/* * 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. */ #include "cartographer/mapping/internal/optimization/optimization_problem_2d.h" #include #include #include #include #include #include #include #include "cartographer/common/internal/ceres_solver_options.h" #include "cartographer/common/histogram.h" #include "cartographer/common/math.h" #include "cartographer/mapping/internal/optimization/ceres_pose.h" #include "cartographer/mapping/internal/optimization/cost_functions/landmark_cost_function_2d.h" #include "cartographer/mapping/internal/optimization/cost_functions/spa_cost_function_2d.h" #include "cartographer/sensor/odometry_data.h" #include "cartographer/transform/transform.h" #include "ceres/ceres.h" #include "glog/logging.h" namespace cartographer { namespace mapping { namespace optimization { namespace { using ::cartographer::mapping::optimization::CeresPose; using LandmarkNode = ::cartographer::mapping::PoseGraphInterface::LandmarkNode; using TrajectoryData = ::cartographer::mapping::PoseGraphInterface::TrajectoryData; // For fixed frame pose. std::unique_ptr Interpolate( const sensor::MapByTime& map_by_time, const int trajectory_id, const common::Time time) { const auto it = map_by_time.lower_bound(trajectory_id, time); if (it == map_by_time.EndOfTrajectory(trajectory_id) || !it->pose.has_value()) { return nullptr; } if (it == map_by_time.BeginOfTrajectory(trajectory_id)) { if (it->time == time) { return absl::make_unique(it->pose.value()); } return nullptr; } const auto prev_it = std::prev(it); if (prev_it->pose.has_value()) { return absl::make_unique( Interpolate(transform::TimestampedTransform{prev_it->time, prev_it->pose.value()}, transform::TimestampedTransform{it->time, it->pose.value()}, time) .transform); } return nullptr; } // Converts a pose into the 3 optimization variable format used for Ceres: // translation in x and y, followed by the rotation angle representing the // orientation. std::array FromPose(const transform::Rigid2d& pose) { return {{pose.translation().x(), pose.translation().y(), pose.normalized_angle()}}; } // Converts a pose as represented for Ceres back to an transform::Rigid2d pose. transform::Rigid2d ToPose(const std::array& values) { return transform::Rigid2d({values[0], values[1]}, values[2]); } // Selects a trajectory node closest in time to the landmark observation and // applies a relative transform from it. transform::Rigid3d GetInitialLandmarkPose( const LandmarkNode::LandmarkObservation& observation, const NodeSpec2D& prev_node, const NodeSpec2D& next_node, const std::array& prev_node_pose, const std::array& next_node_pose) { const double interpolation_parameter = common::ToSeconds(observation.time - prev_node.time) / common::ToSeconds(next_node.time - prev_node.time); const std::tuple, std::array> rotation_and_translation = InterpolateNodes2D(prev_node_pose.data(), prev_node.gravity_alignment, next_node_pose.data(), next_node.gravity_alignment, interpolation_parameter); return transform::Rigid3d::FromArrays(std::get<0>(rotation_and_translation), std::get<1>(rotation_and_translation)) * observation.landmark_to_tracking_transform; } void AddLandmarkCostFunctions( const std::map& landmark_nodes, const MapById& node_data, MapById>* C_nodes, std::map* C_landmarks, ceres::Problem* problem, double huber_scale) { for (const auto& landmark_node : landmark_nodes) { for (const auto& observation : landmark_node.second.landmark_observations) { const std::string& landmark_id = landmark_node.first; const auto& begin_of_trajectory = node_data.BeginOfTrajectory(observation.trajectory_id); // The landmark observation was made before the trajectory was created. if (observation.time < begin_of_trajectory->data.time) { continue; } // Find the trajectory nodes before and after the landmark observation. auto next = node_data.lower_bound(observation.trajectory_id, observation.time); // The landmark observation was made, but the next trajectory node has // not been added yet. if (next == node_data.EndOfTrajectory(observation.trajectory_id)) { continue; } if (next == begin_of_trajectory) { next = std::next(next); } auto prev = std::prev(next); // Add parameter blocks for the landmark ID if they were not added before. std::array* prev_node_pose = &C_nodes->at(prev->id); std::array* next_node_pose = &C_nodes->at(next->id); if (!C_landmarks->count(landmark_id)) { const transform::Rigid3d starting_point = landmark_node.second.global_landmark_pose.has_value() ? landmark_node.second.global_landmark_pose.value() : GetInitialLandmarkPose(observation, prev->data, next->data, *prev_node_pose, *next_node_pose); C_landmarks->emplace( landmark_id, CeresPose(starting_point, nullptr /* translation_parametrization */, absl::make_unique(), problem)); // Set landmark constant if it is frozen. if (landmark_node.second.frozen) { problem->SetParameterBlockConstant( C_landmarks->at(landmark_id).translation()); problem->SetParameterBlockConstant( C_landmarks->at(landmark_id).rotation()); } } problem->AddResidualBlock( LandmarkCostFunction2D::CreateAutoDiffCostFunction( observation, prev->data, next->data), new ceres::HuberLoss(huber_scale), prev_node_pose->data(), next_node_pose->data(), C_landmarks->at(landmark_id).rotation(), C_landmarks->at(landmark_id).translation()); } } } } // namespace OptimizationProblem2D::OptimizationProblem2D( const proto::OptimizationProblemOptions& options) : options_(options) {} OptimizationProblem2D::~OptimizationProblem2D() {} void OptimizationProblem2D::AddImuData(const int trajectory_id, const sensor::ImuData& imu_data) { // IMU data is not used in 2D optimization, so we ignore this part of the // interface. } void OptimizationProblem2D::AddOdometryData( const int trajectory_id, const sensor::OdometryData& odometry_data) { odometry_data_.Append(trajectory_id, odometry_data); } void OptimizationProblem2D::AddFixedFramePoseData( const int trajectory_id, const sensor::FixedFramePoseData& fixed_frame_pose_data) { fixed_frame_pose_data_.Append(trajectory_id, fixed_frame_pose_data); } void OptimizationProblem2D::AddTrajectoryNode(const int trajectory_id, const NodeSpec2D& node_data) { node_data_.Append(trajectory_id, node_data); trajectory_data_[trajectory_id]; } void OptimizationProblem2D::SetTrajectoryData( int trajectory_id, const TrajectoryData& trajectory_data) { trajectory_data_[trajectory_id] = trajectory_data; } void OptimizationProblem2D::InsertTrajectoryNode(const NodeId& node_id, const NodeSpec2D& node_data) { node_data_.Insert(node_id, node_data); trajectory_data_[node_id.trajectory_id]; } void OptimizationProblem2D::TrimTrajectoryNode(const NodeId& node_id) { empty_imu_data_.Trim(node_data_, node_id); odometry_data_.Trim(node_data_, node_id); fixed_frame_pose_data_.Trim(node_data_, node_id); node_data_.Trim(node_id); if (node_data_.SizeOfTrajectoryOrZero(node_id.trajectory_id) == 0) { trajectory_data_.erase(node_id.trajectory_id); } } void OptimizationProblem2D::AddSubmap( const int trajectory_id, const transform::Rigid2d& global_submap_pose) { submap_data_.Append(trajectory_id, SubmapSpec2D{global_submap_pose}); } void OptimizationProblem2D::InsertSubmap( const SubmapId& submap_id, const transform::Rigid2d& global_submap_pose) { submap_data_.Insert(submap_id, SubmapSpec2D{global_submap_pose}); } void OptimizationProblem2D::TrimSubmap(const SubmapId& submap_id) { submap_data_.Trim(submap_id); } void OptimizationProblem2D::SetMaxNumIterations( const int32 max_num_iterations) { options_.mutable_ceres_solver_options()->set_max_num_iterations( max_num_iterations); } void OptimizationProblem2D::Solve( const std::vector& constraints, const std::map& trajectories_state, const std::map& landmark_nodes) { if (node_data_.empty()) { // Nothing to optimize. return; } std::set frozen_trajectories; for (const auto& it : trajectories_state) { if (it.second == PoseGraphInterface::TrajectoryState::FROZEN) { frozen_trajectories.insert(it.first); } } ceres::Problem::Options problem_options; ceres::Problem problem(problem_options); // Set the starting point. // TODO(hrapp): Move ceres data into SubmapSpec. MapById> C_submaps; MapById> C_nodes; std::map C_landmarks; bool first_submap = true; for (const auto& submap_id_data : submap_data_) { const bool frozen = frozen_trajectories.count(submap_id_data.id.trajectory_id) != 0; C_submaps.Insert(submap_id_data.id, FromPose(submap_id_data.data.global_pose)); problem.AddParameterBlock(C_submaps.at(submap_id_data.id).data(), 3); if (first_submap || frozen) { first_submap = false; // Fix the pose of the first submap or all submaps of a frozen // trajectory. problem.SetParameterBlockConstant(C_submaps.at(submap_id_data.id).data()); } } for (const auto& node_id_data : node_data_) { const bool frozen = frozen_trajectories.count(node_id_data.id.trajectory_id) != 0; C_nodes.Insert(node_id_data.id, FromPose(node_id_data.data.global_pose_2d)); problem.AddParameterBlock(C_nodes.at(node_id_data.id).data(), 3); if (frozen) { problem.SetParameterBlockConstant(C_nodes.at(node_id_data.id).data()); } } // Add cost functions for intra- and inter-submap constraints. for (const Constraint& constraint : constraints) { problem.AddResidualBlock( CreateAutoDiffSpaCostFunction(constraint.pose), // Loop closure constraints should have a loss function. constraint.tag == Constraint::INTER_SUBMAP ? new ceres::HuberLoss(options_.huber_scale()) : nullptr, C_submaps.at(constraint.submap_id).data(), C_nodes.at(constraint.node_id).data()); } // Add cost functions for landmarks. AddLandmarkCostFunctions(landmark_nodes, node_data_, &C_nodes, &C_landmarks, &problem, options_.huber_scale()); // Add penalties for violating odometry or changes between consecutive nodes // if odometry is not available. for (auto node_it = node_data_.begin(); node_it != node_data_.end();) { const int trajectory_id = node_it->id.trajectory_id; const auto trajectory_end = node_data_.EndOfTrajectory(trajectory_id); if (frozen_trajectories.count(trajectory_id) != 0) { node_it = trajectory_end; continue; } auto prev_node_it = node_it; for (++node_it; node_it != trajectory_end; ++node_it) { const NodeId first_node_id = prev_node_it->id; const NodeSpec2D& first_node_data = prev_node_it->data; prev_node_it = node_it; const NodeId second_node_id = node_it->id; const NodeSpec2D& second_node_data = node_it->data; if (second_node_id.node_index != first_node_id.node_index + 1) { continue; } // Add a relative pose constraint based on the odometry (if available). std::unique_ptr relative_odometry = CalculateOdometryBetweenNodes(trajectory_id, first_node_data, second_node_data); if (relative_odometry != nullptr) { problem.AddResidualBlock( CreateAutoDiffSpaCostFunction(Constraint::Pose{ *relative_odometry, options_.odometry_translation_weight(), options_.odometry_rotation_weight()}), nullptr /* loss function */, C_nodes.at(first_node_id).data(), C_nodes.at(second_node_id).data()); } // Add a relative pose constraint based on consecutive local SLAM poses. const transform::Rigid3d relative_local_slam_pose = transform::Embed3D(first_node_data.local_pose_2d.inverse() * second_node_data.local_pose_2d); problem.AddResidualBlock( CreateAutoDiffSpaCostFunction( Constraint::Pose{relative_local_slam_pose, options_.local_slam_pose_translation_weight(), options_.local_slam_pose_rotation_weight()}), nullptr /* loss function */, C_nodes.at(first_node_id).data(), C_nodes.at(second_node_id).data()); } } std::map> C_fixed_frames; for (auto node_it = node_data_.begin(); node_it != node_data_.end();) { const int trajectory_id = node_it->id.trajectory_id; const auto trajectory_end = node_data_.EndOfTrajectory(trajectory_id); if (!fixed_frame_pose_data_.HasTrajectory(trajectory_id)) { node_it = trajectory_end; continue; } const TrajectoryData& trajectory_data = trajectory_data_.at(trajectory_id); bool fixed_frame_pose_initialized = false; for (; node_it != trajectory_end; ++node_it) { const NodeId node_id = node_it->id; const NodeSpec2D& node_data = node_it->data; const std::unique_ptr fixed_frame_pose = Interpolate(fixed_frame_pose_data_, trajectory_id, node_data.time); if (fixed_frame_pose == nullptr) { continue; } const Constraint::Pose constraint_pose{ *fixed_frame_pose, options_.fixed_frame_pose_translation_weight(), options_.fixed_frame_pose_rotation_weight()}; if (!fixed_frame_pose_initialized) { transform::Rigid2d fixed_frame_pose_in_map; if (trajectory_data.fixed_frame_origin_in_map.has_value()) { fixed_frame_pose_in_map = transform::Project2D( trajectory_data.fixed_frame_origin_in_map.value()); } else { fixed_frame_pose_in_map = node_data.global_pose_2d * transform::Project2D(constraint_pose.zbar_ij).inverse(); } C_fixed_frames.emplace(trajectory_id, FromPose(fixed_frame_pose_in_map)); fixed_frame_pose_initialized = true; } problem.AddResidualBlock( CreateAutoDiffSpaCostFunction(constraint_pose), options_.fixed_frame_pose_use_tolerant_loss() ? new ceres::TolerantLoss( options_.fixed_frame_pose_tolerant_loss_param_a(), options_.fixed_frame_pose_tolerant_loss_param_b()) : nullptr, C_fixed_frames.at(trajectory_id).data(), C_nodes.at(node_id).data()); } } // Solve. ceres::Solver::Summary summary; ceres::Solve( common::CreateCeresSolverOptions(options_.ceres_solver_options()), &problem, &summary); if (options_.log_solver_summary()) { LOG(INFO) << summary.FullReport(); } // Store the result. for (const auto& C_submap_id_data : C_submaps) { submap_data_.at(C_submap_id_data.id).global_pose = ToPose(C_submap_id_data.data); } for (const auto& C_node_id_data : C_nodes) { node_data_.at(C_node_id_data.id).global_pose_2d = ToPose(C_node_id_data.data); } for (const auto& C_fixed_frame : C_fixed_frames) { trajectory_data_.at(C_fixed_frame.first).fixed_frame_origin_in_map = transform::Embed3D(ToPose(C_fixed_frame.second)); } for (const auto& C_landmark : C_landmarks) { landmark_data_[C_landmark.first] = C_landmark.second.ToRigid(); } } std::unique_ptr OptimizationProblem2D::InterpolateOdometry( const int trajectory_id, const common::Time time) const { const auto it = odometry_data_.lower_bound(trajectory_id, time); if (it == odometry_data_.EndOfTrajectory(trajectory_id)) { return nullptr; } if (it == odometry_data_.BeginOfTrajectory(trajectory_id)) { if (it->time == time) { return absl::make_unique(it->pose); } return nullptr; } const auto prev_it = std::prev(it); return absl::make_unique( Interpolate(transform::TimestampedTransform{prev_it->time, prev_it->pose}, transform::TimestampedTransform{it->time, it->pose}, time) .transform); } std::unique_ptr OptimizationProblem2D::CalculateOdometryBetweenNodes( const int trajectory_id, const NodeSpec2D& first_node_data, const NodeSpec2D& second_node_data) const { if (odometry_data_.HasTrajectory(trajectory_id)) { const std::unique_ptr first_node_odometry = InterpolateOdometry(trajectory_id, first_node_data.time); const std::unique_ptr second_node_odometry = InterpolateOdometry(trajectory_id, second_node_data.time); if (first_node_odometry != nullptr && second_node_odometry != nullptr) { transform::Rigid3d relative_odometry = transform::Rigid3d::Rotation(first_node_data.gravity_alignment) * first_node_odometry->inverse() * (*second_node_odometry) * transform::Rigid3d::Rotation( second_node_data.gravity_alignment.inverse()); return absl::make_unique(relative_odometry); } } return nullptr; } } // namespace optimization } // namespace mapping } // namespace cartographer