/* * Copyright 2016 The Cartographer Authors * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ #ifndef CARTOGRAPHER_MAPPING_INTERNAL_3D_SCAN_MATCHING_INTERPOLATED_GRID_H_ #define CARTOGRAPHER_MAPPING_INTERNAL_3D_SCAN_MATCHING_INTERPOLATED_GRID_H_ #include #include "hybrid_grid.hpp" // Interpolates between HybridGrid voxels. We use the tricubic // interpolation which interpolates the values and has vanishing derivative at // these points. // // This class is templated to work with the autodiff that Ceres provides. // For this reason, it is also important that the interpolation scheme be // continuously differentiable. template class InterpolatedGrid { public: explicit InterpolatedGrid(const HybridGridType& hybrid_grid) : hybrid_grid_(hybrid_grid) {} InterpolatedGrid(const InterpolatedGrid&) = delete; InterpolatedGrid& operator=(const InterpolatedGrid&) = delete; // Returns the interpolated value at (x, y, z) of the HybridGrid // used to perform the interpolation. // // This is a piecewise, continuously differentiable function. We use the // scalar part of Jet parameters to select our interval below. It is the // tensor product volume of piecewise cubic polynomials that interpolate // the values, and have vanishing derivative at the interval boundaries. template T GetInterpolatedValue(const T& x, const T& y, const T& z) const { double x1, y1, z1, x2, y2, z2; ComputeInterpolationDataPoints(x, y, z, &x1, &y1, &z1, &x2, &y2, &z2); const Eigen::Array3i index1 = hybrid_grid_.GetCellIndex(Eigen::Vector3f(x1, y1, z1)); const double q111 = GetValue(hybrid_grid_, index1); const double q112 = GetValue(hybrid_grid_, index1 + Eigen::Array3i(0, 0, 1)); const double q121 = GetValue(hybrid_grid_, index1 + Eigen::Array3i(0, 1, 0)); const double q122 = GetValue(hybrid_grid_, index1 + Eigen::Array3i(0, 1, 1)); const double q211 = GetValue(hybrid_grid_, index1 + Eigen::Array3i(1, 0, 0)); const double q212 = GetValue(hybrid_grid_, index1 + Eigen::Array3i(1, 0, 1)); const double q221 = GetValue(hybrid_grid_, index1 + Eigen::Array3i(1, 1, 0)); const double q222 = GetValue(hybrid_grid_, index1 + Eigen::Array3i(1, 1, 1)); const T normalized_x = (x - x1) / (x2 - x1); const T normalized_y = (y - y1) / (y2 - y1); const T normalized_z = (z - z1) / (z2 - z1); // Compute pow(..., 2) and pow(..., 3). Using pow() here is very expensive. const T normalized_xx = normalized_x * normalized_x; const T normalized_xxx = normalized_x * normalized_xx; const T normalized_yy = normalized_y * normalized_y; const T normalized_yyy = normalized_y * normalized_yy; const T normalized_zz = normalized_z * normalized_z; const T normalized_zzz = normalized_z * normalized_zz; // We first interpolate in z, then y, then x. All 7 times this uses the same // scheme: A * (2t^3 - 3t^2 + 1) + B * (-2t^3 + 3t^2). // The first polynomial is 1 at t=0, 0 at t=1, the second polynomial is 0 // at t=0, 1 at t=1. Both polynomials have derivative zero at t=0 and t=1. const T q11 = (q111 - q112) * normalized_zzz * 2. + (q112 - q111) * normalized_zz * 3. + q111; const T q12 = (q121 - q122) * normalized_zzz * 2. + (q122 - q121) * normalized_zz * 3. + q121; const T q21 = (q211 - q212) * normalized_zzz * 2. + (q212 - q211) * normalized_zz * 3. + q211; const T q22 = (q221 - q222) * normalized_zzz * 2. + (q222 - q221) * normalized_zz * 3. + q221; const T q1 = (q11 - q12) * normalized_yyy * 2. + (q12 - q11) * normalized_yy * 3. + q11; const T q2 = (q21 - q22) * normalized_yyy * 2. + (q22 - q21) * normalized_yy * 3. + q21; return (q1 - q2) * normalized_xxx * 2. + (q2 - q1) * normalized_xx * 3. + q1; } private: template void ComputeInterpolationDataPoints(const T& x, const T& y, const T& z, double* x1, double* y1, double* z1, double* x2, double* y2, double* z2) const { const Eigen::Vector3f lower = CenterOfLowerVoxel(x, y, z); *x1 = lower.x(); *y1 = lower.y(); *z1 = lower.z(); *x2 = lower.x() + hybrid_grid_.resolution(); *y2 = lower.y() + hybrid_grid_.resolution(); *z2 = lower.z() + hybrid_grid_.resolution(); } // Center of the next lower voxel, i.e., not necessarily the voxel containing // (x, y, z). For each dimension, the largest voxel index so that the // corresponding center is at most the given coordinate. Eigen::Vector3f CenterOfLowerVoxel(const double x, const double y, const double z) const { // Center of the cell containing (x, y, z). Eigen::Vector3f center = hybrid_grid_.GetCenterOfCell( hybrid_grid_.GetCellIndex(Eigen::Vector3f(x, y, z))); // Move to the next lower voxel center. if (center.x() > x) { center.x() -= hybrid_grid_.resolution(); } if (center.y() > y) { center.y() -= hybrid_grid_.resolution(); } if (center.z() > z) { center.z() -= hybrid_grid_.resolution(); } return center; } // Uses the scalar part of a Ceres Jet. template Eigen::Vector3f CenterOfLowerVoxel(const T& jet_x, const T& jet_y, const T& jet_z) const { return CenterOfLowerVoxel(jet_x.a, jet_y.a, jet_z.a); } static float GetValue(const HybridGrid& probability_grid, const Eigen::Array3i& index) { return probability_grid.GetProbability(index); } const HybridGridType& hybrid_grid_; }; using InterpolatedProbabilityGrid = InterpolatedGrid; #endif // CARTOGRAPHER_MAPPING_INTERNAL_3D_SCAN_MATCHING_INTERPOLATED_GRID_H_