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Parameters: Changed Grid/FromDepth to Grid/Sensor to add a new choice to use both scan and depth for local grids. Increased version to 0.20.15.

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matlabbe
2021-10-29 20:05:12 -04:00
parent 1886f99cbf
commit 7c5acd8970
9 changed files with 418 additions and 332 deletions
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6
corelib/include/rtabmap/core/OccupancyGrid.h
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@@ -58,7 +58,7 @@ public:
float getCellSize() const {return cellSize_;}
void setCloudAssembling(bool enabled);
float getMinMapSize() const {return minMapSize_;}
bool isGridFromDepth() const {return occupancyFromDepth_;}
bool isGridFromDepth() const {return occupancySensor_;}
bool isFullUpdate() const {return fullUpdate_;}
float getUpdateError() const {return updateError_;}
bool isMapFrameProjection() const {return projMapFrame_;}
@@ -81,7 +81,7 @@ public:
cv::Mat & groundCells,
cv::Mat & obstacleCells,
cv::Mat & emptyCells,
cv::Point3f & viewPoint) const;
cv::Point3f & viewPoint);
void createLocalMap(
const LaserScan & cloud,
@@ -118,7 +118,7 @@ private:
int scanDecimation_;
float cellSize_;
bool preVoxelFiltering_;
bool occupancyFromDepth_;
int occupancySensor_;
bool projMapFrame_;
float maxObstacleHeight_;
int normalKSearch_;

10
corelib/include/rtabmap/core/Parameters.h
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@@ -723,15 +723,15 @@ class RTABMAP_EXP Parameters
#endif
// Occupancy Grid
RTABMAP_PARAM(Grid, FromDepth, bool, true, "Create occupancy grid from depth image(s), otherwise it is created from laser scan.");
RTABMAP_PARAM(Grid, Sensor, int, 1, "Create occupancy grid from selected sensor: 0=laser scan, 1=depth image(s) or 2=both laser scan and depth image(s).");
RTABMAP_PARAM(Grid, DepthDecimation, unsigned int, 4, uFormat("[%s=true] Decimation of the depth image before creating cloud.", kGridDepthDecimation().c_str()));
RTABMAP_PARAM(Grid, RangeMin, float, 0.0, "Minimum range from sensor.");
RTABMAP_PARAM(Grid, RangeMax, float, 5.0, "Maximum range from sensor. 0=inf.");
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()));
RTABMAP_PARAM_STR(Grid, DepthRoiRatios, "0.0 0.0 0.0 0.0", uFormat("[%s>=1] Region of interest ratios [left, right, top, bottom].", kGridSensor().c_str()));
RTABMAP_PARAM(Grid, FootprintLength, float, 0.0, "Footprint length used to filter points over the footprint of the robot.");
RTABMAP_PARAM(Grid, FootprintWidth, float, 0.0, "Footprint width used to filter points over the footprint of the robot. Footprint length should be set.");
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.");
RTABMAP_PARAM(Grid, ScanDecimation, int, 1, uFormat("[%s=false] Decimation of the laser scan before creating cloud.", kGridFromDepth().c_str()));
RTABMAP_PARAM(Grid, ScanDecimation, int, 1, uFormat("[%s=0 or 2] Decimation of the laser scan before creating cloud.", kGridSensor().c_str()));
RTABMAP_PARAM(Grid, CellSize, float, 0.05, "Resolution of the occupancy grid.");
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()));
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.");
@@ -745,9 +745,9 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Grid, MinClusterSize, int, 10, uFormat("[%s=true] Minimum cluster size to project the points.", kGridNormalsSegmentation().c_str()));
RTABMAP_PARAM(Grid, FlatObstacleDetected, bool, true, uFormat("[%s=true] Flat obstacles detected.", kGridNormalsSegmentation().c_str()));
#ifdef RTABMAP_OCTOMAP
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()));
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 0.", kGridSensor().c_str()));
#else
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()));
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 0.", kGridSensor().c_str()));
#endif
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()));
RTABMAP_PARAM(Grid, NoiseFilteringRadius, float, 0.0, "Noise filtering radius (0=disabled). Done after segmentation.");