void CFormPlayVideo::OnprogressBarCmdScrollChanged(wxScrollEvent& event)
{
int idx = progressBar->GetValue();
m_idxInRawlog = idx;
if (idx > 0 && idx < (int)rawlog.size())
{
if (rawlog.getType(idx) == CRawlog::etSensoryFrame)
{
size_t dummy = 0;
CSensoryFrame::Ptr sf = rawlog.getAsObservations(idx);
showSensoryFrame(sf.get(), dummy);
edIndex->SetValue(idx);
}
else if (rawlog.getType(idx) == CRawlog::etObservation)
{
size_t dummy = 0;
CObservation::Ptr o = rawlog.getAsObservation(idx);
CSensoryFrame sf;
sf.insert(o);
showSensoryFrame(&sf, dummy);
edIndex->SetValue(idx);
}
}
}
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_++;
}
/*---------------------------------------------------------------
pushObservation
---------------------------------------------------------------*/
void CHMTSLAM::pushObservation(const CObservation::Ptr& obs)
{
if (m_terminateThreads)
{ // Discard it:
// delete obs;
return;
}
// Add a CSensoryFrame with the obs:
CSensoryFrame::Ptr sf = mrpt::make_aligned_shared<CSensoryFrame>();
sf->insert(
obs); // memory will be freed when deleting the SF in other thread
{ // Wait for critical section
std::lock_guard<std::mutex> lock(m_inputQueue_cs);
m_inputQueue.push(sf);
}
}
void PFLocalizationCore::observation(
CSensoryFrame::Ptr _sf, CObservationOdometry::Ptr _odometry)
{
auto action = CActionCollection::Create();
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_);
}
}
}
/*---------------------------------------------------------------
CLSLAM_RBPF_2DLASER
Implements a 2D local SLAM method based on a RBPF
over an occupancy grid map. A part of HMT-SLAM.
\param LMH The local metric hypothesis which must be updated by this SLAM
algorithm.
\param act The action to process (or nullptr).
\param sf The observations to process (or nullptr).
WE ALREADY HAVE CONTROL OVER THE CRITICAL SECTION OF THE LMHs!
--------------------------------------------------------------- */
void CLSLAM_RBPF_2DLASER::processOneLMH(
CLocalMetricHypothesis* LMH, const CActionCollection::Ptr& actions,
const CSensoryFrame::Ptr& sf)
{
MRPT_START
// Get the current robot pose estimation:
TPoseID currentPoseID = LMH->m_currentRobotPose;
// If this is the first iteration, just create a new robot pose at the
// origin:
if (currentPoseID == POSEID_INVALID)
{
currentPoseID = CHMTSLAM::generatePoseID();
LMH->m_currentRobotPose = currentPoseID; // Change it in the LMH
// Create a new robot pose:
CPose3D initPose(0, 0, 0);
ASSERT_(LMH->m_particles.size() > 0);
for (auto& m_particle : LMH->m_particles)
m_particle.d->robotPoses[currentPoseID] = initPose;
ASSERT_(m_parent->m_map.nodeCount() == 1);
m_parent->m_map_cs.lock();
CHMHMapNode::Ptr firstArea = m_parent->m_map.getFirstNode();
ASSERT_(firstArea);
LMH->m_nodeIDmemberships[currentPoseID] = firstArea->getID();
// Set annotation for the reference pose:
firstArea->m_annotations.setElemental(
NODE_ANNOTATION_REF_POSEID, currentPoseID, LMH->m_ID);
m_parent->m_map_cs.unlock();
}
bool insertNewRobotPose = false;
if (sf)
{
if (LMH->m_nodeIDmemberships.size() < 2) // If there is just 1 node
// (the current robot pose),
// then there is no
// observation in the map yet!
{ // Update map if this is the first observation!
insertNewRobotPose = true;
}
else
{
// Check minimum distance from current robot pose to those in the
// neighborhood:
TMapPoseID2Pose3D lstRobotPoses;
LMH->getMeans(lstRobotPoses);
CPose3D* currentRobotPose = &lstRobotPoses[currentPoseID];
float minDistLin = 1e6f;
float minDistAng = 1e6f;
// printf("Poses in graph:\n");
for (auto& lstRobotPose : lstRobotPoses)
{
if (lstRobotPose.first != currentPoseID)
{
float linDist =
lstRobotPose.second.distanceTo(*currentRobotPose);
float angDist = fabs(math::wrapToPi(
lstRobotPose.second.yaw() - currentRobotPose->yaw()));
minDistLin = min(minDistLin, linDist);
if (linDist < m_parent->m_options.SLAM_MIN_DIST_BETWEEN_OBS)
minDistAng = min(minDistAng, angDist);
}
}
// time to insert a new node??
insertNewRobotPose =
(minDistLin > m_parent->m_options.SLAM_MIN_DIST_BETWEEN_OBS) ||
(minDistAng > m_parent->m_options.SLAM_MIN_HEADING_BETWEEN_OBS);
}
} // end if there are SF
// Save data in members so PF callback "prediction_and_update_pfXXXX" have
// access to them:
m_insertNewRobotPose = insertNewRobotPose;
// ------------------------------------------------
// Execute RBPF method:
// 1) PROCESS ACTION
// 2) PROCESS OBSERVATIONS
// ------------------------------------------------
CParticleFilter pf;
pf.m_options = m_parent->m_options.pf_options;
pf.executeOn(*LMH, actions.get(), sf.get());
// 3) The appearance observation: update the log likelihood
// ...
// -----------------------------------------------------------
// 4) UPDATE THE MAP
// -----------------------------------------------------------
if (insertNewRobotPose)
{
m_parent->logStr(
mrpt::system::LVL_INFO,
"[CLSLAM_RBPF_2DLASER] Adding new pose...\n");
// Leave the up-to-now "current pose" in the map, insert the SF in it,
// and...
// ----------------------------------------------------------------------------
TPoseID newCurrentPoseID = CHMTSLAM::generatePoseID();
// ...and create a new "current pose" making a copy of the previous
// one:
// and insert the observations into the metric maps:
// ----------------------------------------------------------------------------
for (auto& m_particle : LMH->m_particles)
{
const CPose3D* curRobotPose =
&m_particle.d->robotPoses[currentPoseID];
m_particle.d->robotPoses[newCurrentPoseID] = *curRobotPose;
sf->insertObservationsInto(&m_particle.d->metricMaps, curRobotPose);
}
// Add node membership: for now, a copy of the current pose:
LMH->m_nodeIDmemberships[newCurrentPoseID] =
LMH->m_nodeIDmemberships[currentPoseID];
// Now, insert the SF in the just added robot pose:
// -----------------------------------------------------
LMH->m_SFs[currentPoseID] = *sf;
// Sets the new poseID as current robot pose:
// ----------------------------------------------------
TPoseID newlyAddedPose = currentPoseID;
currentPoseID = LMH->m_currentRobotPose = newCurrentPoseID;
// Mark the "newlyAddedPose" as pending to reconsider in the graph-cut
// method
// (Done in the main loop @ LSLAM thread)
// --------------------------------------------------------------------------------
LMH->m_posesPendingAddPartitioner.push_back(newlyAddedPose);
m_parent->logFmt(
mrpt::system::LVL_INFO, "[CLSLAM_RBPF_2DLASER] Added pose %i.\n",
(int)newlyAddedPose);
// Notice LC detectors:
// ------------------------------
{
std::lock_guard<std::mutex> lock(m_parent->m_topLCdets_cs);
for (auto& m_topLCdet : m_parent->m_topLCdets)
m_topLCdet->OnNewPose(newlyAddedPose, sf.get());
}
} // end of insertNewRobotPose
MRPT_END
}
void xRawLogViewerFrame::OnMenuShiftTimestampsByLabel(wxCommandEvent& event)
{
WX_START_TRY
wxMessageBox(
_("The timestamps of all the observations of a given sensor label will "
"be shifted a given number of seconds. Press OK to continue."));
vector_string the_labels =
AskForObservationByLabelMultiple("Choose the sensor(s):");
if (the_labels.empty()) return;
wxString s = wxGetTextFromUser(
_("Enter the number of seconds to shift (can have fractions, be "
"positive or negative)"),
_("Timestamp shift"), _("0.0"), this);
if (s.IsEmpty()) return;
double delta_time_secs;
if (!s.ToDouble(&delta_time_secs))
{
wxMessageBox(_("Invalid number"));
return;
}
size_t i, n = rawlog.size();
unsigned int nChanges = 0;
TTimeStamp DeltaTime = mrpt::system::secondsToTimestamp(delta_time_secs);
for (i = 0; i < n; i++)
{
switch (rawlog.getType(i))
{
case CRawlog::etSensoryFrame:
{
CSensoryFrame::Ptr sf = rawlog.getAsObservations(i);
CObservation::Ptr o;
for (size_t k = 0; k < the_labels.size(); k++)
{
size_t idx = 0;
while (
(o = sf->getObservationBySensorLabel(
the_labels[k], idx++)))
{
o->timestamp += DeltaTime;
nChanges++;
}
}
}
break;
case CRawlog::etObservation:
{
CObservation::Ptr o = rawlog.getAsObservation(i);
for (size_t k = 0; k < the_labels.size(); k++)
if (o->sensorLabel == the_labels[k])
{
o->timestamp += DeltaTime;
nChanges++;
}
}
break;
default:
break;
} // end switch type
} // end for
if (wxYES == wxMessageBox(
wxString::Format(
_("%u changes. Do you want to re-order by timestamp?"),
nChanges),
_("Done"), wxYES_NO, this))
{
OnMenuResortByTimestamp(event);
}
WX_END_TRY
}
void xRawLogViewerFrame::OnMenuCompactRawlog(wxCommandEvent& event)
{
WX_START_TRY
bool onlyOnePerLabel =
(wxYES == wxMessageBox(
_("Keep only one observation of each label within each "
"sensoryframe?"),
_("Compact rawlog"), wxYES_NO, this));
int progress_N = static_cast<int>(rawlog.size());
int progress_i = progress_N;
wxProgressDialog progDia(
wxT("Compacting rawlog"), wxT("Processing..."),
progress_N, // range
this, // parent
wxPD_CAN_ABORT | wxPD_APP_MODAL | wxPD_SMOOTH | wxPD_AUTO_HIDE |
wxPD_ELAPSED_TIME | wxPD_ESTIMATED_TIME | wxPD_REMAINING_TIME);
wxTheApp->Yield(); // Let the app. process messages
CActionRobotMovement2D::Ptr lastAct;
CSensoryFrame::Ptr lastSF; // = nullptr;
unsigned counter_loops = 0;
unsigned nActionsDel = 0;
unsigned nEmptySFDel = 0;
CRawlog::iterator it = rawlog.begin();
for (progress_i = 0; it != rawlog.end(); progress_i--)
{
if (counter_loops++ % 50 == 0)
{
if (!progDia.Update(progress_N - progress_i)) break;
wxTheApp->Yield(); // Let the app. process messages
}
bool deleteThis = false;
if (it.getType() == CRawlog::etActionCollection)
{
// Is this a part of multiple actions?
if (lastAct)
{
// Remove this one and add it to the first in the series:
CActionRobotMovement2D::Ptr act =
std::dynamic_pointer_cast<CActionCollection>(*it)
->getMovementEstimationByType(
CActionRobotMovement2D::emOdometry);
ASSERT_(act);
lastAct->computeFromOdometry(
lastAct->rawOdometryIncrementReading +
act->rawOdometryIncrementReading,
lastAct->motionModelConfiguration);
deleteThis = true;
nActionsDel++;
}
else
{
// This is the first one:
lastAct = std::dynamic_pointer_cast<CActionCollection>(*it)
->getMovementEstimationByType(
CActionRobotMovement2D::emOdometry);
ASSERT_(lastAct);
// Before leaving the last SF, leave only one observation for
// each sensorLabel:
if (onlyOnePerLabel && lastSF)
{
CSensoryFrame::Ptr newSF =
mrpt::make_aligned_shared<CSensoryFrame>();
set<string> knownLabels;
for (CSensoryFrame::const_iterator o = lastSF->begin();
o != lastSF->end(); ++o)
{
if (knownLabels.find((*o)->sensorLabel) ==
knownLabels.end())
newSF->insert(*o);
knownLabels.insert((*o)->sensorLabel);
}
*lastSF = *newSF;
}
// Ok, done:
lastSF.reset();
}
}
else if (it.getType() == CRawlog::etSensoryFrame)
{
// Is this a part of a series?
if (lastSF)
{
// remove this one and accumulate in the first in the serie:
lastSF->moveFrom(
*std::dynamic_pointer_cast<CSensoryFrame>(*it));
deleteThis = true;
nEmptySFDel++;
}
else
{
// This is the first SF:
CSensoryFrame::Ptr sf =
std::dynamic_pointer_cast<CSensoryFrame>(*it);
// Only take into account if not empty!
if (sf->size())
{
lastSF = sf;
ASSERT_(lastSF);
lastAct.reset();
}
else
{
deleteThis = true;
nEmptySFDel++;
}
}
}
else
THROW_EXCEPTION("Unexpected class found!")
if (deleteThis)
{
it = rawlog.erase(it);
progress_i--; // Extra count
}
else
it++;
}
progDia.Update(progress_N);
string str = format(
"%u actions deleted\n%u sensory frames deleted", nActionsDel,
nEmptySFDel);
::wxMessageBox(_U(str.c_str()));
rebuildTreeView();
WX_END_TRY
}
void Run_KF_SLAM(CConfigFile& cfgFile, const std::string& rawlogFileName)
{
// The EKF-SLAM class:
// Traits for this KF implementation (2D or 3D)
using traits_t = kfslam_traits<IMPL>;
using ekfslam_t = typename traits_t::ekfslam_t;
ekfslam_t mapping;
// The rawlog file:
// ----------------------------------------
const unsigned int rawlog_offset =
cfgFile.read_int("MappingApplication", "rawlog_offset", 0);
const unsigned int SAVE_LOG_FREQUENCY =
cfgFile.read_int("MappingApplication", "SAVE_LOG_FREQUENCY", 1);
const bool SAVE_DA_LOG =
cfgFile.read_bool("MappingApplication", "SAVE_DA_LOG", true);
const bool SAVE_3D_SCENES =
cfgFile.read_bool("MappingApplication", "SAVE_3D_SCENES", true);
const bool SAVE_MAP_REPRESENTATIONS = cfgFile.read_bool(
"MappingApplication", "SAVE_MAP_REPRESENTATIONS", true);
bool SHOW_3D_LIVE =
cfgFile.read_bool("MappingApplication", "SHOW_3D_LIVE", false);
const bool CAMERA_3DSCENE_FOLLOWS_ROBOT = cfgFile.read_bool(
"MappingApplication", "CAMERA_3DSCENE_FOLLOWS_ROBOT", false);
#if !MRPT_HAS_WXWIDGETS
SHOW_3D_LIVE = false;
#endif
string OUT_DIR = cfgFile.read_string(
"MappingApplication", "logOutput_dir", "OUT_KF-SLAM");
string ground_truth_file =
cfgFile.read_string("MappingApplication", "ground_truth_file", "");
string ground_truth_file_robot = cfgFile.read_string(
"MappingApplication", "ground_truth_file_robot", "");
string ground_truth_data_association = cfgFile.read_string(
"MappingApplication", "ground_truth_data_association", "");
cout << "RAWLOG FILE:" << endl << rawlogFileName << endl;
ASSERT_FILE_EXISTS_(rawlogFileName);
CFileGZInputStream rawlogFile(rawlogFileName);
cout << "---------------------------------------------------" << endl
<< endl;
deleteFilesInDirectory(OUT_DIR);
createDirectory(OUT_DIR);
// Load the config options for mapping:
// ----------------------------------------
mapping.loadOptions(cfgFile);
mapping.KF_options.dumpToConsole();
mapping.options.dumpToConsole();
// debug:
// mapping.KF_options.use_analytic_observation_jacobian = true;
// mapping.KF_options.use_analytic_transition_jacobian = true;
// mapping.KF_options.debug_verify_analytic_jacobians = true;
// Is there ground truth of the robot poses??
CMatrixDouble GT_PATH(0, 0);
if (ground_truth_file_robot.size() && fileExists(ground_truth_file_robot))
{
GT_PATH.loadFromTextFile(ground_truth_file_robot);
ASSERT_(GT_PATH.rows() > 0 && GT_PATH.cols() == 6);
}
// Is there a ground truth file of the data association?
std::map<double, std::vector<int>>
GT_DA; // Map: timestamp -> vector(index in observation -> real index)
mrpt::containers::bimap<int, int> DA2GTDA_indices; // Landmark indices
// bimapping: SLAM DA <--->
// GROUND TRUTH DA
if (!ground_truth_data_association.empty() &&
fileExists(ground_truth_data_association))
{
CMatrixDouble mGT_DA;
mGT_DA.loadFromTextFile(ground_truth_data_association);
ASSERT_ABOVEEQ_(mGT_DA.cols(), 3);
// Convert the loaded matrix into a std::map in GT_DA:
for (int i = 0; i < mGT_DA.rows(); i++)
{
std::vector<int>& v = GT_DA[mGT_DA(i, 0)];
if (v.size() <= mGT_DA(i, 1)) v.resize(mGT_DA(i, 1) + 1);
v[mGT_DA(i, 1)] = mGT_DA(i, 2);
}
cout << "Loaded " << GT_DA.size()
<< " entries from DA ground truth file\n";
}
// Create output file for DA perf:
std::ofstream out_da_performance_log;
{
const std::string f = std::string(
OUT_DIR + std::string("/data_association_performance.log"));
out_da_performance_log.open(f.c_str());
ASSERTMSG_(
out_da_performance_log.is_open(),
std::string("Error writing to: ") + f);
// Header:
out_da_performance_log
<< "% TIMESTAMP INDEX_IN_OBS TruePos "
"FalsePos TrueNeg FalseNeg NoGroundTruthSoIDontKnow \n"
<< "%--------------------------------------------------------------"
"--------------------------------------------------\n";
}
if (SHOW_3D_LIVE)
{
win3d = mrpt::make_aligned_shared<mrpt::gui::CDisplayWindow3D>(
"KF-SLAM live view", 800, 500);
win3d->addTextMessage(
0.01, 0.96, "Red: Estimated path", TColorf(0.8f, 0.8f, 0.8f), 100,
MRPT_GLUT_BITMAP_HELVETICA_10);
win3d->addTextMessage(
0.01, 0.93, "Black: Ground truth path", TColorf(0.8f, 0.8f, 0.8f),
101, MRPT_GLUT_BITMAP_HELVETICA_10);
}
// Create DA-log output file:
std::ofstream out_da_log;
if (SAVE_DA_LOG)
{
const std::string f =
std::string(OUT_DIR + std::string("/data_association.log"));
out_da_log.open(f.c_str());
ASSERTMSG_(out_da_log.is_open(), std::string("Error writing to: ") + f);
// Header:
out_da_log << "% TIMESTAMP INDEX_IN_OBS ID "
" RANGE(m) YAW(rad) PITCH(rad) \n"
<< "%-------------------------------------------------------"
"-------------------------------------\n";
}
// The main loop:
// ---------------------------------------
CActionCollection::Ptr action;
CSensoryFrame::Ptr observations;
size_t rawlogEntry = 0, step = 0;
vector<TPose3D> meanPath; // The estimated path
typename traits_t::posepdf_t robotPose;
const bool is_pose_3d = robotPose.state_length != 3;
std::vector<typename IMPL::landmark_point_t> LMs;
std::map<unsigned int, CLandmark::TLandmarkID> LM_IDs;
CMatrixDouble fullCov;
CVectorDouble fullState;
CTicTac kftictac;
auto rawlogArch = mrpt::serialization::archiveFrom(rawlogFile);
for (;;)
{
if (os::kbhit())
{
char pushKey = os::getch();
if (27 == pushKey) break;
}
// Load action/observation pair from the rawlog:
// --------------------------------------------------
if (!CRawlog::readActionObservationPair(
rawlogArch, action, observations, rawlogEntry))
break; // file EOF
if (rawlogEntry >= rawlog_offset)
{
// Process the action and observations:
// --------------------------------------------
kftictac.Tic();
mapping.processActionObservation(action, observations);
const double tim_kf_iter = kftictac.Tac();
// Get current state:
// -------------------------------
mapping.getCurrentState(robotPose, LMs, LM_IDs, fullState, fullCov);
cout << "Mean pose: " << endl << robotPose.mean << endl;
cout << "# of landmarks in the map: " << LMs.size() << endl;
// Get the mean robot pose as 3D:
const CPose3D robotPoseMean3D = CPose3D(robotPose.mean);
// Build the path:
meanPath.push_back(robotPoseMean3D.asTPose());
// Save mean pose:
if (!(step % SAVE_LOG_FREQUENCY))
{
const auto p = robotPose.mean.asVectorVal();
p.saveToTextFile(
OUT_DIR +
format("/robot_pose_%05u.txt", (unsigned int)step));
}
// Save full cov:
if (!(step % SAVE_LOG_FREQUENCY))
{
fullCov.saveToTextFile(
OUT_DIR + format("/full_cov_%05u.txt", (unsigned int)step));
}
// Generate Data Association log?
if (SAVE_DA_LOG)
{
const typename ekfslam_t::TDataAssocInfo& da =
mapping.getLastDataAssociation();
const CObservationBearingRange::Ptr obs =
observations
->getObservationByClass<CObservationBearingRange>();
if (obs)
{
const CObservationBearingRange* obsRB = obs.get();
const double tim =
mrpt::system::timestampToDouble(obsRB->timestamp);
for (size_t i = 0; i < obsRB->sensedData.size(); i++)
{
auto it = da.results.associations.find(i);
int assoc_ID_in_SLAM;
if (it != da.results.associations.end())
assoc_ID_in_SLAM = it->second;
else
{
// It should be a newly created LM:
auto itNewLM = da.newly_inserted_landmarks.find(i);
if (itNewLM != da.newly_inserted_landmarks.end())
assoc_ID_in_SLAM = itNewLM->second;
else
assoc_ID_in_SLAM = -1;
}
out_da_log << format(
"%35.22f %8i %10i %10f %12f %12f\n", tim, (int)i,
assoc_ID_in_SLAM,
(double)obsRB->sensedData[i].range,
(double)obsRB->sensedData[i].yaw,
(double)obsRB->sensedData[i].pitch);
}
}
}
// Save report on DA performance:
{
const typename ekfslam_t::TDataAssocInfo& da =
mapping.getLastDataAssociation();
const CObservationBearingRange::Ptr obs =
observations
->getObservationByClass<CObservationBearingRange>();
if (obs)
{
const CObservationBearingRange* obsRB = obs.get();
const double tim =
mrpt::system::timestampToDouble(obsRB->timestamp);
auto itDA = GT_DA.find(tim);
for (size_t i = 0; i < obsRB->sensedData.size(); i++)
{
bool is_FP = false, is_TP = false, is_FN = false,
is_TN = false;
if (itDA != GT_DA.end())
{
const std::vector<int>& vDA = itDA->second;
ASSERT_BELOW_(i, vDA.size());
const int GT_ASSOC = vDA[i];
auto it = da.results.associations.find(i);
if (it != da.results.associations.end())
{
// This observation was assigned the already
// existing LM in the map: "it->second"
// TruePos -> If that LM index corresponds to
// that in the GT (with index mapping):
// mrpt::containers::bimap<int,int>
// DA2GTDA_indices;
// // Landmark indices bimapping: SLAM DA <--->
// GROUND TRUTH DA
if (DA2GTDA_indices.hasKey(it->second))
{
const int slam_asigned_LM_idx =
DA2GTDA_indices.direct(it->second);
if (slam_asigned_LM_idx == GT_ASSOC)
is_TP = true;
else
is_FP = true;
}
else
{
// Is this case possible? Assigned to an
// index not ever seen for the first time
// with a GT....
// Just in case:
is_FP = true;
}
}
else
{
// No pairing, but should be a newly created LM:
auto itNewLM =
da.newly_inserted_landmarks.find(i);
if (itNewLM !=
da.newly_inserted_landmarks.end())
{
const int new_LM_in_SLAM = itNewLM->second;
// Was this really a NEW LM not observed
// before?
if (DA2GTDA_indices.hasValue(GT_ASSOC))
{
// GT says this LM was already observed,
// so it shouldn't appear here as new:
is_FN = true;
}
else
{
// Really observed for the first time:
is_TN = true;
DA2GTDA_indices.insert(
new_LM_in_SLAM, GT_ASSOC);
}
}
else
{
// Not associated neither inserted:
// Shouldn't really never arrive here.
}
}
}
// "% TIMESTAMP INDEX_IN_OBS
// TruePos FalsePos TrueNeg FalseNeg
// NoGroundTruthSoIDontKnow \n"
out_da_performance_log << format(
"%35.22f %13i %8i %8i %8i %8i %8i\n", tim, (int)i,
(int)(is_TP ? 1 : 0), (int)(is_FP ? 1 : 0),
(int)(is_TN ? 1 : 0), (int)(is_FN ? 1 : 0),
(int)(!is_FP && !is_TP && !is_FN && !is_TN ? 1 : 0));
}
}
}
// Save map to file representations?
if (SAVE_MAP_REPRESENTATIONS && !(step % SAVE_LOG_FREQUENCY))
{
mapping.saveMapAndPath2DRepresentationAsMATLABFile(
OUT_DIR + format("/slam_state_%05u.m", (unsigned int)step));
}
// Save 3D view of the filter state:
if (win3d || (SAVE_3D_SCENES && !(step % SAVE_LOG_FREQUENCY)))
{
COpenGLScene::Ptr scene3D =
mrpt::make_aligned_shared<COpenGLScene>();
{
opengl::CGridPlaneXY::Ptr grid =
mrpt::make_aligned_shared<opengl::CGridPlaneXY>(
-1000, 1000, -1000, 1000, 0, 5);
grid->setColor(0.4, 0.4, 0.4);
scene3D->insert(grid);
}
// Robot path:
{
opengl::CSetOfLines::Ptr linesPath =
mrpt::make_aligned_shared<opengl::CSetOfLines>();
linesPath->setColor(1, 0, 0);
TPose3D init_pose;
if (!meanPath.empty())
init_pose = CPose3D(meanPath[0]).asTPose();
int path_decim = 0;
for (auto& it : meanPath)
{
linesPath->appendLine(init_pose, it);
init_pose = it;
if (++path_decim > 10)
{
path_decim = 0;
mrpt::opengl::CSetOfObjects::Ptr xyz =
mrpt::opengl::stock_objects::CornerXYZSimple(
0.3f, 2.0f);
xyz->setPose(CPose3D(it));
scene3D->insert(xyz);
}
}
scene3D->insert(linesPath);
// finally a big corner for the latest robot pose:
{
mrpt::opengl::CSetOfObjects::Ptr xyz =
mrpt::opengl::stock_objects::CornerXYZSimple(
1.0, 2.5);
xyz->setPose(robotPoseMean3D);
scene3D->insert(xyz);
}
// The camera pointing to the current robot pose:
if (CAMERA_3DSCENE_FOLLOWS_ROBOT)
{
win3d->setCameraPointingToPoint(
robotPoseMean3D.x(), robotPoseMean3D.y(),
robotPoseMean3D.z());
}
}
// Do we have a ground truth?
if (GT_PATH.cols() == 6 || GT_PATH.cols() == 3)
{
opengl::CSetOfLines::Ptr GT_path =
mrpt::make_aligned_shared<opengl::CSetOfLines>();
GT_path->setColor(0, 0, 0);
size_t N =
std::min((int)GT_PATH.rows(), (int)meanPath.size());
if (GT_PATH.cols() == 6)
{
double gtx0 = 0, gty0 = 0, gtz0 = 0;
for (size_t i = 0; i < N; i++)
{
const CPose3D p(
GT_PATH(i, 0), GT_PATH(i, 1), GT_PATH(i, 2),
GT_PATH(i, 3), GT_PATH(i, 4), GT_PATH(i, 5));
GT_path->appendLine(
gtx0, gty0, gtz0, p.x(), p.y(), p.z());
gtx0 = p.x();
gty0 = p.y();
gtz0 = p.z();
}
}
else if (GT_PATH.cols() == 3)
{
double gtx0 = 0, gty0 = 0;
for (size_t i = 0; i < N; i++)
{
const CPose2D p(
GT_PATH(i, 0), GT_PATH(i, 1), GT_PATH(i, 2));
GT_path->appendLine(gtx0, gty0, 0, p.x(), p.y(), 0);
gtx0 = p.x();
gty0 = p.y();
}
}
scene3D->insert(GT_path);
}
// Draw latest data association:
{
const typename ekfslam_t::TDataAssocInfo& da =
mapping.getLastDataAssociation();
mrpt::opengl::CSetOfLines::Ptr lins =
mrpt::make_aligned_shared<mrpt::opengl::CSetOfLines>();
lins->setLineWidth(1.2f);
lins->setColor(1, 1, 1);
for (auto it = da.results.associations.begin();
it != da.results.associations.end(); ++it)
{
const prediction_index_t idxPred = it->second;
// This index must match the internal list of features
// in the map:
typename ekfslam_t::KFArray_FEAT featMean;
mapping.getLandmarkMean(idxPred, featMean);
TPoint3D featMean3D;
traits_t::landmark_to_3d(featMean, featMean3D);
// Line: robot -> landmark:
lins->appendLine(
robotPoseMean3D.x(), robotPoseMean3D.y(),
robotPoseMean3D.z(), featMean3D.x, featMean3D.y,
featMean3D.z);
}
scene3D->insert(lins);
}
// The current state of KF-SLAM:
{
opengl::CSetOfObjects::Ptr objs =
mrpt::make_aligned_shared<opengl::CSetOfObjects>();
mapping.getAs3DObject(objs);
scene3D->insert(objs);
}
if (win3d)
{
mrpt::opengl::COpenGLScene::Ptr& scn =
win3d->get3DSceneAndLock();
scn = scene3D;
// Update text messages:
win3d->addTextMessage(
0.02, 0.02,
format(
"Step %u - Landmarks in the map: %u",
(unsigned int)step, (unsigned int)LMs.size()),
TColorf(1, 1, 1), 0, MRPT_GLUT_BITMAP_HELVETICA_12);
win3d->addTextMessage(
0.02, 0.06,
format(
is_pose_3d
? "Estimated pose: (x y z qr qx qy qz) = %s"
: "Estimated pose: (x y yaw) = %s",
robotPose.mean.asString().c_str()),
TColorf(1, 1, 1), 1, MRPT_GLUT_BITMAP_HELVETICA_12);
static vector<double> estHz_vals;
const double curHz = 1.0 / std::max(1e-9, tim_kf_iter);
estHz_vals.push_back(curHz);
if (estHz_vals.size() > 50)
estHz_vals.erase(estHz_vals.begin());
const double meanHz = mrpt::math::mean(estHz_vals);
win3d->addTextMessage(
0.02, 0.10,
format(
"Iteration time: %7ss",
mrpt::system::unitsFormat(tim_kf_iter).c_str()),
TColorf(1, 1, 1), 2, MRPT_GLUT_BITMAP_HELVETICA_12);
win3d->addTextMessage(
0.02, 0.14,
format(
"Execution rate: %7sHz",
mrpt::system::unitsFormat(meanHz).c_str()),
TColorf(1, 1, 1), 3, MRPT_GLUT_BITMAP_HELVETICA_12);
win3d->unlockAccess3DScene();
win3d->repaint();
}
if (SAVE_3D_SCENES && !(step % SAVE_LOG_FREQUENCY))
{
// Save to file:
CFileGZOutputStream f(
OUT_DIR +
format("/kf_state_%05u.3Dscene", (unsigned int)step));
mrpt::serialization::archiveFrom(f) << *scene3D;
}
}
// Free rawlog items memory:
// --------------------------------------------
action.reset();
observations.reset();
} // (rawlogEntry>=rawlog_offset)
cout << format(
"\nStep %u - Rawlog entries processed: %i\n", (unsigned int)step,
(unsigned int)rawlogEntry);
step++;
}; // end "while(1)"
// Partitioning experiment: Only for 6D SLAM:
traits_t::doPartitioningExperiment(mapping, fullCov, OUT_DIR);
// Is there ground truth of landmarks positions??
if (ground_truth_file.size() && fileExists(ground_truth_file))
{
CMatrixFloat GT(0, 0);
try
{
GT.loadFromTextFile(ground_truth_file);
}
catch (const std::exception& e)
{
cerr << "Ignoring the following error loading ground truth file: "
<< mrpt::exception_to_str(e) << endl;
}
if (GT.rows() > 0 && !LMs.empty())
{
// Each row has:
// [0] [1] [2] [6]
// x y z ID
CVectorDouble ERRS(0);
for (size_t i = 0; i < LMs.size(); i++)
{
// Find the entry in the GT for this mapped LM:
bool found = false;
for (int r = 0; r < GT.rows(); r++)
{
if (LM_IDs[i] == GT(r, 6))
{
const CPoint3D gtPt(GT(r, 0), GT(r, 1), GT(r, 2));
ERRS.push_back(gtPt.distanceTo(
CPoint3D(TPoint3D(LMs[i])))); // All these
// conversions
// are to make it
// work with
// either
// CPoint3D &
// TPoint2D
found = true;
break;
}
}
if (!found)
{
cerr << "Ground truth entry not found for landmark ID:"
<< LM_IDs[i] << endl;
}
}
printf("ERRORS VS. GROUND TRUTH:\n");
printf("Mean Error: %f meters\n", math::mean(ERRS));
printf("Minimum error: %f meters\n", math::minimum(ERRS));
printf("Maximum error: %f meters\n", math::maximum(ERRS));
}
} // end if GT
cout << "********* KF-SLAM finished! **********" << endl;
if (win3d)
{
cout << "\n Close the 3D window to quit the application.\n";
win3d->waitForKey();
}
}
// -----------------------------------------------
// MAIN
// -----------------------------------------------
int main(int argc, char** argv)
{
try
{
// Parse arguments:
if (!cmd.parse(argc, argv))
throw std::runtime_error(""); // should exit.
const string input_log = arg_input_file.getValue();
const string output_file = arg_output_file.getValue();
const bool verbose = !arg_quiet.getValue();
const bool overwrite = arg_overwrite.getValue();
const int compress_level = arg_gz_level.getValue();
// Check files:
if (!mrpt::system::fileExists(input_log))
throw runtime_error(
format("Input file doesn't exist: '%s'", input_log.c_str()));
if (mrpt::system::fileExists(output_file) && !overwrite)
throw runtime_error(format(
"Output file already exist: '%s' (Use --overwrite to "
"override)",
output_file.c_str()));
VERBOSE_COUT << "Input log : " << input_log << endl;
VERBOSE_COUT << "Output map file : " << output_file
<< " (Compression level: " << compress_level << ")\n";
// Open I/O streams:
std::ifstream input_stream(input_log.c_str());
if (!input_stream.is_open())
throw runtime_error(
format("Error opening for read: '%s'", input_log.c_str()));
// --------------------------------
// The main loop
// --------------------------------
vector<CObservation::Ptr> importedObservations;
mrpt::maps::CSimpleMap theSimpleMap;
const mrpt::system::TTimeStamp base_timestamp = mrpt::system::now();
const uint64_t totalInFileSize = mrpt::system::getFileSize(input_log);
int decimateUpdateConsole = 0;
while (carmen_log_parse_line(
input_stream, importedObservations, base_timestamp))
{
CPose2D gt_pose;
bool has_gt_pose = false;
for (size_t i = 0; i < importedObservations.size(); i++)
{
// If we have an "odometry" observation but it's not alone, it's
// probably
// a "corrected" odometry from some SLAM program, so save it as
// ground truth:
if (importedObservations.size() > 1 &&
IS_CLASS(importedObservations[i], CObservationOdometry))
{
CObservationOdometry::Ptr odo =
std::dynamic_pointer_cast<CObservationOdometry>(
importedObservations[i]);
gt_pose = odo->odometry;
has_gt_pose = true;
break;
}
}
// Only if we have a valid pose, save it to the simple map:
if (has_gt_pose)
{
CSensoryFrame::Ptr SF =
mrpt::make_aligned_shared<CSensoryFrame>();
for (const auto& importedObservation : importedObservations)
{
if (!IS_CLASS(
importedObservation,
CObservationOdometry)) // Odometry was already used
// as positioning...
{
SF->insert(importedObservation);
}
}
// Insert (observations, pose) pair:
CPosePDFGaussian::Ptr pos =
mrpt::make_aligned_shared<CPosePDFGaussian>();
pos->mean = gt_pose;
theSimpleMap.insert(pos, SF);
}
// Update progress in the console:
// ----------------------------------
if (verbose && ++decimateUpdateConsole > 10)
{
decimateUpdateConsole = 0;
const std::streampos curPos = input_stream.tellg();
const double progress_ratio =
double(curPos) / double(totalInFileSize);
static const int nBlocksTotal = 50;
const int nBlocks = progress_ratio * nBlocksTotal;
cout << "\rProgress: [" << string(nBlocks, '#')
<< string(nBlocksTotal - nBlocks, ' ')
<< format(
"] %6.02f%% (%u frames)", progress_ratio * 100,
static_cast<unsigned int>(theSimpleMap.size()));
cout.flush();
}
};
cout << "\n";
// Save final map object:
{
mrpt::io::CFileGZOutputStream out_map;
if (!out_map.open(output_file, compress_level))
throw runtime_error(format(
"Error opening for write: '%s'", output_file.c_str()));
cout << "Dumping simplemap object to file...";
cout.flush();
mrpt::serialization::archiveFrom(out_map) << theSimpleMap;
cout << "Done\n";
cout.flush();
}
// successful end of program.
return 0;
}
catch (const std::exception& e)
{
std::cerr << mrpt::exception_to_str(e) << std::endl;
return -1;
}
}
// ------------------------------------------------------
// TestGeometry3D
// ------------------------------------------------------
void TestLaser2Imgs()
{
// Set your rawlog file name
if (!mrpt::system::fileExists(RAWLOG_FILE))
THROW_EXCEPTION_FMT(
"Rawlog file does not exist: %s", RAWLOG_FILE.c_str())
CActionCollection::Ptr action;
CSensoryFrame::Ptr observations;
size_t rawlogEntry = 0;
// bool end = false;
CDisplayWindow wind;
// Set relative path for externally-stored images in rawlogs:
string rawlog_images_path = extractFileDirectory(RAWLOG_FILE);
rawlog_images_path += "/Images";
CImage::setImagesPathBase(rawlog_images_path); // Set it.
mrpt::io::CFileGZInputStream rawlogFile(RAWLOG_FILE);
for (;;)
{
if (os::kbhit())
{
char c = os::getch();
if (c == 27) break;
}
// Load action/observation pair from the rawlog:
// --------------------------------------------------
cout << "Reading act/oct pair from rawlog..." << endl;
auto arch = mrpt::serialization::archiveFrom(rawlogFile);
if (!CRawlog::readActionObservationPair(
arch, action, observations, rawlogEntry))
break; // file EOF
// CAMERA............
// Get CObservationStereoImages
CObservationStereoImages::Ptr sImgs;
CObservationImage::Ptr Img;
sImgs = observations->getObservationByClass<CObservationStereoImages>();
if (!sImgs)
{
Img = observations->getObservationByClass<CObservationImage>();
if (!Img) continue;
}
CPose3D cameraPose; // Get Camera Pose (B) (CPose3D)
CMatrixDouble33 K; // Get Calibration matrix (K)
sImgs ? sImgs->getSensorPose(cameraPose)
: Img->getSensorPose(cameraPose);
K = sImgs ? sImgs->leftCamera.intrinsicParams
: Img->cameraParams.intrinsicParams;
// LASER.............
// Get CObservationRange2D
CObservation2DRangeScan::Ptr laserScan =
observations->getObservationByClass<CObservation2DRangeScan>();
if (!laserScan) continue;
// Get Laser Pose (A) (CPose3D)
CPose3D laserPose;
laserScan->getSensorPose(laserPose);
if (abs(laserPose.yaw()) > DEG2RAD(90)) continue; // Only front lasers
// Get 3D Point relative to the Laser coordinate Frame (P1) (CPoint3D)
CPoint3D point;
CSimplePointsMap mapa;
mapa.insertionOptions.minDistBetweenLaserPoints = 0;
observations->insertObservationsInto(
&mapa); // <- The map contains the pose of the points (P1)
// Get the points into the map
vector<float> X, Y, Z;
vector<float>::iterator itX, itY, itZ;
mapa.getAllPoints(X, Y, Z);
unsigned int imgW =
sImgs ? sImgs->imageLeft.getWidth() : Img->image.getWidth();
unsigned int imgH =
sImgs ? sImgs->imageLeft.getHeight() : Img->image.getHeight();
// unsigned int idx = 0;
vector<float> imgX, imgY;
vector<float>::iterator itImgX, itImgY;
imgX.resize(X.size());
imgY.resize(Y.size());
CImage image;
image = sImgs ? sImgs->imageLeft : Img->image;
// Get pixels in the image:
// Pimg = (kx,ky,k)^T = K(I|0)*P2
// Main loop
for (itX = X.begin(), itY = Y.begin(), itZ = Z.begin(),
itImgX = imgX.begin(), itImgY = imgY.begin();
itX != X.end(); itX++, itY++, itZ++, itImgX++, itImgY++)
{
// Coordinates Transformation
CPoint3D pLaser(*itX, *itY, *itZ);
CPoint3D pCamera(pLaser - cameraPose);
if (pCamera.z() > 0)
{
*itImgX = -K(0, 0) * ((pCamera.x()) / (pCamera.z())) + K(0, 2);
*itImgY = -K(1, 1) * ((pCamera.y()) / (pCamera.z())) + K(1, 2);
if (*itImgX > 0 && *itImgX<imgW&& * itImgY> 0 && *itImgY < imgH)
image.filledRectangle(
*itImgX - 1, *itImgY - 1, *itImgX + 1, *itImgY + 1,
TColor(255, 0, 0));
} // end if
} // end for
action.reset();
observations.reset();
wind.showImage(image);
std::this_thread::sleep_for(50ms);
}; // end for
mrpt::system::pause();
}
