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Parameters renamed: "OdomLocalMap" group is now "OdomF2M" for Frame to Map odometry. Visual registration feature matching: using guess transform to limit the radius of correspondences "Vis/CorGuessWinSize=16"

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matlabbe
2016-02-22 16:13:14 -05:00
parent 0d68f74d80
commit ccc4b4a6c2
22 changed files with 844 additions and 638 deletions
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corelib/include/rtabmap/core/OdometryLocalMap.h → corelib/include/rtabmap/core/OdometryF2M.h
+11 -13
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@@ -25,39 +25,37 @@ ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef ODOMETRYLOCALMAP_H_
#define ODOMETRYLOCALMAP_H_
#ifndef ODOMETRYF2M_H_
#define ODOMETRYF2M_H_
#include <rtabmap/core/Odometry.h>
namespace rtabmap {
class Memory;
class Signature;
class RegistrationVis;
class RTABMAP_EXP OdometryLocalMap : public Odometry
class RTABMAP_EXP OdometryF2M : public Odometry
{
public:
OdometryLocalMap(const rtabmap::ParametersMap & parameters = rtabmap::ParametersMap());
virtual ~OdometryLocalMap();
OdometryF2M(const rtabmap::ParametersMap & parameters = rtabmap::ParametersMap());
virtual ~OdometryF2M();
virtual void reset(const Transform & initialPose = Transform::getIdentity());
const std::multimap<int, cv::Point3f> & getLocalMap() const {return localMap_;}
const Memory * getMemory() const {return memory_;}
const std::multimap<int, cv::Point3f> & getLocalMap() const;
private:
virtual Transform computeTransform(const SensorData & image, OdometryInfo * info = 0);
private:
//Parameters
int localHistoryMaxSize_;
std::string fixedLocalMapPath_;
int maximumMapSize_;
std::string fixedMapPath_;
Memory * memory_;
RegistrationVis * regVis_;
std::multimap<int, cv::Point3f> localMap_;
Signature * map_;
};
}
#endif /* ODOMETRYLOCALMAP_H_ */
#endif /* ODOMETRYF2M_H_ */
corelib/include/rtabmap/core/OdometryInfo.h
+1
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@@ -29,6 +29,7 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#define ODOMETRYINFO_H_
#include <map>
#include "rtabmap/core/Transform.h"
namespace rtabmap {
corelib/include/rtabmap/core/Parameters.h
+9 -8
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@@ -348,10 +348,11 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Odom, ParticleLambdaR, float, 100, "Lambda of rotational components (roll,pitch,yaw).");
RTABMAP_PARAM(Odom, KalmanProcessNoise, float, 0.001, "Process noise covariance value.");
RTABMAP_PARAM(Odom, KalmanMeasurementNoise, float, 0.01, "Process measurement covariance value.");
RTABMAP_PARAM(Odom, GuessMotion, bool, true, "Guess next transformation from the last motion computed.");
// Odometry Bag-of-words
RTABMAP_PARAM(OdomLocalMap, HistorySize, int, 1000, "Local history size: If > 0 (example 5000), the odometry will maintain a local map of X maximum words.");
RTABMAP_PARAM_STR(OdomLocalMap, FixedMapPath, "", "Path to a fixed map (RTAB-Map's database) to be used for odometry. Odometry will be constraint to this map. RGB-only images can be used if odometry PnP estimation is used.")
RTABMAP_PARAM(OdomF2M, MaxSize, int, 1000, "Local map size: If > 0 (example 5000), the odometry will maintain a local map of X maximum words.");
RTABMAP_PARAM_STR(OdomF2M, FixedMapPath, "", "Path to a fixed map (RTAB-Map's database) to be used for odometry. Odometry will be constraint to this map. RGB-only images can be used if odometry PnP estimation is used.")
// Odometry Mono
RTABMAP_PARAM(OdomMono, InitMinFlow, float, 100, "Minimum optical flow required for the initialization step.");
@@ -360,8 +361,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(OdomMono, MaxVariance, float, 0.01, "Maximum variance to add new points to local map.");
// Odometry Optical Flow
RTABMAP_PARAM(OdomF2F, KeyFrameThr, int, 0, "Create a new keyframe when the number of inliers drops under this threshold. Setting the value to 0 means that a keyframe is created for each processed frame.");
RTABMAP_PARAM(OdomF2F, GuessMotion, bool, true, "Guess next transformation from the last motion computed.");
RTABMAP_PARAM(OdomF2F, KeyFrameThr, int, 100, "Create a new keyframe when the number of inliers drops under this threshold. Setting the value to 0 means that a keyframe is created for each processed frame.");
// Common registration parameters
RTABMAP_PARAM(Reg, VarianceFromInliersCount, bool, false, "Set variance as the inverse of the number of inliers. Otherwise, the variance is computed as the average 3D position error of the inliers.");
@@ -373,7 +373,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Vis, ForwardEstOnly, bool, true, "Forward estimation only (A->B). If false, a transformation is also computed in backward direction (B->A), then the two resulting transforms are merged (middle interpolation between the transforms).");
RTABMAP_PARAM(Vis, InlierDistance, float, 0.1, "[Vis/EstimationType = 0] Maximum distance for feature correspondences. Used by 3D->3D estimation approach.");
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.");
RTABMAP_PARAM(Vis, PnPReprojError, float, 2.0, "[Vis/EstimationType = 1] PnP reprojection error.");
RTABMAP_PARAM(Vis, PnPReprojError, float, 2.0, "[Vis/EstimationType = 1] PnP reprojection error.");
RTABMAP_PARAM(Vis, PnPFlags, int, 1, "[Vis/EstimationType = 1] PnP flags: 0=Iterative, 1=EPNP, 2=P3P");
RTABMAP_PARAM(Vis, PnPRefineIterations, int, 1, "[Vis/EstimationType = 1] Refine iterations.");
RTABMAP_PARAM(Vis, EpipolarGeometryVar, float, 0.02, "[Vis/EstimationType = 2] Epipolar geometry maximum variance to accept the transformation.");
@@ -386,15 +386,16 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM_STR(Vis, RoiRatios, "0.0 0.0 0.0 0.0", "Region of interest ratios [left, right, top, bottom].");
RTABMAP_PARAM(Vis, SubPixWinSize, int, 3, "See cv::cornerSubPix().");
RTABMAP_PARAM(Vis, SubPixIterations, int, 0, "See cv::cornerSubPix(). 0 disables sub pixel refining.");
RTABMAP_PARAM(Vis, SubPixEps, float, 0.02, "See cv::cornerSubPix().");
RTABMAP_PARAM(Vis, SubPixEps, float, 0.02, "See cv::cornerSubPix().");
RTABMAP_PARAM(Vis, CorType, int, 0, "Correspondences computation approach: 0=Features Matching, 1=Optical Flow");
RTABMAP_PARAM(Vis, CorNNType, int, 3, "[Vis/CorrespondenceType=0] kNNFlannNaive=0, kNNFlannKdTree=1, kNNFlannLSH=2, kNNBruteForce=3, kNNBruteForceGPU=4. Used for features matching approach.");
RTABMAP_PARAM(Vis, CorNNDR, float, 0.8, "[Vis/CorrespondenceType=0] NNDR: nearest neighbor distance ratio. Used for features matching approach.");
RTABMAP_PARAM(Vis, CorGuessWinSize, int, 16, "[Vis/CorrespondenceType=0] Matching window size (pixels) around projected points when a guess transform is provided to find correspondences.");
RTABMAP_PARAM(Vis, CorFlowWinSize, int, 16, "[Vis/CorrespondenceType=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.");
RTABMAP_PARAM(Vis, CorFlowIterations, int, 30, "[Vis/CorrespondenceType=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.");
RTABMAP_PARAM(Vis, CorFlowEps, float, 0.01, "[Vis/CorrespondenceType=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.");
RTABMAP_PARAM(Vis, CorFlowEps, float, 0.01, "[Vis/CorrespondenceType=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.");
RTABMAP_PARAM(Vis, CorFlowMaxLevel, int, 3, "[Vis/CorrespondenceType=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.");
RTABMAP_PARAM(Vis, UseDepthAsMask, bool, true, "Use depth image as mask for features detection.");
RTABMAP_PARAM(Vis, UseDepthAsMask, bool, true, "Use depth image as mask for features detection.");
// ICP registration parameters
RTABMAP_PARAM(Icp, MaxTranslation, float, 0.2, "Maximum ICP translation correction accepted (m).");
corelib/include/rtabmap/core/RegistrationVis.h
+6
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@@ -35,6 +35,8 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
namespace rtabmap {
class Feature2D;
// Visual registration
class RTABMAP_EXP RegistrationVis : public Registration
{
@@ -49,6 +51,8 @@ public:
int getIterations() const {return _iterations;}
int getMinInliers() const {return _minInliers;}
Feature2D * createFeatureDetector() const; // for convenience
protected:
virtual Transform computeTransformationImpl(
Signature & from,
@@ -75,6 +79,8 @@ private:
int _flowIterations;
float _flowEps;
int _flowMaxLevel;
float _nndr;
int _guessWinSize;
bool _useDepthAsMask;
ParametersMap _featureParameters;
corelib/include/rtabmap/core/VWDictionary.h
+2 -1
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@@ -69,7 +69,8 @@ public:
int signatureId);
virtual void addWord(VisualWord * vw);
virtual std::vector<int> findNN(const std::list<VisualWord *> & vws) const;
std::vector<int> findNN(const std::list<VisualWord *> & vws) const;
std::vector<int> findNN(const cv::Mat & descriptors) const;
void addWordRef(int wordId, int signatureId);
void removeAllWordRef(int wordId, int signatureId);