FastCorrelativeScanMatcher outputs unique_ptr. (#643)
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e21fc9f253
commit
6eaf0f344d
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@ -156,12 +156,12 @@ FastCorrelativeScanMatcher::FastCorrelativeScanMatcher(
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FastCorrelativeScanMatcher::~FastCorrelativeScanMatcher() {}
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bool FastCorrelativeScanMatcher::Match(
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std::unique_ptr<FastCorrelativeScanMatcher::Result>
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FastCorrelativeScanMatcher::Match(
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const transform::Rigid3d& global_node_pose,
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const transform::Rigid3d& global_submap_pose,
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const mapping::TrajectoryNode::Data& constant_data, const float min_score,
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float* const score, transform::Rigid3d* const pose_estimate,
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float* const rotational_score, float* const low_resolution_score) const {
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const mapping::TrajectoryNode::Data& constant_data,
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const float min_score) const {
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const auto low_resolution_matcher = scan_matching::CreateLowResolutionMatcher(
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low_resolution_hybrid_grid_, &constant_data.low_resolution_point_cloud);
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const SearchParameters search_parameters{
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@ -173,16 +173,15 @@ bool FastCorrelativeScanMatcher::Match(
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global_submap_pose.cast<float>(),
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constant_data.high_resolution_point_cloud,
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constant_data.rotational_scan_matcher_histogram,
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constant_data.gravity_alignment, min_score, score, pose_estimate,
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rotational_score, low_resolution_score);
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constant_data.gravity_alignment, min_score);
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}
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bool FastCorrelativeScanMatcher::MatchFullSubmap(
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std::unique_ptr<FastCorrelativeScanMatcher::Result>
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FastCorrelativeScanMatcher::MatchFullSubmap(
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const Eigen::Quaterniond& global_node_rotation,
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const Eigen::Quaterniond& global_submap_rotation,
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const mapping::TrajectoryNode::Data& constant_data, const float min_score,
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float* const score, transform::Rigid3d* const pose_estimate,
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float* const rotational_score, float* const low_resolution_score) const {
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const mapping::TrajectoryNode::Data& constant_data,
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const float min_score) const {
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float max_point_distance = 0.f;
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for (const Eigen::Vector3f& point :
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constant_data.high_resolution_point_cloud) {
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@ -201,22 +200,17 @@ bool FastCorrelativeScanMatcher::MatchFullSubmap(
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transform::Rigid3f::Rotation(global_submap_rotation.cast<float>()),
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constant_data.high_resolution_point_cloud,
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constant_data.rotational_scan_matcher_histogram,
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constant_data.gravity_alignment, min_score, score, pose_estimate,
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rotational_score, low_resolution_score);
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constant_data.gravity_alignment, min_score);
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}
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bool FastCorrelativeScanMatcher::MatchWithSearchParameters(
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std::unique_ptr<FastCorrelativeScanMatcher::Result>
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FastCorrelativeScanMatcher::MatchWithSearchParameters(
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const FastCorrelativeScanMatcher::SearchParameters& search_parameters,
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const transform::Rigid3f& global_node_pose,
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const transform::Rigid3f& global_submap_pose,
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const sensor::PointCloud& point_cloud,
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const Eigen::VectorXf& rotational_scan_matcher_histogram,
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const Eigen::Quaterniond& gravity_alignment, const float min_score,
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float* const score, transform::Rigid3d* const pose_estimate,
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float* const rotational_score, float* const low_resolution_score) const {
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CHECK_NOTNULL(score);
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CHECK_NOTNULL(pose_estimate);
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const Eigen::Quaterniond& gravity_alignment, const float min_score) const {
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const std::vector<DiscreteScan> discrete_scans = GenerateDiscreteScans(
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search_parameters, point_cloud, rotational_scan_matcher_histogram,
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gravity_alignment, global_node_pose, global_submap_pose);
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@ -228,15 +222,13 @@ bool FastCorrelativeScanMatcher::MatchWithSearchParameters(
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search_parameters, discrete_scans, lowest_resolution_candidates,
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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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*pose_estimate =
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GetPoseFromCandidate(discrete_scans, best_candidate).cast<double>();
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*rotational_score =
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discrete_scans[best_candidate.scan_index].rotational_score;
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*low_resolution_score = best_candidate.low_resolution_score;
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return true;
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return common::make_unique<Result>(Result{
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best_candidate.score,
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GetPoseFromCandidate(discrete_scans, best_candidate).cast<double>(),
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discrete_scans[best_candidate.scan_index].rotational_score,
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best_candidate.low_resolution_score});
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}
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return false;
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return nullptr;
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}
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DiscreteScan FastCorrelativeScanMatcher::DiscretizeScan(
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@ -49,6 +49,13 @@ using MatchingFunction = std::function<float(const transform::Rigid3f&)>;
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class FastCorrelativeScanMatcher {
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public:
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struct Result {
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float score;
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transform::Rigid3d pose_estimate;
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float rotational_score;
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float low_resolution_score;
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};
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FastCorrelativeScanMatcher(
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const HybridGrid& hybrid_grid,
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const HybridGrid* low_resolution_hybrid_grid,
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@ -61,28 +68,23 @@ class FastCorrelativeScanMatcher {
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delete;
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// Aligns the node with the given 'constant_data' within the 'hybrid_grid'
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// given 'global_node_pose' and 'global_submap_pose'. If a score above
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// 'min_score' (excluding equality) is possible, true is returned, and
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// 'score', 'pose_estimate', 'rotational_score', and 'low_resolution_score'
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// are updated with the result.
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bool Match(const transform::Rigid3d& global_node_pose,
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const transform::Rigid3d& global_submap_pose,
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const mapping::TrajectoryNode::Data& constant_data,
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float min_score, float* score, transform::Rigid3d* pose_estimate,
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float* rotational_score, float* low_resolution_score) const;
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// given 'global_node_pose' and 'global_submap_pose'. 'Result' is only
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// returned if a score above 'min_score' (excluding equality) is possible.
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std::unique_ptr<Result> Match(
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const transform::Rigid3d& global_node_pose,
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const transform::Rigid3d& global_submap_pose,
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const mapping::TrajectoryNode::Data& constant_data,
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float min_score) const;
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// Aligns the node with the given 'constant_data' within the 'hybrid_grid'
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// given rotations which are expected to be approximately gravity aligned.
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// If a score above 'min_score' (excluding equality) is possible, true is
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// returned, and 'score', 'pose_estimate', 'rotational_score', and
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// 'low_resolution_score' are updated with the result.
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bool MatchFullSubmap(const Eigen::Quaterniond& global_node_rotation,
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const Eigen::Quaterniond& global_submap_rotation,
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const mapping::TrajectoryNode::Data& constant_data,
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float min_score, float* score,
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transform::Rigid3d* pose_estimate,
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float* rotational_score,
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float* low_resolution_score) const;
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// 'Result' is only returned if a score above 'min_score' (excluding equality)
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// is possible.
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std::unique_ptr<Result> MatchFullSubmap(
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const Eigen::Quaterniond& global_node_rotation,
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const Eigen::Quaterniond& global_submap_rotation,
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const mapping::TrajectoryNode::Data& constant_data,
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float min_score) const;
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private:
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struct SearchParameters {
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@ -92,15 +94,13 @@ class FastCorrelativeScanMatcher {
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const MatchingFunction* const low_resolution_matcher;
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};
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bool MatchWithSearchParameters(
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std::unique_ptr<Result> MatchWithSearchParameters(
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const SearchParameters& search_parameters,
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const transform::Rigid3f& global_node_pose,
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const transform::Rigid3f& global_submap_pose,
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const sensor::PointCloud& point_cloud,
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const Eigen::VectorXf& rotational_scan_matcher_histogram,
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const Eigen::Quaterniond& gravity_alignment, float min_score,
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float* score, transform::Rigid3d* pose_estimate, float* rotational_score,
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float* low_resolution_score) const;
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const Eigen::Quaterniond& gravity_alignment, float min_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,
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@ -140,26 +140,25 @@ TEST_F(FastCorrelativeScanMatcherTest, CorrectPoseForMatch) {
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std::unique_ptr<FastCorrelativeScanMatcher> fast_correlative_scan_matcher(
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GetFastCorrelativeScanMatcher(options_, expected_pose));
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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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float low_resolution_score = 0.f;
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EXPECT_TRUE(fast_correlative_scan_matcher->Match(
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transform::Rigid3d::Identity(), transform::Rigid3d::Identity(),
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CreateConstantData(point_cloud_), kMinScore, &score, &pose_estimate,
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&rotational_score, &low_resolution_score));
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EXPECT_LT(kMinScore, score);
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EXPECT_LT(0.09f, rotational_score);
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EXPECT_LT(0.14f, low_resolution_score);
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const std::unique_ptr<FastCorrelativeScanMatcher::Result> result =
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fast_correlative_scan_matcher->Match(
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transform::Rigid3d::Identity(), transform::Rigid3d::Identity(),
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CreateConstantData(point_cloud_), kMinScore);
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EXPECT_THAT(result, testing::NotNull());
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EXPECT_LT(kMinScore, result->score);
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EXPECT_LT(0.09f, result->rotational_score);
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EXPECT_LT(0.14f, result->low_resolution_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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transform::IsNearly(result->pose_estimate.cast<float>(), 0.05f))
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<< "Actual: " << transform::ToProto(result->pose_estimate).DebugString()
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<< "\nExpected: " << transform::ToProto(expected_pose).DebugString();
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EXPECT_FALSE(fast_correlative_scan_matcher->Match(
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transform::Rigid3d::Identity(), transform::Rigid3d::Identity(),
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CreateConstantData({Eigen::Vector3f(42.f, 42.f, 42.f)}), kMinScore,
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&score, &pose_estimate, &rotational_score, &low_resolution_score))
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<< low_resolution_score;
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const std::unique_ptr<FastCorrelativeScanMatcher::Result>
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low_resolution_result = fast_correlative_scan_matcher->Match(
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transform::Rigid3d::Identity(), transform::Rigid3d::Identity(),
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CreateConstantData({Eigen::Vector3f(42.f, 42.f, 42.f)}), kMinScore);
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EXPECT_THAT(low_resolution_result, testing::IsNull())
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<< low_resolution_result->low_resolution_score;
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}
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}
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@ -169,26 +168,25 @@ TEST_F(FastCorrelativeScanMatcherTest, CorrectPoseForMatchFullSubmap) {
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std::unique_ptr<FastCorrelativeScanMatcher> fast_correlative_scan_matcher(
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GetFastCorrelativeScanMatcher(options_, expected_pose));
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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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float low_resolution_score = 0.f;
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EXPECT_TRUE(fast_correlative_scan_matcher->MatchFullSubmap(
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Eigen::Quaterniond::Identity(), Eigen::Quaterniond::Identity(),
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CreateConstantData(point_cloud_), kMinScore, &score, &pose_estimate,
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&rotational_score, &low_resolution_score));
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EXPECT_LT(kMinScore, score);
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EXPECT_LT(0.09f, rotational_score);
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EXPECT_LT(0.14f, low_resolution_score);
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const std::unique_ptr<FastCorrelativeScanMatcher::Result> result =
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fast_correlative_scan_matcher->MatchFullSubmap(
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Eigen::Quaterniond::Identity(), Eigen::Quaterniond::Identity(),
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CreateConstantData(point_cloud_), kMinScore);
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EXPECT_THAT(result, testing::NotNull());
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EXPECT_LT(kMinScore, result->score);
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EXPECT_LT(0.09f, result->rotational_score);
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EXPECT_LT(0.14f, result->low_resolution_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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transform::IsNearly(result->pose_estimate.cast<float>(), 0.05f))
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<< "Actual: " << transform::ToProto(result->pose_estimate).DebugString()
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<< "\nExpected: " << transform::ToProto(expected_pose).DebugString();
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EXPECT_FALSE(fast_correlative_scan_matcher->MatchFullSubmap(
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Eigen::Quaterniond::Identity(), Eigen::Quaterniond::Identity(),
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CreateConstantData({Eigen::Vector3f(42.f, 42.f, 42.f)}), kMinScore,
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&score, &pose_estimate, &rotational_score, &low_resolution_score))
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<< low_resolution_score;
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const std::unique_ptr<FastCorrelativeScanMatcher::Result>
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low_resolution_result = fast_correlative_scan_matcher->MatchFullSubmap(
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Eigen::Quaterniond::Identity(), Eigen::Quaterniond::Identity(),
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CreateConstantData({Eigen::Vector3f(42.f, 42.f, 42.f)}), kMinScore);
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EXPECT_THAT(low_resolution_result, testing::IsNull())
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<< low_resolution_result->low_resolution_score;
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}
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} // namespace
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@ -179,43 +179,41 @@ void ConstraintBuilder::ComputeConstraint(
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// The 'constraint_transform' (submap i <- scan j) is computed from:
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// - a 'high_resolution_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.f;
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transform::Rigid3d pose_estimate;
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float rotational_score = 0.f;
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float low_resolution_score = 0.f;
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// TODO(gaschler): Match methods should return unique_ptr<struct>.
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std::unique_ptr<scan_matching::FastCorrelativeScanMatcher::Result>
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match_result;
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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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// 2. Prune if the score is too low.
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// 3. Refine.
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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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match_result =
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submap_scan_matcher->fast_correlative_scan_matcher->MatchFullSubmap(
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global_node_pose.rotation(), global_submap_pose.rotation(),
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*constant_data, options_.global_localization_min_score(), &score,
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&pose_estimate, &rotational_score, &low_resolution_score)) {
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CHECK_GT(score, options_.global_localization_min_score());
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*constant_data, options_.global_localization_min_score());
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if (match_result != nullptr) {
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CHECK_GT(match_result->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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} else {
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return;
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}
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} else {
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if (submap_scan_matcher->fast_correlative_scan_matcher->Match(
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global_node_pose, global_submap_pose, *constant_data,
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options_.min_score(), &score, &pose_estimate, &rotational_score,
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&low_resolution_score)) {
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match_result = submap_scan_matcher->fast_correlative_scan_matcher->Match(
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global_node_pose, global_submap_pose, *constant_data,
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options_.min_score());
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if (match_result != nullptr) {
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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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CHECK_GT(match_result->score, options_.min_score());
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} else {
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return;
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}
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}
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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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low_resolution_score_histogram_.Add(low_resolution_score);
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score_histogram_.Add(match_result->score);
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rotational_score_histogram_.Add(match_result->rotational_score);
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low_resolution_score_histogram_.Add(match_result->low_resolution_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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@ -223,7 +221,8 @@ void ConstraintBuilder::ComputeConstraint(
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// CSM estimate.
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ceres::Solver::Summary unused_summary;
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transform::Rigid3d constraint_transform;
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ceres_scan_matcher_.Match(pose_estimate, pose_estimate,
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ceres_scan_matcher_.Match(match_result->pose_estimate,
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match_result->pose_estimate,
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{{&constant_data->high_resolution_point_cloud,
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submap_scan_matcher->high_resolution_hybrid_grid},
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{&constant_data->low_resolution_point_cloud,
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@ -252,7 +251,8 @@ void ConstraintBuilder::ComputeConstraint(
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<< difference.translation().norm() << " rotation "
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<< std::setprecision(3) << transform::GetAngle(difference);
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}
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info << " with score " << std::setprecision(1) << 100. * score << "%.";
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info << " with score " << std::setprecision(1) << 100. * match_result->score
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<< "%.";
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LOG(INFO) << info.str();
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}
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}
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