24325f2a06
Major changes: - New square-root implementation for optimization and marginalization, giving faster optimization and numerically more stable marginalization. The square root solver is the new default, but the Schur complement based implementation is still available. (Implements the ICCV'21 paper.) - The odometry estimator is now fully templetized and you can run in float or double. Default is float, which works well with the new square-root implementation and gives best runtimes. - Batch evaluation scripts and documentation to reproduce the ICCV'21 experiments. Additional changes: - New options in VIO to marginalize lost landmark right away and not only when the frame is marginalized (enabled by default). - small bugfix for keypoint patch extraction bounds - basalt_vio: more logging for batch evaluation - basalt_vio: better handling of closing the GUI while estimator is still running - basalt_vio: new command line argument to limit the number of frames processed - basalt_vio: new command line argument to save ground truth trajectory - added unit tests for square root marginalization - update basalt-headers - new submodules: gmt, nlohmann/json, magic_enum
260 lines
8.1 KiB
C++
260 lines
8.1 KiB
C++
/**
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BSD 3-Clause License
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This file is part of the Basalt project.
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https://gitlab.com/VladyslavUsenko/basalt.git
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Copyright (c) 2019, Vladyslav Usenko and Nikolaus Demmel.
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright notice, this
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list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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* Neither the name of the copyright holder nor the names of its
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contributors may be used to endorse or promote products derived from
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this software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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#pragma once
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#include <thread>
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#include <basalt/imu/preintegration.h>
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#include <basalt/utils/time_utils.hpp>
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#include <basalt/vi_estimator/sqrt_ba_base.h>
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#include <basalt/vi_estimator/vio_estimator.h>
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#include <basalt/imu/preintegration.h>
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namespace basalt {
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template <class Scalar_>
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class SqrtKeypointVioEstimator : public VioEstimatorBase,
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public SqrtBundleAdjustmentBase<Scalar_> {
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public:
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using Scalar = Scalar_;
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typedef std::shared_ptr<SqrtKeypointVioEstimator> Ptr;
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static const int N = 9;
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using Vec2 = Eigen::Matrix<Scalar, 2, 1>;
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using Vec3 = Eigen::Matrix<Scalar, 3, 1>;
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using Vec4 = Eigen::Matrix<Scalar, 4, 1>;
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using VecN = Eigen::Matrix<Scalar, N, 1>;
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using VecX = Eigen::Matrix<Scalar, Eigen::Dynamic, 1>;
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using MatN3 = Eigen::Matrix<Scalar, N, 3>;
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using MatX = Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>;
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using SE3 = Sophus::SE3<Scalar>;
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using typename SqrtBundleAdjustmentBase<Scalar>::RelLinData;
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using typename SqrtBundleAdjustmentBase<Scalar>::AbsLinData;
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using BundleAdjustmentBase<Scalar>::computeError;
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using BundleAdjustmentBase<Scalar>::get_current_points;
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using BundleAdjustmentBase<Scalar>::computeDelta;
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using BundleAdjustmentBase<Scalar>::computeProjections;
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using BundleAdjustmentBase<Scalar>::triangulate;
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using BundleAdjustmentBase<Scalar>::backup;
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using BundleAdjustmentBase<Scalar>::restore;
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using BundleAdjustmentBase<Scalar>::getPoseStateWithLin;
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using BundleAdjustmentBase<Scalar>::computeModelCostChange;
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using SqrtBundleAdjustmentBase<Scalar>::linearizeHelper;
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using SqrtBundleAdjustmentBase<Scalar>::linearizeAbsHelper;
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using SqrtBundleAdjustmentBase<Scalar>::linearizeRel;
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using SqrtBundleAdjustmentBase<Scalar>::linearizeAbs;
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using SqrtBundleAdjustmentBase<Scalar>::updatePoints;
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using SqrtBundleAdjustmentBase<Scalar>::updatePointsAbs;
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using SqrtBundleAdjustmentBase<Scalar>::linearizeMargPrior;
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using SqrtBundleAdjustmentBase<Scalar>::computeMargPriorError;
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using SqrtBundleAdjustmentBase<Scalar>::computeMargPriorModelCostChange;
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using SqrtBundleAdjustmentBase<Scalar>::checkNullspace;
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using SqrtBundleAdjustmentBase<Scalar>::checkEigenvalues;
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SqrtKeypointVioEstimator(const Eigen::Vector3d& g,
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const basalt::Calibration<double>& calib,
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const VioConfig& config);
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void initialize(int64_t t_ns, const Sophus::SE3d& T_w_i,
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const Eigen::Vector3d& vel_w_i, const Eigen::Vector3d& bg,
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const Eigen::Vector3d& ba) override;
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void initialize(const Eigen::Vector3d& bg,
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const Eigen::Vector3d& ba) override;
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virtual ~SqrtKeypointVioEstimator() { maybe_join(); }
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inline void maybe_join() override {
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if (processing_thread) {
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processing_thread->join();
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processing_thread.reset();
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}
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}
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void addIMUToQueue(const ImuData<double>::Ptr& data) override;
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void addVisionToQueue(const OpticalFlowResult::Ptr& data) override;
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typename ImuData<Scalar>::Ptr popFromImuDataQueue();
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bool measure(const OpticalFlowResult::Ptr& opt_flow_meas,
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const typename IntegratedImuMeasurement<Scalar>::Ptr& meas);
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// int64_t propagate();
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// void addNewState(int64_t data_t_ns);
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void optimize_and_marg(const std::map<int64_t, int>& num_points_connected,
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const std::unordered_set<KeypointId>& lost_landmaks);
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void marginalize(const std::map<int64_t, int>& num_points_connected,
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const std::unordered_set<KeypointId>& lost_landmaks);
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void optimize();
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void debug_finalize() override;
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void logMargNullspace();
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Eigen::VectorXd checkMargNullspace() const;
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Eigen::VectorXd checkMargEigenvalues() const;
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int64_t get_t_ns() const {
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return frame_states.at(last_state_t_ns).getState().t_ns;
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}
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const SE3& get_T_w_i() const {
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return frame_states.at(last_state_t_ns).getState().T_w_i;
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}
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const Vec3& get_vel_w_i() const {
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return frame_states.at(last_state_t_ns).getState().vel_w_i;
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}
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const PoseVelBiasState<Scalar>& get_state() const {
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return frame_states.at(last_state_t_ns).getState();
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}
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PoseVelBiasState<Scalar> get_state(int64_t t_ns) const {
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PoseVelBiasState<Scalar> state;
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auto it = frame_states.find(t_ns);
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if (it != frame_states.end()) {
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return it->second.getState();
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}
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auto it2 = frame_poses.find(t_ns);
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if (it2 != frame_poses.end()) {
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state.T_w_i = it2->second.getPose();
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}
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return state;
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}
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void setMaxStates(size_t val) override { max_states = val; }
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void setMaxKfs(size_t val) override { max_kfs = val; }
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Eigen::aligned_vector<SE3> getFrameStates() const {
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Eigen::aligned_vector<SE3> res;
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for (const auto& kv : frame_states) {
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res.push_back(kv.second.getState().T_w_i);
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}
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return res;
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}
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Eigen::aligned_vector<SE3> getFramePoses() const {
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Eigen::aligned_vector<SE3> res;
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for (const auto& kv : frame_poses) {
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res.push_back(kv.second.getPose());
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}
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return res;
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}
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Eigen::aligned_map<int64_t, SE3> getAllPosesMap() const {
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Eigen::aligned_map<int64_t, SE3> res;
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for (const auto& kv : frame_poses) {
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res[kv.first] = kv.second.getPose();
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}
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for (const auto& kv : frame_states) {
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res[kv.first] = kv.second.getState().T_w_i;
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}
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return res;
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}
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Sophus::SE3d getT_w_i_init() override {
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return T_w_i_init.template cast<double>();
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}
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EIGEN_MAKE_ALIGNED_OPERATOR_NEW
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private:
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using BundleAdjustmentBase<Scalar>::frame_poses;
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using BundleAdjustmentBase<Scalar>::frame_states;
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using BundleAdjustmentBase<Scalar>::lmdb;
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using BundleAdjustmentBase<Scalar>::obs_std_dev;
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using BundleAdjustmentBase<Scalar>::huber_thresh;
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using BundleAdjustmentBase<Scalar>::calib;
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private:
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bool take_kf;
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int frames_after_kf;
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std::set<int64_t> kf_ids;
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int64_t last_state_t_ns;
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Eigen::aligned_map<int64_t, IntegratedImuMeasurement<Scalar>> imu_meas;
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const Vec3 g;
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// Input
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Eigen::aligned_map<int64_t, OpticalFlowResult::Ptr> prev_opt_flow_res;
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std::map<int64_t, int> num_points_kf;
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// Marginalization
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MargLinData<Scalar> marg_data;
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// Used only for debug and log purporses.
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MargLinData<Scalar> nullspace_marg_data;
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Vec3 gyro_bias_sqrt_weight, accel_bias_sqrt_weight;
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size_t max_states;
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size_t max_kfs;
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SE3 T_w_i_init;
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bool initialized;
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bool opt_started;
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VioConfig config;
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Scalar lambda, min_lambda, max_lambda, lambda_vee;
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std::shared_ptr<std::thread> processing_thread;
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// timing and stats
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ExecutionStats stats_all_;
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ExecutionStats stats_sums_;
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};
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} // namespace basalt
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