Register two point clouds using NDT algorithm

returns the rigid transformation that registers the moving point cloud with the
fixed point cloud. The point clouds are voxelized into cubes of size
`tform`

= pcregisterndt(`moving`

,`fixed`

,`gridStep`

)`gridStep`

.

The registration algorithm is based on the normal-distributions transform (NDT)
algorithm [1]
[2]. Best performance of
this iterative process requires adjusting properties for your data. To improve
accuracy and efficiency of registration, consider downsampling the point clouds by
using `pcdownsample`

before using
`pcregisterndt`

.

`[___] = pcregisterndt(`

uses additional options specified by one or more `moving`

,`fixed`

,`gridStep`

,`Name,Value`

)`Name,Value`

pair arguments.

[1] Biber, P., and W. Straßer.
“The Normal Distributions Transform: A New Approach to Laser Scan
Matching.” *Proceedings of IEEE/RSJ International Conference on
Intelligent Robots and Systems (IROS)*. Las Vegas, NV. Vol. 3, November
2003, pp. 2743–2748.

[2] Magnusson, M. “The Three-Dimensional Normal-Distributions Transform — an Efficient Representation for Registration, Surface Analysis, and Loop Detection.” Ph.D. Thesis. Örebro University, Örebro, Sweden, 2013.

`pcdenoise`

|`pcdownsample`

|`pcfitplane`

|`pcmerge`

|`pcregistercpd`

|`pcregistericp`

|`pcshow`

|`pcshowpair`

|`pctransform`