Range Image Registration

Multiple 3D scans are necessary to digitalize environments without occlusions. To create a correct and consistent model, the scans have to be merged in one coordinate system. This process is called registration. If the localization of the robot with the 3D scanner were precise, the registration could be done directly by the robot pose. However, due to the unprecise robot sensors, the self localization is erroneous, so the geometric structure of overlapping 3D scans has to be considered for registration.

Scan matching approaches can be classified into two categories:

Matching as an optimization problem

uses a cost function for the quality of the alignment of the scans. The range images are registered by determining the rigid transformation (rotation and translation) which minimizes the cost function.

Feature based matching

extracts distinguishing features of the range images and uses corresponding features for calculating the alignment of the scans.

The matching of 3D scans can either operate on the whole three-dimensional scan point set or can be reduced to the problem of scan matching in 2D by extracting, e.g., a horizontal plane of fixed height from both scans, merging these 2D scans and applying the resulting translation and rotation matrix to all points of the corresponding 3D scan.

Matching of complete 3D scans has the advantage of having a larger set of attributes (either pure data points or extracted features) to compare the scans. This results in higher precision and lowers the possibility of running into a local minimum. Furthermore, using three dimensions enables the robot control software to recognize changes of height and self rotation of the robot and to take them into account. This is essential for robots driving cross country and in pipes.