318 lines
13 KiB
C++
318 lines
13 KiB
C++
/*
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* Copyright 2016 The Cartographer Authors
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "cartographer/mapping_3d/sparse_pose_graph/constraint_builder.h"
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#include <cmath>
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#include <functional>
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#include <iomanip>
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#include <iostream>
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#include <limits>
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#include <memory>
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#include <sstream>
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#include <string>
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#include "Eigen/Eigenvalues"
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#include "cartographer/common/make_unique.h"
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#include "cartographer/common/math.h"
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#include "cartographer/common/thread_pool.h"
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#include "cartographer/mapping_3d/scan_matching/low_resolution_matcher.h"
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#include "cartographer/mapping_3d/scan_matching/proto/ceres_scan_matcher_options.pb.h"
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#include "cartographer/mapping_3d/scan_matching/proto/fast_correlative_scan_matcher_options.pb.h"
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#include "cartographer/transform/transform.h"
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#include "glog/logging.h"
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namespace cartographer {
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namespace mapping_3d {
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namespace sparse_pose_graph {
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ConstraintBuilder::ConstraintBuilder(
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const mapping::sparse_pose_graph::proto::ConstraintBuilderOptions& options,
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common::ThreadPool* const thread_pool)
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: options_(options),
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thread_pool_(thread_pool),
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sampler_(options.sampling_ratio()),
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high_resolution_adaptive_voxel_filter_(
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options.high_resolution_adaptive_voxel_filter_options()),
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low_resolution_adaptive_voxel_filter_(
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options.low_resolution_adaptive_voxel_filter_options()),
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ceres_scan_matcher_(options.ceres_scan_matcher_options_3d()) {}
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ConstraintBuilder::~ConstraintBuilder() {
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common::MutexLocker locker(&mutex_);
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CHECK_EQ(constraints_.size(), 0) << "WhenDone() was not called";
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CHECK_EQ(pending_computations_.size(), 0);
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CHECK_EQ(submap_queued_work_items_.size(), 0);
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CHECK(when_done_ == nullptr);
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}
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void ConstraintBuilder::MaybeAddConstraint(
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const mapping::SubmapId& submap_id, const Submap* const submap,
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const mapping::NodeId& node_id,
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const sensor::CompressedPointCloud* const compressed_point_cloud,
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const std::vector<mapping::TrajectoryNode>& submap_nodes,
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const transform::Rigid3d& initial_pose) {
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if (initial_pose.translation().norm() > options_.max_constraint_distance()) {
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return;
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}
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if (sampler_.Pulse()) {
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common::MutexLocker locker(&mutex_);
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constraints_.emplace_back();
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auto* const constraint = &constraints_.back();
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++pending_computations_[current_computation_];
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const int current_computation = current_computation_;
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ScheduleSubmapScanMatcherConstructionAndQueueWorkItem(
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submap_id, submap_nodes, submap, [=]() EXCLUDES(mutex_) {
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ComputeConstraint(submap_id, node_id, false, /* match_full_submap */
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nullptr, /* trajectory_connectivity */
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compressed_point_cloud, initial_pose, constraint);
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FinishComputation(current_computation);
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});
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}
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}
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void ConstraintBuilder::MaybeAddGlobalConstraint(
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const mapping::SubmapId& submap_id, const Submap* const submap,
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const mapping::NodeId& node_id,
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const sensor::CompressedPointCloud* const compressed_point_cloud,
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const std::vector<mapping::TrajectoryNode>& submap_nodes,
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const Eigen::Quaterniond& gravity_alignment,
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mapping::TrajectoryConnectivity* const trajectory_connectivity) {
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common::MutexLocker locker(&mutex_);
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constraints_.emplace_back();
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auto* const constraint = &constraints_.back();
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++pending_computations_[current_computation_];
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const int current_computation = current_computation_;
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ScheduleSubmapScanMatcherConstructionAndQueueWorkItem(
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submap_id, submap_nodes, submap, [=]() EXCLUDES(mutex_) {
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ComputeConstraint(submap_id, node_id, true, /* match_full_submap */
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trajectory_connectivity, compressed_point_cloud,
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transform::Rigid3d::Rotation(gravity_alignment),
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constraint);
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FinishComputation(current_computation);
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});
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}
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void ConstraintBuilder::NotifyEndOfScan() {
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common::MutexLocker locker(&mutex_);
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++current_computation_;
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}
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void ConstraintBuilder::WhenDone(
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const std::function<void(const ConstraintBuilder::Result&)>& callback) {
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common::MutexLocker locker(&mutex_);
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CHECK(when_done_ == nullptr);
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when_done_ =
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common::make_unique<std::function<void(const Result&)>>(callback);
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++pending_computations_[current_computation_];
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const int current_computation = current_computation_;
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thread_pool_->Schedule(
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[this, current_computation] { FinishComputation(current_computation); });
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}
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void ConstraintBuilder::ScheduleSubmapScanMatcherConstructionAndQueueWorkItem(
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const mapping::SubmapId& submap_id,
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const std::vector<mapping::TrajectoryNode>& submap_nodes,
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const Submap* const submap, const std::function<void()>& work_item) {
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if (submap_scan_matchers_[submap_id].fast_correlative_scan_matcher !=
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nullptr) {
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thread_pool_->Schedule(work_item);
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} else {
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submap_queued_work_items_[submap_id].push_back(work_item);
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if (submap_queued_work_items_[submap_id].size() == 1) {
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thread_pool_->Schedule([=]() {
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ConstructSubmapScanMatcher(submap_id, submap_nodes, submap);
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});
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}
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}
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}
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void ConstraintBuilder::ConstructSubmapScanMatcher(
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const mapping::SubmapId& submap_id,
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const std::vector<mapping::TrajectoryNode>& submap_nodes,
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const Submap* const submap) {
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auto submap_scan_matcher =
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common::make_unique<scan_matching::FastCorrelativeScanMatcher>(
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submap->high_resolution_hybrid_grid(), submap_nodes,
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options_.fast_correlative_scan_matcher_options_3d());
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common::MutexLocker locker(&mutex_);
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submap_scan_matchers_[submap_id] = {&submap->high_resolution_hybrid_grid(),
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&submap->low_resolution_hybrid_grid(),
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std::move(submap_scan_matcher)};
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for (const std::function<void()>& work_item :
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submap_queued_work_items_[submap_id]) {
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thread_pool_->Schedule(work_item);
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}
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submap_queued_work_items_.erase(submap_id);
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}
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const ConstraintBuilder::SubmapScanMatcher*
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ConstraintBuilder::GetSubmapScanMatcher(const mapping::SubmapId& submap_id) {
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common::MutexLocker locker(&mutex_);
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const SubmapScanMatcher* submap_scan_matcher =
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&submap_scan_matchers_[submap_id];
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CHECK(submap_scan_matcher->fast_correlative_scan_matcher != nullptr);
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return submap_scan_matcher;
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}
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void ConstraintBuilder::ComputeConstraint(
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const mapping::SubmapId& submap_id, const mapping::NodeId& node_id,
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bool match_full_submap,
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mapping::TrajectoryConnectivity* trajectory_connectivity,
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const sensor::CompressedPointCloud* const compressed_point_cloud,
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const transform::Rigid3d& initial_pose,
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std::unique_ptr<OptimizationProblem::Constraint>* constraint) {
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const SubmapScanMatcher* const submap_scan_matcher =
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GetSubmapScanMatcher(submap_id);
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const sensor::PointCloud point_cloud = compressed_point_cloud->Decompress();
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const sensor::PointCloud high_resolution_point_cloud =
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high_resolution_adaptive_voxel_filter_.Filter(point_cloud);
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const sensor::PointCloud low_resolution_point_cloud =
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low_resolution_adaptive_voxel_filter_.Filter(point_cloud);
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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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const auto low_resolution_matcher = scan_matching::CreateLowResolutionMatcher(
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submap_scan_matcher->low_resolution_hybrid_grid,
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&low_resolution_point_cloud);
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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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initial_pose.rotation(), high_resolution_point_cloud, point_cloud,
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options_.global_localization_min_score(), low_resolution_matcher,
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&score, &pose_estimate, &rotational_score, &low_resolution_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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trajectory_connectivity->Connect(node_id.trajectory_id,
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submap_id.trajectory_id);
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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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initial_pose, high_resolution_point_cloud, point_cloud,
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options_.min_score(), low_resolution_matcher, &score,
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&pose_estimate, &rotational_score, &low_resolution_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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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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}
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// Use the CSM estimate as both the initial and previous pose. This has the
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// effect that, in the absence of better information, we prefer the original
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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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{{&high_resolution_point_cloud,
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submap_scan_matcher->high_resolution_hybrid_grid},
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{&low_resolution_point_cloud,
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submap_scan_matcher->low_resolution_hybrid_grid}},
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&constraint_transform, &unused_summary);
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constraint->reset(new OptimizationProblem::Constraint{
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submap_id,
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node_id,
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{constraint_transform, options_.loop_closure_translation_weight(),
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options_.loop_closure_rotation_weight()},
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OptimizationProblem::Constraint::INTER_SUBMAP});
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if (options_.log_matches()) {
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std::ostringstream info;
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info << "Node " << node_id << " with " << high_resolution_point_cloud.size()
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<< " points on submap " << submap_id << std::fixed;
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if (match_full_submap) {
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info << " matches";
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} else {
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const transform::Rigid3d difference =
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initial_pose.inverse() * constraint_transform;
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info << " differs by translation " << std::setprecision(2)
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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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LOG(INFO) << info.str();
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}
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}
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void ConstraintBuilder::FinishComputation(const int computation_index) {
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Result result;
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std::unique_ptr<std::function<void(const Result&)>> callback;
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{
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common::MutexLocker locker(&mutex_);
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if (--pending_computations_[computation_index] == 0) {
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pending_computations_.erase(computation_index);
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}
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if (pending_computations_.empty()) {
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CHECK_EQ(submap_queued_work_items_.size(), 0);
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if (when_done_ != nullptr) {
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for (const std::unique_ptr<OptimizationProblem::Constraint>&
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constraint : constraints_) {
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if (constraint != nullptr) {
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result.push_back(*constraint);
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}
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}
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if (options_.log_matches()) {
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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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LOG(INFO) << "Low resolution score histogram:\n"
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<< low_resolution_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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when_done_.reset();
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}
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}
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}
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if (callback != nullptr) {
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(*callback)(result);
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}
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}
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int ConstraintBuilder::GetNumFinishedScans() {
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common::MutexLocker locker(&mutex_);
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if (pending_computations_.empty()) {
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return current_computation_;
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}
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return pending_computations_.begin()->first;
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}
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} // namespace sparse_pose_graph
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} // namespace mapping_3d
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} // namespace cartographer
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