mbicp

ScanMatching. More...

ScanMatching.

This driver implements the metric-based ICP scan-matching algorithm.

J. Minguez, L. Montesano, and F. Lamiraux, "Metric-based iterative closest point scan matching for sensor displacement estimation," IEEE Transactions on Robotics, vol. 22, no. 5, pp. 1047 1054, 2006.

Compile-time dependencies

• none

Provides

• interface_position2d

Requires

• interface_position2d : source of pose and velocity information
• interface_laser : Pose-stamped laser scans (subtype PLAYER_LASER_DATA_SCANPOSE)

Configuration requests

• none

Configuration file options

• max_laser_range (float)
  • Default: 7.9 m
  • Maximum laser range.
• laserPose_x (float)
  • Default: 0.16 m
  • Offset of the laser on the edge x (in the robot's system of reference).
• laserPose_y (float)
  • Default: 0.0 m
  • Offset of the laser on the edge y (in the robot's system of reference).
• laserPose_th (float)
  • Default: 0.0 rad
  • Offset of the laser on th (in the robot's system of reference).
• radial_window (float)
  • Default: 0.3 m
  • Maximum distance difference between points of different scans. Points with greater Br cannot be correspondent (eliminate spurius asoc.).
• angular_window (float)
  • Default: 0.523333333 rad
  • Maximum angle diference between points of different scans. Points with greater Bw cannot be correspondent (eliminate spurius asoc.).
• L (float)
  • Default: 3.00
  • Value of the metric. When L tends to infinity you are using the standart ICP. When L tends to 0 you use the metric (more importance to rotation), when L tends to infinity you are using Euclidian metric.
• laserStep (integer)
  • Default: 1
  • Selects points of each scan with an step laserStep. When laserStep=1 uses all the points of the scans When laserStep=2 uses one each two ... This is an speed up parameter.
• MaxDistInter (float)
  • Default: 0.5 m
  • Maximum distance to interpolate between points in the ref scan. Consecutive points with less Euclidean distance than MaxDistInter are considered to be a segment.
• filter (float)
  • Default: 0.95
  • In [0,1] sets the % of asociations NOT considered spurious. E.g. if filter=0.9 you use 90% of the associations. The associations are ordered by distance and the (1-filter) with greater distance are not used. This type of filtering is called "trimmed-ICP".
• ProjectionFilter (int)
  • Default: 1
  • Eliminate the points that cannot be seen given the two scans (see Lu&Millios 97). It works well for angles < 45 deg. 1 : activates the filter. 0 : desactivates the filter.
• AsocError (float)
  • Default: 0.1
  • In [0,1]. Sets the % of minimun associations to run the algorithm. One way to check if the algorithm diverges is to supervise if the number of associatios goes below a thresold. When the number of associations is below AsocError, the main function will return error in associations step.
• MaxIter (int)
  • Default: 50
  • Sets the maximum number of iterations for the algorithm to exit. The more iterations, the more chance you give the algorithm to be more accurate.
• errorRatio (float)
  • Default: 0.0001 m
  • In [0,1] sets the maximum error ratio between iterations to exit. In iteration K, let be errorK the residual of the minimization. Error_th=(errorK-1/errorK). When error_th tends to 1 more precise is the solution of the scan matching.
• IterSmoothConv (int)
  • Default: 2
  • Number of consecutive iterations that satisfity the error criteria (the two above criteria) (error_th) OR (errorx_out && errory_out && errt_out). With this parameter >1 avoids random solutions and estabilices the algorithm.
• errx_out (float)
  • Default: 0.0001 m
  • Minimum error in x of the asociations to exit. In each iteration, the error is the residual of the minimization in each component. The condition is (errorKx<errx_out && errorKx<erry_out && errorKx<errt_out). When errorK tends to 0 the more precise is the solution of the scan matching
• erry_out (float)
  • Default: 0.0001 m
  • Minimum error in x of the asociations to exit. In each iteration, the error is the residual of the minimization in each component. The condition is (errorKx<errx_out && errorKx<erry_out && errorKx<errt_out). When errorK tends to 0 the more precise is the solution of the scan matching
• errt_out (float)
  • Default: 0.0001 m
  • Minimum error in x of the asociations to exit. In each iteration, the error is the residual of the minimization in each component. The condition is (errorKx<errx_out && errorKx<erry_out && errorKx<errt_out). When errorK tends to 0 the more precise is the solution of the scan matching

Example

driver
(
  name "mbicp"
  provides ["position2d:1"]
  requires ["position2d:0" "laser:1"]

  max_laser_range               7.9
  laserPose_x                   0.16
  laserPose_y                   0
  laserPose_th                  0
  
  radial_window                 0.3    
  angular_window                0.523333333     
  
  L                             3.00    
  laserStep                     1       
  MaxDistInter                  0.5     
  filter                        0.95    
  ProjectionFilter              1       
  AsocError                     0.1     
  MaxIter                       50      
  
  errorRatio                    0.0001  
  errx_out                      0.0001  
  erry_out                      0.0001  
  errt_out                      0.0001  
  IterSmoothConv                2       
)

Author

Javier Minguez (underlying algorithm)