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Pnp multicam refactoring (#902)

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* gui: fixed wrongly showing landmark rejected when it was not (because a loop closure was rejected at the same time)

* Added Vis/PnPMaxVariance and RGBD/InvertedReg parameters. Implemented inlier distribution computation for multicam.

* On loc/small displacement: don't remove from odom cache if loop is rejected (maybe first loc)

* Loc: don't prune odom cache on small movement if delayed loc is enabled

* loc/small movement: cleanup bidirectional links

* Cov/PnP: fixed objPt transform to estimate depth

Co-authored-by: mathieu86 <mathieu@robust.ai>
This commit is contained in:
matlabbe
2022-09-24 12:29:42 -07:00
committed by GitHub
parent 95a76cb696
commit fa31affea0
14 changed files with 685 additions and 495 deletions
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1
corelib/include/rtabmap/core/Memory.h
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@@ -324,6 +324,7 @@ private:
float _laserScanGroundNormalsUp;
bool _reextractLoopClosureFeatures;
bool _localBundleOnLoopClosure;
bool _invertedReg;
float _rehearsalMaxDistance;
float _rehearsalMaxAngle;
bool _rehearsalWeightIgnoredWhileMoving;

2
corelib/include/rtabmap/core/Parameters.h
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@@ -370,6 +370,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(RGBD, LoopClosureIdentityGuess, bool, false, uFormat("Use Identity matrix as guess when computing loop closure transform, otherwise no guess is used, thus assuming that registration strategy selected (%s) can deal with transformation estimation without guess.", kRegStrategy().c_str()));
RTABMAP_PARAM(RGBD, LoopClosureReextractFeatures, bool, false, "Extract features even if there are some already in the nodes. Raw features are not saved in database.");
RTABMAP_PARAM(RGBD, LocalBundleOnLoopClosure, bool, false, "Do local bundle adjustment with neighborhood of the loop closure.");
RTABMAP_PARAM(RGBD, InvertedReg, bool, false, "On loop closure, do registration from the target to reference instead of reference to target.");
RTABMAP_PARAM(RGBD, CreateOccupancyGrid, bool, false, "Create local occupancy grid maps. See \"Grid\" group for parameters.");
RTABMAP_PARAM(RGBD, MarkerDetection, bool, false, "Detect static markers to be added as landmarks for graph optimization. If input data have already landmarks, this will be ignored. See \"Marker\" group for parameters.");
RTABMAP_PARAM(RGBD, LoopCovLimited, bool, false, "Limit covariance of non-neighbor links to minimum covariance of neighbor links. In other words, if covariance of a loop closure link is smaller than the minimum covariance of odometry links, its covariance is set to minimum covariance of odometry links.");
@@ -594,6 +595,7 @@ class RTABMAP_EXP Parameters
#else
RTABMAP_PARAM(Vis, PnPRefineIterations, int, 1, uFormat("[%s = 1] Refine iterations. Set to 0 if \"%s\" is also used.", kVisEstimationType().c_str(), kVisBundleAdjustment().c_str()));
#endif
RTABMAP_PARAM(Vis, PnPMaxVariance, float, 0.0, uFormat("[%s = 1] Max linear variance between 3D point correspondences after PnP. 0 means disabled.", kVisEstimationType().c_str()));
RTABMAP_PARAM(Vis, EpipolarGeometryVar, float, 0.1, uFormat("[%s = 2] Epipolar geometry maximum variance to accept the transformation.", kVisEstimationType().c_str()));
RTABMAP_PARAM(Vis, MinInliers, int, 20, "Minimum feature correspondences to compute/accept the transformation.");

1
corelib/include/rtabmap/core/RegistrationVis.h
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@@ -82,6 +82,7 @@ private:
float _PnPReprojError;
int _PnPFlags;
int _PnPRefineIterations;
float _PnPMaxVar;
int _correspondencesApproach;
int _flowWinSize;
int _flowIterations;

2
corelib/include/rtabmap/core/util3d_motion_estimation.h
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@@ -48,6 +48,7 @@ Transform RTABMAP_EXP estimateMotion3DTo2D(
double reprojError = 5.,
int flagsPnP = 0,
int pnpRefineIterations = 1,
float maxVariance = 0,
const Transform & guess = Transform::getIdentity(),
const std::map<int, cv::Point3f> & words3B = std::map<int, cv::Point3f>(),
cv::Mat * covariance = 0, // mean reproj error if words3B is not set
@@ -63,6 +64,7 @@ Transform RTABMAP_EXP estimateMotion3DTo2D(
double reprojError = 5.,
int flagsPnP = 0,
int pnpRefineIterations = 1,
float maxVariance = 0,
const Transform & guess = Transform::getIdentity(),
const std::map<int, cv::Point3f> & words3B = std::map<int, cv::Point3f>(),
cv::Mat * covariance = 0, // mean reproj error if words3B is not set