/
Rtabmap.cpp
3899 lines (3601 loc) · 130 KB
/
Rtabmap.cpp
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/*
Copyright (c) 2010-2014, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of the Universite de Sherbrooke nor the
names of its contributors may be used to endorse or promote products
derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#include "rtabmap/core/Rtabmap.h"
#include "rtabmap/core/Version.h"
#include "rtabmap/core/Features2d.h"
#include "rtabmap/core/Optimizer.h"
#include "rtabmap/core/Graph.h"
#include "rtabmap/core/Signature.h"
#include "rtabmap/core/EpipolarGeometry.h"
#include "rtabmap/core/Memory.h"
#include "rtabmap/core/VWDictionary.h"
#include "rtabmap/core/BayesFilter.h"
#include "rtabmap/core/Compression.h"
#include "rtabmap/core/RegistrationInfo.h"
#include <rtabmap/utilite/ULogger.h>
#include <rtabmap/utilite/UFile.h>
#include <rtabmap/utilite/UTimer.h>
#include <rtabmap/utilite/UConversion.h>
#include <rtabmap/utilite/UMath.h>
#include <pcl/search/kdtree.h>
#include <pcl/filters/crop_box.h>
#include <pcl/io/pcd_io.h>
#include <stdlib.h>
#include <set>
#define LOG_F "LogF.txt"
#define LOG_I "LogI.txt"
#define GRAPH_FILE_NAME "Graph.dot"
//
//
//
// =======================================================
// MAIN LOOP, see method "void Rtabmap::process();" below.
// =======================================================
//
//
//
namespace rtabmap
{
Rtabmap::Rtabmap() :
_publishStats(Parameters::defaultRtabmapPublishStats()),
_publishLastSignatureData(Parameters::defaultRtabmapPublishLastSignature()),
_publishPdf(Parameters::defaultRtabmapPublishPdf()),
_publishLikelihood(Parameters::defaultRtabmapPublishLikelihood()),
_maxTimeAllowed(Parameters::defaultRtabmapTimeThr()), // 700 ms
_maxMemoryAllowed(Parameters::defaultRtabmapMemoryThr()), // 0=inf
_loopThr(Parameters::defaultRtabmapLoopThr()),
_loopRatio(Parameters::defaultRtabmapLoopRatio()),
_maxRetrieved(Parameters::defaultRtabmapMaxRetrieved()),
_maxLocalRetrieved(Parameters::defaultRGBDMaxLocalRetrieved()),
_rawDataKept(Parameters::defaultMemImageKept()),
_statisticLogsBufferedInRAM(Parameters::defaultRtabmapStatisticLogsBufferedInRAM()),
_statisticLogged(Parameters::defaultRtabmapStatisticLogged()),
_statisticLoggedHeaders(Parameters::defaultRtabmapStatisticLoggedHeaders()),
_rgbdSlamMode(Parameters::defaultRGBDEnabled()),
_rgbdLinearUpdate(Parameters::defaultRGBDLinearUpdate()),
_rgbdAngularUpdate(Parameters::defaultRGBDAngularUpdate()),
_newMapOdomChangeDistance(Parameters::defaultRGBDNewMapOdomChangeDistance()),
_neighborLinkRefining(Parameters::defaultRGBDNeighborLinkRefining()),
_proximityByTime(Parameters::defaultRGBDProximityByTime()),
_proximityBySpace(Parameters::defaultRGBDProximityBySpace()),
_scanMatchingIdsSavedInLinks(Parameters::defaultRGBDScanMatchingIdsSavedInLinks()),
_localRadius(Parameters::defaultRGBDLocalRadius()),
_localImmunizationRatio(Parameters::defaultRGBDLocalImmunizationRatio()),
_proximityMaxGraphDepth(Parameters::defaultRGBDProximityMaxGraphDepth()),
_proximityFilteringRadius(Parameters::defaultRGBDProximityPathFilteringRadius()),
_proximityRawPosesUsed(Parameters::defaultRGBDProximityPathRawPosesUsed()),
_proximityAngle(Parameters::defaultRGBDProximityAngle()*M_PI/180.0f),
_databasePath(""),
_optimizeFromGraphEnd(Parameters::defaultRGBDOptimizeFromGraphEnd()),
_optimizationMaxLinearError(Parameters::defaultRGBDOptimizeMaxError()),
_startNewMapOnLoopClosure(Parameters::defaultRtabmapStartNewMapOnLoopClosure()),
_goalReachedRadius(Parameters::defaultRGBDGoalReachedRadius()),
_goalsSavedInUserData(Parameters::defaultRGBDGoalsSavedInUserData()),
_pathStuckIterations(Parameters::defaultRGBDPlanStuckIterations()),
_pathLinearVelocity(Parameters::defaultRGBDPlanLinearVelocity()),
_pathAngularVelocity(Parameters::defaultRGBDPlanAngularVelocity()),
_loopClosureHypothesis(0,0.0f),
_highestHypothesis(0,0.0f),
_lastProcessTime(0.0),
_someNodesHaveBeenTransferred(false),
_distanceTravelled(0.0f),
_epipolarGeometry(0),
_bayesFilter(0),
_graphOptimizer(0),
_memory(0),
_foutFloat(0),
_foutInt(0),
_wDir(""),
_mapCorrection(Transform::getIdentity()),
_lastLocalizationNodeId(0),
_pathStatus(0),
_pathCurrentIndex(0),
_pathGoalIndex(0),
_pathTransformToGoal(Transform::getIdentity()),
_pathStuckCount(0)
{
}
Rtabmap::~Rtabmap() {
UDEBUG("");
this->close();
}
void Rtabmap::setupLogFiles(bool overwrite)
{
flushStatisticLogs();
// Log files
if(_foutFloat)
{
fclose(_foutFloat);
_foutFloat = 0;
}
if(_foutInt)
{
fclose(_foutInt);
_foutInt = 0;
}
if(_statisticLogged && !_wDir.empty())
{
std::string attributes = "a+"; // append to log files
if(overwrite)
{
// If a file with the same name already exists
// its content is erased and the file is treated
// as a new empty file.
attributes = "w";
}
bool addLogFHeader = overwrite || !UFile::exists(_wDir+"/"+LOG_F);
bool addLogIHeader = overwrite || !UFile::exists(_wDir+"/"+LOG_I);
#ifdef _MSC_VER
fopen_s(&_foutFloat, (_wDir+"/"+LOG_F).c_str(), attributes.c_str());
fopen_s(&_foutInt, (_wDir+"/"+LOG_I).c_str(), attributes.c_str());
#else
_foutFloat = fopen((_wDir+"/"+LOG_F).c_str(), attributes.c_str());
_foutInt = fopen((_wDir+"/"+LOG_I).c_str(), attributes.c_str());
#endif
// add header (column identification)
if(_statisticLoggedHeaders && addLogFHeader && _foutFloat)
{
fprintf(_foutFloat, "Column headers:\n");
fprintf(_foutFloat, " 1-Total iteration time (s)\n");
fprintf(_foutFloat, " 2-Memory update time (s)\n");
fprintf(_foutFloat, " 3-Retrieval time (s)\n");
fprintf(_foutFloat, " 4-Likelihood time (s)\n");
fprintf(_foutFloat, " 5-Posterior time (s)\n");
fprintf(_foutFloat, " 6-Hypothesis selection time (s)\n");
fprintf(_foutFloat, " 7-Hypothesis validation time (s)\n");
fprintf(_foutFloat, " 8-Transfer time (s)\n");
fprintf(_foutFloat, " 9-Statistics creation time (s)\n");
fprintf(_foutFloat, " 10-Loop closure hypothesis value\n");
fprintf(_foutFloat, " 11-NAN\n");
fprintf(_foutFloat, " 12-NAN\n");
fprintf(_foutFloat, " 13-NAN\n");
fprintf(_foutFloat, " 14-NAN\n");
fprintf(_foutFloat, " 15-NAN\n");
fprintf(_foutFloat, " 16-Virtual place hypothesis\n");
fprintf(_foutFloat, " 17-Join trash time (s)\n");
fprintf(_foutFloat, " 18-Weight Update (rehearsal) similarity\n");
fprintf(_foutFloat, " 19-Empty trash time (s)\n");
fprintf(_foutFloat, " 20-Retrieval database access time (s)\n");
fprintf(_foutFloat, " 21-Add loop closure link time (s)\n");
fprintf(_foutFloat, " 22-Memory cleanup time (s)\n");
fprintf(_foutFloat, " 23-Scan matching (odometry correction) time (s)\n");
fprintf(_foutFloat, " 24-Local time loop closure detection time (s)\n");
fprintf(_foutFloat, " 25-Local space loop closure detection time (s)\n");
fprintf(_foutFloat, " 26-Map optimization (s)\n");
}
if(_statisticLoggedHeaders && addLogIHeader && _foutInt)
{
fprintf(_foutInt, "Column headers:\n");
fprintf(_foutInt, " 1-Loop closure ID\n");
fprintf(_foutInt, " 2-Highest loop closure hypothesis\n");
fprintf(_foutInt, " 3-Locations transferred\n");
fprintf(_foutInt, " 4-NAN\n");
fprintf(_foutInt, " 5-Words extracted from the last image\n");
fprintf(_foutInt, " 6-Vocabulary size\n");
fprintf(_foutInt, " 7-Working memory size\n");
fprintf(_foutInt, " 8-Is loop closure hypothesis rejected?\n");
fprintf(_foutInt, " 9-NAN\n");
fprintf(_foutInt, " 10-NAN\n");
fprintf(_foutInt, " 11-Locations retrieved\n");
fprintf(_foutInt, " 12-Retrieval location ID\n");
fprintf(_foutInt, " 13-Unique words extraced from last image\n");
fprintf(_foutInt, " 14-Retrieval ID\n");
fprintf(_foutInt, " 15-Non-null likelihood values\n");
fprintf(_foutInt, " 16-Weight Update ID\n");
fprintf(_foutInt, " 17-Is last location merged through Weight Update?\n");
fprintf(_foutInt, " 18-Local graph size\n");
fprintf(_foutInt, " 19-Sensor data id\n");
fprintf(_foutInt, " 20-Indexed words\n");
fprintf(_foutInt, " 21-Index memory usage (KB)\n");
}
ULOGGER_DEBUG("Log file (int)=%s", (_wDir+"/"+LOG_I).c_str());
ULOGGER_DEBUG("Log file (float)=%s", (_wDir+"/"+LOG_F).c_str());
}
else
{
if(_statisticLogged)
{
UWARN("Working directory is not set, log disabled!");
}
UDEBUG("Log disabled!");
}
}
void Rtabmap::flushStatisticLogs()
{
if(_foutFloat && _bufferedLogsF.size())
{
UDEBUG("_bufferedLogsF.size=%d", _bufferedLogsF.size());
for(std::list<std::string>::iterator iter = _bufferedLogsF.begin(); iter!=_bufferedLogsF.end(); ++iter)
{
fprintf(_foutFloat, "%s", iter->c_str());
}
_bufferedLogsF.clear();
}
if(_foutInt && _bufferedLogsI.size())
{
UDEBUG("_bufferedLogsI.size=%d", _bufferedLogsI.size());
for(std::list<std::string>::iterator iter = _bufferedLogsI.begin(); iter!=_bufferedLogsI.end(); ++iter)
{
fprintf(_foutInt, "%s", iter->c_str());
}
_bufferedLogsI.clear();
}
}
void Rtabmap::init(const ParametersMap & parameters, const std::string & databasePath)
{
ParametersMap::const_iterator iter;
if((iter=parameters.find(Parameters::kRtabmapWorkingDirectory())) != parameters.end())
{
this->setWorkingDirectory(iter->second.c_str());
}
_databasePath = databasePath;
if(!_databasePath.empty())
{
UASSERT(UFile::getExtension(_databasePath).compare("db") == 0);
UINFO("Using database \"%s\".", _databasePath.c_str());
}
else
{
UWARN("Using empty database. Mapping session will not be saved.");
}
bool newDatabase = _databasePath.empty() || !UFile::exists(_databasePath);
// If not exist, create a memory
if(!_memory)
{
_memory = new Memory(parameters);
_memory->init(_databasePath, false, parameters, true);
}
// Parse all parameters
this->parseParameters(parameters);
if(_databasePath.empty())
{
_statisticLogged = false;
}
setupLogFiles(newDatabase);
}
void Rtabmap::init(const std::string & configFile, const std::string & databasePath)
{
// fill ctrl struct with values from the configuration file
ParametersMap param;// = Parameters::defaultParameters;
if(!configFile.empty())
{
ULOGGER_DEBUG("Read parameters from = %s", configFile.c_str());
Parameters::readINI(configFile, param);
}
this->init(param, databasePath);
}
void Rtabmap::close(bool databaseSaved)
{
UINFO("databaseSaved=%d", databaseSaved?1:0);
_highestHypothesis = std::make_pair(0,0.0f);
_loopClosureHypothesis = std::make_pair(0,0.0f);
_lastProcessTime = 0.0;
_someNodesHaveBeenTransferred = false;
_optimizedPoses.clear();
_constraints.clear();
_mapCorrection.setIdentity();
_lastLocalizationPose.setNull();
_lastLocalizationNodeId = 0;
_distanceTravelled = 0.0f;
this->clearPath(0);
flushStatisticLogs();
if(_foutFloat)
{
fclose(_foutFloat);
_foutFloat = 0;
}
if(_foutInt)
{
fclose(_foutInt);
_foutInt = 0;
}
if(_epipolarGeometry)
{
delete _epipolarGeometry;
_epipolarGeometry = 0;
}
if(_memory)
{
_memory->close(databaseSaved, true);
delete _memory;
_memory = 0;
}
if(_bayesFilter)
{
delete _bayesFilter;
_bayesFilter = 0;
}
if(_graphOptimizer)
{
delete _graphOptimizer;
_graphOptimizer = 0;
}
_databasePath.clear();
parseParameters(Parameters::getDefaultParameters()); // reset to default parameters
_parameters.clear();
}
void Rtabmap::parseParameters(const ParametersMap & parameters)
{
uInsert(_parameters, parameters);
// place this before changing working directory
Parameters::parse(parameters, Parameters::kRtabmapStatisticLogsBufferedInRAM(), _statisticLogsBufferedInRAM);
Parameters::parse(parameters, Parameters::kRtabmapStatisticLogged(), _statisticLogged);
Parameters::parse(parameters, Parameters::kRtabmapStatisticLoggedHeaders(), _statisticLoggedHeaders);
ULOGGER_DEBUG("");
ParametersMap::const_iterator iter;
if((iter=parameters.find(Parameters::kRtabmapWorkingDirectory())) != parameters.end())
{
this->setWorkingDirectory(iter->second.c_str());
}
Parameters::parse(parameters, Parameters::kRtabmapPublishStats(), _publishStats);
Parameters::parse(parameters, Parameters::kRtabmapPublishLastSignature(), _publishLastSignatureData);
Parameters::parse(parameters, Parameters::kRtabmapPublishPdf(), _publishPdf);
Parameters::parse(parameters, Parameters::kRtabmapPublishLikelihood(), _publishLikelihood);
Parameters::parse(parameters, Parameters::kRtabmapTimeThr(), _maxTimeAllowed);
Parameters::parse(parameters, Parameters::kRtabmapMemoryThr(), _maxMemoryAllowed);
Parameters::parse(parameters, Parameters::kRtabmapLoopThr(), _loopThr);
Parameters::parse(parameters, Parameters::kRtabmapLoopRatio(), _loopRatio);
Parameters::parse(parameters, Parameters::kRtabmapMaxRetrieved(), _maxRetrieved);
Parameters::parse(parameters, Parameters::kRGBDMaxLocalRetrieved(), _maxLocalRetrieved);
Parameters::parse(parameters, Parameters::kMemImageKept(), _rawDataKept);
Parameters::parse(parameters, Parameters::kRGBDEnabled(), _rgbdSlamMode);
Parameters::parse(parameters, Parameters::kRGBDLinearUpdate(), _rgbdLinearUpdate);
Parameters::parse(parameters, Parameters::kRGBDAngularUpdate(), _rgbdAngularUpdate);
Parameters::parse(parameters, Parameters::kRGBDNewMapOdomChangeDistance(), _newMapOdomChangeDistance);
Parameters::parse(parameters, Parameters::kRGBDNeighborLinkRefining(), _neighborLinkRefining);
Parameters::parse(parameters, Parameters::kRGBDProximityByTime(), _proximityByTime);
Parameters::parse(parameters, Parameters::kRGBDProximityBySpace(), _proximityBySpace);
Parameters::parse(parameters, Parameters::kRGBDScanMatchingIdsSavedInLinks(), _scanMatchingIdsSavedInLinks);
Parameters::parse(parameters, Parameters::kRGBDLocalRadius(), _localRadius);
Parameters::parse(parameters, Parameters::kRGBDLocalImmunizationRatio(), _localImmunizationRatio);
Parameters::parse(parameters, Parameters::kRGBDProximityMaxGraphDepth(), _proximityMaxGraphDepth);
Parameters::parse(parameters, Parameters::kRGBDProximityPathFilteringRadius(), _proximityFilteringRadius);
Parameters::parse(parameters, Parameters::kRGBDProximityPathRawPosesUsed(), _proximityRawPosesUsed);
Parameters::parse(parameters, Parameters::kRGBDProximityAngle(), _proximityAngle);
_proximityAngle *= M_PI/180.0f;
Parameters::parse(parameters, Parameters::kRGBDOptimizeFromGraphEnd(), _optimizeFromGraphEnd);
Parameters::parse(parameters, Parameters::kRGBDOptimizeMaxError(), _optimizationMaxLinearError);
Parameters::parse(parameters, Parameters::kRtabmapStartNewMapOnLoopClosure(), _startNewMapOnLoopClosure);
Parameters::parse(parameters, Parameters::kRGBDGoalReachedRadius(), _goalReachedRadius);
Parameters::parse(parameters, Parameters::kRGBDGoalsSavedInUserData(), _goalsSavedInUserData);
Parameters::parse(parameters, Parameters::kRGBDPlanStuckIterations(), _pathStuckIterations);
Parameters::parse(parameters, Parameters::kRGBDPlanLinearVelocity(), _pathLinearVelocity);
Parameters::parse(parameters, Parameters::kRGBDPlanAngularVelocity(), _pathAngularVelocity);
UASSERT(_rgbdLinearUpdate >= 0.0f);
UASSERT(_rgbdAngularUpdate >= 0.0f);
// By default, we create our strategies if they are not already created.
// If they already exists, we check the parameters if a change is requested
// Graph optimizer
Optimizer::Type optimizerType = Optimizer::kTypeUndef;
if((iter=parameters.find(Parameters::kOptimizerStrategy())) != parameters.end())
{
optimizerType = (Optimizer::Type)std::atoi((*iter).second.c_str());
}
if(optimizerType!=Optimizer::kTypeUndef)
{
UDEBUG("new detector strategy %d", int(optimizerType));
if(_graphOptimizer)
{
delete _graphOptimizer;
_graphOptimizer = 0;
}
_graphOptimizer = Optimizer::create(optimizerType, _parameters);
}
else if(_graphOptimizer)
{
_graphOptimizer->parseParameters(parameters);
}
else
{
optimizerType = (Optimizer::Type)Parameters::defaultOptimizerStrategy();
_graphOptimizer = Optimizer::create(optimizerType, parameters);
}
if(_memory)
{
_memory->parseParameters(parameters);
}
VhStrategy vhStrategy = kVhUndef;
// Verifying hypotheses strategy
if((iter=parameters.find(Parameters::kRtabmapVhStrategy())) != parameters.end())
{
vhStrategy = (VhStrategy)std::atoi((*iter).second.c_str());
}
if(!_epipolarGeometry && vhStrategy == kVhEpipolar)
{
_epipolarGeometry = new EpipolarGeometry(_parameters);
}
else if(_epipolarGeometry && vhStrategy == kVhNone)
{
delete _epipolarGeometry;
_epipolarGeometry = 0;
}
else if(_epipolarGeometry)
{
_epipolarGeometry->parseParameters(parameters);
}
// Bayes filter, create one if not exists
if(!_bayesFilter)
{
_bayesFilter = new BayesFilter(_parameters);
}
else
{
_bayesFilter->parseParameters(parameters);
}
}
int Rtabmap::getLastLocationId() const
{
int id = 0;
if(_memory)
{
id = _memory->getLastSignatureId();
}
return id;
}
std::list<int> Rtabmap::getWM() const
{
std::list<int> mem;
if(_memory)
{
mem = uKeysList(_memory->getWorkingMem());
mem.remove(-1);// Ignore the virtual signature (if here)
}
return mem;
}
int Rtabmap::getWMSize() const
{
if(_memory)
{
return (int)_memory->getWorkingMem().size()-1; // remove virtual place
}
return 0;
}
std::map<int, int> Rtabmap::getWeights() const
{
std::map<int, int> weights;
if(_memory)
{
weights = _memory->getWeights();
weights.erase(-1);// Ignore the virtual signature (if here)
}
return weights;
}
std::set<int> Rtabmap::getSTM() const
{
if(_memory)
{
return _memory->getStMem();
}
return std::set<int>();
}
int Rtabmap::getSTMSize() const
{
if(_memory)
{
return (int)_memory->getStMem().size();
}
return 0;
}
int Rtabmap::getTotalMemSize() const
{
if(_memory)
{
const Signature * s =_memory->getLastWorkingSignature();
if(s)
{
return s->id();
}
}
return 0;
}
std::multimap<int, cv::KeyPoint> Rtabmap::getWords(int locationId) const
{
if(_memory)
{
const Signature * s = _memory->getSignature(locationId);
if(s)
{
return s->getWords();
}
}
return std::multimap<int, cv::KeyPoint>();
}
bool Rtabmap::isInSTM(int locationId) const
{
if(_memory)
{
return _memory->isInSTM(locationId);
}
return false;
}
bool Rtabmap::isIDsGenerated() const
{
if(_memory)
{
return _memory->isIDsGenerated();
}
return Parameters::defaultMemGenerateIds();
}
const Statistics & Rtabmap::getStatistics() const
{
return statistics_;
}
/*
bool Rtabmap::getMetricData(int locationId, cv::Mat & rgb, cv::Mat & depth, float & depthConstant, Transform & pose, Transform & localTransform) const
{
if(_memory)
{
const Signature * s = _memory->getSignature(locationId);
if(s && _optimizedPoses.find(s->id()) != _optimizedPoses.end())
{
rgb = s->getImage();
depth = s->getDepth();
depthConstant = s->getDepthConstant();
pose = _optimizedPoses.at(s->id());
localTransform = s->getLocalTransform();
return true;
}
}
return false;
}
*/
Transform Rtabmap::getPose(int locationId) const
{
if(_memory)
{
const Signature * s = _memory->getSignature(locationId);
if(s && _optimizedPoses.find(s->id()) != _optimizedPoses.end())
{
return _optimizedPoses.at(s->id());
}
}
return Transform();
}
int Rtabmap::triggerNewMap()
{
int mapId = -1;
if(_memory)
{
std::map<int, int> reducedIds;
mapId = _memory->incrementMapId(&reducedIds);
UINFO("New map triggered, new map = %d", mapId);
_optimizedPoses.clear();
_constraints.clear();
_lastLocalizationNodeId = 0;
//Verify if there are nodes that were merged through graph reduction
if(reducedIds.size() && _path.size())
{
for(unsigned int i=0; i<_path.size(); ++i)
{
std::map<int, int>::const_iterator iter = reducedIds.find(_path[i].first);
if(iter!= reducedIds.end())
{
// change path ID to loop closure ID
_path[i].first = iter->second;
}
}
}
}
return mapId;
}
bool Rtabmap::labelLocation(int id, const std::string & label)
{
if(_memory)
{
if(id > 0)
{
return _memory->labelSignature(id, label);
}
else if(_memory->getLastWorkingSignature())
{
return _memory->labelSignature(_memory->getLastWorkingSignature()->id(), label);
}
else
{
UERROR("Last signature is null! Cannot set label \"%s\"", label.c_str());
}
}
return false;
}
bool Rtabmap::setUserData(int id, const cv::Mat & data)
{
if(_memory)
{
if(id > 0)
{
return _memory->setUserData(id, data);
}
else if(_memory->getLastWorkingSignature())
{
return _memory->setUserData(_memory->getLastWorkingSignature()->id(), data);
}
else
{
UERROR("Last signature is null! Cannot set user data!");
}
}
return false;
}
void Rtabmap::generateDOTGraph(const std::string & path, int id, int margin)
{
if(_memory)
{
_memory->joinTrashThread(); // make sure the trash is flushed
if(id > 0)
{
std::map<int, int> ids = _memory->getNeighborsId(id, margin, -1, false);
if(ids.size() > 0)
{
ids.insert(std::pair<int,int>(id, 0));
std::set<int> idsSet;
for(std::map<int, int>::iterator iter = ids.begin(); iter!=ids.end(); ++iter)
{
idsSet.insert(idsSet.end(), iter->first);
}
_memory->generateGraph(path, idsSet);
}
else
{
UERROR("No neighbors found for signature %d.", id);
}
}
else
{
_memory->generateGraph(path);
}
}
}
void Rtabmap::exportPoses(const std::string & path, bool optimized, bool global, int format)
{
if(_memory && _memory->getLastWorkingSignature())
{
std::map<int, Transform> poses;
std::multimap<int, Link> constraints;
if(optimized)
{
this->optimizeCurrentMap(_memory->getLastWorkingSignature()->id(), global, poses, &constraints);
}
else
{
std::map<int, int> ids = _memory->getNeighborsId(_memory->getLastWorkingSignature()->id(), 0, global?-1:0, true);
_memory->getMetricConstraints(uKeysSet(ids), poses, constraints, global);
}
std::map<int, double> stamps;
if(format == 1)
{
for(std::map<int, Transform>::iterator iter=poses.begin(); iter!=poses.end(); ++iter)
{
Transform o,g;
int m, w;
std::string l;
double stamp = 0.0;
_memory->getNodeInfo(iter->first, o, m, w, l, stamp, g, true);
stamps.insert(std::make_pair(iter->first, stamp));
}
}
graph::exportPoses(path, format, poses, constraints, stamps);
}
}
void Rtabmap::resetMemory()
{
_highestHypothesis = std::make_pair(0,0.0f);
_loopClosureHypothesis = std::make_pair(0,0.0f);
_lastProcessTime = 0.0;
_someNodesHaveBeenTransferred = false;
_optimizedPoses.clear();
_constraints.clear();
_mapCorrection.setIdentity();
_lastLocalizationPose.setNull();
_lastLocalizationNodeId = 0;
_distanceTravelled = 0.0f;
this->clearPath(0);
if(_memory)
{
_memory->init(_databasePath, true, _parameters, true);
if(_memory->getLastWorkingSignature())
{
optimizeCurrentMap(_memory->getLastWorkingSignature()->id(), false, _optimizedPoses, &_constraints);
}
if(_bayesFilter)
{
_bayesFilter->reset();
}
}
else
{
UERROR("RTAB-Map is not initialized. No memory to reset...");
}
this->setupLogFiles(true);
}
//============================================================
// MAIN LOOP
//============================================================
bool Rtabmap::process(
const SensorData & data,
const Transform & odomPose,
const cv::Mat & covariance)
{
UDEBUG("");
//============================================================
// Initialization
//============================================================
UTimer timer;
UTimer timerTotal;
double timeMemoryUpdate = 0;
double timeNeighborLinkRefining = 0;
double timeProximityByTimeDetection = 0;
double timeProximityBySpaceDetection = 0;
double timeCleaningNeighbors = 0;
double timeReactivations = 0;
double timeAddLoopClosureLink = 0;
double timeMapOptimization = 0;
double timeRetrievalDbAccess = 0;
double timeLikelihoodCalculation = 0;
double timePosteriorCalculation = 0;
double timeHypothesesCreation = 0;
double timeHypothesesValidation = 0;
double timeRealTimeLimitReachedProcess = 0;
double timeMemoryCleanup = 0;
double timeEmptyingTrash = 0;
double timeJoiningTrash = 0;
double timeStatsCreation = 0;
float hypothesisRatio = 0.0f; // Only used for statistics
bool rejectedHypothesis = false;
std::map<int, float> rawLikelihood;
std::map<int, float> adjustedLikelihood;
std::map<int, float> likelihood;
std::map<int, int> weights;
std::map<int, float> posterior;
std::list<std::pair<int, float> > reactivateHypotheses;
std::map<int, int> childCount;
std::set<int> signaturesRetrieved;
int proximityDetectionsInTimeFound = 0;
const Signature * signature = 0;
const Signature * sLoop = 0;
_loopClosureHypothesis = std::make_pair(0,0.0f);
std::pair<int, float> lastHighestHypothesis = _highestHypothesis;
_highestHypothesis = std::make_pair(0,0.0f);
std::set<int> immunizedLocations;
statistics_ = Statistics(); // reset
//============================================================
// Wait for an image...
//============================================================
ULOGGER_INFO("getting data...");
timer.start();
timerTotal.start();
UASSERT_MSG(_memory, "RTAB-Map is not initialized!");
UASSERT_MSG(_bayesFilter, "RTAB-Map is not initialized!");
UASSERT_MSG(_graphOptimizer, "RTAB-Map is not initialized!");
//============================================================
// If RGBD SLAM is enabled, a pose must be set.
//============================================================
if(_rgbdSlamMode)
{
if(odomPose.isNull())
{
UERROR("RGB-D SLAM mode is enabled and no odometry is provided. "
"Image %d is ignored!", data.id());
return false;
}
else if(_memory->isIncremental()) // only in mapping mode
{
// Detect if the odometry is reset. If yes, trigger a new map.
if(_memory->getLastWorkingSignature())
{
const Transform & lastPose = _memory->getLastWorkingSignature()->getPose(); // use raw odometry
// look for identity
if(!lastPose.isIdentity() && odomPose.isIdentity())
{
int mapId = triggerNewMap();
UWARN("Odometry is reset (identity pose detected). Increment map id to %d!", mapId);
}
else if(_newMapOdomChangeDistance > 0.0)
{
// look for large change
Transform lastPoseToNewPose = lastPose.inverse() * odomPose;
float x,y,z, roll,pitch,yaw;
lastPoseToNewPose.getTranslationAndEulerAngles(x,y,z, roll,pitch,yaw);
if((x*x + y*y + z*z) > _newMapOdomChangeDistance*_newMapOdomChangeDistance)
{
int mapId = triggerNewMap();
UWARN("Odometry is reset (large odometry change detected > %f). A new map (%d) is created! Last pose = %s, new pose = %s",
_newMapOdomChangeDistance,
mapId,
lastPose.prettyPrint().c_str(),
odomPose.prettyPrint().c_str());
}
}
}
}
}
//============================================================
// Memory Update : Location creation + Add to STM + Weight Update (Rehearsal)
//============================================================
ULOGGER_INFO("Updating memory...");
if(_rgbdSlamMode)
{
if(!_memory->update(data, odomPose, covariance, &statistics_))
{
return false;
}
}
else
{
if(!_memory->update(data, Transform(), cv::Mat(), &statistics_))
{
return false;
}
}
signature = _memory->getLastWorkingSignature();
if(!signature)
{
UFATAL("Not supposed to be here...last signature is null?!?");
}
ULOGGER_INFO("Processing signature %d w=%d", signature->id(), signature->getWeight());
timeMemoryUpdate = timer.ticks();
ULOGGER_INFO("timeMemoryUpdate=%fs", timeMemoryUpdate);
//============================================================
// Metric
//============================================================
bool smallDisplacement = false;
std::list<int> signaturesRemoved;
if(_rgbdSlamMode)
{
//Verify if there was a rehearsal
int rehearsedId = (int)uValue(statistics_.data(), Statistics::kMemoryRehearsal_merged(), 0.0f);
if(rehearsedId > 0)
{
_optimizedPoses.erase(rehearsedId);
}
else if(signature->getWeight() >= 0 && _rgbdLinearUpdate > 0.0f && _rgbdAngularUpdate > 0.0f)
{
//============================================================
// Minimum displacement required to add to Memory
//============================================================
const std::map<int, Link> & links = signature->getLinks();
if(links.size() == 1)
{
// don't do this if there are intermediate nodes
const Signature * s = _memory->getSignature(links.begin()->second.to());
UASSERT(s!=0);
if(s->getWeight() >= 0)
{
float x,y,z, roll,pitch,yaw;
links.begin()->second.transform().getTranslationAndEulerAngles(x,y,z, roll,pitch,yaw);
bool isMoving = fabs(x) > _rgbdLinearUpdate ||
fabs(y) > _rgbdLinearUpdate ||
fabs(z) > _rgbdLinearUpdate ||
fabs(roll) > _rgbdAngularUpdate ||
fabs(pitch) > _rgbdAngularUpdate ||
fabs(yaw) > _rgbdAngularUpdate;
if(!isMoving)
{
// This will disable global loop closure detection, only retrieval will be done.
// The location will also be deleted at the end.
smallDisplacement = true;
}
}
}
}
// Update optimizedPoses with the newly added node
Transform newPose;
if(_neighborLinkRefining &&
signature->getLinks().size() == 1 &&
_memory->isIncremental() && // ignore pose matching in localization mode
rehearsedId == 0) // don't do it if rehearsal happened
{
int oldId = signature->getLinks().begin()->first;
const Signature * oldS = _memory->getSignature(oldId);
UASSERT(oldS != 0);
Transform guess = signature->getLinks().begin()->second.transform().inverse();