Name

Mapper_MRPT

Brief

Mapper RTC using MRPT (Mobile Robot Programming Toolkit)

Description

RT-component for SLAM (Simaltaneously Localization and Mapping) algorithm using MRPT (Mobile Robot Programming Toolkit). If you want to know about MRPT, see http://mrpt.org This RT-Component supports only 3 patterns of ICP SLAM. (Actually MRPT supports other types of SLAM). Use with NavigationManager, and Mobile Robot which has common interface for mobile robot. To build this component, please install mrpt-1.3.0. In windows, binary installing is recommended. Please see official website of mrpt.

License

GPL

Image

Language

C++

URL

https://github.com/sugarsweetrobotics/Mapper_MRPT.git

Platform

[‘win’, ‘ubuntu’]

Data In Ports

Name	Type	Unit	Description
range	RTC::RangeData		Input for Ranger Data (LiDAR sensors.)
odometry	RTC::TimedPose2D		Input for odometry of mobile robot.

Data Out Ports

Name	Type	Unit	Description
estimatedPose	RTC::TimedPose2D	meter, rad	Estimated pose of robot with SLAM algorithm (ICP)

Service Ports

gridMapper

This port provides the services for Mapper. Please see MobileRobot.idl to know more about the interface. Ths port provides OGMapper service.

Name	Direction	Type	Description
OGMapper	Provided	RTC::OGMapper	This port provides the services for Mapper. Please see MobileRobot.idl to know more about the interface. Ths port provides OGMapper service.

Configurations

Name	Type	Default	Unit	Description
debug	int	0		For Debug, set 1 to get verbosity output on console.
start_map_update_in_activated	string	false		If true,
ICP_algorithm	string	icpClassic		Select algorithm of ICP mapping. icpClassic, icpLevenbergMarquardt, icpIKF
ICP_onlyClosestCorrespondences	string	true		The usual approach: to consider only the closest correspondence for each local point (Default to true)
ICP_onlyUniqueRobust	string	false		Apart of “onlyClosestCorrespondences=true”, if this option is enabled only the closest correspondence for each reference point will be kept (default=false).
ICP_maxIterations	unsigned int	80		Maximum number of iterations to run.
ICP_minAbsStep_trans	float	0.000001		If the correction in all translation coordinates (X,Y,Z) is below this threshold (in meters), iterations are terminated (Default:1e-6)
ICP_minAbsStep_rot	float	0.000001		If the correction in all rotation coordinates (yaw,pitch,roll) is below this threshold (in radians), iterations are terminated (Default:1e-6)
ICP_thresholdDist	float	0.2		Initial threshold distance for two points to become a correspondence.
ICP_thresholdAng	float	0.1745		Initial threshold distance for two points to become a correspondence.
ICP_ALFA	float	0.8		The scale factor for threshold everytime convergence is achieved.
ICP_smallestThresholdDist	float	0.05		The size for threshold such that iterations will stop, since it is considered precise enough.
ICP_covariance_varPoints	float	0.0004		This is the normalization constant \sigma^2_p that is used to scale the whole 3×3 covariance. This has a default value of (0.02)^2 , that is, a 2cm sigma.
ICP_doRANSAC	string	false		Perform a RANSAC step after the ICP convergence, to obtain a better estimation of the pose PDF.
ICP_ransac_nSimulations	unsigned int	100		RANSAC-step options
ICP_ransac_minSetSize	unsigned int	5		RANSAC-step options
ICP_ransac_maxSetSize	unsigned int	20		RANSAC-step options
ICP_ransac_mahalanobisDistanceThreshold	float	3.0		RANSAC-step options
ICP_ransac_normalizationStd	float	0.2		RANSAC-step option: The standard deviation in X,Y of landmarks/points which are being matched (used to compute covariances in the SoG)
ICP_ransac_fuseByCorrsMatch	string	false		RANSAC-step option: The standard deviation in X,Y of landmarks/points which are being matched (used to compute covariances in the SoG)
ICP_ransac_fuseMaxDiffXY	float	0.01		RANSAC-step option: The standard deviation in X,Y of landmarks/points which are being matched (used to compute covariances in the SoG)
ICP_ransac_fuseMaxDiffPhi	float	0.001745		RANSAC-step option: The standard deviation in X,Y of landmarks/points which are being matched (used to compute covariances in the SoG)
ICP_kernel_rho	float	0.07		Cauchy kernel rho, for estimating the optimal transformation covariance, in meters (default = 0.07m).
ICP_use_kernel	string	true		Whether to use kernel_rho to smooth distances, or use distances directly (default=true)
ICP_Axy_aprox_derivatives	float	0.05		The size of the perturbance in x & y used to estimate the Jacobians of the square error (in LM & IKF methods, default=0.05).
ICP_LM_initial_lambda	float	0.0001		The initial value of the lambda parameter in the LM method (default=1e-4).
ICP_skip_cov_calculation	string	false		Skip the computation of the covariance (saves some time) (default=false)
ICP_skip_quality_calculation	string	true		Skip the (sometimes) expensive evaluation of the term ‘quality’ at ICP output (Default=true)
ICP_corresponding_points_decimation	unsigned int	5		Decimation of the point cloud being registered against the reference one (default=5) – set to 1 to have the older (MRPT <0.9.5) behavior of not approximating ICP by ignoring the correspondence of some points. The speed-up comes from a decimation of the number of KD-tree queries, the most expensive step in ICP.
ICP_matchAgainstTheGrid	string	0		(default:false) Match against the occupancy grid or the points map? The former is quicker but less precise.
ICP_insertionLinDistance	double	0.5	meter	Minimum robot linear (m) displacement for a new observation to be inserted in the map.
ICP_insertionAngDistance	double	0.8	rad	Minimum robot angular (rad, deg when loaded from the .ini) displacement for a new observation to be inserted in the map.
ICP_localizationLinDistance	double	0.5	meter	Minimum robot linear (m) displacement for a new observation to be used to do ICP-based localization (otherwise, dead-reckon with odometry).
ICP_localizationAngDistance	double	0.8	rad	Minimum robot angular (rad, deg when loaded from the .ini) displacement for a new observation to be used to do ICP-based localization (otherwise, dead-reckon with odometry).
ICP_minICPgoodnessToAccept	float	0.40		Minimum ICP goodness (0,1) to accept the resulting corrected position (default: 0.40)
MAP_min_x	float	-10.0		Initial size of Occupancy Grid Map
MAP_max_x	float	10.0	meter	Initial size of Occupancy Grid Map
MAP_min_y	float	-10.0	meter	Initial size of Occupancy Grid Map
MAP_max_y	float	10.0	meter	Initial size of Occupancy Grid Map
MAP_resolution	float	0.05	meter	Resolution of Grid Map. Length of the grid
MAP_insertion_mapAltitude	float	0.0	meter	The altitude (z-axis) of 2D scans (within a 0.01m tolerance) for they to be inserted in this map!
MAP_insertion_useMapAltitude	string	false		The parameter “mapAltitude” has effect while inserting observations in the grid only if this is true.
MAP_insertion_maxDistanceInsertion	float	15		The largest distance at which cells will be updated (Default 15 meters)
MAP_insertion_maxOccupancyUpdateCertainty	float	0.55		A value in the range [0.5,1] used for updating cell with a bayesian approach (default 0.8)
MAP_insertion_considerInvalidRangesAsFreeSpace	string	true		If set to true (default), invalid range values (no echo rays) as consider as free space until “maxOccupancyUpdateCertainty”, but ONLY when the previous and next rays are also an invalid ray.
MAP_insertion_decimation	unsigned short int	1		Specify the decimation of the range scan (default=1 : take all the range values!)
MAP_insertion_horizontalTolerance	float	0		The tolerance in rads in pitch & roll for a laser scan to be considered horizontal, then processed by calls to this class (default=0).
MAP_insertion_CFD_features_gaussian_size	float	1		Gaussian sigma of the filter used in getAsImageFiltered (for features detection) (Default=1) (0:Disabled)
MAP_insertion_CFD_features_median_size	float	3		Size of the Median filter used in getAsImageFiltered (for features detection) (Default=3) (0:Disabled)
MAP_insertion_wideningBeamsWithDistance	string	false		Enabled: Rays widen with distance to approximate the real behavior of lasers, disabled: insert rays as simple lines (Default=false)
initial_pose_x	double	0.0		Initial Pose of Robot
initial_pose_y	double	0.0	meter	Initial Pose of Robot
initial_pose_phi	double	0.0	rad	Initial Pose of Robot

How To Build

Linux
  $ git clone https://github.com/sugarsweetrobotics/Mapper_MRPT.git
  $ cd Mapper_MRPT
  $ mkdir build
  $ cd build
  $ cmake ../
  $ make
Windows
  Download ZIP file from the website, and use CMake to generate VC2010 project.
  Then, open the project and build it.

How To Build in wasanbon

  $ wasanbon-admin.py package create Mapper_MRPT_test_project # You can also use other preinstalled package 
  $ wasanbon-cd Mapper_MRPT_test_project
  $ ./mgr.py repository clone Mapper_MRPT
  $ ./mgr.py rtc build Mapper_MRPT
  $ ./mgr.py rtc run Mapper_MRPT # To Run RTC

Profile Status

Not available

Build Status

Build in Windows

Success (2015-01-23 10:25:21.799000)

Build in OSX

Not available

Build in Linux

Failed (2015-01-22 20:35:05.493615)

Copyright

Sugar Sweet Robotics