diff --git a/preview/pr-1748/api/latest/BayesFilter_8h_source.html b/preview/pr-1748/api/latest/BayesFilter_8h_source.html
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--- a/preview/pr-1748/api/latest/BayesFilter_8h_source.html
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@@ -139,108 +139,99 @@ $(document).ready(function(){initNavTree('BayesFilter_8h_source.html',''); initR
31 #include "rtabmap/core/rtabmap_core_export.h" 33 #include <opencv2/core/core.hpp> 34 #include <Eigen/SparseCore> 38 #include "rtabmap/utilite/UEventsHandler.h" 39 #include "rtabmap/core/Parameters.h"
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171 bool posteriorHasSameIds(
const std::vector<int> & ids)
const ;
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176 cv::Mat updatePrediction(
const cv::Mat & oldPrediction,
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178 const std::vector<int> & oldIds,
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179 const std::vector<int> & newIds);
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184 void updatePosterior(
const Memory * memory,
const std::vector<int> & likelihoodIds);
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194 void fillVirtualPlaceColumn(
float * column,
size_t stride,
int size)
const ;
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205 void normalize(
float * column,
size_t stride,
int size,
unsigned int index,
float addedProbabilitiesSum,
bool virtualPlaceUsed)
const ;
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221 bool generateSparsePrediction(
const Memory * memory,
const std::vector<int> & ids);
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231 void updateSparsePredictionFromDense();
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236 void appendSparseColumn(std::vector<float> & column,
int index,
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237 std::vector<Eigen::Triplet<float> > & triplets)
const ;
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242 void clearSparsePrediction();
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247 unsigned long getSparsePredictionMemoryUsed()
const ;
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258 void multiplySparsePrediction(
const cv::Mat & posterior, cv::Mat & prior)
const ;
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261 std::map<int, float> _posterior;
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263 float _virtualPlacePrior;
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264 std::vector<double> _predictionLC;
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265 bool _fullPredictionUpdate;
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266 float _totalPredictionLCValues;
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267 float _predictionEpsilon;
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268 bool _sparsePrediction;
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269 bool _predictionChanged;
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270 bool _sparsePredictionRejected;
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271 Eigen::SparseMatrix<float, Eigen::RowMajor> _sparsePredictionMatrix;
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272 std::map<int, std::map<int, int> > _neighborsIndex;
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39 #include "rtabmap/utilite/UEventsHandler.h"
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40 #include "rtabmap/core/Parameters.h"
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50 class SparsePrediction;
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188 bool posteriorHasSameIds(
const std::vector<int> & ids)
const ;
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195 void updatePosterior(
const Memory * memory,
const std::map<int, float> & likelihood);
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198 std::vector<int> _posteriorIds;
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199 std::vector<float> _posteriorValues;
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200 std::vector<int> _likelihoodIds;
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201 std::vector<float> _likelihoodValues;
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202 std::vector<float> _priorValues;
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204 bayes::PredictionModel * _model;
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205 bayes::DensePrediction * _dense;
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206 bayes::SparsePrediction * _sparse;
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207 std::map<int, std::map<int, int> > _neighborsIndex;
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209 bool _fullPredictionUpdate;
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210 bool _sparsePrediction;
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211 bool _predictionChanged;
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212 bool _sparsePredictionRejected;
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Recursive Bayesian filter for loop-closure hypothesis estimation in RTAB-Map.
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Recursive Bayesian filter for loop-closure hypothesis estimation in RTAB-Map.
std::string getPredictionLCStr() const
Returns the loop-closure prediction model as a space-separated string.
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float getVirtualPlacePrior() const
Returns the virtual place prior threshold.
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float getVirtualPlacePrior() const
Returns the virtual place prior threshold.
BayesFilter(const ParametersMap ¶meters=ParametersMap())
Constructs a Bayes filter with default or custom parameters.
void setPredictionLC(const std::string &prediction)
Sets the loop-closure prediction model from a space-separated string.
cv::Mat generatePrediction(const Memory *memory, const std::vector< int > &ids)
Builds or updates the prediction (transition) matrix for the given signature ids.
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const std::vector< int > & getPosteriorIds() const
The locations the posterior is over, ascending by id.
unsigned long getMemoryUsed() const
Estimates memory usage of this object and its internal containers.
virtual void parseParameters(const ParametersMap ¶meters)
Updates internal settings from the parameter map.
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const std::map< int, float > & computePosterior(const Memory *memory, const std::map< int, float > &likelihood)
Runs one Bayes filter iteration (prediction + update).
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bool computePosterior(const Memory *memory, const std::map< int, float > &likelihood)
Runs one Bayes filter iteration (prediction + update).
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const std::vector< float > & getPosteriorValues() const
The probability of each location of getPosteriorIds(), in the same order.
const std::vector< double > & getPredictionLC() const
Returns the loop-closure prediction model as a vector of values.
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const std::map< int, float > & getPosterior() const
Returns the current posterior probability map.
void reset()
Clears posterior, prediction matrix and cached neighbor indices.
Three-tiered memory management (STM, WM, LTM) for RTAB-Map.
Represents a node in RTAB-Map's pose graph.
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std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Container class for all sensor data captured at a specific time.
A class representing a calibrated stereo camera system.
Container class for all sensor data captured at a specific time.
A class representing a calibrated stereo camera system.
Container class for all sensor data captured at a specific time.
A class representing a calibrated stereo camera system.
virtual bool odomProvided() const
Checks if the sensor provides odometry poses.
Metadata structure for sensor data capture and processing.
Container class for all sensor data captured at a specific time.
Metadata structure for sensor data capture and processing.
Container class for all sensor data captured at a specific time.
virtual ~CameraModel()
Destructor.
double cx() const
Returns principal point x.
RTABMAP_CORE_EXPORT std::ostream & operator<<(std::ostream &os, const CameraModel &model)
Stream operator for printing a camera model to an output stream.
Container class for all sensor data captured at a specific time.
A class representing a calibrated stereo camera system.
Container class for all sensor data captured at a specific time.
A class representing a calibrated stereo camera system.
Metadata structure for sensor data capture and processing.
Container class for all sensor data captured at a specific time.
Metadata structure for sensor data capture and processing.
Container class for all sensor data captured at a specific time.
Metadata structure for sensor data capture and processing.
Container class for all sensor data captured at a specific time.
virtual bool init(const std::string &calibrationFolder=".", const std::string &cameraName="")
Initializes the sensor.
Container class for all sensor data captured at a specific time.
A class representing a calibrated stereo camera system.
Metadata structure for sensor data capture and processing.
Container class for all sensor data captured at a specific time.
Metadata structure for sensor data capture and processing.
Container class for all sensor data captured at a specific time.
Container class for all sensor data captured at a specific time.
A class representing a calibrated stereo camera system.
Metadata structure for sensor data capture and processing.
Container class for all sensor data captured at a specific time.
virtual std::string getSerial() const
Returns the sensor's serial number or unique identifier.
virtual bool init(const std::string &calibrationFolder=".", const std::string &cameraName="")
Initializes the sensor.
Container class for all sensor data captured at a specific time.
A class representing a calibrated stereo camera system.
virtual bool init(const std::string &calibrationFolder=".", const std::string &cameraName="")
Initializes the sensor.
Container class for all sensor data captured at a specific time.
A class representing a calibrated stereo camera system.
Container class for all sensor data captured at a specific time.
A class representing a calibrated stereo camera system.
virtual std::string getSerial() const
Returns the sensor's serial number or unique identifier.
Abstract base class for sensor data capture (cameras, lidars, etc.)
Container class for all sensor data captured at a specific time.
virtual void assemble(const std::list< std::pair< int, Transform > > &newPoses)
Subclass hook: merge newPoses into the global map; call addAssembledNode().
Abstract base for assembling per-node LocalGrid data into a global map.
Cache of LocalGrid entries keyed by map node id.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
CompressionThread(const cv::Mat &mat, const std::string &format="")
Constructs a thread in compress mode.
CompressionThread(const cv::Mat &bytes, bool isImage)
Constructs a thread in uncompress mode.
cv::Mat & getUncompressedData()
cv::Mat RTABMAP_CORE_EXPORT uncompressImage(const cv::Mat &bytes)
Decodes compressed image bytes to a @cv::Mat.
cv::Mat RTABMAP_CORE_EXPORT compressString(const std::string &str)
Compresses a null-terminated string using compressData2().
std::vector< unsigned char > RTABMAP_CORE_EXPORT compressImage(const cv::Mat &image, const std::string &format=".png")
Encodes image to a byte buffer (OpenCV imencode or RVL for depth).
Collects and manages runtime statistics for RTAB-Map.
Manages a dictionary of visual words for visual place recognition and loop closure detection.
std::map< EnvSensor::Type, EnvSensor > EnvSensors
Map of environmental readings keyed by EnvSensor::Type (at most one per type).
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Manages a dictionary of visual words for visual place recognition and loop closure detection.
Represents a visual word (feature descriptor) used in the bag-of-words (BoW) model.
std::map< EnvSensor::Type, EnvSensor > EnvSensors
Map of environmental readings keyed by EnvSensor::Type (at most one per type).
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Metadata structure for sensor data capture and processing.
Container class for all sensor data captured at a specific time.
EnvSensor()
Default constructor: kUndefined type, zero value and stamp.
EnvSensor(const Type &type, const double &value, const double &stamp=0)
Constructs a reading with the given type, value, and optional stamp.
const Type & type() const
std::map< EnvSensor::Type, EnvSensor > EnvSensors
Map of environmental readings keyed by EnvSensor::Type (at most one per type).
static int findPairs(const std::map< int, T > &wordsA, const std::map< int, T > &wordsB, std::list< std::pair< int, std::pair< T, T > > > &pairs, bool ignoreNegativeIds=true)
static int findPairsAll(const std::multimap< int, T > &wordsA, const std::multimap< int, T > &wordsB, std::list< std::pair< int, std::pair< T, T > > > &pairs, bool ignoreNegativeIds=true)
Represents a node in RTAB-Map's pose graph.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
virtual bool isGpuAvailable() const override
Returns true when a GPU/CUDA code path could be used by this detector on this host: i....
SuperPoint via LibTorch (RTAB-Map must be built with libtorch support).
virtual bool isGpuAvailable() const override
Returns true when a GPU/CUDA code path could be used by this detector on this host: i....
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
void buildIndex(flann_algorithm_t algorithm, const cv::Mat &features, bool useDistanceL1=false, float rebalancingFactor=2.0f)
Build the index over the given features, releasing any previous one.
void knnSearch(const cv::Mat &query, cv::Mat &indices, cv::Mat &dists, int knn, int checks=32, float eps=0.0, bool sorted=true) const
Search the k nearest neighbors of each query.
const double & longitude() const
const double & error() const
WGS84 geodetic latitude, longitude and altitude with coordinate conversions.
cv::Point3d toGeocentric_WGS84() const
cv::Point3d toENU_WGS84(const GeodeticCoords &origin) const
void setAltitude(const double &value)
Sets altitude in meters.
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
static float logodds(double probability)
Converts probability in (0, 1) to log-odds.
Cache of LocalGrid entries keyed by map node id.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
RTABMAP_DEPRECATED std::map< int, Transform > RTABMAP_CORE_EXPORT getPosesInRadius(int nodeId, const std::map< int, Transform > &nodes, float radius, float angle=0.0f)
bool RTABMAP_CORE_EXPORT exportPoses(const std::string &filePath, int format, const std::map< int, Transform > &poses, const std::multimap< int, Link > &constraints=std::multimap< int, Link >(), const std::map< int, double > &stamps=std::map< int, double >(), const ParametersMap ¶meters=ParametersMap())
Writes poses (and optional constraints) to disk.
RTABMAP_DEPRECATED std::map< int, float > RTABMAP_CORE_EXPORT getNodesInRadius(int nodeId, const std::map< int, Transform > &nodes, float radius)
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Largest pose-graph constraint violations after optimization.
float angular
Absolute angular error (rad) of the worst link.
virtual void clear()
Clears assembled nodes and grid bounds; does not clear LocalGridCache.
virtual void assemble(const std::list< std::pair< int, Transform > > &newPoses)
Subclass hook: merge newPoses into the global map; call addAssembledNode().
Cache of LocalGrid entries keyed by map node id.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
void update(double gx, double gy, double gz, double ax, double ay, double az, double stamp)
Integrates one IMU sample and updates the internal orientation estimate.
virtual IMUFilter::Type type() const =0
virtual void getOrientation(double &qx, double &qy, double &qz, double &qw) const =0
Current orientation estimate.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
void enableIMUFiltering(int filteringStrategy=1, const ParametersMap ¶meters=ParametersMap(), bool baseFrameConversion=false)
Enables orientation fusion on replayed samples.
bool init(const std::string &path)
Opens and validates an IMU CSV file.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
bool empty() const
True when localTransform() is null (placeholder / unset sample).
const cv::Vec3d & angularVelocity() const
int RTABMAP_CORE_EXPORT saveLASFile(const std::string &filePath, const pcl::PointCloud< pcl::PointXYZ > &cloud, const std::vector< int > &cameraIds=std::vector< int >())
Writes a PCL point cloud to a LAS/LAZ file (requires RTAB-Map built with libLAS).
const float & size() const
std::map< int, Landmark > Landmarks
Map of landmark id → Landmark (typically positive keys).
void clear()
Clear the scan data.
LaserScan & operator+=(const LaserScan &)
Concatenate scan's data (localTransform is ignored).
Metadata structure for sensor data capture and processing.
Container class for all sensor data captured at a specific time.
Lidar(float lidarRate=0, const Transform &localTransform=Transform::getIdentity())
Abstract base class for sensor data capture (cameras, lidars, etc.)
cv::Mat uncompressUserDataConst() const
void uncompressUserData()
Decompresses user data into userDataRaw() if compressed data is stored.
bool isMapFrameProjection() const
Represents a node in RTAB-Map's pose graph.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
cv::Point3f viewPoint
View point used to build the grid.
cv::Mat obstacleCells
Obstacle cells (same layout as groundCells).
pcl::PointCloud< pcl::PointXYZ >::Ptr RTABMAP_CORE_EXPORT voxelize(const pcl::PointCloud< pcl::PointXYZ >::Ptr &cloud, const pcl::IndicesPtr &indices, float voxelSize)
Performs voxel grid downsampling on a point cloud of type pcl::PointXYZ on provided indices.
pcl::IndicesPtr RTABMAP_CORE_EXPORT concatenate(const std::vector< pcl::IndicesPtr > &indices)
Concatenates multiple sets of indices into a single index vector.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Collects and manages runtime statistics for RTAB-Map.
Manages a dictionary of visual words for visual place recognition and loop closure detection.
std::map< EnvSensor::Type, EnvSensor > EnvSensors
Map of environmental readings keyed by EnvSensor::Type (at most one per type).
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Container class for all sensor data captured at a specific time.
Represents a node in RTAB-Map's pose graph.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Container class for all sensor data captured at a specific time.
Represents a node in RTAB-Map's pose graph.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
float localBundleTime
Time spent in the local bundle adjustment (s).
Statistics and diagnostics returned by Registration.
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Abstract base class for visual, lidar and visual-inertial odometry backends.
Event class for sensor data communication in RTAB-Map's event system.
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Type
Odometry backend selected by Parameters::kOdomStrategy().
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Odometry(const rtabmap::ParametersMap ¶meters)
Constructs the base odometry state from RTAB-Map parameters.
Container class for all sensor data captured at a specific time.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
virtual Type type() const
Returns the concrete back-end identifier (one of Type).
Abstract base for pose-graph and bundle-adjustment optimizers.
Type
Graph-optimizer back-end identifier.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
virtual std::map< int, Transform > optimizeBA(int rootId, const std::map< int, Transform > &poses, const std::multimap< int, Link > &links, const std::map< int, std::vector< CameraModel > > &models, std::map< int, cv::Point3f > &points3DMap, const std::map< int, std::map< int, FeatureBA > > &wordReferences, BAOutliers *outliers=0)
Bundle adjustment: jointly refine poses and 3D points (back-end-level entry point).
Abstract base for pose-graph and bundle-adjustment optimizers.
Type
Graph-optimizer back-end identifier.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
virtual std::map< int, Transform > optimizeBA(int rootId, const std::map< int, Transform > &poses, const std::multimap< int, Link > &links, const std::map< int, std::vector< CameraModel > > &models, std::map< int, cv::Point3f > &points3DMap, const std::map< int, std::map< int, FeatureBA > > &wordReferences, BAOutliers *outliers=0)
Bundle adjustment: jointly refine poses and 3D points (back-end-level entry point).
Abstract base for pose-graph and bundle-adjustment optimizers.
Type
Graph-optimizer back-end identifier.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
virtual void parseParameters(const ParametersMap ¶meters)
Reads shared knobs from parameters and applies them to this instance.
Abstract base for pose-graph and bundle-adjustment optimizers.
Type
Graph-optimizer back-end identifier.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
virtual Type type() const
Returns the concrete back-end identifier (one of Type).
Abstract base for pose-graph and bundle-adjustment optimizers.
Type
Graph-optimizer back-end identifier.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
virtual std::map< int, Transform > optimize(int rootId, const std::map< int, Transform > &poses, const std::multimap< int, Link > &constraints, cv::Mat &outputCovariance, std::list< std::map< int, Transform > > *intermediateGraphes=0, double *finalError=0, int *iterationsDone=0)
Pose-graph optimization with marginal covariance of rootId.
static bool isAvailable(Optimizer::Type type)
Returns whether type was compiled in (its third-party dependency was found).
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
virtual std::string getClassName() const
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Semi-Global Block Matching algorithm for dense stereo matching.
Sparse stereo matching using block matching.
SuperPoint (rpautrat) via Torch + Python (RTAB-Map must be built with libtorch and Python support).
std::pair< std::string, std::string > ParametersPair
A single parameter key/value pair, the entry type of ParametersMap.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
T uSum(const std::list< T > &list)
bool uIsFinite(const T &value)
ULogger class and convenient macros.
bool RTABMAP_CORE_EXPORT databaseRecovery(const std::string &corruptedDatabase, bool keepCorruptedDatabase=true, std::string *errorMsg=0, ProgressState *progressState=0)
Abstract base for registering two observations (visual, ICP, or both).
Represents a node in RTAB-Map's pose graph.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
std::vector< int > matchesPerCam
RegistrationInfo copyWithoutData() const
Copies scalar metrics and covariance; omits correspondence ID vectors.
Abstract base for registering two observations (visual, ICP, or both).
Represents a node in RTAB-Map's pose graph.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Container class for all sensor data captured at a specific time.
Represents a node in RTAB-Map's pose graph.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
virtual std::string getClassName() const
Collects and manages runtime statistics for RTAB-Map.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
void clearBufferedData()
Drops the buffered frames, the pending user data and the odometry state.
Top-level RTAB-Map SLAM pipeline (mapping, localization and loop closure).
Recursive Bayesian filter for loop-closure hypothesis estimation in RTAB-Map.
Recursive Bayesian filter for loop-closure hypothesis estimation in RTAB-Map.
Represents 2D or 3D laser scan data with support for multiple point data formats.
Directed constraint between two nodes in RTAB-Map's pose graph.
Represents a node in RTAB-Map's pose graph.
Collects and manages runtime statistics for RTAB-Map.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Largest pose-graph constraint violations after optimization.
float timeDisparity
Time to compute stereo disparity (seconds)
float timeUndistortDepth
Time to undistort depth image (seconds)
RTABMAP_DEPRECATED typedef SensorCaptureInfo CameraInfo
Backward compatibility typedef.
Container class for all sensor data captured at a specific time.
Abstract base class for dense stereo matching algorithms.
RTABMAP_DEPRECATED typedef SensorCaptureThread CameraThread
Backward compatibility typedef.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
void resetTimer()
Resets the frame rate timer.
Container class for all sensor data captured at a specific time.
const std::vector< cv::KeyPoint > & keypoints() const
Returns the 2D keypoints.
A class representing a calibrated stereo camera system.
std::map< int, Landmark > Landmarks
Map of landmark id → Landmark (typically positive keys).
std::map< EnvSensor::Type, EnvSensor > EnvSensors
Map of environmental readings keyed by EnvSensor::Type (at most one per type).
SensorEvent(const cv::Mat &image, int seq=0, double stamp=0.0, const std::string &cameraName=std::string())
Constructor from a single image.
const std::string & cameraName() const
Returns the camera name.
SensorEvent()
Constructor for end-of-stream event.
RTABMAP_DEPRECATED typedef SensorEvent CameraEvent
Backward compatibility typedef.
void addLinks(const std::map< int, Link > &links)
Adds multiple links from a map.
cv::Mat getPoseCovariance() const
Gets the pose covariance matrix.
virtual ~Statistics()
Virtual destructor.
const std::map< int, std::string > & labels() const
Returns node labels.
virtual cv::Mat computeDisparity(const cv::Mat &leftImage, const cv::Mat &rightImage) const
Compute disparity map from stereo image pair.
virtual void parseParameters(const ParametersMap ¶meters)
Parse parameters from a parameters map.
Abstract base class for dense stereo matching algorithms.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
virtual ~StereoCameraModel()
Destructor.
unsigned int deserialize(const unsigned char *data, unsigned int dataSize)
Deserializes stereo camera model data from a raw byte array.
RTABMAP_CORE_EXPORT std::ostream & operator<<(std::ostream &os, const CameraModel &model)
Stream operator for printing a camera model to an output stream.
virtual cv::Mat computeDisparity(const cv::Mat &leftImage, const cv::Mat &rightImage) const =0
Compute disparity map from stereo image pair.
static StereoDense * create(const ParametersMap ¶meters)
Factory method to create a StereoDense instance from parameters.
static StereoDense * create(StereoDense::Type type, const ParametersMap ¶meters=ParametersMap())
Factory method to create a StereoDense instance of a specific type.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
virtual void parseParameters(const ParametersMap ¶meters)
Parse parameters from a parameters map.
StereoSGBM(const ParametersMap ¶meters=ParametersMap())
Constructor with parameters map.
virtual cv::Mat computeDisparity(const cv::Mat &leftImage, const cv::Mat &rightImage) const
Compute disparity map from stereo image pair.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
virtual ~Stereo()
Virtual destructor.
bool winSSD() const
Check if SSD (Sum of Squared Differences) is used.
virtual std::vector< cv::Point2f > computeCorrespondences(const cv::Mat &leftImage, const cv::Mat &rightImage, const std::vector< cv::Point2f > &leftCorners, std::vector< unsigned char > &status) const
Compute stereo correspondences using block matching.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
RTABMAP_CORE_EXPORT std::ostream & operator<<(std::ostream &os, const CameraModel &model)
Stream operator for printing a camera model to an output stream.
virtual std::string getClassName() const
bool setNNStrategy(NNStrategy strategy)
Set the nearest neighbor search strategy.
virtual ~VWDictionary()
Destructor.
Represents a visual word (feature descriptor) used in the bag-of-words (BoW) model.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
unsigned long getMemoryUsed() const
Estimates the memory used by this visual word in bytes.
const std::map< int, int > & getReferences() const
Returns the references of this word.
This is the complete list of members for rtabmap::BayesFilter , including all inherited members.
diff --git a/preview/pr-1748/api/latest/classrtabmap_1_1BayesFilter.html b/preview/pr-1748/api/latest/classrtabmap_1_1BayesFilter.html
index 0c26cbb2..66788a56 100644
--- a/preview/pr-1748/api/latest/classrtabmap_1_1BayesFilter.html
+++ b/preview/pr-1748/api/latest/classrtabmap_1_1BayesFilter.html
@@ -118,9 +118,9 @@ Public Member Functions
virtual void parseParameters (const ParametersMap ¶meters) Updates internal settings from the parameter map. const std::map< int, float > & computePosterior (const Memory *memory, const std::map< int, float > &likelihood) Runs one Bayes filter iteration (prediction + update). bool computePosterior (const Memory *memory, const std::map< int, float > &likelihood) Runs one Bayes filter iteration (prediction + update). reset () Clears posterior, prediction matrix and cached neighbor indices. reset ()void setPredictionLC (const std::string &prediction) Sets the loop-closure prediction model from a space-separated string. const std::map< int, float > & getPosterior () const Returns the current posterior probability map. const std::vector< int > & getPosteriorIds () const The locations the posterior is over, ascending by id. const std::vector< float > & getPosteriorValues () const The probability of each location of getPosteriorIds() , in the same order. float getVirtualPlacePrior () const Returns the virtual place prior threshold. reset ()Rtabmap
-Definition at line 74 of file BayesFilter.h .
+Definition at line 81 of file BayesFilter.h .
◆ reset ()◆ ◆
- const std::map< int, float > & rtabmap::BayesFilter::computePosterior
+ bool rtabmap::BayesFilter::computePosterior
(
const Memory *
memory , reset () Runs one Bayes filter iteration (prediction + update).
Given a likelihood map over signature ids, computes and stores the normalized posterior. The prediction matrix is generated or updated from Memory using the ids present in likelihood.
+Read the result with getPosteriorIds() and getPosteriorValues() .
Parameters
memory Working memory instance (must not be null). reset ()Returns Reference to the internal posterior map (id → probability). On error (null memory, empty likelihood, or invalid prediction model), returns the unchanged posterior. Returns False on error (null memory, empty likelihood, or invalid prediction model), the posterior being left unchanged. reset ()◆ ◆
@@ -309,7 +313,7 @@ void
reset ()
- const std::map< int, float > & rtabmap::BayesFilter::getPosterior
+ const std::vector< int > & rtabmap::BayesFilter::getPosteriorIds
(
)
const
@@ -322,10 +326,39 @@ void reset ()
-
Returns the current posterior probability map.
-
Returns Map of signature id to normalized posterior probability. This is the probability to be at the given location.
+
The locations the posterior is over, ascending by id.
+
The virtual place (Memory::kIdVirtual ) is the first of them when it is one.
-
Definition at line 128 of file BayesFilter.h .
+
Definition at line 138 of file BayesFilter.h .
+
+
◆
+
+
+
+
+
+
+ const std::vector< float > & rtabmap::BayesFilter::getPosteriorValues
+ (
+ )
+ const
+
+
+
+
+inline
+
+
+
reset ()
-
-
-
float rtabmap::BayesFilter::getVirtualPlacePrior
@@ -345,18 +375,11 @@ void reset () const
-
-
-inline
-
-
Returns the virtual place prior threshold.
Returns Value in [0, 1] used when building the virtual place row of the prediction matrix.
-
Definition at line 134 of file BayesFilter.h .
-
reset ()Returns Square CV_32FC1 matrix of size ids.size() × ids.size(). Returns Square CV_32FC1 matrix of size ids.size() × ids.size(), or an empty matrix when Parameters::kBayesSparsePrediction() is enabled and the prediction is being kept in its sparse form, in which case no matrix exists to return. computeIcpTransformMulti() : rtabmap::Memory
computeLikelihood() : rtabmap::Memory
computePath() : rtabmap::Rtabmap
-computePosterior() : rtabmap::BayesFilter
+computePosterior() : rtabmap::BayesFilter
computeRoi() : rtabmap::Feature2D
computeTransform() : rtabmap::Memory
computeTransformation() : rtabmap::Registration
diff --git a/preview/pr-1748/api/latest/functions_func_c.html b/preview/pr-1748/api/latest/functions_func_c.html
index 638b1574..e9d53f93 100644
--- a/preview/pr-1748/api/latest/functions_func_c.html
+++ b/preview/pr-1748/api/latest/functions_func_c.html
@@ -136,7 +136,7 @@ $(document).ready(function(){initNavTree('functions_func_c.html',''); initResiza
computeIcpTransformMulti() : rtabmap::Memory
computeLikelihood() : rtabmap::Memory
computePath() : rtabmap::Rtabmap
-computePosterior() : rtabmap::BayesFilter
+computePosterior() : rtabmap::BayesFilter
computeRoi() : rtabmap::Feature2D
computeTransform() : rtabmap::Memory
computeTransformation() : rtabmap::Registration
diff --git a/preview/pr-1748/api/latest/functions_func_g.html b/preview/pr-1748/api/latest/functions_func_g.html
index d0674997..da2263f8 100644
--- a/preview/pr-1748/api/latest/functions_func_g.html
+++ b/preview/pr-1748/api/latest/functions_func_g.html
@@ -146,7 +146,7 @@ $(document).ready(function(){initNavTree('functions_func_g.html',''); initResiza
getGoalReachedRadius() : rtabmap::Rtabmap
getGPS() : rtabmap::Memory
getGraph() : rtabmap::Rtabmap
-getGridMax() : rtabmap::GlobalMap
+getGridMax() : rtabmap::GlobalMap
getGridMin() : rtabmap::GlobalMap
getGroundTruthPose() : rtabmap::Memory , rtabmap::Signature
getGroundTruths() : rtabmap::Memory
@@ -209,7 +209,7 @@ $(document).ready(function(){initNavTree('functions_func_g.html',''); initResiza
getNodeCalibration() : rtabmap::Memory
getNodeData() : rtabmap::Memory
getNodeInfo() : rtabmap::Memory
-getNodesInRadius() : rtabmap::Rtabmap
+getNodesInRadius() : rtabmap::Rtabmap
getNodesObservingLandmark() : rtabmap::Memory
getNodeWordsAndGlobalDescriptors() : rtabmap::Memory
getNorm() : rtabmap::Transform
@@ -230,7 +230,8 @@ $(document).ready(function(){initNavTree('functions_func_g.html',''); initResiza
getPathTransformToGoal() : rtabmap::Rtabmap
getPose() : rtabmap::CameraRealSense2 , rtabmap::CameraSeerSense , rtabmap::CameraStereoZed , rtabmap::DBReader , rtabmap::Odometry , rtabmap::OdometryResetEvent , rtabmap::Rtabmap , rtabmap::SensorCapture , rtabmap::Signature
getPoseCovariance() : rtabmap::Signature
-getPosterior() : rtabmap::BayesFilter
+getPosteriorIds() : rtabmap::BayesFilter
+getPosteriorValues() : rtabmap::BayesFilter
getPredictionLC() : rtabmap::BayesFilter
getPredictionLCStr() : rtabmap::BayesFilter
getReferences() : rtabmap::VisualWord
diff --git a/preview/pr-1748/api/latest/functions_func_t.html b/preview/pr-1748/api/latest/functions_func_t.html
index 68256bcd..8dc83313 100644
--- a/preview/pr-1748/api/latest/functions_func_t.html
+++ b/preview/pr-1748/api/latest/functions_func_t.html
@@ -129,7 +129,7 @@ $(document).ready(function(){initNavTree('functions_func_t.html',''); initResiza
toUShort() : UVariant
toUShortArray() : UVariant
transform() : rtabmap::Link
-Transform() : rtabmap::Transform
+Transform() : rtabmap::Transform
translation() : rtabmap::Transform
translationMatrix() : rtabmap::Transform
transVariance() : rtabmap::Link
diff --git a/preview/pr-1748/api/latest/functions_g.html b/preview/pr-1748/api/latest/functions_g.html
index cf3572bc..b6f4d556 100644
--- a/preview/pr-1748/api/latest/functions_g.html
+++ b/preview/pr-1748/api/latest/functions_g.html
@@ -230,7 +230,8 @@ $(document).ready(function(){initNavTree('functions_g.html',''); initResizable()
getPathTransformToGoal() : rtabmap::Rtabmap
getPose() : rtabmap::CameraRealSense2 , rtabmap::CameraSeerSense , rtabmap::CameraStereoZed , rtabmap::DBReader , rtabmap::Odometry , rtabmap::OdometryResetEvent , rtabmap::Rtabmap , rtabmap::SensorCapture , rtabmap::Signature
getPoseCovariance() : rtabmap::Signature
-getPosterior() : rtabmap::BayesFilter
+getPosteriorIds() : rtabmap::BayesFilter
+getPosteriorValues() : rtabmap::BayesFilter
getPredictionLC() : rtabmap::BayesFilter
getPredictionLCStr() : rtabmap::BayesFilter
getReferences() : rtabmap::VisualWord
diff --git a/preview/pr-1748/api/latest/functions_t.html b/preview/pr-1748/api/latest/functions_t.html
index 6e7ea70c..a0cc050a 100644
--- a/preview/pr-1748/api/latest/functions_t.html
+++ b/preview/pr-1748/api/latest/functions_t.html
@@ -143,7 +143,7 @@ $(document).ready(function(){initNavTree('functions_t.html',''); initResizable()
toUShort() : UVariant
toUShortArray() : UVariant
transform() : rtabmap::Link , rtabmap::OdometryInfo
-Transform() : rtabmap::Transform
+Transform() : rtabmap::Transform
transformFiltered : rtabmap::OdometryInfo
transformGroundTruth : rtabmap::OdometryInfo
translation() : rtabmap::Transform
@@ -153,9 +153,9 @@ $(document).ready(function(){initNavTree('functions_t.html',''); initResizable()
Tx() : rtabmap::CameraModel
Type : rtabmap::EnvSensor
type() : rtabmap::EnvSensor
-Type : rtabmap::Feature2D , rtabmap::IMUFilter
+Type : rtabmap::Feature2D
type() : rtabmap::IMUFilter
-Type : rtabmap::Link
+Type : rtabmap::IMUFilter , rtabmap::Link
type() : rtabmap::Link
Type : rtabmap::Odometry
type : rtabmap::OdometryInfo
diff --git a/preview/pr-1748/api/latest/global__map_2OccupancyGrid_8h_source.html b/preview/pr-1748/api/latest/global__map_2OccupancyGrid_8h_source.html
index 7f38eeaf..d6a12750 100644
--- a/preview/pr-1748/api/latest/global__map_2OccupancyGrid_8h_source.html
+++ b/preview/pr-1748/api/latest/global__map_2OccupancyGrid_8h_source.html
@@ -182,7 +182,7 @@ $(document).ready(function(){initNavTree('global__map_2OccupancyGrid_8h_source.h
unsigned long getMemoryUsed() const
Approximate memory used by assembled-node bookkeeping (bytes).
virtual void assemble(const std::list< std::pair< int, Transform > > &newPoses)
Subclass hook: merge newPoses into the global map; call addAssembledNode().
virtual void clear()
Clears assembled nodes and grid bounds; does not clear LocalGridCache.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
static StaticMemberInitializer RtabmapColorOcTreeMemberInit
static member to ensure static initialization (only once)
RtabmapColorOcTree * create() const
virtual bool pruneNode(RtabmapColorOcTreeNode *node)
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
UtiLite is a simple library to create small cross-platform applications using threads , events-based communication and a powerful logger . The first three sections show the core classes of the library, then last sections show some useful functions added through time.
UtiLite provides a utility application called uResourceGenerator to generate resources to include in an executable. For example:
$
rtabmap -res_tool DatabaseSchema.sql
-
+
This will generate a HEX file "DatabaseSchema_sql.h" which can be included in source files. Data of the file is global and can be accessed by the generated const char * DATABASESCHEMA_SQL.
#include "DatabaseSchema_sql.h"
...
std::string hex = DATABASESCHEMA_SQL;
diff --git a/preview/pr-1748/api/latest/index.html b/preview/pr-1748/api/latest/index.html
index c03ed655..9af02c93 100644
--- a/preview/pr-1748/api/latest/index.html
+++ b/preview/pr-1748/api/latest/index.html
@@ -168,7 +168,7 @@ Start here
-
+
Throttling is the caller's job here: rtabmap::Rtabmap::process() maps every frame it is given. rtabmap::RtabmapThread does this same stamp comparison internally, from Rtabmap/DetectionRate , so the threaded pipeline only needs the parameter to be set.
Odometry drifts and the graph gets re-optimized, so the odometry pose is not a map pose. rtabmap::Statistics::mapCorrection() is what reconciles the two, and since it only changes on a map update it can be applied to every incoming frame – which is how the pose stays available at full rate while the map is built at 1 Hz. This is the transform published as /map → /odom by the ROS wrapper, and what the MapBuilder of each example composes with the live odometry pose to place the clouds. It is also readable outside the statistics, as rtabmap::Rtabmap::getMapCorrection() .
Complete programs live under examples/
diff --git a/preview/pr-1748/api/latest/navtreedata.js b/preview/pr-1748/api/latest/navtreedata.js
index 84c9cf57..870d1d1e 100644
--- a/preview/pr-1748/api/latest/navtreedata.js
+++ b/preview/pr-1748/api/latest/navtreedata.js
@@ -128,21 +128,21 @@ var NAVTREEINDEX =
[
"BayesFilter_8h_source.html",
"UStl_8h.html#ab4e2c55d7930e99514a2315a2c6b4f82",
-"classrtabmap_1_1BayesFilter.html#ad415ee334d31eebc3685e61862f32573",
-"classrtabmap_1_1CameraVideo.html",
-"classrtabmap_1_1FlannIndex.html#a5a2eed18fe1216142d09c05243e9d06f",
-"classrtabmap_1_1LaserScan.html#a38f5602d1411c204d54be9b3c7320007ab169cf98665cb3f33d81240b37cc501c",
-"classrtabmap_1_1Memory.html#a838b48bb9c2e6ccfe4f916ea2b2d00fd",
-"classrtabmap_1_1OdometryInfo.html#a08ee9e84949857719b76d082559f3cbc",
-"classrtabmap_1_1OptimizerG2O.html#af69edaad65a7f7f936fa99f8c617e10b",
-"classrtabmap_1_1Rtabmap.html#a80add8fadd488d0c7781c249abea0d5d",
-"classrtabmap_1_1SensorCaptureInfo.html#a5f544019df408896fed21c48fb3c0197",
-"classrtabmap_1_1SensorEvent.html#a02d0ef0c42eab24adb8013a9693e02b1",
-"classrtabmap_1_1Stereo.html",
-"classrtabmap_1_1TransformStamped.html",
-"group__CropBox.html#gaa6737135785f73d1a2f3ec966ab22bc7",
-"namespacertabmap.html",
-"parameters.html#autotoc_md58"
+"classrtabmap_1_1BayesFilter.html#ab13c8acecfbb4fcfff4e809e2b0a7538",
+"classrtabmap_1_1CameraStereoZedOC.html#a37264abe58baa727bb5ee8d6653fa443",
+"classrtabmap_1_1FlannIndex.html#a4a5c33446a515bd8f0c2f73a1adaeb23",
+"classrtabmap_1_1LaserScan.html#a38f5602d1411c204d54be9b3c7320007a7df3c8f97dd52461787060befaf7f2d7",
+"classrtabmap_1_1Memory.html#a7e16d27512d0daf17b9dbb17aab3b201",
+"classrtabmap_1_1OdometryInfo.html#a028f791a3005377516d217608a696556",
+"classrtabmap_1_1OptimizerG2O.html#a9400bdf57331af310cf6b02e661d0a03",
+"classrtabmap_1_1Rtabmap.html#a809673c3d0e6d8fb05ebb4a52218d438",
+"classrtabmap_1_1SensorCaptureInfo.html#a5c086f941e4fa816ec608779ac03f640",
+"classrtabmap_1_1SensorEvent.html",
+"classrtabmap_1_1Statistics.html#afeb2fd18d35f6a760ffa46ca0ebe4e49",
+"classrtabmap_1_1Transform.html#afe833cfcd56f2f147091e7d309dadb36",
+"group__CropBox.html#ga8065c61da2295bf203e4ee7471e9332d",
+"namespacemembers_v.html",
+"parameters.html#autotoc_md56"
];
var SYNCONMSG = 'click to disable panel synchronisation';
diff --git a/preview/pr-1748/api/latest/navtreeindex1.js b/preview/pr-1748/api/latest/navtreeindex1.js
index f0deddd6..f44a45bd 100644
--- a/preview/pr-1748/api/latest/navtreeindex1.js
+++ b/preview/pr-1748/api/latest/navtreeindex1.js
@@ -228,26 +228,26 @@ var NAVTREEINDEX1 =
"classes.html":[7,1],
"classrtabmap_1_1BRISK.html":[7,0,1,2],
"classrtabmap_1_1BRISK.html":[6,0,0,4],
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-"classrtabmap_1_1BayesFilter.html#a2955edc4b79110b5bd1bd03f1616056e":[7,0,1,1,0],
+"classrtabmap_1_1BayesFilter.html":[7,0,1,1],
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diff --git a/preview/pr-1748/api/latest/parameters.html b/preview/pr-1748/api/latest/parameters.html
index 824a1dfd..03df220f 100644
--- a/preview/pr-1748/api/latest/parameters.html
+++ b/preview/pr-1748/api/latest/parameters.html
@@ -106,7 +106,7 @@ $(document).ready(function(){initNavTree('parameters.html',''); initResizable();
rtabmap .init(parameters,
"map.db" );
static std::string kMemSTMSize()
Key of parameter Mem/STMSize : "Short-term memory size." Default value: 10 ( unsigned int ).
std::pair< std::string, std::string > ParametersPair
A single parameter key/value pair, the entry type of ParametersMap.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
Each key links to its accessor on rtabmap::Parameters , which is also how the key is spelled in code (Parameters::kMemSTMSize() for Mem/STMSize). Defaults given with a condition depend on how RTAB-Map was built; call rtabmap::Parameters::getDefaultParameters() to read the values of the build in use.
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@@ -146,7 +146,7 @@ $(document).ready(function(){initNavTree('rvl__codec_8h_source.html',''); initRe
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index ee16543f..7fc6e468 100644
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];
diff --git a/preview/pr-1748/api/latest/stereoRectifyFisheye_8h_source.html b/preview/pr-1748/api/latest/stereoRectifyFisheye_8h_source.html
index fa2a6549..4f63514b 100644
--- a/preview/pr-1748/api/latest/stereoRectifyFisheye_8h_source.html
+++ b/preview/pr-1748/api/latest/stereoRectifyFisheye_8h_source.html
@@ -1359,7 +1359,7 @@ $(document).ready(function(){initNavTree('stereoRectifyFisheye_8h_source.html','
-
+
diff --git a/preview/pr-1748/api/latest/uResourceGeneratorPage.html b/preview/pr-1748/api/latest/uResourceGeneratorPage.html
index 1d288a6d..4a384943 100644
--- a/preview/pr-1748/api/latest/uResourceGeneratorPage.html
+++ b/preview/pr-1748/api/latest/uResourceGeneratorPage.html
@@ -102,7 +102,7 @@ $(document).ready(function(){initNavTree('uResourceGeneratorPage.html',''); init
UtiLite provides a utility application called uResourceGenerator to generate resources to include in an executable. For example:
$
rtabmap -res_tool DatabaseSchema.sql
-
+
This will generate a HEX file "DatabaseSchema_sql.h" which can be included in source files. Data of the file is global and can be accessed by the generated const char * DATABASESCHEMA_SQL.
#include "DatabaseSchema_sql.h"
...
std::string hex = DATABASESCHEMA_SQL;
diff --git a/preview/pr-1748/api/latest/util2d_8h_source.html b/preview/pr-1748/api/latest/util2d_8h_source.html
index 520d4984..5022cb37 100644
--- a/preview/pr-1748/api/latest/util2d_8h_source.html
+++ b/preview/pr-1748/api/latest/util2d_8h_source.html
@@ -331,7 +331,7 @@ $(document).ready(function(){initNavTree('util2d_8h_source.html',''); initResiza
cv::Mat RTABMAP_CORE_EXPORT fillDepthHoles(const cv::Mat &depth, int maximumHoleSize=1, float errorRatio=0.02f)
Fills holes in the depth image using linear interpolation.
cv::Mat RTABMAP_CORE_EXPORT interpolate(const cv::Mat &image, int factor, float depthErrorRatio=0.02f)
Upsamples a depth image using bilinear interpolation with depth consistency check.
void RTABMAP_CORE_EXPORT fillRegisteredDepthHoles(cv::Mat &depthRegistered, bool vertical, bool horizontal, bool fillDoubleHoles=false)
Fill holes in a registered depth image using linear interpolation.
-
+
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
diff --git a/preview/pr-1748/api/latest/util3d_8h_source.html b/preview/pr-1748/api/latest/util3d_8h_source.html
index 2fea52ad..4709132b 100644
--- a/preview/pr-1748/api/latest/util3d_8h_source.html
+++ b/preview/pr-1748/api/latest/util3d_8h_source.html
@@ -554,7 +554,7 @@ $(document).ready(function(){initNavTree('util3d_8h_source.html',''); initResiza
pcl::PointCloud< pcl::PointXYZ >::Ptr RTABMAP_CORE_EXPORT cloudFromDisparity(const cv::Mat &imageDisparity, const StereoCameraModel &model, int decimation=1, float maxDepth=0.0f, float minDepth=0.0f, std::vector< int > *validIndices=0)
Converts a disparity image to a 3D point cloud.
LaserScan RTABMAP_CORE_EXPORT loadScan(const std::string &path)
Loads a 3D scan from a file (.pcd, .ply, or .bin format).
pcl::IndicesPtr RTABMAP_CORE_EXPORT concatenate(const std::vector< pcl::IndicesPtr > &indices)
Concatenates multiple sets of indices into a single index vector.
std::map< std::string, std::string > ParametersMap
Parameter keys mapped to their values, as used by every configurable class (see Parameters).
This namespace contains 3D point cloud processing utilities.
LaserScan laserScanFromPointCloud(const PointCloud2T &cloud, bool filterNaNs, bool is2D, const Transform &transform)
Convert pcl::PCLPointCloud2 to rtabmap::LaserScan with all supported fields (see rtabmap::LaserScan::...
void RTABMAP_CORE_EXPORT filterMaxDepth(pcl::PointCloud< pcl::PointXYZ > &inliers1, pcl::PointCloud< pcl::PointXYZ > &inliers2, float maxDepth, char depthAxis, bool removeDuplicates)
Filters pairs of 3D points by maximum depth along a specified axis and optionally removes duplicates.
void RTABMAP_CORE_EXPORT extractXYZCorrespondencesRANSAC(const std::multimap< int, pcl::PointXYZ > &words1, const std::multimap< int, pcl::PointXYZ > &words2, pcl::PointCloud< pcl::PointXYZ > &cloud1, pcl::PointCloud< pcl::PointXYZ > &cloud2)
Extracts reliable 3D point correspondences between two sets of labeled 3D points using RANSAC filteri...
int RTABMAP_CORE_EXPORT countUniquePairs(const std::multimap< int, pcl::PointXYZ > &wordsA, const std::multimap< int, pcl::PointXYZ > &wordsB)
Counts the number of unique 3D point correspondences between two sets of word-indexed features.
std::vector< cv::Point3f > RTABMAP_CORE_EXPORT generateKeypoints3DStereo(const std::vector< cv::Point2f > &leftCorners, const std::vector< cv::Point2f > &rightCorners, const StereoCameraModel &model, const std::vector< unsigned char > &mask=std::vector< unsigned char >(), float minDepth=0, float maxDepth=0)
Computes 3D keypoints from corresponding 2D points in a stereo image pair.
std::multimap< int, cv::KeyPoint > RTABMAP_CORE_EXPORT aggregate(const std::list< int > &wordIds, const std::vector< cv::KeyPoint > &keypoints)
Aggregates word IDs and corresponding keypoints into a multimap.
std::vector< cv::Point3f > RTABMAP_CORE_EXPORT generateKeypoints3DDisparity(const std::vector< cv::KeyPoint > &keypoints, const cv::Mat &disparity, const StereoCameraModel &stereoCameraModel, float minDepth=0, float maxDepth=0)
Projects 2D keypoints into 3D space using a disparity image and a stereo camera model.
pcl::PointCloud< pcl::PointXYZ >::Ptr uniformSampling(const pcl::PointCloud< pcl::PointXYZ >::Ptr &cloud, float voxelSize)
DEPRECATED: Use voxelize() instead.
pcl::IndicesPtr RTABMAP_CORE_EXPORT extractPlane(const pcl::PointCloud< pcl::PointXYZ >::Ptr &cloud, const pcl::IndicesPtr &indices, float distanceThreshold, int maxIterations=100, pcl::ModelCoefficients *coefficientsOut=0)
Extracts the indices of the inliers that belong to a plane using RANSAC.
LaserScan RTABMAP_CORE_EXPORT rangeFiltering(const LaserScan &scan, float rangeMin, float rangeMax)
Filters a LaserScan data on a minimum and maximum Euclidean range.
cv::Mat RTABMAP_CORE_EXPORT convertImage8U2Map(const cv::Mat &map8U, bool pgmFormat=false)
Converts a grayscale occupancy image (CV_8U) to an occupancy grid map (CV_8S).
cv::Mat RTABMAP_CORE_EXPORT convertMap2Image8U(const cv::Mat &map8S, bool pgmFormat=false)
Converts an occupancy grid map (CV_8S) to a grayscale image (CV_8U).
RTABMAP_DEPRECATED cv::Mat RTABMAP_CORE_EXPORT create2DMap(const std::map< int, Transform > &poses, const std::map< int, pcl::PointCloud< pcl::PointXYZ >::Ptr > &scans, float cellSize, bool unknownSpaceFilled, float &xMin, float &yMin, float minMapSize=0.0f, float scanMaxRange=0.0f)
void occupancy2DFromCloud3D(const typename pcl::PointCloud< PointT >::Ptr &cloud, const pcl::IndicesPtr &indices, cv::Mat &ground, cv::Mat &obstacles, float cellSize, float groundNormalAngle, int minClusterSize, bool segmentFlatObstacles, float maxGroundHeight)
Generates 2D ground and obstacle occupancy data from a 3D point cloud.
void occupancy2DFromGroundObstacles(const typename pcl::PointCloud< PointT >::Ptr &cloud, const pcl::IndicesPtr &groundIndices, const pcl::IndicesPtr &obstaclesIndices, cv::Mat &ground, cv::Mat &obstacles, float cellSize)
Projects 3D ground and obstacle point clouds onto the 2D XY plane and voxelizes them into 2D occupanc...
pcl::IndicesPtr RTABMAP_CORE_EXPORT concatenate(const std::vector< pcl::IndicesPtr > &indices)
Concatenates multiple sets of indices into a single index vector.
Transform RTABMAP_CORE_EXPORT estimateMotion3DTo2D(const std::map< int, cv::Point3f > &words3A, const std::map< int, cv::KeyPoint > &words2B, const CameraModel &cameraModel, int minInliers=10, int iterations=100, double reprojError=5., int flagsPnP=0, int pnpRefineIterations=1, int varianceMedianRatio=4, float maxVariance=0, const Transform &guess=Transform::getIdentity(), const std::map< int, cv::Point3f > &words3B=std::map< int, cv::Point3f >(), cv::Mat *covariance=0, std::vector< int > *matchesOut=0, std::vector< int > *inliersOut=0, bool splitLinearCovarianceComponents=false)
Estimates a 6-DOF camera transform from 3D-2D point correspondences using PnP RANSAC.
void RTABMAP_CORE_EXPORT solvePnPRansac(const std::vector< cv::Point3f > &objectPoints, const std::vector< cv::Point2f > &imagePoints, const cv::Mat &cameraMatrix, const cv::Mat &distCoeffs, cv::Mat &rvec, cv::Mat &tvec, bool useExtrinsicGuess, int iterationsCount, float reprojectionError, int minInliersCount, std::vector< int > &inliers, int flags, int refineIterations=1, float refineSigma=3.0f)
Estimates the camera pose using the PnP RANSAC algorithm and optionally refines it.
bool RTABMAP_CORE_EXPORT ransacDeterministicSeedEnabled()
Transform RTABMAP_CORE_EXPORT icpPointToPlane(const pcl::PointCloud< pcl::PointNormal >::ConstPtr &cloud_source, const pcl::PointCloud< pcl::PointNormal >::ConstPtr &cloud_target, double maxCorrespondenceDistance, int maximumIterations, bool &hasConverged, pcl::PointCloud< pcl::PointNormal > &cloud_source_registered, float epsilon=0.0f, bool icp2D=false, float ransacOutlierRatio=0.0f, int *iterationsDone=nullptr)
Performs Iterative Closest Point (ICP) alignment using a point-to-plane error metric.
Transform RTABMAP_CORE_EXPORT transformFromXYZCorrespondences(const pcl::PointCloud< pcl::PointXYZ >::ConstPtr &cloud1, const pcl::PointCloud< pcl::PointXYZ >::ConstPtr &cloud2, double inlierThreshold=0.02, int iterations=100, int refineModelIterations=10, double refineModelSigma=3.0, std::vector< int > *inliers=0, cv::Mat *variance=0)
Estimates a rigid transformation between two point clouds using RANSAC with optional refinement.
Transform RTABMAP_CORE_EXPORT icp(const pcl::PointCloud< pcl::PointXYZ >::ConstPtr &cloud_source, const pcl::PointCloud< pcl::PointXYZ >::ConstPtr &cloud_target, double maxCorrespondenceDistance, int maximumIterations, bool &hasConverged, pcl::PointCloud< pcl::PointXYZ > &cloud_source_registered, float epsilon=0.0f, bool icp2D=false, float ransacOutlierRatio=0.0f, int *iterationsDone=nullptr)
Performs Iterative Closest Point (ICP) alignment between two point clouds and returns the resulting t...
void RTABMAP_CORE_EXPORT createPolygonIndexes(const std::vector< pcl::Vertices > &polygons, int cloudSize, std::vector< std::set< int > > &neighborPolygons, std::vector< std::set< int > > &vertexPolygons)
Given a set of polygons, create two indexes: polygons to neighbor polygons and vertices to polygons.
bool RTABMAP_CORE_EXPORT intersectRayTriangle(const Eigen::Vector3f &p, const Eigen::Vector3f &dir, const Eigen::Vector3f &v0, const Eigen::Vector3f &v1, const Eigen::Vector3f &v2, float &distance, Eigen::Vector3f &normal)
cv::Mat RTABMAP_CORE_EXPORT mergeTextures(pcl::TextureMesh &mesh, const std::map< int, cv::Mat > &images, const std::map< int, CameraModel > &calibrations, const Memory *memory=0, const DBDriver *dbDriver=0, int textureSize=4096, int textureCount=1, const std::vector< std::map< int, pcl::PointXY > > &vertexToPixels=std::vector< std::map< int, pcl::PointXY > >(), bool gainCompensation=true, float gainBeta=10.0f, bool gainRGB=true, bool blending=true, int blendingDecimation=0, int brightnessContrastRatioLow=0, int brightnessContrastRatioHigh=0, bool exposureFusion=false, const ProgressState *state=0, unsigned char blankValue=255, bool clearVertexColorUnderTexture=true, std::map< int, std::map< int, cv::Vec4d > > *gains=0, std::map< int, std::map< int, cv::Mat > > *blendingGains=0, std::pair< float, float > *contrastValues=0)
#define UASSERT(condition)
void RTABMAP_CORE_EXPORT createPolygonIndexes(const std::vector< pcl::Vertices > &polygons, int cloudSize, std::vector< std::set< int > > &neighborPolygons, std::vector< std::set< int > > &vertexPolygons)
Given a set of polygons, create two indexes: polygons to neighbor polygons and vertices to polygons.
bool RTABMAP_CORE_EXPORT intersectRayTriangle(const Eigen::Vector3f &p, const Eigen::Vector3f &dir, const Eigen::Vector3f &v0, const Eigen::Vector3f &v1, const Eigen::Vector3f &v2, float &distance, Eigen::Vector3f &normal)
LaserScan RTABMAP_CORE_EXPORT transformLaserScan(const LaserScan &laserScan, const Transform &transform)
Applies a 3D transform to all points (and normals if present) in a LaserScan.
RTAB-Map | Real-Time Appearance-Based Mapping