33 #include "rtabmap/core/Version.h" 62 #define RTABMAP_PARAM(PREFIX, NAME, TYPE, DEFAULT_VALUE, DESCRIPTION) \ 64 static std::string k##PREFIX##NAME() {return std::string(#PREFIX "/" #NAME);} \ 65 static TYPE default##PREFIX##NAME() {return DEFAULT_VALUE;} \ 66 static std::string type##PREFIX##NAME() {return std::string(#TYPE);} \ 68 class Dummy##PREFIX##NAME { \ 70 Dummy##PREFIX##NAME() {parameters_.insert(ParametersPair(#PREFIX "/" #NAME, #DEFAULT_VALUE)); \ 71 parametersType_.insert(ParametersPair(#PREFIX "/" #NAME, #TYPE)); \ 72 descriptions_.insert(ParametersPair(#PREFIX "/" #NAME, DESCRIPTION));} \ 74 Dummy##PREFIX##NAME dummy##PREFIX##NAME; 96 #define RTABMAP_PARAM_STR(PREFIX, NAME, DEFAULT_VALUE, DESCRIPTION) \ 98 static std::string k##PREFIX##NAME() {return std::string(#PREFIX "/" #NAME);} \ 99 static std::string default##PREFIX##NAME() {return DEFAULT_VALUE;} \ 100 static std::string type##PREFIX##NAME() {return std::string("string");} \ 102 class Dummy##PREFIX##NAME { \ 104 Dummy##PREFIX##NAME() {parameters_.insert(ParametersPair(#PREFIX "/" #NAME, DEFAULT_VALUE)); \ 105 parametersType_.insert(ParametersPair(#PREFIX "/" #NAME, "string")); \ 106 descriptions_.insert(ParametersPair(#PREFIX "/" #NAME, DESCRIPTION));} \ 108 Dummy##PREFIX##NAME dummy##PREFIX##NAME; 129 #define RTABMAP_PARAM_COND(PREFIX, NAME, TYPE, COND, DEFAULT_VALUE1, DEFAULT_VALUE2, DESCRIPTION) \ 131 static std::string k##PREFIX##NAME() {return std::string(#PREFIX "/" #NAME);} \ 132 static TYPE default##PREFIX##NAME() {return COND?DEFAULT_VALUE1:DEFAULT_VALUE2;} \ 133 static std::string type##PREFIX##NAME() {return std::string(#TYPE);} \ 135 class Dummy##PREFIX##NAME { \ 137 Dummy##PREFIX##NAME() {parameters_.insert(ParametersPair(#PREFIX "/" #NAME, COND?#DEFAULT_VALUE1:#DEFAULT_VALUE2)); \ 138 parametersType_.insert(ParametersPair(#PREFIX "/" #NAME, #TYPE)); \ 139 descriptions_.insert(ParametersPair(#PREFIX "/" #NAME, DESCRIPTION));} \ 141 Dummy##PREFIX##NAME dummy##PREFIX##NAME; 175 RTABMAP_PARAM(
Rtabmap, PublishRAMUsage,
bool,
false,
"Publishing RAM usage in statistics (may add a small overhead to get info from the system).");
176 RTABMAP_PARAM(
Rtabmap, ComputeRMSE,
bool,
true,
"Compute root mean square error (RMSE) and publish it in statistics, if ground truth is provided.");
177 RTABMAP_PARAM(
Rtabmap, SaveWMState,
bool,
false,
"Save working memory state after each update in statistics.");
178 RTABMAP_PARAM(
Rtabmap, TimeThr,
float, 0,
"Maximum time allowed for map update (ms) (0 means infinity). When map update time exceeds this fixed time threshold, some nodes in Working Memory (WM) are transferred to Long-Term Memory to limit the size of the WM and decrease the update time.");
179 RTABMAP_PARAM(
Rtabmap, MemoryThr,
int, 0,
uFormat(
"Maximum nodes in the Working Memory (0 means infinity). Similar to \"%s\", when the number of nodes in Working Memory (WM) exceeds this treshold, some nodes are transferred to Long-Term Memory to keep WM size fixed.", kRtabmapTimeThr().c_str()));
180 RTABMAP_PARAM(
Rtabmap, DetectionRate,
float, 1,
"Detection rate (Hz). RTAB-Map will filter input images to satisfy this rate.");
182 RTABMAP_PARAM(
Rtabmap, CreateIntermediateNodes,
bool,
false,
uFormat(
"Create intermediate nodes between loop closure detection. Only used when %s>0.", kRtabmapDetectionRate().c_str()));
184 RTABMAP_PARAM(
Rtabmap, MaxRetrieved,
unsigned int, 2,
"Maximum locations retrieved at the same time from LTM.");
185 RTABMAP_PARAM(
Rtabmap, StatisticLogsBufferedInRAM,
bool,
true,
"Statistic logs buffered in RAM instead of written to hard drive after each iteration.");
187 RTABMAP_PARAM(
Rtabmap, StatisticLoggedHeaders,
bool,
true,
"Add column header description to log files.");
188 RTABMAP_PARAM(
Rtabmap, StartNewMapOnLoopClosure,
bool,
false,
"Start a new map only if there is a global loop closure with a previous map.");
189 RTABMAP_PARAM(
Rtabmap, StartNewMapOnGoodSignature,
bool,
false,
uFormat(
"Start a new map only if the first signature is not bad (i.e., has enough features, see %s).", kKpBadSignRatio().c_str()));
190 RTABMAP_PARAM(
Rtabmap, ImagesAlreadyRectified,
bool,
true,
"Images are already rectified. By default RTAB-Map assumes that received images are rectified. If they are not, they can be rectified by RTAB-Map if this parameter is false.");
191 RTABMAP_PARAM(
Rtabmap, RectifyOnlyFeatures,
bool,
false,
uFormat(
"If \"%s\" is false and this parameter is true, the whole RGB image will not be rectified, only the features. Warning: As projection of RGB-D image to point cloud is assuming that images are rectified, the generated point cloud map will have wrong colors if this parameter is true.", kRtabmapImagesAlreadyRectified().c_str()));
195 RTABMAP_PARAM(
Rtabmap, LoopRatio,
float, 0,
"The loop closure hypothesis must be over LoopRatio x lastHypothesisValue.");
198 RTABMAP_PARAM(
Mem, RehearsalSimilarity,
float, 0.6,
"Rehearsal similarity.");
201 RTABMAP_PARAM(
Mem, RawDescriptorsKept,
bool,
true,
"Raw descriptors kept in memory.");
202 RTABMAP_PARAM(
Mem, MapLabelsAdded,
bool,
true,
"Create map labels. The first node of a map will be labelled as \"map#\" where # is the map ID.");
203 RTABMAP_PARAM(
Mem, SaveDepth16Format,
bool,
false,
"Save depth image into 16 bits format to reduce memory used. Warning: values over ~65 meters are ignored (maximum 65535 millimeters).");
204 RTABMAP_PARAM(
Mem, NotLinkedNodesKept,
bool,
true,
"Keep not linked nodes in db (rehearsed nodes and deleted nodes).");
205 RTABMAP_PARAM(
Mem, IntermediateNodeDataKept,
bool,
false,
"Keep intermediate node data in db.");
207 RTABMAP_PARAM(
Mem, IncrementalMemory,
bool,
true,
"SLAM mode, otherwise it is Localization mode.");
208 RTABMAP_PARAM(
Mem, ReduceGraph,
bool,
false,
"Reduce graph. Merge nodes when loop closures are added (ignoring those with user data set).");
209 RTABMAP_PARAM(
Mem, RecentWmRatio,
float, 0.2,
"Ratio of locations after the last loop closure in WM that cannot be transferred.");
210 RTABMAP_PARAM(
Mem, TransferSortingByWeightId,
bool,
false,
"On transfer, signatures are sorted by weight->ID only (i.e. the oldest of the lowest weighted signatures are transferred first). If false, the signatures are sorted by weight->Age->ID (i.e. the oldest inserted in WM of the lowest weighted signatures are transferred first). Note that retrieval updates the age, not the ID.");
211 RTABMAP_PARAM(
Mem, RehearsalIdUpdatedToNewOne,
bool,
false,
"On merge, update to new id. When false, no copy.");
212 RTABMAP_PARAM(
Mem, RehearsalWeightIgnoredWhileMoving,
bool,
false,
"When the robot is moving, weights are not updated on rehearsal.");
213 RTABMAP_PARAM(
Mem, GenerateIds,
bool,
true,
"True=Generate location IDs, False=use input image IDs.");
214 RTABMAP_PARAM(
Mem, BadSignaturesIgnored,
bool,
false,
"Bad signatures are ignored.");
215 RTABMAP_PARAM(
Mem, InitWMWithAllNodes,
bool,
false,
"Initialize the Working Memory with all nodes in Long-Term Memory. When false, it is initialized with nodes of the previous session.");
216 RTABMAP_PARAM(
Mem, DepthAsMask,
bool,
true,
"Use depth image as mask when extracting features for vocabulary.");
217 RTABMAP_PARAM(
Mem, ImagePreDecimation,
int, 1,
"Image decimation (>=1) before features extraction. Negative decimation is done from RGB size instead of depth size (if depth is smaller than RGB, it may be interpolated depending of the decimation value).");
218 RTABMAP_PARAM(
Mem, ImagePostDecimation,
int, 1,
"Image decimation (>=1) of saved data in created signatures (after features extraction). Decimation is done from the original image. Negative decimation is done from RGB size instead of depth size (if depth is smaller than RGB, it may be interpolated depending of the decimation value).");
219 RTABMAP_PARAM(
Mem, CompressionParallelized,
bool,
true,
"Compression of sensor data is multi-threaded.");
220 RTABMAP_PARAM(
Mem, LaserScanDownsampleStepSize,
int, 1,
"If > 1, downsample the laser scans when creating a signature.");
221 RTABMAP_PARAM(
Mem, LaserScanVoxelSize,
float, 0.0,
uFormat(
"If > 0 m, voxel filtering is done on laser scans when creating a signature. If the laser scan had normals, they will be removed. To recompute the normals, make sure to use \"%s\" or \"%s\" parameters.", kMemLaserScanNormalK().c_str(), kMemLaserScanNormalRadius().c_str()).c_str());
222 RTABMAP_PARAM(
Mem, LaserScanNormalK,
int, 0,
"If > 0 and laser scans don't have normals, normals will be computed with K search neighbors when creating a signature.");
223 RTABMAP_PARAM(
Mem, LaserScanNormalRadius,
float, 0.0,
"If > 0 m and laser scans don't have normals, normals will be computed with radius search neighbors when creating a signature.");
225 RTABMAP_PARAM(
Mem, CovOffDiagIgnored,
bool,
true,
"Ignore off diagonal values of the covariance matrix.");
228 RTABMAP_PARAM(Kp, NNStrategy,
int, 1,
"kNNFlannNaive=0, kNNFlannKdTree=1, kNNFlannLSH=2, kNNBruteForce=3, kNNBruteForceGPU=4");
230 RTABMAP_PARAM(Kp, IncrementalFlann,
bool,
true,
uFormat(
"When using FLANN based strategy, add/remove points to its index without always rebuilding the index (the index is built only when the dictionary increases of the factor \"%s\" in size).", kKpFlannRebalancingFactor().c_str()));
231 RTABMAP_PARAM(Kp, FlannRebalancingFactor,
float, 2.0,
uFormat(
"Factor used when rebuilding the incremental FLANN index (see \"%s\"). Set <=1 to disable.", kKpIncrementalFlann().c_str()));
232 RTABMAP_PARAM(Kp, MaxDepth,
float, 0,
"Filter extracted keypoints by depth (0=inf).");
233 RTABMAP_PARAM(Kp, MinDepth,
float, 0,
"Filter extracted keypoints by depth.");
234 RTABMAP_PARAM(Kp, MaxFeatures,
int, 500,
"Maximum features extracted from the images (0 means not bounded, <0 means no extraction).");
235 RTABMAP_PARAM(Kp, BadSignRatio,
float, 0.5,
"Bad signature ratio (less than Ratio x AverageWordsPerImage = bad).");
236 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.)");
237 #ifndef RTABMAP_NONFREE 238 #ifdef RTABMAP_OPENCV3 240 RTABMAP_PARAM(Kp, DetectorStrategy,
int, 8,
"0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE.");
242 RTABMAP_PARAM(Kp, DetectorStrategy,
int, 6,
"0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE.");
245 RTABMAP_PARAM(Kp, DetectorStrategy,
int, 6,
"0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE.");
247 RTABMAP_PARAM(Kp, TfIdfLikelihoodUsed,
bool,
true,
"Use of the td-idf strategy to compute the likelihood.");
248 RTABMAP_PARAM(Kp, Parallelized,
bool,
true,
"If the dictionary update and signature creation were parallelized.");
249 RTABMAP_PARAM_STR(Kp, RoiRatios,
"0.0 0.0 0.0 0.0",
"Region of interest ratios [left, right, top, bottom].");
250 RTABMAP_PARAM_STR(Kp, DictionaryPath,
"",
"Path of the pre-computed dictionary");
251 RTABMAP_PARAM(Kp, NewWordsComparedTogether,
bool,
true,
"When adding new words to dictionary, they are compared also with each other (to detect same words in the same signature).");
252 RTABMAP_PARAM(Kp, SubPixWinSize,
int, 3,
"See cv::cornerSubPix().");
253 RTABMAP_PARAM(Kp, SubPixIterations,
int, 0,
"See cv::cornerSubPix(). 0 disables sub pixel refining.");
254 RTABMAP_PARAM(Kp, SubPixEps,
double, 0.02,
"See cv::cornerSubPix().");
255 RTABMAP_PARAM(Kp, GridRows,
int, 1,
uFormat(
"Number of rows of the grid used to extract uniformly \"%s / grid cells\" features from each cell.", kKpMaxFeatures().c_str()));
256 RTABMAP_PARAM(Kp, GridCols,
int, 1,
uFormat(
"Number of columns of the grid used to extract uniformly \"%s / grid cells\" features from each cell.", kKpMaxFeatures().c_str()));
259 RTABMAP_PARAM(DbSqlite3, InMemory,
bool,
false,
"Using database in the memory instead of a file on the hard disk.");
260 RTABMAP_PARAM(DbSqlite3, CacheSize,
unsigned int, 10000,
"Sqlite cache size (default is 2000).");
261 RTABMAP_PARAM(DbSqlite3, JournalMode,
int, 3,
"0=DELETE, 1=TRUNCATE, 2=PERSIST, 3=MEMORY, 4=OFF (see sqlite3 doc : \"PRAGMA journal_mode\")");
262 RTABMAP_PARAM(DbSqlite3, Synchronous,
int, 0,
"0=OFF, 1=NORMAL, 2=FULL (see sqlite3 doc : \"PRAGMA synchronous\")");
263 RTABMAP_PARAM(DbSqlite3, TempStore,
int, 2,
"0=DEFAULT, 1=FILE, 2=MEMORY (see sqlite3 doc : \"PRAGMA temp_store\")");
266 RTABMAP_PARAM(
SURF, Extended,
bool,
false,
"Extended descriptor flag (true - use extended 128-element descriptors; false - use 64-element descriptors).");
267 RTABMAP_PARAM(
SURF, HessianThreshold,
float, 500,
"Threshold for hessian keypoint detector used in SURF.");
268 RTABMAP_PARAM(
SURF, Octaves,
int, 4,
"Number of pyramid octaves the keypoint detector will use.");
269 RTABMAP_PARAM(
SURF, OctaveLayers,
int, 2,
"Number of octave layers within each octave.");
270 RTABMAP_PARAM(
SURF, Upright,
bool,
false,
"Up-right or rotated features flag (true - do not compute orientation of features; false - compute orientation).");
271 RTABMAP_PARAM(
SURF, GpuVersion,
bool,
false,
"GPU-SURF: Use GPU version of SURF. This option is enabled only if OpenCV is built with CUDA and GPUs are detected.");
274 RTABMAP_PARAM(
SIFT, NFeatures,
int, 0,
"The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast).");
275 RTABMAP_PARAM(
SIFT, NOctaveLayers,
int, 3,
"The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.");
276 RTABMAP_PARAM(
SIFT, ContrastThreshold,
double, 0.04,
"The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector.");
277 RTABMAP_PARAM(
SIFT, EdgeThreshold,
double, 10,
"The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).");
278 RTABMAP_PARAM(
SIFT, Sigma,
double, 1.6,
"The sigma of the Gaussian applied to the input image at the octave #0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.");
280 RTABMAP_PARAM(BRIEF, Bytes,
int, 32,
"Bytes is a length of descriptor in bytes. It can be equal 16, 32 or 64 bytes.");
282 RTABMAP_PARAM(
FAST, Threshold,
int, 20,
"Threshold on difference between intensity of the central pixel and pixels of a circle around this pixel.");
283 RTABMAP_PARAM(
FAST, NonmaxSuppression,
bool,
true,
"If true, non-maximum suppression is applied to detected corners (keypoints).");
284 RTABMAP_PARAM(
FAST, Gpu,
bool,
false,
"GPU-FAST: Use GPU version of FAST. This option is enabled only if OpenCV is built with CUDA and GPUs are detected.");
286 RTABMAP_PARAM(
FAST, MinThreshold,
int, 7,
"Minimum threshold. Used only when FAST/GridRows and FAST/GridCols are set.");
287 RTABMAP_PARAM(
FAST, MaxThreshold,
int, 200,
"Maximum threshold. Used only when FAST/GridRows and FAST/GridCols are set.");
288 RTABMAP_PARAM(
FAST, GridRows,
int, 0,
"Grid rows (0 to disable). Adapts the detector to partition the source image into a grid and detect points in each cell.");
289 RTABMAP_PARAM(
FAST, GridCols,
int, 0,
"Grid cols (0 to disable). Adapts the detector to partition the source image into a grid and detect points in each cell.");
297 RTABMAP_PARAM(
ORB, ScaleFactor,
float, 1.2,
"Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor will mean that to cover certain scale range you will need more pyramid levels and so the speed will suffer.");
298 RTABMAP_PARAM(
ORB, NLevels,
int, 8,
"The number of pyramid levels. The smallest level will have linear size equal to input_image_linear_size/pow(scaleFactor, nlevels).");
299 RTABMAP_PARAM(
ORB, EdgeThreshold,
int, 31,
"This is size of the border where the features are not detected. It should roughly match the patchSize parameter.");
300 RTABMAP_PARAM(
ORB, FirstLevel,
int, 0,
"It should be 0 in the current implementation.");
301 RTABMAP_PARAM(
ORB, WTA_K,
int, 2,
"The number of points that produce each element of the oriented BRIEF descriptor. The default value 2 means the BRIEF where we take a random point pair and compare their brightnesses, so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3 random points (of course, those point coordinates are random, but they are generated from the pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such output will occupy 2 bits, and therefore it will need a special variant of Hamming distance, denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3).");
302 RTABMAP_PARAM(
ORB, ScoreType,
int, 0,
"The default HARRIS_SCORE=0 means that Harris algorithm is used to rank features (the score is written to KeyPoint::score and is used to retain best nfeatures features); FAST_SCORE=1 is alternative value of the parameter that produces slightly less stable keypoints, but it is a little faster to compute.");
303 RTABMAP_PARAM(
ORB, PatchSize,
int, 31,
"size of the patch used by the oriented BRIEF descriptor. Of course, on smaller pyramid layers the perceived image area covered by a feature will be larger.");
304 RTABMAP_PARAM(
ORB, Gpu,
bool,
false,
"GPU-ORB: Use GPU version of ORB. This option is enabled only if OpenCV is built with CUDA and GPUs are detected.");
306 RTABMAP_PARAM(FREAK, OrientationNormalized,
bool,
true,
"Enable orientation normalization.");
307 RTABMAP_PARAM(FREAK, ScaleNormalized,
bool,
true,
"Enable scale normalization.");
308 RTABMAP_PARAM(FREAK, PatternScale,
float, 22,
"Scaling of the description pattern.");
309 RTABMAP_PARAM(FREAK, NOctaves,
int, 4,
"Number of octaves covered by the detected keypoints.");
312 RTABMAP_PARAM(
BRISK, Octaves,
int, 3,
"Detection octaves. Use 0 to do single scale.");
313 RTABMAP_PARAM(
BRISK, PatternScale,
float, 1,
"Apply this scale to the pattern used for sampling the neighbourhood of a keypoint.");
315 RTABMAP_PARAM(
KAZE, Extended,
bool,
false,
"Set to enable extraction of extended (128-byte) descriptor.");
316 RTABMAP_PARAM(
KAZE, Upright,
bool,
false,
"Set to enable use of upright descriptors (non rotation-invariant).");
317 RTABMAP_PARAM(
KAZE, Threshold,
float, 0.001,
"Detector response threshold to accept point.");
319 RTABMAP_PARAM(
KAZE, NOctaveLayers,
int, 4,
"Default number of sublevels per scale level.");
320 RTABMAP_PARAM(
KAZE, Diffusivity,
int, 1,
"Diffusivity type: 0=DIFF_PM_G1, 1=DIFF_PM_G2, 2=DIFF_WEICKERT or 3=DIFF_CHARBONNIER.");
323 RTABMAP_PARAM(Bayes, VirtualPlacePriorThr,
float, 0.9,
"Virtual place prior");
324 RTABMAP_PARAM_STR(Bayes, PredictionLC,
"0.1 0.36 0.30 0.16 0.062 0.0151 0.00255 0.000324 2.5e-05 1.3e-06 4.8e-08 1.2e-09 1.9e-11 2.2e-13 1.7e-15 8.5e-18 2.9e-20 6.9e-23",
"Prediction of loop closures (Gaussian-like, here with sigma=1.6) - Format: {VirtualPlaceProb, LoopClosureProb, NeighborLvl1, NeighborLvl2, ...}.");
325 RTABMAP_PARAM(Bayes, FullPredictionUpdate,
bool,
false,
"Regenerate all the prediction matrix on each iteration (otherwise only removed/added ids are updated).");
328 RTABMAP_PARAM(VhEp, Enabled,
bool,
false,
uFormat(
"Verify visual loop closure hypothesis by computing a fundamental matrix. This is done prior to transformation computation when %s is enabled.", kRGBDEnabled().c_str()));
329 RTABMAP_PARAM(VhEp, MatchCountMin,
int, 8,
"Minimum of matching visual words pairs to accept the loop hypothesis.");
330 RTABMAP_PARAM(VhEp, RansacParam1,
float, 3,
"Fundamental matrix (see cvFindFundamentalMat()): Max distance (in pixels) from the epipolar line for a point to be inlier.");
331 RTABMAP_PARAM(VhEp, RansacParam2,
float, 0.99,
"Fundamental matrix (see cvFindFundamentalMat()): Performance of RANSAC.");
335 RTABMAP_PARAM(RGBD, LinearUpdate,
float, 0.1,
"Minimum linear displacement (m) to update the map. Rehearsal is done prior to this, so weights are still updated.");
336 RTABMAP_PARAM(RGBD, AngularUpdate,
float, 0.1,
"Minimum angular displacement (rad) to update the map. Rehearsal is done prior to this, so weights are still updated.");
337 RTABMAP_PARAM(RGBD, LinearSpeedUpdate,
float, 0.0,
"Maximum linear speed (m/s) to update the map (0 means not limit).");
338 RTABMAP_PARAM(RGBD, AngularSpeedUpdate,
float, 0.0,
"Maximum angular speed (rad/s) to update the map (0 means not limit).");
339 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).");
340 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 node 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).");
341 RTABMAP_PARAM(RGBD, OptimizeMaxError,
float, 1.0,
uFormat(
"Reject loop closures if optimization error ratio is greater than this value (0=disabled). Ratio is computed as absolute error over standard deviation of each link. This will help to detect when a wrong loop closure is added to the graph. Not compatible with \"%s\" if enabled.", kOptimizerRobust().c_str()));
342 RTABMAP_PARAM(RGBD, SavedLocalizationIgnored,
bool,
false,
"Ignore last saved localization pose from previous session. If true, RTAB-Map won't assume it is restarting from the same place than where it shut down previously.");
343 RTABMAP_PARAM(RGBD, GoalReachedRadius,
float, 0.5,
"Goal reached radius (m).");
344 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.");
345 RTABMAP_PARAM(RGBD, PlanLinearVelocity,
float, 0,
"Linear velocity (m/sec) used to compute path weights.");
346 RTABMAP_PARAM(RGBD, PlanAngularVelocity,
float, 0,
"Angular velocity (rad/sec) used to compute path weights.");
347 RTABMAP_PARAM(RGBD, GoalsSavedInUserData,
bool,
false,
"When a goal is received and processed with success, it is saved in user data of the location with this format: \"GOAL:#\".");
348 RTABMAP_PARAM(RGBD, MaxLocalRetrieved,
unsigned int, 2,
"Maximum local locations retrieved (0=disabled) near the current pose in the local map or on the current planned path (those on the planned path have priority).");
349 RTABMAP_PARAM(RGBD, LocalRadius,
float, 10,
"Local radius (m) for nodes selection in the local map. This parameter is used in some approaches about the local map management.");
350 RTABMAP_PARAM(RGBD, LocalImmunizationRatio,
float, 0.25,
"Ratio of working memory for which local nodes are immunized from transfer.");
351 RTABMAP_PARAM(RGBD, ScanMatchingIdsSavedInLinks,
bool,
true,
"Save scan matching IDs in link's user data.");
352 RTABMAP_PARAM(RGBD, NeighborLinkRefining,
bool,
false,
uFormat(
"When a new node is added to the graph, the transformation of its neighbor link to the previous node is refined using registration approach selected (%s).", kRegStrategy().c_str()));
353 RTABMAP_PARAM(RGBD, LoopClosureReextractFeatures,
bool,
false,
"Extract features even if there are some already in the nodes.");
354 RTABMAP_PARAM(RGBD, LocalBundleOnLoopClosure,
bool,
false,
"Do local bundle adjustment with neighborhood of the loop closure.");
355 RTABMAP_PARAM(RGBD, CreateOccupancyGrid,
bool,
false,
"Create local occupancy grid maps. See \"Grid\" group for parameters.");
358 RTABMAP_PARAM(RGBD, ProximityByTime,
bool,
false,
"Detection over all locations in STM.");
359 RTABMAP_PARAM(RGBD, ProximityBySpace,
bool,
true,
"Detection over locations (in Working Memory) near in space.");
360 RTABMAP_PARAM(RGBD, ProximityMaxGraphDepth,
int, 50,
"Maximum depth from the current/last loop closure location and the local loop closure hypotheses. Set 0 to ignore.");
361 RTABMAP_PARAM(RGBD, ProximityMaxPaths,
int, 3,
"Maximum paths compared (from the most recent) for proximity detection by space. 0 means no limit.");
362 RTABMAP_PARAM(RGBD, ProximityPathFilteringRadius,
float, 1,
"Path filtering radius to reduce the number of nodes to compare in a path. A path should also be inside that radius to be considered for proximity detection.");
363 RTABMAP_PARAM(RGBD, ProximityPathMaxNeighbors,
int, 0,
"Maximum neighbor nodes compared on each path. Set to 0 to disable merging the laser scans.");
364 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.");
365 RTABMAP_PARAM(RGBD, ProximityAngle,
float, 45,
"Maximum angle (degrees) for visual proximity detection.");
371 RTABMAP_PARAM(
Optimizer, Epsilon,
double, 0.00001,
"Stop optimizing when the error improvement is less than this value.");
376 RTABMAP_PARAM(
Optimizer, Epsilon,
double, 0.0,
"Stop optimizing when the error improvement is less than this value.");
380 RTABMAP_PARAM(
Optimizer, Epsilon,
double, 0.00001,
"Stop optimizing when the error improvement is less than this value.");
383 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.");
384 RTABMAP_PARAM(
Optimizer, Robust,
bool,
false,
uFormat(
"Robust graph optimization using Vertigo (only work for g2o and GTSAM optimization strategies). Not compatible with \"%s\" if enabled.", kRGBDOptimizeMaxError().c_str()));
385 RTABMAP_PARAM(
Optimizer, PriorsIgnored,
bool,
true,
"Ignore prior constraints (global pose or GPS) while optimizing. Currently only g2o and gtsam optimization supports this.");
387 #ifdef RTABMAP_ORB_SLAM2 388 RTABMAP_PARAM(g2o, Solver,
int, 3,
"0=csparse 1=pcg 2=cholmod 3=Eigen");
390 RTABMAP_PARAM(g2o, Solver,
int, 0,
"0=csparse 1=pcg 2=cholmod 3=Eigen");
393 RTABMAP_PARAM(g2o, PixelVariance,
double, 1.0,
"Pixel variance used for bundle adjustment.");
394 RTABMAP_PARAM(g2o, RobustKernelDelta,
double, 8,
"Robust kernel delta used for bundle adjustment (0 means don't use robust kernel). Observations with chi2 over this threshold will be ignored in the second optimization pass.");
395 RTABMAP_PARAM(g2o, Baseline,
double, 0.075,
"When doing bundle adjustment with RGB-D data, we can set a fake baseline (m) to do stereo bundle adjustment (if 0, mono bundle adjustment is done). For stereo data, the baseline in the calibration is used directly.");
400 RTABMAP_PARAM(Odom, Strategy,
int, 0,
"0=Frame-to-Map (F2M) 1=Frame-to-Frame (F2F) 2=Fovis 3=viso2 4=DVO-SLAM 5=ORB_SLAM2 6=OKVIS 7=LOAM 8=MSCKF_VIO");
401 RTABMAP_PARAM(Odom, ResetCountdown,
int, 0,
"Automatically reset odometry after X consecutive images on which odometry cannot be computed (value=0 disables auto-reset).");
402 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)).");
403 RTABMAP_PARAM(Odom, FillInfoData,
bool,
true,
"Fill info with data (inliers/outliers features).");
404 RTABMAP_PARAM(Odom, ImageBufferSize,
unsigned int, 1,
"Data buffer size (0 min inf).");
405 RTABMAP_PARAM(Odom, FilteringStrategy,
int, 0,
"0=No filtering 1=Kalman filtering 2=Particle filtering");
406 RTABMAP_PARAM(Odom, ParticleSize,
unsigned int, 400,
"Number of particles of the filter.");
407 RTABMAP_PARAM(Odom, ParticleNoiseT,
float, 0.002,
"Noise (m) of translation components (x,y,z).");
408 RTABMAP_PARAM(Odom, ParticleLambdaT,
float, 100,
"Lambda of translation components (x,y,z).");
409 RTABMAP_PARAM(Odom, ParticleNoiseR,
float, 0.002,
"Noise (rad) of rotational components (roll,pitch,yaw).");
410 RTABMAP_PARAM(Odom, ParticleLambdaR,
float, 100,
"Lambda of rotational components (roll,pitch,yaw).");
411 RTABMAP_PARAM(Odom, KalmanProcessNoise,
float, 0.001,
"Process noise covariance value.");
412 RTABMAP_PARAM(Odom, KalmanMeasurementNoise,
float, 0.01,
"Process measurement covariance value.");
413 RTABMAP_PARAM(Odom, GuessMotion,
bool,
true,
"Guess next transformation from the last motion computed.");
414 RTABMAP_PARAM(Odom, KeyFrameThr,
float, 0.3,
"[Visual] Create a new keyframe when the number of inliers drops under this ratio of features in last frame. Setting the value to 0 means that a keyframe is created for each processed frame.");
415 RTABMAP_PARAM(Odom, VisKeyFrameThr,
int, 150,
"[Visual] 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.");
416 RTABMAP_PARAM(Odom, ScanKeyFrameThr,
float, 0.9,
"[Geometry] Create a new keyframe when the number of ICP inliers drops under this ratio of points in last frame's scan. Setting the value to 0 means that a keyframe is created for each processed frame.");
417 RTABMAP_PARAM(Odom, ImageDecimation,
int, 1,
"Decimation of the images before registration. Negative decimation is done from RGB size instead of depth size (if depth is smaller than RGB, it may be interpolated depending of the decimation value).");
418 RTABMAP_PARAM(Odom, AlignWithGround,
bool,
false,
"Align odometry with the ground on initialization.");
421 RTABMAP_PARAM(OdomF2M, MaxSize,
int, 2000,
"[Visual] Local map size: If > 0 (example 5000), the odometry will maintain a local map of X maximum words.");
422 RTABMAP_PARAM(OdomF2M, MaxNewFeatures,
int, 0,
"[Visual] Maximum features (sorted by keypoint response) added to local map from a new key-frame. 0 means no limit.");
423 RTABMAP_PARAM(OdomF2M, ScanMaxSize,
int, 2000,
"[Geometry] Maximum local scan map size.");
424 RTABMAP_PARAM(OdomF2M, ScanSubtractRadius,
float, 0.05,
"[Geometry] Radius used to filter points of a new added scan to local map. This could match the voxel size of the scans.");
425 RTABMAP_PARAM(OdomF2M, ScanSubtractAngle,
float, 45,
uFormat(
"[Geometry] Max angle (degrees) used to filter points of a new added scan to local map (when \"%s\">0). 0 means any angle.", kOdomF2MScanSubtractRadius().c_str()).c_str());
426 #if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM2) 427 RTABMAP_PARAM(OdomF2M, BundleAdjustment,
int, 1,
"Local bundle adjustment: 0=disabled, 1=g2o, 2=cvsba.");
429 RTABMAP_PARAM(OdomF2M, BundleAdjustment,
int, 0,
"Local bundle adjustment: 0=disabled, 1=g2o, 2=cvsba.");
431 RTABMAP_PARAM(OdomF2M, BundleAdjustmentMaxFrames,
int, 10,
"Maximum frames used for bundle adjustment (0=inf or all current frames in the local map).");
434 RTABMAP_PARAM(OdomMono, InitMinFlow,
float, 100,
"Minimum optical flow required for the initialization step.");
435 RTABMAP_PARAM(OdomMono, InitMinTranslation,
float, 0.1,
"Minimum translation required for the initialization step.");
436 RTABMAP_PARAM(OdomMono, MinTranslation,
float, 0.02,
"Minimum translation to add new points to local map. On initialization, translation x 5 is used as the minimum.");
437 RTABMAP_PARAM(OdomMono, MaxVariance,
float, 0.01,
"Maximum variance to add new points to local map.");
440 RTABMAP_PARAM(OdomFovis, FeatureWindowSize,
int, 9,
"The size of the n x n image patch surrounding each feature, used for keypoint matching.");
441 RTABMAP_PARAM(OdomFovis, MaxPyramidLevel,
int, 3,
"The maximum Gaussian pyramid level to process the image at. Pyramid level 1 corresponds to the original image.");
442 RTABMAP_PARAM(OdomFovis, MinPyramidLevel,
int, 0,
"The minimum pyramid level.");
443 RTABMAP_PARAM(OdomFovis, TargetPixelsPerFeature,
int, 250,
"Specifies the desired feature density as a ratio of input image pixels per feature detected. This number is used to control the adaptive feature thresholding.");
444 RTABMAP_PARAM(OdomFovis, FastThreshold,
int, 20,
"FAST threshold.");
445 RTABMAP_PARAM(OdomFovis, UseAdaptiveThreshold,
bool,
true,
"Use FAST adaptive threshold.");
446 RTABMAP_PARAM(OdomFovis, FastThresholdAdaptiveGain,
double, 0.005,
"FAST threshold adaptive gain.");
447 RTABMAP_PARAM(OdomFovis, UseHomographyInitialization,
bool,
true,
"Use homography initialization.");
452 RTABMAP_PARAM(OdomFovis, MaxKeypointsPerBucket,
int, 25,
"");
453 RTABMAP_PARAM(OdomFovis, UseImageNormalization,
bool,
false,
"");
455 RTABMAP_PARAM(OdomFovis, InlierMaxReprojectionError,
double, 1.5,
"The maximum image-space reprojection error (in pixels) a feature match is allowed to have and still be considered an inlier in the set of features used for motion estimation.");
456 RTABMAP_PARAM(OdomFovis, CliqueInlierThreshold,
double, 0.1,
"See Howard's greedy max-clique algorithm for determining the maximum set of mutually consisten feature matches. This specifies the compatibility threshold, in meters.");
457 RTABMAP_PARAM(OdomFovis, MinFeaturesForEstimate,
int, 20,
"Minimum number of features in the inlier set for the motion estimate to be considered valid.");
458 RTABMAP_PARAM(OdomFovis, MaxMeanReprojectionError,
double, 10.0,
"Maximum mean reprojection error over the inlier feature matches for the motion estimate to be considered valid.");
459 RTABMAP_PARAM(OdomFovis, UseSubpixelRefinement,
bool,
true,
"Specifies whether or not to refine feature matches to subpixel resolution.");
460 RTABMAP_PARAM(OdomFovis, FeatureSearchWindow,
int, 25,
"Specifies the size of the search window to apply when searching for feature matches across time frames. The search is conducted around the feature location predicted by the initial rotation estimate.");
461 RTABMAP_PARAM(OdomFovis, UpdateTargetFeaturesWithRefined,
bool,
false,
"When subpixel refinement is enabled, the refined feature locations can be saved over the original feature locations. This has a slightly negative impact on frame-to-frame visual odometry, but is likely better when using this library as part of a visual SLAM algorithm.");
463 RTABMAP_PARAM(OdomFovis, StereoRequireMutualMatch,
bool,
true,
"");
464 RTABMAP_PARAM(OdomFovis, StereoMaxDistEpipolarLine,
double, 1.5,
"");
465 RTABMAP_PARAM(OdomFovis, StereoMaxRefinementDisplacement,
double, 1.0,
"");
469 RTABMAP_PARAM(OdomViso2, RansacIters,
int, 200,
"Number of RANSAC iterations.");
470 RTABMAP_PARAM(OdomViso2, InlierThreshold,
double, 2.0,
"Fundamental matrix inlier threshold.");
471 RTABMAP_PARAM(OdomViso2, Reweighting,
bool,
true,
"Lower border weights (more robust to calibration errors).");
472 RTABMAP_PARAM(OdomViso2, MatchNmsN,
int, 3,
"Non-max-suppression: min. distance between maxima (in pixels).");
473 RTABMAP_PARAM(OdomViso2, MatchNmsTau,
int, 50,
"Non-max-suppression: interest point peakiness threshold.");
474 RTABMAP_PARAM(OdomViso2, MatchBinsize,
int, 50,
"Matching bin width/height (affects efficiency only).");
475 RTABMAP_PARAM(OdomViso2, MatchRadius,
int, 200,
"Matching radius (du/dv in pixels).");
476 RTABMAP_PARAM(OdomViso2, MatchDispTolerance,
int, 2,
"Disparity tolerance for stereo matches (in pixels).");
477 RTABMAP_PARAM(OdomViso2, MatchOutlierDispTolerance,
int, 5,
"Outlier removal: disparity tolerance (in pixels).");
478 RTABMAP_PARAM(OdomViso2, MatchOutlierFlowTolerance,
int, 5,
"Outlier removal: flow tolerance (in pixels).");
479 RTABMAP_PARAM(OdomViso2, MatchMultiStage,
bool,
true,
"Multistage matching (denser and faster).");
480 RTABMAP_PARAM(OdomViso2, MatchHalfResolution,
bool,
true,
"Match at half resolution, refine at full resolution.");
481 RTABMAP_PARAM(OdomViso2, MatchRefinement,
int, 1,
"Refinement (0=none,1=pixel,2=subpixel).");
482 RTABMAP_PARAM(OdomViso2, BucketMaxFeatures,
int, 2,
"Maximal number of features per bucket.");
483 RTABMAP_PARAM(OdomViso2, BucketWidth,
double, 50,
"Width of bucket.");
484 RTABMAP_PARAM(OdomViso2, BucketHeight,
double, 50,
"Height of bucket.");
488 RTABMAP_PARAM(OdomORBSLAM2, Bf,
double, 0.076,
"Fake IR projector baseline (m) used only when stereo is not used.");
489 RTABMAP_PARAM(OdomORBSLAM2, ThDepth,
double, 40.0,
"Close/Far threshold. Baseline times.");
491 RTABMAP_PARAM(OdomORBSLAM2, MaxFeatures,
int, 1000,
"Maximum ORB features extracted per frame.");
492 RTABMAP_PARAM(OdomORBSLAM2, MapSize,
int, 3000,
"Maximum size of the feature map (0 means infinite).");
498 RTABMAP_PARAM(OdomLOAM, Sensor,
int, 2,
"Velodyne sensor: 0=VLP-16, 1=HDL-32, 2=HDL-64E");
499 RTABMAP_PARAM(OdomLOAM, ScanPeriod,
float, 0.1,
"Scan period (s)");
500 RTABMAP_PARAM(OdomLOAM, LinVar,
float, 0.01,
"Linear output variance.");
501 RTABMAP_PARAM(OdomLOAM, AngVar,
float, 0.01,
"Angular output variance.");
502 RTABMAP_PARAM(OdomLOAM, LocalMapping,
bool,
true,
"Local mapping. It adds more time to compute odometry, but accuracy is significantly improved.");
516 RTABMAP_PARAM(OdomMSCKF, PositionStdThreshold,
double, 8.0,
"");
517 RTABMAP_PARAM(OdomMSCKF, RotationThreshold,
double, 0.2618,
"");
518 RTABMAP_PARAM(OdomMSCKF, TranslationThreshold,
double, 0.4,
"");
519 RTABMAP_PARAM(OdomMSCKF, TrackingRateThreshold,
double, 0.5,
"");
520 RTABMAP_PARAM(OdomMSCKF, OptTranslationThreshold,
double, 0,
"");
529 RTABMAP_PARAM(OdomMSCKF, InitCovExRot,
double, 0.00030462,
"");
530 RTABMAP_PARAM(OdomMSCKF, InitCovExTrans,
double, 0.000025,
"");
534 RTABMAP_PARAM(Reg, RepeatOnce,
bool,
true,
"Do a second registration with the output of the first registration as guess. Only done if no guess was provided for the first registration (like on loop closure). It can be useful if the registration approach used can use a guess to get better matches.");
535 RTABMAP_PARAM(Reg, Strategy,
int, 0,
"0=Vis, 1=Icp, 2=VisIcp");
536 RTABMAP_PARAM(Reg, Force3DoF,
bool,
false,
"Force 3 degrees-of-freedom transform (3Dof: x,y and yaw). Parameters z, roll and pitch will be set to 0.");
539 RTABMAP_PARAM(Vis, EstimationType,
int, 1,
"Motion estimation approach: 0:3D->3D, 1:3D->2D (PnP), 2:2D->2D (Epipolar Geometry)");
540 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).");
541 RTABMAP_PARAM(Vis, InlierDistance,
float, 0.1,
uFormat(
"[%s = 0] Maximum distance for feature correspondences. Used by 3D->3D estimation approach.", kVisEstimationType().c_str()));
542 RTABMAP_PARAM(Vis, RefineIterations,
int, 5,
uFormat(
"[%s = 0] Number of iterations used to refine the transformation found by RANSAC. 0 means that the transformation is not refined.", kVisEstimationType().c_str()));
543 RTABMAP_PARAM(Vis, PnPReprojError,
float, 2,
uFormat(
"[%s = 1] PnP reprojection error.", kVisEstimationType().c_str()));
544 RTABMAP_PARAM(Vis, PnPFlags,
int, 0,
uFormat(
"[%s = 1] PnP flags: 0=Iterative, 1=EPNP, 2=P3P", kVisEstimationType().c_str()));
545 #if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM2) 546 RTABMAP_PARAM(Vis, PnPRefineIterations,
int, 0,
uFormat(
"[%s = 1] Refine iterations. Set to 0 if \"%s\" is also used.", kVisEstimationType().c_str(), kVisBundleAdjustment().c_str()));
548 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()));
551 RTABMAP_PARAM(Vis, EpipolarGeometryVar,
float, 0.02,
uFormat(
"[%s = 2] Epipolar geometry maximum variance to accept the transformation.", kVisEstimationType().c_str()));
552 RTABMAP_PARAM(Vis, MinInliers,
int, 20,
"Minimum feature correspondences to compute/accept the transformation.");
553 RTABMAP_PARAM(Vis, Iterations,
int, 300,
"Maximum iterations to compute the transform.");
554 #ifndef RTABMAP_NONFREE 555 #ifdef RTABMAP_OPENCV3 557 RTABMAP_PARAM(Vis, FeatureType,
int, 8,
"0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE.");
559 RTABMAP_PARAM(Vis, FeatureType,
int, 6,
"0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE.");
562 RTABMAP_PARAM(Vis, FeatureType,
int, 6,
"0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE.");
565 RTABMAP_PARAM(Vis, MaxDepth,
float, 0,
"Max depth of the features (0 means no limit).");
566 RTABMAP_PARAM(Vis, MinDepth,
float, 0,
"Min depth of the features (0 means no limit).");
567 RTABMAP_PARAM(Vis, DepthAsMask,
bool,
true,
"Use depth image as mask when extracting features.");
568 RTABMAP_PARAM_STR(Vis, RoiRatios,
"0.0 0.0 0.0 0.0",
"Region of interest ratios [left, right, top, bottom].");
569 RTABMAP_PARAM(Vis, SubPixWinSize,
int, 3,
"See cv::cornerSubPix().");
570 RTABMAP_PARAM(Vis, SubPixIterations,
int, 0,
"See cv::cornerSubPix(). 0 disables sub pixel refining.");
571 RTABMAP_PARAM(Vis, SubPixEps,
float, 0.02,
"See cv::cornerSubPix().");
572 RTABMAP_PARAM(Vis, GridRows,
int, 1,
uFormat(
"Number of rows of the grid used to extract uniformly \"%s / grid cells\" features from each cell.", kVisMaxFeatures().c_str()));
573 RTABMAP_PARAM(Vis, GridCols,
int, 1,
uFormat(
"Number of columns of the grid used to extract uniformly \"%s / grid cells\" features from each cell.", kVisMaxFeatures().c_str()));
574 RTABMAP_PARAM(Vis, CorType,
int, 0,
"Correspondences computation approach: 0=Features Matching, 1=Optical Flow");
575 RTABMAP_PARAM(Vis, CorNNType,
int, 1,
uFormat(
"[%s=0] kNNFlannNaive=0, kNNFlannKdTree=1, kNNFlannLSH=2, kNNBruteForce=3, kNNBruteForceGPU=4. Used for features matching approach.", kVisCorType().c_str()));
576 RTABMAP_PARAM(Vis, CorNNDR,
float, 0.6,
uFormat(
"[%s=0] NNDR: nearest neighbor distance ratio. Used for features matching approach.", kVisCorType().c_str()));
577 RTABMAP_PARAM(Vis, CorGuessWinSize,
int, 20,
uFormat(
"[%s=0] Matching window size (pixels) around projected points when a guess transform is provided to find correspondences. 0 means disabled.", kVisCorType().c_str()));
578 RTABMAP_PARAM(Vis, CorGuessMatchToProjection,
bool,
false,
uFormat(
"[%s=0] Match frame's corners to source's projected points (when guess transform is provided) instead of projected points to frame's corners.", kVisCorType().c_str()));
579 RTABMAP_PARAM(Vis, CorFlowWinSize,
int, 16,
uFormat(
"[%s=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.", kVisCorType().c_str()));
580 RTABMAP_PARAM(Vis, CorFlowIterations,
int, 30,
uFormat(
"[%s=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.", kVisCorType().c_str()));
581 RTABMAP_PARAM(Vis, CorFlowEps,
float, 0.01,
uFormat(
"[%s=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.", kVisCorType().c_str()));
582 RTABMAP_PARAM(Vis, CorFlowMaxLevel,
int, 3,
uFormat(
"[%s=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.", kVisCorType().c_str()));
583 #if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM2) 584 RTABMAP_PARAM(Vis, BundleAdjustment,
int, 1,
"Optimization with bundle adjustment: 0=disabled, 1=g2o, 2=cvsba.");
586 RTABMAP_PARAM(Vis, BundleAdjustment,
int, 0,
"Optimization with bundle adjustment: 0=disabled, 1=g2o, 2=cvsba.");
590 RTABMAP_PARAM(Icp, MaxTranslation,
float, 0.2,
"Maximum ICP translation correction accepted (m).");
591 RTABMAP_PARAM(Icp, MaxRotation,
float, 0.78,
"Maximum ICP rotation correction accepted (rad).");
592 RTABMAP_PARAM(Icp, VoxelSize,
float, 0.0,
"Uniform sampling voxel size (0=disabled).");
593 RTABMAP_PARAM(Icp, DownsamplingStep,
int, 1,
"Downsampling step size (1=no sampling). This is done before uniform sampling.");
594 #ifdef RTABMAP_POINTMATCHER 595 RTABMAP_PARAM(Icp, MaxCorrespondenceDistance,
float, 0.1,
"Max distance for point correspondences.");
597 RTABMAP_PARAM(Icp, MaxCorrespondenceDistance,
float, 0.05,
"Max distance for point correspondences.");
600 RTABMAP_PARAM(Icp, Epsilon,
float, 0,
"Set the transformation epsilon (maximum allowable difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution.");
601 RTABMAP_PARAM(Icp, CorrespondenceRatio,
float, 0.1,
"Ratio of matching correspondences to accept the transform.");
602 #ifdef RTABMAP_POINTMATCHER 603 RTABMAP_PARAM(Icp, PointToPlane,
bool,
true,
"Use point to plane ICP.");
605 RTABMAP_PARAM(Icp, PointToPlane,
bool,
false,
"Use point to plane ICP.");
607 RTABMAP_PARAM(Icp, PointToPlaneK,
int, 5,
"Number of neighbors to compute normals for point to plane if the cloud doesn't have already normals.");
608 RTABMAP_PARAM(Icp, PointToPlaneRadius,
float, 1.0,
"Search radius to compute normals for point to plane if the cloud doesn't have already normals.");
609 RTABMAP_PARAM(Icp, PointToPlaneMinComplexity,
float, 0.02,
"Minimum structural complexity (0.0=low, 1.0=high) of the scan to do point to plane registration, otherwise point to point registration is done instead.");
612 #ifdef RTABMAP_POINTMATCHER 613 RTABMAP_PARAM(Icp, PM,
bool,
true,
"Use libpointmatcher for ICP registration instead of PCL's implementation.");
615 RTABMAP_PARAM(Icp, PM,
bool,
false,
"Use libpointmatcher for ICP registration instead of PCL's implementation.");
617 RTABMAP_PARAM_STR(Icp, PMConfig,
"",
uFormat(
"Configuration file (*.yaml) used by libpointmatcher. Note that data filters set for libpointmatcher are done after filtering done by rtabmap (i.e., %s, %s), so make sure to disable those in rtabmap if you want to use only those from libpointmatcher. Parameters %s, %s and %s are also ignored if configuration file is set.", kIcpVoxelSize().c_str(), kIcpDownsamplingStep().c_str(), kIcpIterations().c_str(), kIcpEpsilon().c_str(), kIcpMaxCorrespondenceDistance().c_str()).c_str());
618 RTABMAP_PARAM(Icp, PMMatcherKnn,
int, 1,
"KDTreeMatcher/knn: number of nearest neighbors to consider it the reference. For convenience when configuration file is not set.");
619 RTABMAP_PARAM(Icp, PMMatcherEpsilon,
float, 0.0,
"KDTreeMatcher/epsilon: approximation to use for the nearest-neighbor search. For convenience when configuration file is not set.");
620 RTABMAP_PARAM(Icp, PMOutlierRatio,
float, 0.95,
"TrimmedDistOutlierFilter/ratio: For convenience when configuration file is not set. For kinect-like point cloud, use 0.65.");
629 RTABMAP_PARAM(
Stereo, OpticalFlow,
bool,
true,
"Use optical flow to find stereo correspondences, otherwise a simple block matching approach is used.");
630 RTABMAP_PARAM(
Stereo, SSD,
bool,
true,
uFormat(
"[%s=false] Use Sum of Squared Differences (SSD) window, otherwise Sum of Absolute Differences (SAD) window is used.", kStereoOpticalFlow().c_str()));
644 RTABMAP_PARAM(Grid, FromDepth,
bool,
true,
"Create occupancy grid from depth image(s), otherwise it is created from laser scan.");
645 RTABMAP_PARAM(Grid, DepthDecimation,
int, 4,
uFormat(
"[%s=true] Decimation of the depth image before creating cloud. Negative decimation is done from RGB size instead of depth size (if depth is smaller than RGB, it may be interpolated depending of the decimation value).", kGridDepthDecimation().c_str()));
646 RTABMAP_PARAM(Grid, RangeMin,
float, 0.0,
"Minimum range from sensor.");
647 RTABMAP_PARAM(Grid, RangeMax,
float, 5.0,
"Maximum range from sensor. 0=inf.");
648 RTABMAP_PARAM_STR(Grid, DepthRoiRatios,
"0.0 0.0 0.0 0.0",
uFormat(
"[%s=true] Region of interest ratios [left, right, top, bottom].", kGridFromDepth().c_str()));
649 RTABMAP_PARAM(Grid, FootprintLength,
float, 0.0,
"Footprint length used to filter points over the footprint of the robot.");
650 RTABMAP_PARAM(Grid, FootprintWidth,
float, 0.0,
"Footprint width used to filter points over the footprint of the robot. Footprint length should be set.");
651 RTABMAP_PARAM(Grid, FootprintHeight,
float, 0.0,
"Footprint height used to filter points over the footprint of the robot. Footprint length and width should be set.");
652 RTABMAP_PARAM(Grid, ScanDecimation,
int, 1,
uFormat(
"[%s=false] Decimation of the laser scan before creating cloud.", kGridFromDepth().c_str()));
653 RTABMAP_PARAM(Grid, CellSize,
float, 0.05,
"Resolution of the occupancy grid.");
654 RTABMAP_PARAM(Grid, PreVoxelFiltering,
bool,
true,
uFormat(
"Input cloud is downsampled by voxel filter (voxel size is \"%s\") before doing segmentation of obstacles and ground.", kGridCellSize().c_str()));
655 RTABMAP_PARAM(Grid, MapFrameProjection,
bool,
false,
"Projection in map frame. On a 3D terrain and a fixed local camera transform (the cloud is created relative to ground), you may want to disable this to do the projection in robot frame instead.");
656 RTABMAP_PARAM(Grid, NormalsSegmentation,
bool,
true,
"Segment ground from obstacles using point normals, otherwise a fast passthrough is used.");
657 RTABMAP_PARAM(Grid, MaxObstacleHeight,
float, 0.0,
"Maximum obstacles height (0=disabled).");
658 RTABMAP_PARAM(Grid, MinGroundHeight,
float, 0.0,
"Minimum ground height (0=disabled).");
659 RTABMAP_PARAM(Grid, MaxGroundHeight,
float, 0.0,
uFormat(
"Maximum ground height (0=disabled). Should be set if \"%s\" is false.", kGridNormalsSegmentation().c_str()));
660 RTABMAP_PARAM(Grid, MaxGroundAngle,
float, 45,
uFormat(
"[%s=true] Maximum angle (degrees) between point's normal to ground's normal to label it as ground. Points with higher angle difference are considered as obstacles.", kGridNormalsSegmentation().c_str()));
661 RTABMAP_PARAM(Grid, NormalK,
int, 20,
uFormat(
"[%s=true] K neighbors to compute normals.", kGridNormalsSegmentation().c_str()));
662 RTABMAP_PARAM(Grid, ClusterRadius,
float, 0.1,
uFormat(
"[%s=true] Cluster maximum radius.", kGridNormalsSegmentation().c_str()));
663 RTABMAP_PARAM(Grid, MinClusterSize,
int, 10,
uFormat(
"[%s=true] Minimum cluster size to project the points.", kGridNormalsSegmentation().c_str()));
664 RTABMAP_PARAM(Grid, FlatObstacleDetected,
bool,
true,
uFormat(
"[%s=true] Flat obstacles detected.", kGridNormalsSegmentation().c_str()));
665 #ifdef RTABMAP_OCTOMAP 666 RTABMAP_PARAM(Grid, 3D,
bool,
true,
uFormat(
"A 3D occupancy grid is required if you want an OctoMap (3D ray tracing). Set to false if you want only a 2D map, the cloud will be projected on xy plane. A 2D map can be still generated if checked, but it requires more memory and time to generate it. Ignored if laser scan is 2D and \"%s\" is false.", kGridFromDepth().c_str()));
668 RTABMAP_PARAM(Grid, 3D,
bool,
false,
uFormat(
"A 3D occupancy grid is required if you want an OctoMap (3D ray tracing). Set to false if you want only a 2D map, the cloud will be projected on xy plane. A 2D map can be still generated if checked, but it requires more memory and time to generate it. Ignored if laser scan is 2D and \"%s\" is false.", kGridFromDepth().c_str()));
670 RTABMAP_PARAM(Grid, GroundIsObstacle,
bool,
false,
uFormat(
"[%s=true] Ground segmentation (%s) is ignored, all points are obstacles. Use this only if you want an OctoMap with ground identified as an obstacle (e.g., with an UAV).", kGrid3D().c_str(), kGridNormalsSegmentation().c_str()));
671 RTABMAP_PARAM(Grid, NoiseFilteringRadius,
float, 0.0,
"Noise filtering radius (0=disabled). Done after segmentation.");
672 RTABMAP_PARAM(Grid, NoiseFilteringMinNeighbors,
int, 5,
"Noise filtering minimum neighbors.");
673 RTABMAP_PARAM(Grid, Scan2dUnknownSpaceFilled,
bool,
false,
uFormat(
"Unknown space filled. Only used with 2D laser scans. Use %s to set maximum range if laser scan max range is to set.", kGridRangeMax().c_str()));
674 RTABMAP_PARAM(Grid, RayTracing,
bool,
false,
uFormat(
"Ray tracing is done for each occupied cell, filling unknown space between the sensor and occupied cells. If %s=true, RTAB-Map should be built with OctoMap support, otherwise 3D ray tracing is ignored.", kGrid3D().c_str()));
676 RTABMAP_PARAM(GridGlobal, FullUpdate,
bool,
true,
"When the graph is changed, the whole map will be reconstructed instead of moving individually each cells of the map. Also, data added to cache won't be released after updating the map. This process is longer but more robust to drift that would erase some parts of the map when it should not.");
677 RTABMAP_PARAM(GridGlobal, UpdateError,
float, 0.01,
"Graph changed detection error (m). Update map only if poses in new optimized graph have moved more than this value.");
678 RTABMAP_PARAM(GridGlobal, FootprintRadius,
float, 0.0,
"Footprint radius (m) used to clear all obstacles under the graph.");
679 RTABMAP_PARAM(GridGlobal, MinSize,
float, 0.0,
"Minimum map size (m).");
680 RTABMAP_PARAM(GridGlobal, Eroded,
bool,
false,
"Erode obstacle cells.");
681 RTABMAP_PARAM(GridGlobal, MaxNodes,
int, 0,
"Maximum nodes assembled in the map starting from the last node (0=unlimited).");
682 RTABMAP_PARAM(GridGlobal, OccupancyThr,
float, 0.5,
"Occupancy threshold (value between 0 and 1).");
683 RTABMAP_PARAM(GridGlobal, ProbHit,
float, 0.7,
"Probability of a hit (value between 0.5 and 1).");
684 RTABMAP_PARAM(GridGlobal, ProbMiss,
float, 0.4,
"Probability of a miss (value between 0 and 0.5).");
685 RTABMAP_PARAM(GridGlobal, ProbClampingMin,
float, 0.1192,
"Probability clamping minimum (value between 0 and 1).");
686 RTABMAP_PARAM(GridGlobal, ProbClampingMax,
float, 0.971,
"Probability clamping maximum (value between 0 and 1).");
704 static std::string getType(
const std::string & paramKey);
710 static std::string getDescription(
const std::string & paramKey);
712 static bool parse(
const ParametersMap & parameters,
const std::string & key,
bool & value);
713 static bool parse(
const ParametersMap & parameters,
const std::string & key,
int & value);
714 static bool parse(
const ParametersMap & parameters,
const std::string & key,
unsigned int & value);
715 static bool parse(
const ParametersMap & parameters,
const std::string & key,
float & value);
716 static bool parse(
const ParametersMap & parameters,
const std::string & key,
double & value);
717 static bool parse(
const ParametersMap & parameters,
const std::string & key, std::string & value);
718 static void parse(
const ParametersMap & parameters, ParametersMap & parametersOut);
721 static ParametersMap parseArguments(
int argc,
char * argv[],
bool onlyParameters =
false);
723 static std::string getVersion();
724 static std::string getDefaultDatabaseName();
726 static std::string
serialize(
const ParametersMap & parameters);
727 static ParametersMap
deserialize(
const std::string & parameters);
729 static bool isFeatureParameter(
const std::string & param);
730 static ParametersMap getDefaultOdometryParameters(
bool stereo =
false,
bool vis =
true,
bool icp =
false);
731 static ParametersMap getDefaultParameters(
const std::string & group);
732 static ParametersMap filterParameters(
const ParametersMap & parameters,
const std::string & group);
734 static void readINI(
const std::string & configFile, ParametersMap & parameters,
bool modifiedOnly =
false);
735 static void writeINI(
const std::string & configFile,
const ParametersMap & parameters);
741 static const std::map<std::string, std::pair<bool, std::string> > & getRemovedParameters();
746 static const ParametersMap & getBackwardCompatibilityMap();
748 static std::string createDefaultWorkingDirectory();
#define RTABMAP_PARAM_STR(PREFIX, NAME, DEFAULT_VALUE, DESCRIPTION)
void serialize(const Eigen::Matrix< S, T, U > &mat, std::ostream &strm)
std::pair< std::string, std::string > ParametersPair
std::map< std::string, std::string > ParametersMap
static ParametersMap descriptions_
static ParametersMap backwardCompatibilityMap_
Some conversion functions.
static Parameters instance_
Transform RTABMAP_EXP 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)
static ParametersMap parameters_
static const ParametersMap & getDefaultParameters()
static ParametersMap parametersType_
#define RTABMAP_PARAM(PREFIX, NAME, TYPE, DEFAULT_VALUE, DESCRIPTION)
std::string UTILITE_EXP uFormat(const char *fmt,...)
static std::map< std::string, std::pair< bool, std::string > > removedParameters_
void deserialize(std::istream &strm, Eigen::Matrix< S, T, U > *mat)