Add rotational score histograms in 3D. (#403)
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167047173c
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10a19d0a3f
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@ -106,21 +106,23 @@ bool FastCorrelativeScanMatcher::Match(
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const transform::Rigid3d& initial_pose_estimate,
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const sensor::PointCloud& coarse_point_cloud,
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const sensor::PointCloud& fine_point_cloud, const float min_score,
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float* const score, transform::Rigid3d* const pose_estimate) const {
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float* const score, transform::Rigid3d* const pose_estimate,
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float* const rotational_score) const {
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const SearchParameters search_parameters{
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common::RoundToInt(options_.linear_xy_search_window() / resolution_),
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common::RoundToInt(options_.linear_z_search_window() / resolution_),
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options_.angular_search_window()};
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return MatchWithSearchParameters(search_parameters, initial_pose_estimate,
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coarse_point_cloud, fine_point_cloud,
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min_score, score, pose_estimate);
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return MatchWithSearchParameters(
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search_parameters, initial_pose_estimate, coarse_point_cloud,
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fine_point_cloud, min_score, score, pose_estimate, rotational_score);
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}
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bool FastCorrelativeScanMatcher::MatchFullSubmap(
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const Eigen::Quaterniond& gravity_alignment,
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const sensor::PointCloud& coarse_point_cloud,
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const sensor::PointCloud& fine_point_cloud, const float min_score,
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float* const score, transform::Rigid3d* const pose_estimate) const {
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float* const score, transform::Rigid3d* const pose_estimate,
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float* const rotational_score) const {
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const transform::Rigid3d initial_pose_estimate(Eigen::Vector3d::Zero(),
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gravity_alignment);
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float max_point_distance = 0.f;
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@ -132,9 +134,9 @@ bool FastCorrelativeScanMatcher::MatchFullSubmap(
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common::RoundToInt(max_point_distance / resolution_ + 0.5f);
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const SearchParameters search_parameters{linear_window_size,
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linear_window_size, M_PI};
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return MatchWithSearchParameters(search_parameters, initial_pose_estimate,
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coarse_point_cloud, fine_point_cloud,
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min_score, score, pose_estimate);
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return MatchWithSearchParameters(
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search_parameters, initial_pose_estimate, coarse_point_cloud,
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fine_point_cloud, min_score, score, pose_estimate, rotational_score);
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}
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bool FastCorrelativeScanMatcher::MatchWithSearchParameters(
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@ -142,7 +144,8 @@ bool FastCorrelativeScanMatcher::MatchWithSearchParameters(
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const transform::Rigid3d& initial_pose_estimate,
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const sensor::PointCloud& coarse_point_cloud,
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const sensor::PointCloud& fine_point_cloud, const float min_score,
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float* const score, transform::Rigid3d* const pose_estimate) const {
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float* const score, transform::Rigid3d* const pose_estimate,
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float* const rotational_score) const {
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CHECK_NOTNULL(score);
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CHECK_NOTNULL(pose_estimate);
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@ -158,12 +161,14 @@ bool FastCorrelativeScanMatcher::MatchWithSearchParameters(
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precomputation_grid_stack_->max_depth(), min_score);
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if (best_candidate.score > min_score) {
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*score = best_candidate.score;
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const auto& discrete_scan = discrete_scans[best_candidate.scan_index];
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*pose_estimate =
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(transform::Rigid3f(
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resolution_ * best_candidate.offset.matrix().cast<float>(),
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Eigen::Quaternionf::Identity()) *
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discrete_scans[best_candidate.scan_index].pose)
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discrete_scan.pose)
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.cast<double>();
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*rotational_score = discrete_scan.rotational_score;
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return true;
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}
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return false;
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@ -171,8 +176,8 @@ bool FastCorrelativeScanMatcher::MatchWithSearchParameters(
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DiscreteScan FastCorrelativeScanMatcher::DiscretizeScan(
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const FastCorrelativeScanMatcher::SearchParameters& search_parameters,
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const sensor::PointCloud& point_cloud,
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const transform::Rigid3f& pose) const {
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const sensor::PointCloud& point_cloud, const transform::Rigid3f& pose,
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const float rotational_score) const {
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std::vector<std::vector<Eigen::Array3i>> cell_indices_per_depth;
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const PrecomputationGrid& original_grid = precomputation_grid_stack_->Get(0);
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std::vector<Eigen::Array3i> full_resolution_cell_indices;
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@ -210,7 +215,7 @@ DiscreteScan FastCorrelativeScanMatcher::DiscretizeScan(
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low_resolution_cell_at_start - low_resolution_search_window_start);
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}
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}
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return DiscreteScan{pose, cell_indices_per_depth};
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return DiscreteScan{pose, cell_indices_per_depth, rotational_score};
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}
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std::vector<DiscreteScan> FastCorrelativeScanMatcher::GenerateDiscreteScans(
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@ -253,7 +258,7 @@ std::vector<DiscreteScan> FastCorrelativeScanMatcher::GenerateDiscreteScans(
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transform::AngleAxisVectorToRotationQuaternion(angle_axis) *
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initial_pose.rotation());
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result.push_back(
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DiscretizeScan(search_parameters, coarse_point_cloud, pose));
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DiscretizeScan(search_parameters, coarse_point_cloud, pose, scores[i]));
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}
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return result;
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}
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@ -46,6 +46,7 @@ struct DiscreteScan {
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transform::Rigid3f pose;
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// Contains a vector of discretized scans for each 'depth'.
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std::vector<std::vector<Eigen::Array3i>> cell_indices_per_depth;
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float rotational_score;
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};
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struct Candidate {
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@ -81,24 +82,27 @@ class FastCorrelativeScanMatcher {
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// Aligns 'coarse_point_cloud' within the 'hybrid_grid' given an
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// 'initial_pose_estimate'. If a score above 'min_score' (excluding equality)
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// is possible, true is returned, and 'score' and 'pose_estimate' are updated
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// with the result. 'fine_point_cloud' is used to compute the rotational scan
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// matcher score.
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// is possible, true is returned, and 'score', 'pose_estimate', and
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// 'rotational_score' are updated with the result. 'fine_point_cloud' is used
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// to compute the rotational scan matcher score.
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bool Match(const transform::Rigid3d& initial_pose_estimate,
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const sensor::PointCloud& coarse_point_cloud,
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const sensor::PointCloud& fine_point_cloud, float min_score,
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float* score, transform::Rigid3d* pose_estimate) const;
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float* score, transform::Rigid3d* pose_estimate,
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float* rotational_score) const;
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// Aligns 'coarse_point_cloud' within the 'hybrid_grid' given a rotation which
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// is expected to be approximately gravity aligned. If a score above
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// 'min_score' (excluding equality) is possible, true is returned, and 'score'
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// and 'pose_estimate' are updated with the result. 'fine_point_cloud' is used
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// to compute the rotational scan matcher score.
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// 'min_score' (excluding equality) is possible, true is returned, and
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// 'score', 'pose_estimate', and 'rotational_score' are updated with the
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// result. 'fine_point_cloud' is used to compute the rotational scan matcher
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// score.
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bool MatchFullSubmap(const Eigen::Quaterniond& gravity_alignment,
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const sensor::PointCloud& coarse_point_cloud,
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const sensor::PointCloud& fine_point_cloud,
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float min_score, float* score,
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transform::Rigid3d* pose_estimate) const;
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transform::Rigid3d* pose_estimate,
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float* rotational_score) const;
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private:
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struct SearchParameters {
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@ -112,10 +116,11 @@ class FastCorrelativeScanMatcher {
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const transform::Rigid3d& initial_pose_estimate,
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const sensor::PointCloud& coarse_point_cloud,
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const sensor::PointCloud& fine_point_cloud, float min_score, float* score,
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transform::Rigid3d* pose_estimate) const;
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transform::Rigid3d* pose_estimate, float* rotational_score) const;
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DiscreteScan DiscretizeScan(const SearchParameters& search_parameters,
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const sensor::PointCloud& point_cloud,
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const transform::Rigid3f& pose) const;
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const transform::Rigid3f& pose,
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float rotational_score) const;
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std::vector<DiscreteScan> GenerateDiscreteScans(
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const SearchParameters& search_parameters,
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const sensor::PointCloud& coarse_point_cloud,
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@ -98,12 +98,14 @@ TEST(FastCorrelativeScanMatcherTest, CorrectPose) {
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FastCorrelativeScanMatcher fast_correlative_scan_matcher(hybrid_grid, {},
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options);
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float score = 0.f;
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transform::Rigid3d pose_estimate;
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float score;
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float rotational_score = 0.f;
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EXPECT_TRUE(fast_correlative_scan_matcher.Match(
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transform::Rigid3d::Identity(), point_cloud, point_cloud, kMinScore,
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&score, &pose_estimate));
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&score, &pose_estimate, &rotational_score));
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EXPECT_LT(kMinScore, score);
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EXPECT_LT(0.09f, rotational_score);
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EXPECT_THAT(expected_pose,
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transform::IsNearly(pose_estimate.cast<float>(), 0.05f))
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<< "Actual: " << transform::ToProto(pose_estimate).DebugString()
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@ -181,8 +181,9 @@ void ConstraintBuilder::ComputeConstraint(
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// The 'constraint_transform' (submap i <- scan j) is computed from:
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// - a 'filtered_point_cloud' in scan j and
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// - the initial guess 'initial_pose' (submap i <- scan j).
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float score = 0.;
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float score = 0.f;
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transform::Rigid3d pose_estimate;
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float rotational_score = 0.f;
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// Compute 'pose_estimate' in three stages:
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// 1. Fast estimate using the fast correlative scan matcher.
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@ -191,7 +192,8 @@ void ConstraintBuilder::ComputeConstraint(
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if (match_full_submap) {
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if (submap_scan_matcher->fast_correlative_scan_matcher->MatchFullSubmap(
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initial_pose.rotation(), filtered_point_cloud, point_cloud,
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options_.global_localization_min_score(), &score, &pose_estimate)) {
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options_.global_localization_min_score(), &score, &pose_estimate,
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&rotational_score)) {
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CHECK_GT(score, options_.global_localization_min_score());
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CHECK_GE(node_id.trajectory_id, 0);
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CHECK_GE(submap_id.trajectory_id, 0);
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@ -203,7 +205,7 @@ void ConstraintBuilder::ComputeConstraint(
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} else {
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if (submap_scan_matcher->fast_correlative_scan_matcher->Match(
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initial_pose, filtered_point_cloud, point_cloud,
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options_.min_score(), &score, &pose_estimate)) {
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options_.min_score(), &score, &pose_estimate, &rotational_score)) {
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// We've reported a successful local match.
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CHECK_GT(score, options_.min_score());
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} else {
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@ -213,6 +215,7 @@ void ConstraintBuilder::ComputeConstraint(
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{
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common::MutexLocker locker(&mutex_);
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score_histogram_.Add(score);
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rotational_score_histogram_.Add(rotational_score);
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}
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// Use the CSM estimate as both the initial and previous pose. This has the
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@ -282,6 +285,8 @@ void ConstraintBuilder::FinishComputation(const int computation_index) {
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LOG(INFO) << constraints_.size() << " computations resulted in "
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<< result.size() << " additional constraints.";
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LOG(INFO) << "Score histogram:\n" << score_histogram_.ToString(10);
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LOG(INFO) << "Rotational score histogram:\n"
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<< rotational_score_histogram_.ToString(10);
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}
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constraints_.clear();
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callback = std::move(when_done_);
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@ -185,8 +185,9 @@ class ConstraintBuilder {
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const sensor::AdaptiveVoxelFilter adaptive_voxel_filter_;
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scan_matching::CeresScanMatcher ceres_scan_matcher_;
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// Histogram of scan matcher scores.
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// Histograms of scan matcher scores.
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common::Histogram score_histogram_ GUARDED_BY(mutex_);
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common::Histogram rotational_score_histogram_ GUARDED_BY(mutex_);
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};
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} // namespace sparse_pose_graph
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