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Optimizer/PriosIgnored description update (#1774)

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matlabbe
2026-09-27 14:29:15 -07:00
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parent 66c72be7db
commit 8035be52ff
1 changed files with 2 additions and 2 deletions
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corelib/include/rtabmap/core/Parameters.h
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@@ -472,7 +472,7 @@ class RTABMAP_CORE_EXPORT Parameters
#endif
RTABMAP_PARAM(Optimizer, VarianceIgnored, bool, false, "Ignore constraints' variance. If checked, identity information matrix is used for each constraint. Otherwise, an information matrix is generated from the variance saved in the links.");
RTABMAP_PARAM(Optimizer, Robust, bool, false, "Robust graph optimization using Vertigo (only work for g2o and GTSAM optimization strategies).");
RTABMAP_PARAM(Optimizer, PriorsIgnored, bool, true, "Ignore prior constraints (global pose or GPS) while optimizing. Currently only g2o and gtsam optimization supports this.");
RTABMAP_PARAM(Optimizer, PriorsIgnored, bool, true, "Ignore prior constraints (global pose, GPS or marker priors) while optimizing. Currently only g2o and gtsam optimization supports this.");
RTABMAP_PARAM(Optimizer, LandmarksIgnored, bool, false, "Ignore landmark constraints while optimizing. Currently only g2o and gtsam optimization supports this.");
#if defined(RTABMAP_G2O) || defined(RTABMAP_GTSAM)
RTABMAP_PARAM(Optimizer, GravitySigma, float, 0.3, uFormat("Gravity sigma value (>=0, typically between 0.1 and 0.3). Optimization is done while preserving gravity orientation of the poses. This should be used only with visual/lidar inertial odometry approaches, for which we assume that all odometry poses are aligned with gravity. Set to 0 to disable gravity constraints. Currently supported only with g2o and GTSAM optimization strategies (see %s).", kOptimizerStrategy().c_str()));
@@ -961,7 +961,7 @@ class RTABMAP_CORE_EXPORT Parameters
RTABMAP_PARAM(Marker, VarianceOrientationIgnored, bool, false, uFormat("When this setting is false, the landmark's orientation is optimized during graph optimization. When this setting is true, only the position of the landmark is optimized. This can be useful when the landmark's orientation estimation is not reliable. Note that for %s=1 (g2o), only %s needs be set if we ignore orientation. For %s=2 (GTSAM), instead of optimizing the landmark's position directly, a bearing/range factor is used, with %s as the variance of the range factor (with 9999 to optimize the position with only a bearing factor) and %s as the variance of the bearing factor (pitch/yaw).", kOptimizerStrategy().c_str(), kMarkerVarianceLinear().c_str(), kOptimizerStrategy().c_str(), kMarkerVarianceLinear().c_str(), kMarkerVarianceAngular().c_str()));
RTABMAP_PARAM(Marker, MaxRange, float, 0.0, "Maximum range in which markers will be detected. <=0 for unlimited range.");
RTABMAP_PARAM(Marker, MinRange, float, 0.0, "Miniminum range in which markers will be detected. <=0 for unlimited range.");
RTABMAP_PARAM_STR(Marker, Priors, "", "World prior locations of the markers. The map will be transformed in marker's world frame when a tag is detected. Format is the marker's ID followed by its position (angles in rad), multiple markers are separated by vertical line (\"id1 x y z roll pitch yaw|id2 x y z roll pitch yaw\"). Example: \"1 0 0 1 0 0 0|2 1 0 1 0 0 1.57\" (marker 2 is 1 meter forward than marker 1 with 90 deg yaw rotation).");
RTABMAP_PARAM_STR(Marker, Priors, "", uFormat("World prior locations of the markers. The map will be transformed in marker's world frame when a tag is detected. Format is the marker's ID followed by its position (angles in rad), multiple markers are separated by vertical line (\"id1 x y z roll pitch yaw|id2 x y z roll pitch yaw\"). Example: \"1 0 0 1 0 0 0|2 1 0 1 0 0 1.57\" (marker 2 is 1 meter forward than marker 1 with 90 deg yaw rotation). The priors are used only if %s is false.", kOptimizerPriorsIgnored().c_str()));
RTABMAP_PARAM(Marker, PriorsVarianceLinear, float, 0.001, "Linear variance to set on marker priors.");
RTABMAP_PARAM(Marker, PriorsVarianceAngular, float, 0.001, "Angular variance to set on marker priors.");