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https://github.com/introlab/rtabmap.git
synced 2026-09-02 01:20:25 +08:00
Explicitly show licenses of optional dependencies on CMake
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@@ -69,12 +69,20 @@ public:
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virtual Type type() const = 0;
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// getters
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int iterations() const {return iterations_;}
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bool isSlam2d() const {return slam2d_;}
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bool isCovarianceIgnored() const {return covarianceIgnored_;}
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double epsilon() const {return epsilon_;}
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bool isRobust() const {return robust_;}
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// setters
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void setIterations(int iterations) {iterations_ = iterations;}
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void setSlam2d(bool enabled) {slam2d_ = enabled;}
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void setCovarianceIgnored(bool enabled) {covarianceIgnored_ = enabled;}
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void setEpsilon(double epsilon) {epsilon_ = epsilon;}
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void setRobust(bool enabled) {robust_ = enabled;}
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// inherited classes should implement one of these methods
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virtual std::map<int, Transform> optimize(
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int rootId,
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@@ -36,6 +36,9 @@ namespace rtabmap {
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class RTABMAP_EXP OptimizerTORO : public Optimizer
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{
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public:
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static bool available();
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public:
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static bool saveGraph(
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const std::string & fileName,
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@@ -220,7 +220,11 @@ class RTABMAP_EXP Parameters
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RTABMAP_PARAM(Kp, MaxFeatures, int, 400, "Maximum features extracted from the images (0 means not bounded, <0 means no extraction).");
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RTABMAP_PARAM(Kp, BadSignRatio, float, 0.5, "Bad signature ratio (less than Ratio x AverageWordsPerImage = bad).");
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RTABMAP_PARAM(Kp, NndrRatio, float, 0.8, "NNDR ratio (A matching pair is detected, if its distance is closer than X times the distance of the second nearest neighbor.)");
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RTABMAP_PARAM_COND(Kp, DetectorStrategy, int, RTABMAP_NONFREE, 0, 2, "0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK.");
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#ifdef RTABMAP_NONFREE
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RTABMAP_PARAM(Kp, DetectorStrategy, int, 0, "0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK.");
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#else
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RTABMAP_PARAM(Kp, DetectorStrategy, int, 2, "0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK.");
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#endif
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RTABMAP_PARAM(Kp, TfIdfLikelihoodUsed, bool, true, "Use of the td-idf strategy to compute the likelihood.");
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RTABMAP_PARAM(Kp, Parallelized, bool, true, "If the dictionary update and signature creation were parallelized.");
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RTABMAP_PARAM_STR(Kp, RoiRatios, "0.0 0.0 0.0 0.0", "Region of interest ratios [left, right, top, bottom].");
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@@ -303,7 +307,7 @@ class RTABMAP_EXP Parameters
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RTABMAP_PARAM(RGBD, AngularUpdate, float, 0.1, "Minimum angular displacement to update the map. Rehearsal is done prior to this, so weights are still updated.");
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RTABMAP_PARAM(RGBD, NewMapOdomChangeDistance, float, 0, "A new map is created if a change of odometry translation greater than X m is detected (0 m = disabled).");
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RTABMAP_PARAM(RGBD, OptimizeFromGraphEnd, bool, false, "Optimize graph from the newest node. If false, the graph is optimized from the oldest node of the current graph (this adds an overhead computation to detect to oldest mode of the current graph, but it can be useful to preserve the map referential from the oldest node). Warning when set to false: when some nodes are transferred, the first referential of the local map may change, resulting in momentary changes in robot/map position (which are annoying in teleoperation).");
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RTABMAP_PARAM(RGBD, OptimizeMaxError, float, 1.0, "Reject loop closures if optimization error is greater than this value (0=disabled). This will help to detect when a wrong loop closure is added to the graph.");
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RTABMAP_PARAM(RGBD, OptimizeMaxError, float, 1.0, "Reject loop closures if optimization error is greater than this value (0=disabled). This will help to detect when a wrong loop closure is added to the graph. Not compatible with \"Optimizer/Robust\" if enabled.");
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RTABMAP_PARAM(RGBD, GoalReachedRadius, float, 0.5, "Goal reached radius (m).");
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RTABMAP_PARAM(RGBD, PlanStuckIterations, int, 0, "Mark the current goal node on the path as unreachable if it is not updated after X iterations (0=disabled). If all upcoming nodes on the path are unreachabled, the plan fails.");
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RTABMAP_PARAM(RGBD, PlanLinearVelocity, float, 0.0, "Linear velocity (m/sec) used to compute path weights.");
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@@ -325,18 +329,24 @@ class RTABMAP_EXP Parameters
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RTABMAP_PARAM(RGBD, ProximityPathRawPosesUsed, bool, true, "When comparing to a local path, merge the scan using the odometry poses (with neighbor link optimizations) instead of the ones in the optimized local graph.");
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// Graph optimization
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RTABMAP_PARAM_COND(Optimizer, Strategy, int, RTABMAP_GTSAM, 2, 0, "Graph optimization strategy: 0=TORO, 1=g2o and 2=GTSAM.");
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#ifdef RTABMAP_GTSAM
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RTABMAP_PARAM(Optimizer, Strategy, int, 2, "Graph optimization strategy: 0=TORO, 1=g2o and 2=GTSAM.");
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#elif RTABMAP_G2O
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RTABMAP_PARAM(Optimizer, Strategy, int, 1, "Graph optimization strategy: 0=TORO, 1=g2o and 2=GTSAM.");
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#else
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RTABMAP_PARAM(Optimizer, Strategy, int, 0, "Graph optimization strategy: 0=TORO, 1=g2o and 2=GTSAM.");
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#endif
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RTABMAP_PARAM(Optimizer, Iterations, int, 100, "Optimization iterations.");
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RTABMAP_PARAM(Optimizer, Slam2D, bool, false, "If optimization is done only on x,y and theta (3DoF). Otherwise, it is done on full 6DoF poses.");
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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.");
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RTABMAP_PARAM(Optimizer, Epsilon, double, 0.0001, "Stop optimizing when the error improvement is less than this value.");
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RTABMAP_PARAM(Optimizer, Robust, bool, false, "Robust graph optimization using Vertigo (only work for g2o and GTSAM optimization strategies).");
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RTABMAP_PARAM(Optimizer, Robust, bool, false, "Robust graph optimization using Vertigo (only work for g2o and GTSAM optimization strategies). Not compatible with \"RGBD/OptimizeMaxError\" if enabled.");
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RTABMAP_PARAM(g2o, Solver, int, 0, "0=csparse 1=pcg 2=cholmod");
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RTABMAP_PARAM(g2o, Optimizer, int, 0, "0=Levenberg 1=GaussNewton");
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// Odometry
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RTABMAP_PARAM(Odom, Strategy, int, 0, "0=Local Map 1=Frame-to-Frame");
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RTABMAP_PARAM(Odom, Strategy, int, 0, "0=Frame-to-Map (F2M) 1=Frame-to-Frame (F2F)");
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RTABMAP_PARAM(Odom, ResetCountdown, int, 0, "Automatically reset odometry after X consecutive images on which odometry cannot be computed (value=0 disables auto-reset).");
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RTABMAP_PARAM(Odom, Holonomic, bool, true, "If the robot is holonomic (strafing commands can be issued). If not, y value will be estimated from x and yaw values (y=x*tan(yaw)).");
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RTABMAP_PARAM(Odom, FillInfoData, bool, true, "Fill info with data (inliers/outliers features).");
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@@ -376,7 +386,11 @@ class RTABMAP_EXP Parameters
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RTABMAP_PARAM(Vis, RefineIterations, int, 10, "[Vis/EstimationType = 0] Number of iterations used to refine the transformation found by RANSAC. 0 means that the transformation is not refined.");
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RTABMAP_PARAM(Vis, PnPReprojError, float, 2.0, "[Vis/EstimationType = 1] PnP reprojection error.");
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RTABMAP_PARAM(Vis, PnPFlags, int, 1, "[Vis/EstimationType = 1] PnP flags: 0=Iterative, 1=EPNP, 2=P3P");
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RTABMAP_PARAM_COND(Vis, PnPRefineIterations, int, RTABMAP_OPENCV3, 0, 1, "[Vis/EstimationType = 1] Refine iterations.");
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#ifdef RTABMAP_OPENCV3
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RTABMAP_PARAM(Vis, PnPRefineIterations, int, 0, "[Vis/EstimationType = 1] Refine iterations.");
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#else
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RTABMAP_PARAM(Vis, PnPRefineIterations, int, 1, "[Vis/EstimationType = 1] Refine iterations.");
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#endif
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RTABMAP_PARAM(Vis, EpipolarGeometryVar, float, 0.02, "[Vis/EstimationType = 2] Epipolar geometry maximum variance to accept the transformation.");
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RTABMAP_PARAM(Vis, MinInliers, int, 10, "Minimum feature correspondences to compute/accept the transformation.");
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RTABMAP_PARAM(Vis, Iterations, int, 100, "Maximum iterations to compute the transform.");
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