MonteCarloLocalization_App.cpp

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/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          https://www.mrpt.org/                         |
   |                                                                        |
   | Copyright (c) 2005-2020, Individual contributors, see AUTHORS file     |
   | See: https://www.mrpt.org/Authors - All rights reserved.               |
   | Released under BSD License. See: https://www.mrpt.org/License          |
   +------------------------------------------------------------------------+ */

#include "apps-precomp.h"  // Precompiled headers

#include <mrpt/apps/MonteCarloLocalization_App.h>
#include <mrpt/bayes/CParticleFilter.h>
#include <mrpt/config/CConfigFile.h>
#include <mrpt/gui/CDisplayWindow3D.h>
#include <mrpt/gui/CDisplayWindowPlots.h>
#include <mrpt/io/CFileGZInputStream.h>
#include <mrpt/io/CFileGZOutputStream.h>
#include <mrpt/io/CFileOutputStream.h>
#include <mrpt/io/vector_loadsave.h>
#include <mrpt/maps/CMultiMetricMap.h>
#include <mrpt/maps/COccupancyGridMap2D.h>
#include <mrpt/maps/CSimpleMap.h>
#include <mrpt/maps/CSimplePointsMap.h>
#include <mrpt/math/data_utils.h>
#include <mrpt/math/distributions.h>
#include <mrpt/math/ops_vectors.h>  // << for vector<>
#include <mrpt/math/utils.h>
#include <mrpt/obs/CActionCollection.h>
#include <mrpt/obs/CActionRobotMovement2D.h>
#include <mrpt/obs/CActionRobotMovement3D.h>
#include <mrpt/obs/CObservationOdometry.h>
#include <mrpt/obs/CRawlog.h>
#include <mrpt/opengl/CDisk.h>
#include <mrpt/opengl/CEllipsoid2D.h>
#include <mrpt/opengl/CEllipsoid3D.h>
#include <mrpt/opengl/CGridPlaneXY.h>
#include <mrpt/opengl/CPointCloud.h>
#include <mrpt/opengl/stock_objects.h>
#include <mrpt/poses/CPose2D.h>
#include <mrpt/poses/CPose2DInterpolator.h>
#include <mrpt/random.h>
#include <mrpt/serialization/CArchive.h>
#include <mrpt/slam/CMonteCarloLocalization2D.h>
#include <mrpt/slam/CMonteCarloLocalization3D.h>
#include <mrpt/system/CTicTac.h>
#include <mrpt/system/filesystem.h>
#include <mrpt/system/os.h>
#include <mrpt/system/vector_loadsave.h>
#include <Eigen/Dense>

using namespace mrpt::apps;

// ---------------------------------------
//   MonteCarloLocalization_Base
// ---------------------------------------
MonteCarloLocalization_Base::MonteCarloLocalization_Base()
{
    // Set logger display name:
    this->setLoggerName("MonteCarloLocalization_Base");
}

void MonteCarloLocalization_Base::initialize(int argc, const char** argv)
{
    MRPT_START

    MRPT_LOG_INFO_FMT(
        " pf-localization - Part of the MRPT\n"
        " MRPT C++ Library: %s - Sources timestamp: %s\n\n",
        mrpt::system::MRPT_getVersion().c_str(),
        mrpt::system::MRPT_getCompilationDate().c_str());

    // Process arguments:
    if (argc < 2)
    {
        THROW_EXCEPTION_FMT("Usage: %s", impl_get_usage().c_str());
    }

    // Config file:
    const std::string configFile = std::string(argv[1]);

    ASSERT_FILE_EXISTS_(configFile);
    params.setContent(mrpt::io::file_get_contents(configFile));

    impl_initialize(argc, argv);

    MRPT_END
}

// All these "using"s, to easily reuse old code from the pf-localization app:
using namespace mrpt;
using namespace mrpt::slam;
using namespace mrpt::maps;
using namespace mrpt::opengl;
using namespace mrpt::gui;
using namespace mrpt::math;
using namespace mrpt::system;
using namespace mrpt::random;
using namespace mrpt::poses;
using namespace mrpt::bayes;
using namespace mrpt::obs;
using namespace mrpt::io;
using namespace mrpt::img;
using namespace mrpt::config;
using namespace mrpt::serialization;
using namespace std;

// Auxiliary trait classes for template implementations below:
template <class PDF>
struct pf2gauss_t
{
};

template <>
struct pf2gauss_t<mrpt::slam::CMonteCarloLocalization2D>
{
    using type = mrpt::poses::CPosePDFGaussian;
    static constexpr bool PF_IS_3D = false;

    static void resetOnFreeSpace(
        CMonteCarloLocalization2D& pdf, mrpt::maps::CMultiMetricMap& metricMap,
        size_t PARTICLE_COUNT, const mrpt::math::TPose3D& init_min,
        const mrpt::math::TPose3D& init_max)
    {
        pdf.resetUniformFreeSpace(
            metricMap.mapByClass<COccupancyGridMap2D>().get(), 0.7f,
            PARTICLE_COUNT, init_min.x, init_max.x, init_min.y, init_max.y,
            init_min.yaw, init_max.yaw);
    }

    static void resetUniform(
        CMonteCarloLocalization2D& pdf, size_t PARTICLE_COUNT,
        const mrpt::math::TPose3D& init_min,
        const mrpt::math::TPose3D& init_max)
    {
        pdf.resetUniform(
            init_min.x, init_max.x, init_min.y, init_max.y, init_min.yaw,
            init_max.yaw, PARTICLE_COUNT);
    }
};
template <>
struct pf2gauss_t<CMonteCarloLocalization3D>
{
    using type = CPose3DPDFGaussian;
    static constexpr bool PF_IS_3D = true;

    static void resetOnFreeSpace(
        CMonteCarloLocalization3D& pdf, mrpt::maps::CMultiMetricMap& metricMap,
        size_t PARTICLE_COUNT, const mrpt::math::TPose3D& init_min,
        const mrpt::math::TPose3D& init_max)
    {
        THROW_EXCEPTION("init_PDF_mode=0 not supported for 3D particles");
    }

    static void resetUniform(
        CMonteCarloLocalization3D& pdf, size_t PARTICLE_COUNT,
        const mrpt::math::TPose3D& init_min,
        const mrpt::math::TPose3D& init_max)
    {
        pdf.resetUniform(init_min, init_max, PARTICLE_COUNT);
    }
};

template <class MONTECARLO_TYPE>
void MonteCarloLocalization_Base::do_pf_localization()
{
    auto& cfg = this->params;  // rename for reusing old code

    // Number of initial particles (if size>1, run the experiments N times)
    std::vector<int> particles_count;

    // Load parameters:

    // Mandatory entries:
    cfg.read_vector(
        sect, "particles_count", std::vector<int>(1, 0), particles_count,
        /*Fail if not found*/ true);
    string OUT_DIR_PREFIX =
        cfg.read_string(sect, "logOutput_dir", "", /*Fail if not found*/ true);

    // Non-mandatory entries:
    string MAP_FILE = cfg.read_string(sect, "map_file", "");
    size_t rawlog_offset = cfg.read_int(sect, "rawlog_offset", 0);
    string GT_FILE = cfg.read_string(sect, "ground_truth_path_file", "");
    const auto NUM_REPS = cfg.read_uint64_t(sect, "experimentRepetitions", 1);
    int SCENE3D_FREQ = cfg.read_int(sect, "3DSceneFrequency", 10);
    bool SCENE3D_FOLLOW = cfg.read_bool(sect, "3DSceneFollowRobot", true);
    unsigned int testConvergenceAt =
        cfg.read_int(sect, "experimentTestConvergenceAtStep", -1);

    bool SAVE_STATS_ONLY = cfg.read_bool(sect, "SAVE_STATS_ONLY", false);
    bool DO_RELIABILITY_ESTIMATE = false;
    bool DO_SCAN_LIKELIHOOD_DEBUG = false;
    MRPT_LOAD_CONFIG_VAR(DO_RELIABILITY_ESTIMATE, bool, cfg, sect);
    MRPT_LOAD_CONFIG_VAR(DO_SCAN_LIKELIHOOD_DEBUG, bool, cfg, sect);

    bool SHOW_PROGRESS_3D_REAL_TIME =
        cfg.read_bool(sect, "SHOW_PROGRESS_3D_REAL_TIME", false);
    int SHOW_PROGRESS_3D_REAL_TIME_DELAY_MS =
        cfg.read_int(sect, "SHOW_PROGRESS_3D_REAL_TIME_DELAY_MS", 1);
    double STATS_CONF_INTERVAL =
        cfg.read_double(sect, "STATS_CONF_INTERVAL", 0.2);

    CPose2D initial_odo;
    initial_odo.x(cfg.read_double(sect, "initial_odo_x", 0));
    initial_odo.y(cfg.read_double(sect, "initial_odo_y", 0));
    initial_odo.phi(cfg.read_double(sect, "initial_odo_phi", 0));

#if !MRPT_HAS_WXWIDGETS
    SHOW_PROGRESS_3D_REAL_TIME = false;
#endif

    // Default odometry uncertainty parameters in "actOdom2D_params" depending
    // on how fast the robot moves, etc...
    //  Only used for observations-only rawlogs:
    CActionRobotMovement2D::TMotionModelOptions actOdom2D_params;
    actOdom2D_params.modelSelection = CActionRobotMovement2D::mmGaussian;
    actOdom2D_params.gaussianModel.minStdXY =
        cfg.read_double("DummyOdometryParams", "minStdXY", 0.04);
    actOdom2D_params.gaussianModel.minStdPHI =
        DEG2RAD(cfg.read_double("DummyOdometryParams", "minStdPHI", 2.0));

    CActionRobotMovement3D::TMotionModelOptions actOdom3D_params;
    actOdom3D_params.mm6DOFModel.additional_std_XYZ =
        cfg.read_double("DummyOdometryParams", "additional_std_XYZ", 0.01);
    actOdom3D_params.mm6DOFModel.additional_std_angle = DEG2RAD(
        cfg.read_double("DummyOdometryParams", "additional_std_angle", 0.1));

    // PF-algorithm Options:
    // ---------------------------
    CParticleFilter::TParticleFilterOptions pfOptions;
    pfOptions.loadFromConfigFile(cfg, "PF_options");

    // PDF Options:
    // ------------------
    TMonteCarloLocalizationParams pdfPredictionOptions;
    pdfPredictionOptions.KLD_params.loadFromConfigFile(cfg, "KLD_options");

    // Metric map options:
    // -----------------------------
    TSetOfMetricMapInitializers mapList;
    mapList.loadFromConfigFile(cfg, "MetricMap");

    MRPT_LOG_INFO_STREAM(
        "" << endl
           << "MAP_FILE       : " << MAP_FILE << endl
           << "GT_FILE        : " << GT_FILE << endl
           << "OUT_DIR_PREFIX : " << OUT_DIR_PREFIX << endl
           << "particles_count :" << particles_count << endl);

    // --------------------------------------------------------------------
    //                      EXPERIMENT PREPARATION
    // --------------------------------------------------------------------
    CTicTac tictac;
    CSimpleMap simpleMap;
    CParticleFilter::TParticleFilterStats PF_stats;

    // Load the set of metric maps to consider in the experiments:
    CMultiMetricMap metricMap;
    metricMap.setListOfMaps(mapList);

    {
        std::stringstream ss;
        pfOptions.dumpToTextStream(ss);
        mapList.dumpToTextStream(ss);

        MRPT_LOG_INFO_STREAM(ss.str());
    }

    getRandomGenerator().randomize();

    // Load the map (if any):
    // -------------------------
    if (MAP_FILE.size())
    {
        ASSERT_(fileExists(MAP_FILE));

        // Detect file extension:
        // -----------------------------
        string mapExt = lowerCase(extractFileExtension(
            MAP_FILE, true));  // Ignore possible .gz extensions

        if (!mapExt.compare("simplemap"))
        {
            // It's a ".simplemap":
            // -------------------------
            MRPT_LOG_INFO_STREAM("Loading '.simplemap' file: " << MAP_FILE);
            {
                CFileGZInputStream f(MAP_FILE);
                archiveFrom(f) >> simpleMap;
            }
            MRPT_LOG_INFO_STREAM(
                "Map loaded ok, with " << simpleMap.size() << " frames.");

            ASSERT_(simpleMap.size() > 0);

            // Build metric map:
            // ------------------------------
            MRPT_LOG_INFO("Building metric map(s) from '.simplemap'...");
            metricMap.loadFromProbabilisticPosesAndObservations(simpleMap);
            MRPT_LOG_INFO("Done.");
        }
        else if (!mapExt.compare("gridmap"))
        {
            // It's a ".gridmap":
            // -------------------------
            MRPT_LOG_INFO("Loading gridmap from '.gridmap'...");
            auto grid = metricMap.mapByClass<COccupancyGridMap2D>();
            ASSERT_(grid);
            {
                CFileGZInputStream f(MAP_FILE);
                archiveFrom(f) >> (*grid);
            }
            MRPT_LOG_INFO("Done.");
        }
        else
        {
            THROW_EXCEPTION_FMT(
                "Map file has unknown extension: '%s'", mapExt.c_str());
        }
    }

    // Load the Ground Truth:
    CMatrixDouble GT(0, 0);
    if (fileExists(GT_FILE))
    {
        MRPT_LOG_INFO("Loading ground truth file...");
        GT.loadFromTextFile(GT_FILE);
        MRPT_LOG_INFO("Done.");

        prepareGT(GT);
    }
    else
        MRPT_LOG_INFO("Ground truth file: not available.");

    // PDF initialization uniform distribution limits:
    const auto init_min = mrpt::math::TPose3D(
        cfg.read_double(sect, "init_PDF_min_x", 0),
        cfg.read_double(sect, "init_PDF_min_y", 0),
        cfg.read_double(sect, "init_PDF_min_z", 0),
        mrpt::DEG2RAD(cfg.read_double(sect, "init_PDF_min_yaw_deg", -180.0)),
        mrpt::DEG2RAD(cfg.read_double(sect, "init_PDF_min_pitch_deg", 0)),
        mrpt::DEG2RAD(cfg.read_double(sect, "init_PDF_min_roll_deg", 0)));

    const auto init_max = mrpt::math::TPose3D(
        cfg.read_double(sect, "init_PDF_max_x", 0),
        cfg.read_double(sect, "init_PDF_max_y", 0),
        cfg.read_double(sect, "init_PDF_max_z", 0),
        mrpt::DEG2RAD(cfg.read_double(sect, "init_PDF_max_yaw_deg", +180.0)),
        mrpt::DEG2RAD(cfg.read_double(sect, "init_PDF_max_pitch_deg", 0)),
        mrpt::DEG2RAD(cfg.read_double(sect, "init_PDF_max_roll_deg", 0)));

    MRPT_LOG_INFO_STREAM(
        "Initial PDF limits:\n Min=" << init_min.asString()
                                     << "\n Max=" << init_max.asString());

    // Gridmap / area of initial uncertainty:
    COccupancyGridMap2D::TEntropyInfo gridInfo;
    if (auto grid = metricMap.mapByClass<COccupancyGridMap2D>(); grid)
    {
        grid->computeEntropy(gridInfo);
        MRPT_LOG_INFO_FMT(
            "The gridmap has %.04fm2 observed area, %u observed cells.",
            gridInfo.effectiveMappedArea,
            (unsigned)gridInfo.effectiveMappedCells);
    }
    else
    {
        gridInfo.effectiveMappedArea =
            (init_max.x - init_min.x) * (init_max.y - init_min.y);
    }

    for (int PARTICLE_COUNT : particles_count)
    {
        MRPT_LOG_INFO_FMT(
            "Initial PDF: %f particles/m2",
            PARTICLE_COUNT / gridInfo.effectiveMappedArea);

        // Global stats for all the experiment loops:
        int nConvergenceTests = 0, nConvergenceOK = 0;
        CVectorDouble convergenceErrors;
        std::mutex convergenceErrors_mtx;

        // --------------------------------------------------------------------
        //                  EXPERIMENT REPETITIONS LOOP
        // --------------------------------------------------------------------

        // Generate list of repetition indices:
        std::vector<unsigned int> rep_indices(NUM_REPS);
        std::iota(rep_indices.begin(), rep_indices.end(), 0);

        // Run each repetition in parallel:
        // GCC 7 still has not implemented C++17 for_each(std::execution::par
        // So: home-made parallel loops:

        // std::for_each(std::execution::par, rep_indices.begin(),
        // rep_indices.end(),
        auto run_localization_code = [&](const size_t repetition) {
            CVectorDouble indivConvergenceErrors, executionTimes, odoError;
            MRPT_LOG_INFO_STREAM(
                "====== RUNNING FOR " << PARTICLE_COUNT
                                      << " INITIAL PARTICLES  - Repetition "
                                      << 1 + repetition << " / " << NUM_REPS);

            // Create 3D window if requested:
            CDisplayWindow3D::Ptr win3D;
            if (SHOW_PROGRESS_3D_REAL_TIME)
            {
                win3D = std::make_shared<CDisplayWindow3D>(
                    "pf-localization - The MRPT project", 1000, 600);
                win3D->setCameraAzimuthDeg(-45);
            }

            // Create the 3D scene and get the map only once, later we'll modify
            // only the particles, etc..
            COpenGLScene scene;
            if (SCENE3D_FREQ > 0 || SHOW_PROGRESS_3D_REAL_TIME)
            {
                mrpt::math::TPoint3D bbox_max(50, 50, 0), bbox_min(-50, -50, 0);
                if (auto pts = metricMap.getAsSimplePointsMap(); pts)
                {
                    pts->boundingBox(bbox_min, bbox_max);
                }

                scene.insert(mrpt::opengl::CGridPlaneXY::Create(
                    bbox_min.x, bbox_max.x, bbox_min.y, bbox_max.y, 0, 5));

                if (win3D)
                    win3D->setCameraZoom(
                        2 *
                        std::max(
                            bbox_max.x - bbox_min.x, bbox_max.y - bbox_min.y));

                CSetOfObjects::Ptr gl_obj = std::make_shared<CSetOfObjects>();
                metricMap.getAs3DObject(gl_obj);
                scene.insert(gl_obj);
            }

            // The experiment directory is:
            string sOUT_DIR_PARTS, sOUT_DIR_3D;
            const auto sOUT_DIR = format(
                "%s_%03u_%07i", OUT_DIR_PREFIX.c_str(), repetition,
                PARTICLE_COUNT);
            MRPT_LOG_INFO_FMT("Creating directory: %s", sOUT_DIR.c_str());
            deleteFilesInDirectory(sOUT_DIR);
            createDirectory(sOUT_DIR);
            ASSERT_DIRECTORY_EXISTS_(sOUT_DIR);

            if (!SAVE_STATS_ONLY)
            {
                sOUT_DIR_PARTS = format("%s/particles", sOUT_DIR.c_str());
                sOUT_DIR_3D = format("%s/3D", sOUT_DIR.c_str());

                MRPT_LOG_INFO_FMT(
                    "Creating directory: %s", sOUT_DIR_PARTS.c_str());
                deleteFilesInDirectory(sOUT_DIR_PARTS);
                createDirectory(sOUT_DIR_PARTS);
                ASSERT_DIRECTORY_EXISTS_(sOUT_DIR_PARTS);

                MRPT_LOG_INFO_FMT(
                    "Creating directory: %s", sOUT_DIR_3D.c_str());
                deleteFilesInDirectory(sOUT_DIR_3D);
                createDirectory(sOUT_DIR_3D);
                ASSERT_DIRECTORY_EXISTS_(sOUT_DIR_3D);

                using namespace std::string_literals;
                metricMap.saveMetricMapRepresentationToFile(sOUT_DIR + "/map"s);
            }

            int M = PARTICLE_COUNT;

            MONTECARLO_TYPE pdf;

            // PDF Options:
            pdf.options = pdfPredictionOptions;

            pdf.options.metricMap = &metricMap;

            // Create the PF object:
            CParticleFilter PF;
            PF.m_options = pfOptions;

            size_t step = 0;
            size_t rawlogEntry = 0;

            // Initialize the PDF:
            // -----------------------------
            tictac.Tic();
            if (!cfg.read_bool(
                    sect, "init_PDF_mode", false,
                    /*Fail if not found*/ true))
            {
                // Reset uniform on free space:
                pf2gauss_t<MONTECARLO_TYPE>::resetOnFreeSpace(
                    pdf, metricMap, PARTICLE_COUNT, init_min, init_max);
            }
            else
            {
                // Reset uniform:
                pf2gauss_t<MONTECARLO_TYPE>::resetUniform(
                    pdf, PARTICLE_COUNT, init_min, init_max);
            }

            MRPT_LOG_INFO_FMT(
                "PDF of %u particles initialized in %.03fms", M,
                1000 * tictac.Tac());

            pdf.saveToTextFile(
                format("%s/particles_0_initial.txt", sOUT_DIR_PARTS.c_str()));

            // -----------------------------
            //      Particle filter
            // -----------------------------
            CPose2D odometryEstimation = initial_odo;

            using PDF_MEAN_TYPE = typename MONTECARLO_TYPE::type_value;

            PDF_MEAN_TYPE pdfEstimation;

            CMatrixDouble cov;
            bool end = false;

            CFileOutputStream f_cov_est, f_pf_stats, f_odo_est;

            if (!SAVE_STATS_ONLY)
            {
                f_cov_est.open(sOUT_DIR.c_str() + string("/cov_est.txt"));
                f_pf_stats.open(sOUT_DIR.c_str() + string("/PF_stats.txt"));
                f_odo_est.open(sOUT_DIR.c_str() + string("/odo_est.txt"));
            }

            Clock::time_point cur_obs_timestamp;
            CPose2D last_used_abs_odo(0, 0, 0),
                pending_most_recent_odo(0, 0, 0);

            while (!end)
            {
                // Finish if ESC is pushed:
                if (allow_quit_on_esc_key && os::kbhit())
                    if (os::getch() == 27)
                    {
                        end = true;
                        break;
                    }

                // Load pose change from the rawlog:
                // ----------------------------------------
                CActionCollection::Ptr action;
                CSensoryFrame::Ptr observations;
                CObservation::Ptr obs;

                if (!impl_get_next_observations(action, observations, obs))
                {
                    // EOF
                    end = true;
                    break;
                }

                // Determine if we are reading a Act-SF or an Obs-only
                // rawlog:
                if (obs)
                {
                    // It's an observation-only rawlog: build an auxiliary
                    // pair of action-SF, since
                    //  montecarlo-localization only accepts those pairs as
                    //  input:

                    // If it's an odometry reading, don't feed it to the PF.
                    // Instead,
                    // store its value for use as an "action" together with
                    // the next actual observation:
                    if (IS_CLASS(*obs, CObservationOdometry))
                    {
                        auto obs_odo =
                            std::dynamic_pointer_cast<CObservationOdometry>(
                                obs);
                        pending_most_recent_odo = obs_odo->odometry;
                        static bool is_1st_odo = true;
                        if (is_1st_odo)
                        {
                            is_1st_odo = false;
                            last_used_abs_odo = pending_most_recent_odo;
                        }
                        continue;
                    }
                    else
                    {
                        // SF: Just one observation:
                        // ------------------------------------------------------
                        observations = std::make_shared<CSensoryFrame>();
                        observations->insert(obs);

                        // ActionCollection: Just one action with a dummy
                        // odometry
                        // ------------------------------------------------------
                        action = std::make_shared<CActionCollection>();

                        if (pf2gauss_t<MONTECARLO_TYPE>::PF_IS_3D)
                        {
                            CActionRobotMovement3D actOdom3D;

                            const CPose3D odo_incr = CPose3D(
                                pending_most_recent_odo - last_used_abs_odo);
                            last_used_abs_odo = pending_most_recent_odo;

                            actOdom3D.computeFromOdometry(
                                odo_incr, actOdom3D_params);
                            action->insert(actOdom3D);
                        }
                        else
                        {
                            CActionRobotMovement2D actOdom2D;

                            const CPose2D odo_incr =
                                pending_most_recent_odo - last_used_abs_odo;
                            last_used_abs_odo = pending_most_recent_odo;

                            actOdom2D.computeFromOdometry(
                                odo_incr, actOdom2D_params);
                            action->insert(actOdom2D);
                        }
                    }
                }
                else
                {
                    // Already in Act-SF format, nothing else to do!
                }

                CPose2D expectedPose;  // Ground truth

                if (observations->size() > 0)
                    cur_obs_timestamp =
                        observations->getObservationByIndex(0)->timestamp;
                else if (obs)
                    cur_obs_timestamp = obs->timestamp;

                if (step >= rawlog_offset)
                {
                    // Do not execute the PF at "step=0", to let the initial
                    // PDF to be reflected in the logs.
                    if (step > rawlog_offset)
                    {
                        // Show 3D?
                        if (SHOW_PROGRESS_3D_REAL_TIME)
                        {
                            const auto [cov, meanPose] =
                                pdf.getCovarianceAndMean();

                            if (rawlogEntry >= 2)
                                getGroundTruth(
                                    expectedPose, rawlogEntry - 2, GT,
                                    cur_obs_timestamp);

                            // The particles' cov:
                            {
                                CRenderizable::Ptr ellip =
                                    scene.getByName("parts_cov");
                                if (!ellip)
                                {
                                    if (pf2gauss_t<MONTECARLO_TYPE>::PF_IS_3D)
                                    {
                                        auto el = CEllipsoid3D::Create();
                                        ellip =
                                            mrpt::ptr_cast<CRenderizable>::from(
                                                el);
                                        el->setLineWidth(2);
                                        el->setQuantiles(3);
                                        el->enableDrawSolid3D(false);
                                    }
                                    else
                                    {
                                        auto el = CEllipsoid2D::Create();
                                        ellip =
                                            mrpt::ptr_cast<CRenderizable>::from(
                                                el);
                                        el->setLineWidth(2);
                                        el->setQuantiles(3);
                                        el->enableDrawSolid3D(false);
                                    }
                                    ellip->setName("parts_cov");
                                    ellip->setColor(1, 0, 0, 0.6);
                                    scene.insert(ellip);
                                }
                                else
                                {
                                    if (pf2gauss_t<MONTECARLO_TYPE>::PF_IS_3D)
                                    {
                                        mrpt::ptr_cast<CEllipsoid3D>::from(
                                            ellip)
                                            ->setCovMatrix(
                                                cov.template blockCopy<3, 3>());
                                    }
                                    else
                                    {
                                        mrpt::ptr_cast<CEllipsoid2D>::from(
                                            ellip)
                                            ->setCovMatrix(
                                                cov.template blockCopy<2, 2>());
                                    }
                                }
                                double ellipse_z =
                                    mrpt::poses::CPose3D(meanPose).z() + 0.01;

                                ellip->setLocation(
                                    meanPose.x(), meanPose.y(), ellipse_z);
                            }

                            COpenGLScene::Ptr ptrSceneWin =
                                win3D->get3DSceneAndLock();

                            win3D->setCameraPointingToPoint(
                                meanPose.x(), meanPose.y(), 0);

                            win3D->addTextMessage(
                                10, 10,
                                mrpt::format(
                                    "timestamp: %s",
                                    mrpt::system::dateTimeLocalToString(
                                        cur_obs_timestamp)
                                        .c_str()),
                                6001);

                            win3D->addTextMessage(
                                10, 33,
                                mrpt::format(
                                    "#particles= %7u",
                                    static_cast<unsigned int>(pdf.size())),
                                6002);

                            win3D->addTextMessage(
                                10, 55,
                                mrpt::format(
                                    "mean pose (x y phi_deg)= %s",
                                    meanPose.asString().c_str()),
                                6003);

                            *ptrSceneWin = scene;
                            win3D->unlockAccess3DScene();

                            // Update:
                            win3D->forceRepaint();

                            std::this_thread::sleep_for(
                                std::chrono::milliseconds(
                                    SHOW_PROGRESS_3D_REAL_TIME_DELAY_MS));
                        }  // end show 3D real-time

                        // ----------------------------------------
                        // RUN ONE STEP OF THE PARTICLE FILTER:
                        // ----------------------------------------
                        tictac.Tic();
                        if (!SAVE_STATS_ONLY)
                        {
                            MRPT_LOG_INFO_STREAM(
                                "Step "
                                << step << ". Executing ParticleFilter on "
                                << pdf.particlesCount() << " particles...");
                        }

                        PF.executeOn(
                            pdf,
                            action.get(),  // Action
                            observations.get(),  // Obs.
                            &PF_stats  // Output statistics
                        );

                        double run_time = tictac.Tac();
                        executionTimes.push_back(run_time);
                        if (!SAVE_STATS_ONLY)
                        {
                            MRPT_LOG_INFO_FMT(
                                "Done in %.03fms, ESS=%f", 1e3 * run_time,
                                pdf.ESS());
                        }
                    }

                    // Avrg. error:
                    // ----------------------------------------
                    CActionRobotMovement2D::Ptr best_mov_estim =
                        action->getBestMovementEstimation();
                    if (best_mov_estim)
                    {
                        odometryEstimation =
                            odometryEstimation +
                            best_mov_estim->poseChange->getMeanVal();
                    }

                    pdf.getMean(pdfEstimation);

                    // save estimated mean in history:
                    if (cur_obs_timestamp != INVALID_TIMESTAMP &&
                        fill_out_estimated_path)
                    {
                        out_estimated_path.insert(
                            cur_obs_timestamp,
                            mrpt::math::TPose3D(pdfEstimation.asTPose()));
                    }

                    getGroundTruth(
                        expectedPose, rawlogEntry, GT, cur_obs_timestamp);

                    if (expectedPose.x() != 0 || expectedPose.y() != 0 ||
                        expectedPose.phi() != 0)
                    {  // Averaged error to GT
                        double sumW = 0;
                        double locErr = 0;
                        for (size_t k = 0; k < pdf.size(); k++)
                            sumW += exp(pdf.getW(k));
                        for (size_t k = 0; k < pdf.size(); k++)
                        {
                            const auto pk = pdf.getParticlePose(k);
                            locErr += mrpt::hypot_fast(
                                          expectedPose.x() - pk.x,
                                          expectedPose.y() - pk.y) *
                                      exp(pdf.getW(k)) / sumW;
                        }
                        convergenceErrors_mtx.lock();
                        convergenceErrors.push_back(locErr);
                        convergenceErrors_mtx.unlock();

                        indivConvergenceErrors.push_back(locErr);
                        odoError.push_back(
                            expectedPose.distanceTo(odometryEstimation));
                    }

                    const auto [C, M] = pdf.getCovarianceAndMean();
                    const auto current_pdf_gaussian =
                        typename pf2gauss_t<MONTECARLO_TYPE>::type(M, C);

                    // Text output:
                    // ----------------------------------------
                    if (!SAVE_STATS_ONLY)
                    {
                        MRPT_LOG_INFO_STREAM(
                            "Odometry estimation: " << odometryEstimation);
                        MRPT_LOG_INFO_STREAM(
                            "PDF estimation: "
                            << pdfEstimation << ", ESS (B.R.)= "
                            << PF_stats.ESS_beforeResample << " tr(cov): "
                            << std::sqrt(current_pdf_gaussian.cov.trace()));

                        if (GT.rows() > 0)
                            MRPT_LOG_INFO_STREAM(
                                "Ground truth: " << expectedPose);
                    }

                    // Evaluate the "reliability" of the pose estimation
                    // (for now, only for 2D laser scans + grid maps)
                    double obs_reliability_estim = .0;
                    if (DO_RELIABILITY_ESTIMATE)
                    {
                        // We need: a gridmap & a 2D LIDAR:
                        CObservation2DRangeScan::Ptr obs_scan;
                        if (observations)
                            obs_scan = observations->getObservationByClass<
                                CObservation2DRangeScan>(0);  // Get the 0'th
                        // scan, if
                        // several are
                        // present.
                        COccupancyGridMap2D::Ptr gridmap =
                            metricMap.mapByClass<COccupancyGridMap2D>();
                        if (obs_scan && gridmap)  // We have both, go on:
                        {
                            // Simulate scan + uncertainty:
                            COccupancyGridMap2D::TLaserSimulUncertaintyParams
                                ssu_params;
                            COccupancyGridMap2D::TLaserSimulUncertaintyResult
                                ssu_out;
                            ssu_params.method =
                                COccupancyGridMap2D::sumUnscented;
                            // ssu_params.UT_alpha = 0.99;
                            // obs_scan->stdError = 0.07;
                            // obs_scan->maxRange = 10.0;

                            ssu_params.robotPose =
                                CPosePDFGaussian(current_pdf_gaussian);
                            ssu_params.aperture = obs_scan->aperture;
                            ssu_params.rangeNoiseStd = obs_scan->stdError;
                            ssu_params.nRays = obs_scan->getScanSize();
                            ssu_params.rightToLeft = obs_scan->rightToLeft;
                            ssu_params.sensorPose = obs_scan->sensorPose;
                            ssu_params.maxRange = obs_scan->maxRange;

                            gridmap->laserScanSimulatorWithUncertainty(
                                ssu_params, ssu_out);

                            // Evaluate reliability:
                            CObservation2DRangeScanWithUncertainty::TEvalParams
                                evalParams;
                            // evalParams.prob_outliers = 0.40;
                            // evalParams.max_prediction_std_dev = 1.0;
                            obs_reliability_estim =
                                ssu_out.scanWithUncert.evaluateScanLikelihood(
                                    *obs_scan, evalParams);

                            if (DO_SCAN_LIKELIHOOD_DEBUG)
                            {
                                static mrpt::gui::CDisplayWindowPlots win;

                                std::vector<float> ranges_mean, ranges_obs;
                                for (size_t i = 0; i < obs_scan->getScanSize();
                                     i++)
                                {
                                    ranges_mean.push_back(
                                        ssu_out.scanWithUncert.rangeScan
                                            .getScanRange(i));
                                    ranges_obs.push_back(
                                        obs_scan->getScanRange(i));
                                }

                                win.plot(ranges_mean, "3k-", "mean");
                                win.plot(ranges_obs, "r-", "obs");

                                Eigen::VectorXd ci1 =
                                    ssu_out.scanWithUncert.rangesMean
                                        .asEigen() +
                                    3 * ssu_out.scanWithUncert.rangesCovar
                                            .asEigen()
                                            .diagonal()
                                            .array()
                                            .sqrt()
                                            .matrix();
                                Eigen::VectorXd ci2 =
                                    ssu_out.scanWithUncert.rangesMean
                                        .asEigen() -
                                    3 * ssu_out.scanWithUncert.rangesCovar
                                            .asEigen()
                                            .diagonal()
                                            .array()
                                            .sqrt()
                                            .matrix();
                                win.plot(ci1, "k-", "CI+");
                                win.plot(ci2, "k-", "CI-");

                                win.setWindowTitle(mrpt::format(
                                    "obs_reliability_estim: %f",
                                    obs_reliability_estim));
                                win.axis_fit();
                            }
                        }
                        MRPT_LOG_INFO_STREAM(
                            "Reliability measure [0-1]: "
                            << obs_reliability_estim);
                    }

                    if (!SAVE_STATS_ONLY)
                    {
                        f_cov_est.printf("%e\n", sqrt(cov.det()));
                        f_pf_stats.printf(
                            "%u %e %e %f %f\n", (unsigned int)pdf.size(),
                            PF_stats.ESS_beforeResample,
                            PF_stats.weightsVariance_beforeResample,
                            obs_reliability_estim,
                            sqrt(current_pdf_gaussian.cov.det()));
                        f_odo_est.printf(
                            "%f %f %f\n", odometryEstimation.x(),
                            odometryEstimation.y(), odometryEstimation.phi());
                    }

                    const auto [cov, meanPose] = pdf.getCovarianceAndMean();

                    if ((!SAVE_STATS_ONLY && SCENE3D_FREQ > 0) ||
                        SHOW_PROGRESS_3D_REAL_TIME)
                    {
                        // Generate 3D scene:
                        // ------------------------------

                        // The Ground Truth (GT):
                        if (GT.rows() > 0)
                        {
                            CRenderizable::Ptr GTpt = scene.getByName("GT");
                            if (!GTpt)
                            {
                                GTpt = std::make_shared<CDisk>();
                                GTpt = std::make_shared<CDisk>();
                                GTpt->setName("GT");
                                GTpt->setColor(0, 0, 0, 0.9);

                                mrpt::ptr_cast<CDisk>::from(GTpt)
                                    ->setDiskRadius(0.04f);
                                scene.insert(GTpt);
                            }

                            GTpt->setPose(expectedPose);
                        }

                        // The particles:
                        {
                            CRenderizable::Ptr parts =
                                scene.getByName("particles");
                            if (parts) scene.removeObject(parts);

                            auto p = pdf.template getAs3DObject<
                                CSetOfObjects::Ptr>();
                            p->setName("particles");
                            scene.insert(p);
                        }

                        // The laser scan:
                        {
                            CRenderizable::Ptr scanPts =
                                scene.getByName("scan");
                            if (!scanPts)
                            {
                                scanPts = std::make_shared<CPointCloud>();
                                scanPts->setName("scan");
                                scanPts->setColor(1, 0, 0, 0.9);
                                mrpt::ptr_cast<CPointCloud>::from(scanPts)
                                    ->enableColorFromZ(false);
                                mrpt::ptr_cast<CPointCloud>::from(scanPts)
                                    ->setPointSize(4);
                                scene.insert(scanPts);
                            }

                            CSimplePointsMap map;

                            CPose3D robotPose3D(meanPose);

                            map.clear();
                            observations->insertObservationsInto(&map);

                            mrpt::ptr_cast<CPointCloud>::from(scanPts)
                                ->loadFromPointsMap(&map);
                            mrpt::ptr_cast<CPointCloud>::from(scanPts)->setPose(
                                robotPose3D);
                        }

                        // The camera:
                        scene.enableFollowCamera(SCENE3D_FOLLOW);

                        // Views:
                        COpenGLViewport::Ptr view1 = scene.getViewport("main");
                        {
                            CCamera& cam = view1->getCamera();
                            cam.setAzimuthDegrees(-90);
                            cam.setElevationDegrees(90);
                            cam.setPointingAt(meanPose);
                            cam.setZoomDistance(5);
                            cam.setOrthogonal();
                        }
                    }

                    if (!SAVE_STATS_ONLY && SCENE3D_FREQ != -1 &&
                        ((step + 1) % SCENE3D_FREQ) == 0)
                    {
                        // Save 3D scene:
                        CFileGZOutputStream f(format(
                            "%s/progress_%05u.3Dscene", sOUT_DIR_3D.c_str(),
                            (unsigned)step));
                        archiveFrom(f) << scene;

                        // Generate text files for matlab:
                        // ------------------------------------
                        pdf.saveToTextFile(format(
                            "%s/particles_%05u.txt", sOUT_DIR_PARTS.c_str(),
                            (unsigned)step));
                    }

                }  // end if rawlog_offset

                step++;

                // Test for end condition if we are testing convergence:
                if (step == testConvergenceAt)
                {
                    nConvergenceTests++;

                    // Convergence??
                    if (sqrt(cov.det()) < 2)
                    {
                        if (pdfEstimation.distanceTo(expectedPose) < 2)
                            nConvergenceOK++;
                    }
                    end = true;
                }
            };  // while rawlogEntries

            indivConvergenceErrors.saveToTextFile(sOUT_DIR + "/GT_error.txt");
            odoError.saveToTextFile(sOUT_DIR + "/ODO_error.txt");
            executionTimes.saveToTextFile(sOUT_DIR + "/exec_times.txt");

            if (win3D && NUM_REPS == 1) mrpt::system::pause();
        };  // for repetitions

        CTicTac tictacGlobal;
        tictacGlobal.Tic();

        const auto max_num_threads = std::thread::hardware_concurrency();
        size_t runs_per_thread = NUM_REPS;
        if (max_num_threads > 1)
            runs_per_thread = static_cast<size_t>(
                std::ceil((NUM_REPS) / static_cast<double>(max_num_threads)));

        MRPT_LOG_INFO_STREAM(
            "Running " << NUM_REPS << " repetitions, on max " << max_num_threads
                       << " parallel threads: " << runs_per_thread
                       << " runs/thread.");

        std::vector<std::thread> running_tasks;
        for (size_t r = 0; r < NUM_REPS; r += runs_per_thread)
        {
            auto runner = [&](size_t i_start, size_t i_end) {
                if (i_end > NUM_REPS) i_end = NUM_REPS;  // sanity check
                for (size_t i = i_start; i < i_end; i++)
                    run_localization_code(i);
            };

            running_tasks.emplace_back(runner, r, r + runs_per_thread);
            std::this_thread::sleep_for(std::chrono::milliseconds(100));
        }

        // Wait for all threads to end:
        for (auto& t : running_tasks)
            if (t.joinable()) t.join();

        double repetitionTime = tictacGlobal.Tac();

        // Avr. error:
        double covergenceErrorMean = 0, convergenceErrorsMin = 0,
               convergenceErrorsMax = 0;
        if (!convergenceErrors.empty())
            math::confidenceIntervals(
                convergenceErrors, covergenceErrorMean, convergenceErrorsMin,
                convergenceErrorsMax, STATS_CONF_INTERVAL);

        // Save overall results:
        {
            CFileOutputStream f(
                format("%s_SUMMARY.txt", OUT_DIR_PREFIX.c_str()),
                true /* append */);

            f.printf(
                "%% Ratio_covergence_success  #particles  "
                "average_time_per_execution  convergence_mean_error "
                "convergence_error_conf_int_inf "
                "convergence_error_conf_int_sup "
                "\n");
            if (!nConvergenceTests) nConvergenceTests = 1;
            f.printf(
                "%f %u %f %f %f %f\n",
                ((double)nConvergenceOK) / nConvergenceTests, PARTICLE_COUNT,
                repetitionTime / NUM_REPS, covergenceErrorMean,
                convergenceErrorsMin, convergenceErrorsMax);
        }

        MRPT_LOG_INFO_FMT("Total execution time: %.06f sec", repetitionTime);

    }  // end of loop for different # of particles
}

void MonteCarloLocalization_Base::getGroundTruth(
    mrpt::poses::CPose2D& expectedPose, size_t rawlogEntry,
    const mrpt::math::CMatrixDouble& GT, const Clock::time_point& cur_time)
{
    // Either:
    // - time x y phi
    // or
    // - time x y z yaw pitch roll

    if (GT.cols() == 4 || GT.cols() == 7)
    {
        bool GT_index_is_time;

        // First column can be: timestamps, or rawlogentries:
        //  Auto-figure it out:
        if (GT.rows() > 2)
        {
            GT_index_is_time =
                floor(GT(0, 0)) != GT(0, 0) && floor(GT(1, 0)) != GT(1, 0);
        }
        else
        {
            GT_index_is_time = false;
        }

        if (GT_index_is_time)
        {
            // Look for the timestamp:
            using namespace std::chrono_literals;

            bool interp_ok = false;
            GT_path.interpolate(cur_time, expectedPose, interp_ok);
            if (!interp_ok)
            {
                /*
                cerr << format(
                    "GT time not found: %f\n",
                    mrpt::system::timestampTotime_t(cur_time));
                    */
            }
        }
        else
        {
            // Look for the rawlogEntry:
            size_t k, N = GT.rows();
            for (k = 0; k < N; k++)
            {
                if (GT(k, 0) == rawlogEntry) break;
            }

            if (k < N)
            {
                expectedPose.x(GT(k, 1));
                expectedPose.y(GT(k, 2));
                expectedPose.phi(GT(k, 3));
            }
        }
    }
    else if (GT.cols() == 3)
    {
        if ((int)rawlogEntry < GT.rows())
        {
            expectedPose.x(GT(rawlogEntry, 0));
            expectedPose.y(GT(rawlogEntry, 1));
            expectedPose.phi(GT(rawlogEntry, 2));
        }
    }
    else if (GT.cols() > 0)
        THROW_EXCEPTION("Unexpected number of columns in ground truth file");
}

void MonteCarloLocalization_Base::prepareGT(const mrpt::math::CMatrixDouble& GT)
{
    // Either:
    // - time x y phi
    // or
    // - time x y z yaw pitch roll
    if (GT.cols() == 4 || GT.cols() == 7)
    {
        const bool GT_is_3D = (GT.cols() == 7);
        bool GT_index_is_time = false;

        // First column can be: timestamps, or rawlogentries:
        //  Auto-figure it out:
        if (GT.rows() > 2)
        {
            GT_index_is_time =
                floor(GT(0, 0)) != GT(0, 0) && floor(GT(1, 0)) != GT(1, 0);
        }

        if (GT_index_is_time)
        {
            // Look for the timestamp:
            using namespace std::chrono_literals;
            GT_path.setMaxTimeInterpolation(200ms);

            for (int i = 0; i < GT.rows(); i++)
            {
                GT_path.insert(
                    mrpt::Clock::fromDouble(GT(i, 0)),
                    TPose2D(GT(i, 1), GT(i, 2), GT(i, GT_is_3D ? 4 : 3)));
            }
        }
    }
}

void MonteCarloLocalization_Base::run()
{
    MRPT_START

    // Detect 2D vs 3D particle filter?
    const bool is_3D = params.read_bool(sect, "use_3D_poses", false);

    if (is_3D)
    {
        MRPT_LOG_INFO("Running for: CMonteCarloLocalization3D");
        do_pf_localization<CMonteCarloLocalization3D>();
    }
    else
    {
        MRPT_LOG_INFO("Running for: CMonteCarloLocalization2D");
        do_pf_localization<CMonteCarloLocalization2D>();
    }

    MRPT_END
}

// ---------------------------------------
//   MonteCarloLocalization_Rawlog
// ---------------------------------------
MonteCarloLocalization_Rawlog::MonteCarloLocalization_Rawlog()
{
    setLoggerName("MonteCarloLocalization_Rawlog");
}

void MonteCarloLocalization_Rawlog::impl_initialize(int argc, const char** argv)
{
    MRPT_START
    // Rawlog file: from args. line or from config file:
    if (argc == 3)
        m_rawlogFileName = std::string(argv[2]);
    else
        m_rawlogFileName = params.read_string(
            sect, "rawlog_file", std::string("log.rawlog"), true);

    m_rawlog_offset = params.read_int(sect, "rawlog_offset", 0);

    ASSERT_FILE_EXISTS_(m_rawlogFileName);

    MRPT_END
}