Optimizer.cpp
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1 /*
2 Copyright (c) 2010-2016, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
3 All rights reserved.
4 
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15 
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27 
28 #include <rtabmap/utilite/ULogger.h>
29 #include <rtabmap/utilite/UStl.h>
30 #include <rtabmap/utilite/UMath.h>
31 #include <rtabmap/utilite/UConversion.h>
32 #include <rtabmap/core/Optimizer.h>
33 #include <rtabmap/core/Graph.h>
34 #include <rtabmap/core/util3d_transforms.h>
35 #include <rtabmap/core/RegistrationVis.h>
36 #include <set>
37 #include <queue>
38 
39 #include <rtabmap/core/optimizer/OptimizerTORO.h>
40 #include <rtabmap/core/optimizer/OptimizerG2O.h>
41 #include <rtabmap/core/optimizer/OptimizerGTSAM.h>
42 #include <rtabmap/core/optimizer/OptimizerCVSBA.h>
43 #include <rtabmap/core/optimizer/OptimizerCeres.h>
44 
45 namespace rtabmap {
46 
47 bool Optimizer::isAvailable(Optimizer::Type type)
48 {
49  if(type == Optimizer::kTypeG2O)
50  {
51  return OptimizerG2O::available();
52  }
53  else if(type == Optimizer::kTypeGTSAM)
54  {
55  return OptimizerGTSAM::available();
56  }
57  else if(type == Optimizer::kTypeCVSBA)
58  {
59  return OptimizerCVSBA::available();
60  }
61  else if(type == Optimizer::kTypeTORO)
62  {
63  return OptimizerTORO::available();
64  }
65  else if(type == Optimizer::kTypeCeres)
66  {
67  return OptimizerCeres::available();
68  }
69  return false;
70 }
71 
72 Optimizer * Optimizer::create(const ParametersMap & parameters)
73 {
74  int optimizerTypeInt = Parameters::defaultOptimizerStrategy();
75  Parameters::parse(parameters, Parameters::kOptimizerStrategy(), optimizerTypeInt);
76  return create((Optimizer::Type)optimizerTypeInt, parameters);
77 }
78 
79 Optimizer * Optimizer::create(Optimizer::Type type, const ParametersMap & parameters)
80 {
81  UASSERT_MSG(OptimizerG2O::available() || OptimizerGTSAM::available() || OptimizerTORO::available() || OptimizerCeres::available(),
82  "RTAB-Map is not built with any graph optimization approach!");
83 
84  if(!OptimizerTORO::available() && type == Optimizer::kTypeTORO)
85  {
86  if(OptimizerGTSAM::available())
87  {
88  UWARN("TORO optimizer not available. GTSAM will be used instead.");
89  type = Optimizer::kTypeGTSAM;
90  }
91  else if(OptimizerG2O::available())
92  {
93  UWARN("TORO optimizer not available. g2o will be used instead.");
94  type = Optimizer::kTypeG2O;
95  }
96  else if(OptimizerCeres::available())
97  {
98  UWARN("TORO optimizer not available. ceres will be used instead.");
99  type = Optimizer::kTypeCeres;
100  }
101  }
102  if(!OptimizerG2O::available() && type == Optimizer::kTypeG2O)
103  {
104  if(OptimizerGTSAM::available())
105  {
106  UWARN("g2o optimizer not available. GTSAM will be used instead.");
107  type = Optimizer::kTypeGTSAM;
108  }
109  else if(OptimizerTORO::available())
110  {
111  UWARN("g2o optimizer not available. TORO will be used instead.");
112  type = Optimizer::kTypeTORO;
113  }
114  else if(OptimizerCeres::available())
115  {
116  UWARN("g2o optimizer not available. ceres will be used instead.");
117  type = Optimizer::kTypeCeres;
118  }
119  }
120  if(!OptimizerGTSAM::available() && type == Optimizer::kTypeGTSAM)
121  {
122  if(OptimizerG2O::available())
123  {
124  UWARN("GTSAM optimizer not available. g2o will be used instead.");
125  type = Optimizer::kTypeG2O;
126  }
127  else if(OptimizerTORO::available())
128  {
129  UWARN("GTSAM optimizer not available. TORO will be used instead.");
130  type = Optimizer::kTypeTORO;
131  }
132  else if(OptimizerCeres::available())
133  {
134  UWARN("GTSAM optimizer not available. ceres will be used instead.");
135  type = Optimizer::kTypeCeres;
136  }
137  }
138  if(!OptimizerCVSBA::available() && type == Optimizer::kTypeCVSBA)
139  {
140  if(OptimizerG2O::available())
141  {
142  UWARN("CVSBA optimizer not available. g2o will be used instead.");
143  type = Optimizer::kTypeG2O;
144  }
145  }
146  if(!OptimizerCeres::available() && type == Optimizer::kTypeCeres)
147  {
148  if(OptimizerGTSAM::available())
149  {
150  UWARN("Ceres optimizer not available. gtsam will be used instead.");
151  type = Optimizer::kTypeGTSAM;
152  }
153  else if(OptimizerG2O::available())
154  {
155  UWARN("Ceres optimizer not available. g2o will be used instead.");
156  type = Optimizer::kTypeG2O;
157  }
158  else if(OptimizerTORO::available())
159  {
160  UWARN("Ceres optimizer not available. TORO will be used instead.");
161  type = Optimizer::kTypeTORO;
162  }
163  }
164  Optimizer * optimizer = 0;
165  switch(type)
166  {
167  case Optimizer::kTypeGTSAM:
168  optimizer = new OptimizerGTSAM(parameters);
169  break;
170  case Optimizer::kTypeG2O:
171  optimizer = new OptimizerG2O(parameters);
172  break;
173  case Optimizer::kTypeCVSBA:
174  optimizer = new OptimizerCVSBA(parameters);
175  break;
176  case Optimizer::kTypeCeres:
177  optimizer = new OptimizerCeres(parameters);
178  break;
179  case Optimizer::kTypeTORO:
180  default:
181  optimizer = new OptimizerTORO(parameters);
182  break;
183 
184  }
185  return optimizer;
186 }
187 
188 void Optimizer::getConnectedGraph(
189  int fromId,
190  const std::map<int, Transform> & posesIn,
191  const std::multimap<int, Link> & linksIn,
192  std::map<int, Transform> & posesOut,
193  std::multimap<int, Link> & linksOut) const
194 {
195  UDEBUG("IN: fromId=%d poses=%d links=%d priorsIgnored=%d landmarksIgnored=%d", fromId, (int)posesIn.size(), (int)linksIn.size(), priorsIgnored()?1:0, landmarksIgnored()?1:0);
196  UASSERT(fromId>0);
197  UASSERT(uContains(posesIn, fromId));
198 
199  posesOut.clear();
200  linksOut.clear();
201 
202  std::set<int> nextPoses;
203  nextPoses.insert(fromId);
204  std::multimap<int, std::pair<int, Link::Type> > biLinks;
205  for(std::multimap<int, Link>::const_iterator iter=linksIn.begin(); iter!=linksIn.end(); ++iter)
206  {
207  if(iter->second.from() != iter->second.to())
208  {
209  if(graph::findLink(biLinks, iter->second.from(), iter->second.to(), true, iter->second.type()) == biLinks.end())
210  {
211  biLinks.insert(std::make_pair(iter->second.from(), std::make_pair(iter->second.to(), iter->second.type())));
212  biLinks.insert(std::make_pair(iter->second.to(), std::make_pair(iter->second.from(), iter->second.type())));
213  }
214  }
215  }
216 
217  while(nextPoses.size())
218  {
219  int currentId = *nextPoses.rbegin(); // fill up all nodes before landmarks
220  nextPoses.erase(*nextPoses.rbegin());
221 
222  if(posesOut.empty())
223  {
224  posesOut.insert(std::make_pair(currentId, posesIn.find(currentId)->second));
225 
226  // add prior links
227  for(std::multimap<int, Link>::const_iterator pter=linksIn.find(currentId); pter!=linksIn.end() && pter->first==currentId; ++pter)
228  {
229  if(pter->second.from() == pter->second.to() && (!priorsIgnored() || pter->second.type() != Link::kPosePrior))
230  {
231  linksOut.insert(*pter);
232  }
233  }
234  }
235 
236  for(std::multimap<int, std::pair<int, Link::Type> >::const_iterator iter=biLinks.find(currentId); iter!=biLinks.end() && iter->first==currentId; ++iter)
237  {
238  int toId = iter->second.first;
239  Link::Type type = iter->second.second;
240  if(posesIn.find(toId) != posesIn.end() && (!landmarksIgnored() || toId>0))
241  {
242  std::multimap<int, Link>::const_iterator kter = graph::findLink(linksIn, currentId, toId, true, type);
243  if(nextPoses.find(toId) == nextPoses.end())
244  {
245  if(!uContains(posesOut, toId))
246  {
247  const Transform & poseToIn = posesIn.at(toId);
248  Transform t = kter->second.from()==currentId?kter->second.transform():kter->second.transform().inverse();
249  if(isSlam2d() && kter->second.type() == Link::kLandmark && toId>0 && (poseToIn.is3DoF() || poseToIn.is4DoF()))
250  {
251  if(poseToIn.is3DoF())
252  {
253  posesOut.insert(std::make_pair(toId, (posesOut.at(currentId) * t).to3DoF()));
254  }
255  else
256  {
257  posesOut.insert(std::make_pair(toId, (posesOut.at(currentId) * t).to4DoF()));
258  }
259  }
260  else
261  {
262  posesOut.insert(std::make_pair(toId, posesOut.at(currentId)* t));
263  }
264 
265  // add prior links
266  for(std::multimap<int, Link>::const_iterator pter=linksIn.find(toId); pter!=linksIn.end() && pter->first==toId; ++pter)
267  {
268  if(pter->second.from() == pter->second.to() && (!priorsIgnored() || pter->second.type() != Link::kPosePrior))
269  {
270  linksOut.insert(*pter);
271  }
272  }
273 
274  nextPoses.insert(toId);
275  }
276 
277  // only add unique links
278  if(graph::findLink(linksOut, currentId, toId, true, kter->second.type()) == linksOut.end())
279  {
280  if(kter->second.to() < 0)
281  {
282  // For landmarks, make sure fromId is the landmark
283  linksOut.insert(std::make_pair(kter->second.to(), kter->second.inverse()));
284  }
285  else
286  {
287  linksOut.insert(*kter);
288  }
289  }
290  }
291  }
292  }
293  }
294  UDEBUG("OUT: poses=%d links=%d", (int)posesOut.size(), (int)linksOut.size());
295 }
296 
297 Optimizer::Optimizer(int iterations, bool slam2d, bool covarianceIgnored, double epsilon, bool robust, bool priorsIgnored, bool landmarksIgnored, float gravitySigma) :
298  iterations_(iterations),
299  slam2d_(slam2d),
300  covarianceIgnored_(covarianceIgnored),
301  epsilon_(epsilon),
302  robust_(robust),
303  priorsIgnored_(priorsIgnored),
304  landmarksIgnored_(landmarksIgnored),
305  gravitySigma_(gravitySigma)
306 {
307 }
308 
309 Optimizer::Optimizer(const ParametersMap & parameters) :
310  iterations_(Parameters::defaultOptimizerIterations()),
311  slam2d_(Parameters::defaultRegForce3DoF()),
312  covarianceIgnored_(Parameters::defaultOptimizerVarianceIgnored()),
313  epsilon_(Parameters::defaultOptimizerEpsilon()),
314  robust_(Parameters::defaultOptimizerRobust()),
315  priorsIgnored_(Parameters::defaultOptimizerPriorsIgnored()),
316  landmarksIgnored_(Parameters::defaultOptimizerLandmarksIgnored()),
317  gravitySigma_(Parameters::defaultOptimizerGravitySigma())
318 {
319  parseParameters(parameters);
320 }
321 
322 void Optimizer::parseParameters(const ParametersMap & parameters)
323 {
324  Parameters::parse(parameters, Parameters::kOptimizerIterations(), iterations_);
325  Parameters::parse(parameters, Parameters::kOptimizerVarianceIgnored(), covarianceIgnored_);
326  Parameters::parse(parameters, Parameters::kRegForce3DoF(), slam2d_);
327  Parameters::parse(parameters, Parameters::kOptimizerEpsilon(), epsilon_);
328  Parameters::parse(parameters, Parameters::kOptimizerRobust(), robust_);
329  Parameters::parse(parameters, Parameters::kOptimizerPriorsIgnored(), priorsIgnored_);
330  Parameters::parse(parameters, Parameters::kOptimizerLandmarksIgnored(), landmarksIgnored_);
331  Parameters::parse(parameters, Parameters::kOptimizerGravitySigma(), gravitySigma_);
332 }
333 
334 std::map<int, Transform> Optimizer::optimizeIncremental(
335  int rootId,
336  const std::map<int, Transform> & poses,
337  const std::multimap<int, Link> & constraints,
338  std::list<std::map<int, Transform> > * intermediateGraphes,
339  double * finalError,
340  int * iterationsDone)
341 {
342  std::map<int, Transform> incGraph;
343  std::multimap<int, Link> incGraphLinks;
344  incGraph.insert(*poses.begin());
345  int i=0;
346  std::multimap<int, Link> constraintsCpy = constraints;
347  UDEBUG("Incremental optimization... poses=%d constraints=%d", (int)poses.size(), (int)constraints.size());
348  for(std::map<int, Transform>::const_iterator iter=poses.begin(); iter!=poses.end(); ++iter)
349  {
350  incGraph.insert(*iter);
351  bool hasLoopClosure = false;
352  for(std::multimap<int, Link>::iterator jter=constraintsCpy.lower_bound(iter->first); jter!=constraintsCpy.end() && jter->first==iter->first; ++jter)
353  {
354  UDEBUG("%d: %d -> %d type=%d", iter->first, jter->second.from(), jter->second.to(), jter->second.type());
355  if(jter->second.type() == Link::kNeighbor || jter->second.type() == Link::kNeighborMerged)
356  {
357  UASSERT(uContains(incGraph, iter->first));
358  incGraph.insert(std::make_pair(jter->second.to(), incGraph.at(iter->first) * jter->second.transform()));
359  incGraphLinks.insert(*jter);
360  }
361  else
362  {
363  if(!uContains(incGraph, jter->second.to()) && jter->second.to() > iter->first)
364  {
365  // node not yet in graph, switch link direction
366  constraintsCpy.insert(std::make_pair(jter->second.to(), jter->second.inverse()));
367  }
368  else
369  {
370  UASSERT(uContains(incGraph, jter->second.to()));
371  incGraphLinks.insert(*jter);
372  hasLoopClosure = true;
373  }
374  }
375  }
376  if(hasLoopClosure)
377  {
378  incGraph = this->optimize(incGraph.begin()->first, incGraph, incGraphLinks);
379  if(incGraph.empty())
380  {
381  UWARN("Failed incremental optimization... last pose added is %d", iter->first);
382  break;
383  }
384  }
385  UDEBUG("Iteration %d/%d %s", ++i, (int)poses.size(), hasLoopClosure?"*":"");
386  }
387  if(!incGraph.empty() && incGraph.size() == poses.size())
388  {
389  UASSERT(incGraphLinks.size() == constraints.size());
390  UASSERT(uContains(poses, rootId) && uContains(incGraph, rootId));
391  incGraph.at(rootId) = poses.at(rootId);
392  return this->optimize(rootId, incGraph, incGraphLinks, intermediateGraphes, finalError, iterationsDone);
393  }
394 
395  UDEBUG("Failed incremental optimization");
396  return std::map<int, Transform>();
397 }
398 
399 std::map<int, Transform> Optimizer::optimize(
400  int rootId,
401  const std::map<int, Transform> & poses,
402  const std::multimap<int, Link> & edgeConstraints,
403  std::list<std::map<int, Transform> > * intermediateGraphes,
404  double * finalError,
405  int * iterationsDone)
406 {
407  cv::Mat covariance;
408  return optimize(rootId,
409  poses,
410  edgeConstraints,
411  covariance,
412  intermediateGraphes,
413  finalError,
414  iterationsDone);
415 }
416 
417 std::map<int, Transform> Optimizer::optimize(
418  int rootId,
419  const std::map<int, Transform> & poses,
420  const std::multimap<int, Link> & constraints,
421  cv::Mat & outputCovariance,
422  std::list<std::map<int, Transform> > * intermediateGraphes,
423  double * finalError,
424  int * iterationsDone)
425 {
426  UERROR("Optimizer %d doesn't implement optimize() method.", (int)this->type());
427  return std::map<int, Transform>();
428 }
429 
430 std::map<int, Transform> Optimizer::optimizeBA(
431  int rootId,
432  const std::map<int, Transform> & poses,
433  const std::multimap<int, Link> & links,
434  const std::map<int, std::vector<CameraModel> > & models,
435  std::map<int, cv::Point3f> & points3DMap,
436  const std::map<int, std::map<int, FeatureBA> > & wordReferences,
437  std::set<int> * outliers)
438 {
439  UERROR("Optimizer %d doesn't implement optimizeBA() method.", (int)this->type());
440  return std::map<int, Transform>();
441 }
442 
443 std::map<int, Transform> Optimizer::optimizeBA(
444  int rootId,
445  const std::map<int, Transform> & posesIn,
446  const std::multimap<int, Link> & links,
447  const std::map<int, Signature> & signatures,
448  std::map<int, cv::Point3f> & points3DMap,
449  std::map<int, std::map<int, FeatureBA> > & wordReferences,
450  bool rematchFeatures)
451 {
452  UDEBUG("");
453  std::map<int, std::vector<CameraModel> > multiModels;
454  std::map<int, Transform> poses;
455  for(std::map<int, Transform>::const_iterator iter=posesIn.lower_bound(1); iter!=posesIn.end(); ++iter)
456  {
457  // Get camera model
458  std::vector<CameraModel> models;
459  if(uContains(signatures, iter->first))
460  {
461  const SensorData & s = signatures.at(iter->first).sensorData();
462  if(s.cameraModels().size() >= 1 && s.cameraModels().at(0).isValidForProjection())
463  {
464  models = s.cameraModels();
465  }
466  else if(!s.stereoCameraModels().empty() && s.stereoCameraModels()[0].isValidForProjection())
467  {
468  for(size_t i=0; i<s.stereoCameraModels().size(); ++i)
469  {
470  CameraModel model = s.stereoCameraModels()[i].left();
471 
472  // Set Tx = -baseline*fx for stereo BA
473  models.push_back(CameraModel(
474  model.fx(),
475  model.fy(),
476  model.cx(),
477  model.cy(),
478  model.localTransform(),
479  -s.stereoCameraModels()[i].baseline()*model.fx(),
480  model.imageSize()));
481  }
482  }
483  else
484  {
485  UERROR("Missing calibration for node %d", iter->first);
486  return std::map<int, Transform>();
487  }
488  }
489  else
490  {
491  UERROR("Did not find node %d in cache", iter->first);
492  return std::map<int, Transform>();
493  }
494 
495  multiModels.insert(std::make_pair(iter->first, models));
496  poses.insert(*iter);
497  }
498 
499  // compute correspondences
500  this->computeBACorrespondences(poses, links, signatures, points3DMap, wordReferences, rematchFeatures);
501 
502  return optimizeBA(rootId, poses, links, multiModels, points3DMap, wordReferences);
503 }
504 
505 std::map<int, Transform> Optimizer::optimizeBA(
506  int rootId,
507  const std::map<int, Transform> & poses,
508  const std::multimap<int, Link> & links,
509  const std::map<int, Signature> & signatures,
510  bool rematchFeatures)
511 {
512  std::map<int, cv::Point3f> points3DMap;
513  std::map<int, std::map<int, FeatureBA> > wordReferences;
514  return optimizeBA(rootId, poses, links, signatures, points3DMap, wordReferences, rematchFeatures);
515 }
516 
517 Transform Optimizer::optimizeBA(
518  const Link & link,
519  const CameraModel & model,
520  std::map<int, cv::Point3f> & points3DMap,
521  const std::map<int, std::map<int, FeatureBA> > & wordReferences,
522  std::set<int> * outliers)
523 {
524  std::map<int, Transform> poses;
525  poses.insert(std::make_pair(link.from(), Transform::getIdentity()));
526  poses.insert(std::make_pair(link.to(), link.transform()));
527  std::multimap<int, Link> links;
528  links.insert(std::make_pair(link.from(), link));
529  std::map<int, std::vector<CameraModel> > models;
530  std::vector<CameraModel> tmp;
531  tmp.push_back(model);
532  models.insert(std::make_pair(link.from(), tmp));
533  models.insert(std::make_pair(link.to(), tmp));
534  poses = optimizeBA(link.from(), poses, links, models, points3DMap, wordReferences, outliers);
535  if(poses.size() == 2)
536  {
537  return poses.rbegin()->second;
538  }
539  else
540  {
541  return link.transform();
542  }
543 }
544 
545 struct KeyPointCompare
546 {
547  bool operator() (const cv::KeyPoint& lhs, const cv::KeyPoint& rhs) const
548  {
549  return lhs.pt.x < rhs.pt.x || (lhs.pt.x == rhs.pt.x && lhs.pt.y < rhs.pt.y);
550  }
551 };
552 
553 void Optimizer::computeBACorrespondences(
554  const std::map<int, Transform> & poses,
555  const std::multimap<int, Link> & links,
556  const std::map<int, Signature> & signatures,
557  std::map<int, cv::Point3f> & points3DMap,
558  std::map<int, std::map<int, FeatureBA> > & wordReferences,
559  bool rematchFeatures)
560 {
561  UDEBUG("rematchFeatures=%d", rematchFeatures?1:0);
562  int wordCount = 0;
563  int edgeWithWordsAdded = 0;
564  std::map<int, std::map<cv::KeyPoint, int, KeyPointCompare> > frameToWordMap; // <FrameId, <Keypoint, wordId> >
565  for(std::multimap<int, Link>::const_iterator iter=links.lower_bound(1); iter!=links.end(); ++iter)
566  {
567  Link link = iter->second;
568  if(link.to() < link.from())
569  {
570  link = link.inverse();
571  }
572  if(link.to() != link.from() &&
573  uContains(signatures, link.from()) &&
574  uContains(signatures, link.to()) &&
575  uContains(poses, link.from()))
576  {
577  Signature sFrom = signatures.at(link.from());
578  if(sFrom.getWeight() >= 0) // ignore intermediate links
579  {
580  Signature sTo = signatures.at(link.to());
581 
582  if((sFrom.sensorData().cameraModels().empty() && sFrom.sensorData().stereoCameraModels().empty()) ||
583  (sTo.sensorData().cameraModels().empty() && sTo.sensorData().stereoCameraModels().empty()))
584  {
585  UERROR("No camera models found");
586  continue;
587  }
588 
589  if(sTo.getWeight() < 0)
590  {
591  for(std::multimap<int, Link>::const_iterator jter=links.find(sTo.id());
592  sTo.getWeight() < 0 && jter!=links.end() && uContains(signatures, jter->second.to());
593  ++jter)
594  {
595  sTo = signatures.at(jter->second.to());
596  }
597  }
598 
599  if(sFrom.getWords().size() &&
600  sTo.getWords().size() &&
601  sFrom.getWords3().size())
602  {
603  ParametersMap regParam;
604  regParam.insert(ParametersPair(Parameters::kVisEstimationType(), "1"));
605  regParam.insert(ParametersPair(Parameters::kVisPnPReprojError(), "5"));
606  regParam.insert(ParametersPair(Parameters::kVisMinInliers(), "6"));
607  regParam.insert(ParametersPair(Parameters::kVisCorNNDR(), "0.6"));
608  RegistrationVis reg(regParam);
609 
610  if(!rematchFeatures)
611  {
612  sFrom.setWordsDescriptors(cv::Mat());
613  sTo.setWordsDescriptors(cv::Mat());
614  }
615 
616  RegistrationInfo info;
617  Transform t = reg.computeTransformationMod(sFrom, sTo, Transform(), &info);
618  //Transform t = reg.computeTransformationMod(sFrom, sTo, iter->second.transform(), &info);
619  UDEBUG("%d->%d, inliers=%d",sFrom.id(), sTo.id(), (int)info.inliersIDs.size());
620 
621  if(!t.isNull())
622  {
623  if(!rematchFeatures)
624  {
625  // set descriptors for the output
626  if(sFrom.getWords().size() &&
627  sFrom.getWordsDescriptors().empty() &&
628  (int)sFrom.getWords().size() == signatures.at(link.from()).getWordsDescriptors().rows)
629  {
630  sFrom.setWordsDescriptors(signatures.at(link.from()).getWordsDescriptors());
631  }
632  if(sTo.getWords().size() &&
633  sTo.getWordsDescriptors().empty() &&
634  (int)sTo.getWords().size() == signatures.at(link.to()).getWordsDescriptors().rows)
635  {
636  sTo.setWordsDescriptors(signatures.at(link.to()).getWordsDescriptors());
637  }
638  }
639 
640  Transform pose = poses.at(sFrom.id());
641  UASSERT(!pose.isNull());
642  for(unsigned int i=0; i<info.inliersIDs.size(); ++i)
643  {
644  int indexFrom = sFrom.getWords().lower_bound(info.inliersIDs[i])->second;
645  cv::Point3f p = sFrom.getWords3()[indexFrom];
646  if(p.x > 0.0f) // make sure the point is valid
647  {
648  cv::KeyPoint ptFrom = sFrom.getWordsKpts()[indexFrom];
649  int indexTo = sTo.getWords().lower_bound(info.inliersIDs[i])->second;
650  cv::KeyPoint ptTo = sTo.getWordsKpts()[indexTo];
651 
652  int wordId = -1;
653 
654  // find if the word is already added
655  std::map<int, std::map<cv::KeyPoint, int, KeyPointCompare> >::iterator fromIter = frameToWordMap.find(sFrom.id());
656  std::map<int, std::map<cv::KeyPoint, int, KeyPointCompare> >::iterator toIter = frameToWordMap.find(sTo.id());
657  bool fromAlreadyAdded = false;
658  bool toAlreadyAdded = false;
659  if( fromIter != frameToWordMap.end() &&
660  fromIter->second.find(ptFrom) != fromIter->second.end())
661  {
662  wordId = fromIter->second.at(ptFrom);
663  fromAlreadyAdded = true;
664  }
665  if( toIter != frameToWordMap.end() &&
666  toIter->second.find(ptTo) != toIter->second.end())
667  {
668  wordId = toIter->second.at(ptTo);
669  toAlreadyAdded = true;
670  }
671 
672  if(wordId == -1)
673  {
674  wordId = ++wordCount;
675  wordReferences.insert(std::make_pair(wordId, std::map<int, FeatureBA>()));
676 
677  points3DMap.insert(std::make_pair(wordId, util3d::transformPoint(p, pose)));
678  }
679  else
680  {
681  UASSERT(wordReferences.find(wordId) != wordReferences.end());
682  UASSERT(points3DMap.find(wordId) != points3DMap.end());
683  }
684 
685  if(!fromAlreadyAdded)
686  {
687  cv::Mat descriptorFrom;
688  if(!sFrom.getWordsDescriptors().empty())
689  {
690  UASSERT(indexFrom < sFrom.getWordsDescriptors().rows);
691  descriptorFrom = sFrom.getWordsDescriptors().row(indexFrom);
692  }
693  int cameraIndex = 0;
694  if(sFrom.sensorData().cameraModels().size()>1 || sFrom.sensorData().stereoCameraModels().size()>1)
695  {
696  float subImageWidth = sFrom.sensorData().cameraModels().size()>1?sFrom.sensorData().cameraModels()[0].imageWidth():sFrom.sensorData().stereoCameraModels()[0].left().imageWidth();
697  cameraIndex = int(ptFrom.pt.x / subImageWidth);
698  ptFrom.pt.x = ptFrom.pt.x - (subImageWidth*float(cameraIndex));
699  }
700 
701  float depth = 0.0f;
702  if(!sFrom.sensorData().cameraModels().empty())
703  {
704  depth = util3d::transformPoint(p, sFrom.sensorData().cameraModels()[cameraIndex].localTransform().inverse()).z;
705  }
706  else
707  {
708  UASSERT(!sFrom.sensorData().stereoCameraModels().empty());
709  depth = util3d::transformPoint(p, sFrom.sensorData().stereoCameraModels()[cameraIndex].localTransform().inverse()).z;
710  }
711 
712 
713  wordReferences.at(wordId).insert(std::make_pair(sFrom.id(), FeatureBA(ptFrom, depth, descriptorFrom, cameraIndex)));
714  frameToWordMap.insert(std::make_pair(sFrom.id(), std::map<cv::KeyPoint, int, KeyPointCompare>()));
715  frameToWordMap.at(sFrom.id()).insert(std::make_pair(ptFrom, wordId));
716  }
717 
718  if(!toAlreadyAdded)
719  {
720  cv::Mat descriptorTo;
721  if(!sTo.getWordsDescriptors().empty())
722  {
723  UASSERT(indexTo < sTo.getWordsDescriptors().rows);
724  descriptorTo = sTo.getWordsDescriptors().row(indexTo);
725  }
726 
727  int cameraIndex = 0;
728  if(sTo.sensorData().cameraModels().size()>1 || sTo.sensorData().stereoCameraModels().size()>1)
729  {
730  float subImageWidth = sTo.sensorData().cameraModels().size()>1?sTo.sensorData().cameraModels()[0].imageWidth():sTo.sensorData().stereoCameraModels()[0].left().imageWidth();
731  cameraIndex = int(ptTo.pt.x / subImageWidth);
732  ptTo.pt.x = ptTo.pt.x - (subImageWidth*float(cameraIndex));
733  }
734 
735  float depth = 0.0f;
736  if(!sTo.getWords3().empty())
737  {
738  UASSERT(indexTo < (int)sTo.getWords3().size());
739  const cv::Point3f & pt = sTo.getWords3()[indexTo];
740  if(!sTo.sensorData().cameraModels().empty())
741  {
742  depth = util3d::transformPoint(pt, sTo.sensorData().cameraModels()[cameraIndex].localTransform().inverse()).z;
743  }
744  else
745  {
746  UASSERT(!sTo.sensorData().stereoCameraModels().empty());
747  depth = util3d::transformPoint(pt, sTo.sensorData().stereoCameraModels()[cameraIndex].localTransform().inverse()).z;
748  }
749  }
750 
751  wordReferences.at(wordId).insert(std::make_pair(sTo.id(), FeatureBA(ptTo, depth, descriptorTo, cameraIndex)));
752  frameToWordMap.insert(std::make_pair(sTo.id(), std::map<cv::KeyPoint, int, KeyPointCompare>()));
753  frameToWordMap.at(sTo.id()).insert(std::make_pair(ptTo, wordId));
754  }
755  }
756  }
757  ++edgeWithWordsAdded;
758  }
759  else
760  {
761  UWARN("Not enough inliers (%d) between %d and %d", info.inliersIDs.size(), sFrom.id(), sTo.id());
762  }
763  }
764  }
765  }
766  }
767  UDEBUG("Added %d words (edges with words=%d/%d)", wordCount, edgeWithWordsAdded, links.size());
768  if(links.empty())
769  {
770  UERROR("No links found for BA?!");
771  }
772  else if(wordCount == 0)
773  {
774  UERROR("No words added for BA?!");
775  }
776 }
777 
778 } /* namespace rtabmap */
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rtabmap
Author(s): Mathieu Labbe
autogenerated on Mon Jul 1 2024 02:42:31