/*---------------------------------------------------------------
addMapFrame
---------------------------------------------------------------*/
unsigned int CIncrementalMapPartitioner::addMapFrame(
const CSensoryFramePtr &frame,
const CPose3DPDFPtr &robotPose )
{
size_t i=0,j=0,n=0;
CPose3D pose_i, pose_j, relPose;
CPose3DPDFPtr posePDF_i, posePDF_j;
CSensoryFramePtr sf_i, sf_j;
CMultiMetricMap *map_i=NULL,*map_j=NULL;
int debug_CheckPoint = 0;
mrpt::utils::TMatchingPairList corrs;
static CPose3D nullPose(0,0,0);
// Set options in graph partition:
CGraphPartitioner::DEBUG_SAVE_EIGENVECTOR_FILES = options.debugSaveAllEigenvectors;
// Create the maps:
TSetOfMetricMapInitializers mapInitializer;
TMetricMapInitializer mapElement;
mapElement.metricMapClassType = CLASS_ID( CSimplePointsMap );
mapInitializer.push_back( mapElement );
// mapElement.metricMapClassType = CLASS_ID( COccupancyGridMap2D );
// mapElement.occupancyGridMap2D_options.resolution = options.gridResolution;
// mapInitializer.push_back( mapElement );
mapElement.metricMapClassType = CLASS_ID( CLandmarksMap );
// mapElement.landmarksMap_options.insertionOpts.
mapInitializer.push_back( mapElement );
// Add new metric map to "m_individualMaps"
// --------------------------------------------
//CMultiMetricMap *newMetricMap = new CMultiMetricMap( &mapInitializer );
m_individualMaps.push_back( CMultiMetricMap() );
CMultiMetricMap &newMetricMap = m_individualMaps.back();
newMetricMap.setListOfMaps( &mapInitializer );
MRPT_START
// Create the metric map:
// -----------------------------------------------------------------
ASSERT_(newMetricMap.m_pointsMaps.size()>0);
newMetricMap.m_pointsMaps[0]->insertionOptions.isPlanarMap = false; // true
newMetricMap.m_pointsMaps[0]->insertionOptions.minDistBetweenLaserPoints = 0.20f;
options.minDistForCorrespondence = max(options.minDistForCorrespondence,1.3f*newMetricMap.m_pointsMaps[0]->insertionOptions.minDistBetweenLaserPoints);
// JLBC,17/AGO/2006: "m_individualMaps" were created from the robot pose, but it is
// more convenient now to save them as the robot being at (0,0,0).
//frame->insertObservationsInto( newMetricMap.m_pointsMaps[0] );
newMetricMap.m_pointsMaps[0]->copyFrom( * frame->buildAuxPointsMap<CPointsMap>(&newMetricMap.m_pointsMaps[0]->insertionOptions)); // Faster :-)
// Insert just the VisualLandmarkObservations:
newMetricMap.m_landmarksMap->insertionOptions.insert_SIFTs_from_monocular_images = false;
newMetricMap.m_landmarksMap->insertionOptions.insert_SIFTs_from_stereo_images = false;
newMetricMap.m_landmarksMap->insertionOptions.insert_Landmarks_from_range_scans = false;
frame->insertObservationsInto( newMetricMap.m_landmarksMap );
debug_CheckPoint=1;
// Add to corresponding vectors:
m_individualFrames.insert(robotPose, frame);
// Already added to "m_individualMaps" above
debug_CheckPoint=2;
// Ampliar la matriz de adyacencias:
// -----------------------------------------------------------------
n = m_A.getColCount();
n++;
m_A.setSize(n,n);
debug_CheckPoint=3;
ASSERT_(m_individualMaps.size() == n);
ASSERT_(m_individualFrames.size() == n);
// Ajustar tamaño del vector de nodos modificados:
// ---------------------------------------------------
// El nuevo evidentemente debe ser tenido en cuenta:
m_modified_nodes.push_back(true);
// Methods to compute adjacency matrix:
// true: matching between maps
// false: matching between observations through "CObservation::likelihoodWith"
// ------------------------------------------------------------------------------
bool useMapOrSF = options.useMapMatching;
debug_CheckPoint=4;
// Calcular los nuevos matchings y meterlos en la matriz:
// ----------------------------------------------------------------
//for (i=n-1;i<n;i++)
i=n-1; // Solo ejecutar para "i=n-1" la ultima fila/columna que esta vacia
{
// Get node "i":
m_individualFrames.get(i, posePDF_i, sf_i);
posePDF_i->getMean(pose_i);
// And its points map:
map_i = &m_individualMaps[i];
debug_CheckPoint=5;
// for (j=0;j<n;j++)
for (j=0;j<n-1;j++)
{
// Get node "j":
m_individualFrames.get(j, posePDF_j, sf_j);
posePDF_j->getMean( pose_j );
debug_CheckPoint=6;
relPose = pose_j - pose_i;
// And its points map:
map_j = &m_individualMaps[j];
debug_CheckPoint=66;
// Compute matching ratio:
if (useMapOrSF)
{
m_A(i,j) = map_i->compute3DMatchingRatio(
map_j,
relPose,
options.minDistForCorrespondence,
options.minMahaDistForCorrespondence );
}
else
{
//m_A(i,j) = sf_i->likelihoodWith(sf_j.pointer());
m_A(i,j) = observationsOverlap(sf_i, sf_j, &relPose );
}
} // for j
} // for i
for (i=0;i<n-1;i++) // Solo ejecutar para "i=n-1" la ultima fila/columna que esta vacia
{
debug_CheckPoint=8;
// Get node "i":
m_individualFrames.get(i, posePDF_i, sf_i);
posePDF_i->getMean(pose_i);
// And its points map:
map_i = &m_individualMaps[i];
debug_CheckPoint=9;
j=n-1; //for (j=n-1;j<n;j++)
{
// Get node "j":
m_individualFrames.get(j, posePDF_j, sf_j);
posePDF_j->getMean(pose_j);
debug_CheckPoint=10;
relPose = pose_j - pose_i;
// And its points map:
map_j = &m_individualMaps[j];
// Compute matching ratio:
if (useMapOrSF)
{
m_A(i,j) = map_i->compute3DMatchingRatio(
map_j,
CPose3D(relPose),
options.minDistForCorrespondence,
options.minMahaDistForCorrespondence );
}
else
{
//m_A(i,j) = sf_i->likelihoodWith(sf_j.pointer());
m_A(i,j) = observationsOverlap(sf_i, sf_j, &relPose );
}
debug_CheckPoint=12;
} // for j
} // for i
debug_CheckPoint=13;
// Self-similatity: Not used
m_A(n-1,n-1) = 0;
// Hacer que la matriz sea simetrica:
// -----------------------------------------------------------------
for (i=0;i<n;i++)
for (j=i+1;j<n;j++)
m_A(i,j) = m_A(j,i) = 0.5f * (m_A(i,j) + m_A(j,i) );
debug_CheckPoint=14;
/* DEBUG: Guardar la matriz: * /
A.saveToTextFile("debug_matriz.txt",1);
/ **/
// Añadir a la lista de nodos modificados los nodos afectados:
// -----------------------------------------------------------------
for (i=0;i<n;i++)
m_modified_nodes[i] = m_A(i,n-1) > 0;
debug_CheckPoint=15;
if (m_last_last_partition_are_new_ones)
{
// Insert into the "new_ones" partition:
m_last_partition[m_last_partition.size()-1].push_back( n-1 );
}
else
{
// Add a new partition:
vector_uint dummyPart;
dummyPart.push_back(n-1);
m_last_partition.push_back( dummyPart );
// The last one is the new_ones partition:
m_last_last_partition_are_new_ones = true;
}
return n-1; // Index of the new node
MRPT_END_WITH_CLEAN_UP( \
cout << "Unexpected runtime error at checkPoint="<< debug_CheckPoint << "\n"; \
cout << "\tn=" << n << "\n"; \
cout << "\ti=" << i << "\n"; \
cout << "\tj=" << j << "\n"; \
cout << "\tmap_i=" << map_i << "\n"; \
cout << "\tmap_j=" << map_j << "\n"; \
cout << "relPose: "<< relPose << endl; \
cout << "map_i.size()=" << map_i->m_pointsMaps[0]->size() << "\n"; \
cout << "map_j.size()=" << map_j->m_pointsMaps[0]->size() << "\n"; \
map_i->m_pointsMaps[0]->save2D_to_text_file(string("debug_DUMP_map_i.txt")); \
map_j->m_pointsMaps[0]->save2D_to_text_file(string("debug_DUMP_map_j.txt")); \
m_A.saveToTextFile("debug_DUMP_exception_A.txt"); \
);
// ------------------------------------------------------
// Benchmark: A whole ICP-SLAM run
// ------------------------------------------------------
double icp_test_1(int a1, int a2)
{
#ifdef MRPT_DATASET_DIR
const string rawlog_file = MRPT_DATASET_DIR "/2006-01ENE-21-SENA_Telecom Faculty_one_loop_only.rawlog";
if (!mrpt::system::fileExists(rawlog_file))
return 1;
CTicTac tictac;
int step = 0;
size_t rawlogEntry = 0;
CFileGZInputStream rawlogFile( rawlog_file );
TSetOfMetricMapInitializers metricMapsOpts;
const bool use_grid = a1!=0;
if (use_grid)
{
COccupancyGridMap2D::TMapDefinition def;
def.resolution = 0.05;
metricMapsOpts.push_back( def );
}
else
{
CSimplePointsMap::TMapDefinition def;
def.insertionOpts.minDistBetweenLaserPoints = 0.03;
metricMapsOpts.push_back( def );
}
double insertionLinDistance = 0.75;
double insertionAngDistance = DEG2RAD(30);
CICP::TConfigParams icpOptions;
icpOptions.maxIterations = 40;
// ---------------------------------
// Constructor
// ---------------------------------
CMetricMapBuilderICP mapBuilder;
mapBuilder.ICP_options.mapInitializers = metricMapsOpts;
mapBuilder.ICP_options.insertionLinDistance = insertionLinDistance;
mapBuilder.ICP_options.insertionAngDistance = insertionAngDistance;
mapBuilder.ICP_options.matchAgainstTheGrid = use_grid ;
mapBuilder.ICP_params = icpOptions;
// Start with an empty map:
mapBuilder.initialize( CSimpleMap() );
// ---------------------------------
// CMetricMapBuilder::TOptions
// ---------------------------------
mapBuilder.options.verbose = false;
mapBuilder.options.enableMapUpdating = true;
// ----------------------------------------------------------
// Map Building
// ----------------------------------------------------------
CActionCollectionPtr action;
CSensoryFramePtr observations;
for (;;)
{
// Load action/observation pair from the rawlog:
// --------------------------------------------------
if (! CRawlog::readActionObservationPair( rawlogFile, action, observations, rawlogEntry) )
break; // file EOF
// Execute:
mapBuilder.processActionObservation( *action, *observations );
step++;
// printf("\n---------------- STEP %u | RAWLOG ENTRY %u ----------------\n",step, (unsigned)rawlogEntry);
// Free memory:
action.clear_unique();
observations.clear_unique();
}
#if 0
mapBuilder.getCurrentlyBuiltMetricMap()->saveMetricMapRepresentationToFile( format("icp_%i_result",a1) );
#endif
if (!step) step++;
return tictac.Tac()/step;
#else
return 1;
#endif
}
// TSetOfMetricMapInitializers
void TSetOfMetricMapInitializers_push_back(
TSetOfMetricMapInitializers& self, TMetricMapInitializer::Ptr& o)
{
self.push_back(o);
}
/*---------------------------------------------------------------
process
---------------------------------------------------------------*/
void CDetectorDoorCrossing::process(
CActionRobotMovement2D &in_poseChange,
CSensoryFrame &in_sf,
TDoorCrossingOutParams &out_estimation
)
{
// Variables for generic use:
size_t i;
out_estimation.cumulativeTurning = 0;
MRPT_START
// 1) Add new pair to the list:
// -----------------------------------------
lastObs.addAction( in_poseChange );
lastObs.addObservations( in_sf );
// 2) Remove oldest pair:
// -----------------------------------------
ASSERT_( options.windowSize > 1 );
ASSERT_( (lastObs.size() % 2) == 0 ); // Assure even size
while (lastObs.size()>options.windowSize*2)
{
lastObs.remove(0);
lastObs.remove(0);
}
if ( lastObs.size() < options.windowSize * 2 )
{
// Not enought old data yet:
out_estimation.enoughtInformation = false;
return;
}
// 3) Build an occupancy grid map with observations
// -------------------------------------------------
CPose2D p, pos;
TSetOfMetricMapInitializers mapInitializer;
{
CSimplePointsMap::TMapDefinition def;
mapInitializer.push_back( def );
}
{
COccupancyGridMap2D::TMapDefinition def;
def.resolution = options.gridResolution;
mapInitializer.push_back( def );
}
CMultiMetricMap auxMap( &mapInitializer );
for (i=0;i<options.windowSize;i++)
{
CActionCollectionPtr acts = lastObs.getAsAction( i*2+0 );
CActionPtr act = acts->get(0);
ASSERT_( act->GetRuntimeClass()->derivedFrom( CLASS_ID( CActionRobotMovement2D ) ) )
CActionRobotMovement2DPtr action = CActionRobotMovement2DPtr( act );
action->poseChange->getMean(pos);
out_estimation.cumulativeTurning+= fabs(pos.phi());
// Get the cumulative pose for the current observation:
p = p + pos;
// Add SF to the grid map:
CSensoryFramePtr sf = lastObs.getAsObservations( i*2+1 );
CPose3D pose3D(p);
sf->insertObservationsInto( &auxMap, &pose3D );
}
// 4) Compute the information differece between this
// "map patch" and the previous one:
// -------------------------------------------------------
auxMap.m_gridMaps[0]->computeEntropy( entropy );
if (!lastEntropyValid)
{
out_estimation.enoughtInformation = false;
}
else
{
// 5) Fill output data
// ---------------------------------
out_estimation.enoughtInformation = true;
out_estimation.informationGain = entropy.I - lastEntropy.I;
out_estimation.pointsMap.copyFrom( *auxMap.m_pointsMaps[0] );
}
// For next iterations:
lastEntropy = entropy;
lastEntropyValid = true;
MRPT_END
}
