_color_gradients targets point color gradients of same dtype as
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/// source point positions.
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/// \param correspondence_indices Tensor of type Int64 containing indices of
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/// corresponding target positions, where the value is the target index and the
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/// index of the value itself is the source index. It contains -1 as value at
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/// index with no correspondence.
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/// \param kernel statistical robust kernel for outlier rejection.
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/// \param lambda_geometric `λ ∈ [0,1]` in the overall energy `λEG + (1−λ)EC`.
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/// Refer the documentation of Colored-ICP for more information.
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/// \return Pose [alpha beta gamma, tx, ty, tz], a shape {6} tensor of dtype
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/// Float64, where alpha, beta, gamma are the Euler angles in the ZYX order.
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core::Tensor ComputePoseColoredICP(const core::Tensor &source_positions,
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const core::Tensor &source_colors,
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const core::Tensor &target_positions,
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const core::Tensor &target_normals,
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const core::Tensor &target_colors,
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const core::Tensor &target_color_gradients,
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const core::Tensor &correspondence_indices,
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const registration::RobustKernel &kernel,
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const double &lambda_geometric);
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/// \brief Computes pose for DopplerICP registration method.
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///
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/// \param source_points source point positions of Float32 or Float64 dtype.
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/// \param source_dopplers source point Dopplers of same dtype as source point
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/// positions.
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/// \param source_directions source point direction of same dtype as source
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/// point positions.
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/// \param target_points target point positions of same dtype as source point
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/// positions.
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/// \param target_normals target point normals of same dtype as source point
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/// positions.
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/// \param correspondence_indices Tensor of type Int64 containing indices of
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/// corresponding target positions, where the value is the target index and the
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/// index of the value itself is the source index. It contains -1 as value at
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/// index with no correspondence.
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/// \param current_transform The current pose estimate of ICP.
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/// \param transform_vehicle_to_sensor The 4x4 extrinsic transformation matrix
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/// between the vehicle and the sensor frames.
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/// \param iteration current iteration number of the ICP algorithm.
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/// \param period Time period (in seconds) between the source and the target
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/// point clouds.
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/// \param lambda_doppler weight for the Doppler objective.
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/// \param reject_dynamic_outliers Whether or not to prune dynamic point
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/// outlier correspondences.
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/// \param doppler_outlier_threshold Correspondences with Doppler error
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/// greater than this threshold are rejected from optimization.
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/// \param outlier_rejection_min_iteration Number of iterations of ICP after
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/// which outlier rejection is enabled.
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/// \param geometric_robust_loss_min_iteration Number of iterations of ICP
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/// after which robust loss for geometric term kicks in.
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/// \param doppler_robust_loss_min_iteration Number of iterations of ICP
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/// after which robust loss for Doppler term kicks in.
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/// \param geometric_kernel statistical robust kernel for outlier rejection.
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/// \param doppler_kernel statistical robust kernel for outlier rejection.
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/// \return Pose [alpha beta gamma, tx, ty, tz], a shape {6} tensor of dtype
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/// Float64, where alpha, beta, gamma are the Euler angles in the ZYX order.
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core::Tensor ComputePoseDopplerICP(
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const core::Tensor &source_points,
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const core::Tensor &source_dopplers,
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const core::Tensor &source_directions,
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const core::Tensor &target_points,
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const core::Tensor &target_normals,
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const core::Tensor &correspondence_indices,
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const core::Tensor ¤t_transform,
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const core::Tensor &transform_vehicle_to_sensor,
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const std::size_t iteration,
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const double period,
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const double lambda_doppler,
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const bool reject_dynamic_outliers,
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const double doppler_outlier_threshold,
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const std::size_t outlier_rejection_min_iteration,
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const std::size_t geometric_robust_loss_min_iteration,
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const std::size_t doppler_robust_loss_min_iteration,
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const registration::RobustKernel &geometric_kernel,
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const registration::RobustKernel &doppler_kernel);
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/// \brief Computes (R) Rotation {3,3} and (t) translation {3,}
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/// for point to point registration method.
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///
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/// \param source_positions source point positions of Float32 or Float64 dtype.
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/// \param target_positions target point positions of same dtype as source point
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/// positions.
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/// \param correspondence_indices Tensor of type Int64 containing indices of
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/// corresponding target positions, where the value is the target index and the
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/// index of the value itself is the source index. It contains -1 as value at
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/// index with no correspondence.
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/// \return tuple of (R, t). [Dtype: Float64].
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std::tuple<core::Tensor, core::Tensor> ComputeRtPointToPoint(
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const core::Tensor &source_positions,
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const core::Tensor &target_positions,
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const core::Tensor &correspondence_indices);
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/// \brief Computes `Information Matrix` of shape {6, 6}, of dtype `Float64` on
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/// device `CPU:0`, from the target point cloud and correspondence indices
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/// w.r.t. target point cloud.
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/// Only target positions and correspondence indices are required.
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///
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/// \param target_positions The target point positions.
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/// \param correspondence_indices Tensor of type Int64 containing indices of
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/// corresponding target positions, where the value is the target index and the
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/// index of the value itself is the source index. It contains -1 as value
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/// at index with no correspondence.
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core::Tensor ComputeInformationMatrix(
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const core::Tensor &target_positions,
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const core::Tensor &correspondence_indices);
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} // namespace kernel
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} // namespace pipelines
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} // namespace t
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} // namespace open3d
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