mrpt_localization_core.cpp

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#include <mrpt_localization/mrpt_localization_core.h>

using namespace mrpt;
using namespace mrpt::slam;
using namespace mrpt::opengl;
using namespace mrpt::math;
using namespace mrpt::system;
using namespace mrpt::utils;
using namespace std;

PFLocalizationCore::~PFLocalizationCore() {}
PFLocalizationCore::PFLocalizationCore() : state_(NA) {}
void PFLocalizationCore::init()
{
        mrpt::math::CMatrixDouble33 cov;
        cov(0, 0) = 1, cov(1, 1) = 1, cov(2, 2) = 2 * M_PI;
        initial_pose_ =
                mrpt::poses::CPosePDFGaussian(mrpt::poses::CPose2D(0, 0, 0), cov);
        initial_particle_count_ = 1000;

        motion_model_default_options_.modelSelection =
                CActionRobotMovement2D::mmGaussian;
        motion_model_default_options_.gaussianModel.minStdXY = 0.10;
        motion_model_default_options_.gaussianModel.minStdPHI = 2.0;
}

void PFLocalizationCore::initializeFilter()
{
        mrpt::math::CMatrixDouble33 cov;
        mrpt::poses::CPose2D mean_point;
        initial_pose_.getCovarianceAndMean(cov, mean_point);
        log_info(
                "InitializeFilter: %4.3fm, %4.3fm, %4.3frad ", mean_point.x(),
                mean_point.y(), mean_point.phi());
        float min_x = mean_point.x() - cov(0, 0);
        float max_x = mean_point.x() + cov(0, 0);
        float min_y = mean_point.y() - cov(1, 1);
        float max_y = mean_point.y() + cov(1, 1);
        float min_phi = mean_point.phi() - cov(2, 2);
        float max_phi = mean_point.phi() + cov(2, 2);
        if (metric_map_.m_gridMaps.size() && !init_PDF_mode)
        {
                pdf_.resetUniformFreeSpace(
                        metric_map_.m_gridMaps[0].get(), 0.7f, initial_particle_count_,
                        min_x, max_x, min_y, max_y, min_phi, max_phi);
        }
        else if (metric_map_.m_landmarksMap || init_PDF_mode)
        {
                pdf_.resetUniform(
                        min_x, max_x, min_y, max_y, min_phi, max_phi,
                        initial_particle_count_);
        }
        state_ = RUN;
}

void PFLocalizationCore::updateFilter(
        CActionCollection::Ptr _action, CSensoryFrame::Ptr _sf)
{
        if (state_ == INIT) initializeFilter();
        tictac_.Tic();
        pf_.executeOn(pdf_, _action.get(), _sf.get(), &pf_stats_);
        time_last_update_ = _sf->getObservationByIndex(0)->timestamp;
        update_counter_++;
}

void PFLocalizationCore::observation(
        CSensoryFrame::Ptr _sf, CObservationOdometry::Ptr _odometry)
{
        CActionCollection::Ptr action =
                mrpt::make_aligned_shared<CActionCollection>();
        CActionRobotMovement2D odom_move;
        odom_move.timestamp = _sf->getObservationByIndex(0)->timestamp;
        if (_odometry)
        {
                if (odom_last_observation_.empty())
                {
                        odom_last_observation_ = _odometry->odometry;
                }
                mrpt::poses::CPose2D incOdoPose =
                        _odometry->odometry - odom_last_observation_;
                odom_last_observation_ = _odometry->odometry;
                odom_move.computeFromOdometry(incOdoPose, motion_model_options_);
                action->insert(odom_move);
                updateFilter(action, _sf);
        }
        else
        {
                if (use_motion_model_default_options_)
                {
                        log_info(
                                "No odometry at update %4i -> using dummy", update_counter_);
                        odom_move.computeFromOdometry(
                                mrpt::poses::CPose2D(0, 0, 0), motion_model_default_options_);
                        action->insert(odom_move);
                        updateFilter(action, _sf);
                }
                else
                {
                        log_info(
                                "No odometry at update %4i -> skipping observation",
                                update_counter_);
                }
        }
}