Add a part of the new rigid registration method [FRICP]

[yaoyx689]

Hi, thanks for the suggestions of the contributor (#6061 (comment)), I added a class, TransformationEstimationPointToPointRobust, which contains the implementation of the robust ICP part of the FRICP (https://github.com/yaoyx689/Fast-Robust-ICP).

Compared with TransformationEstimation, I added a parameter setting function, because its adaptive setting is very important for the results. If there is no additional setting for the parameter, I define a default setting.

If possible, I hope to add a FastRobustIterativeClosestPoint class later, similar to IterativeClosestPoint, to perform adaptive parameter adjustment and pass it into the TransformationEstimationPointToPointRobust class.

Furthermore, for Anderson acceleration, it is not enough to just create an accelerated class of TransformationEstimation. The iterative process needs to be modified. If possible, these parts can also be organized in FastRobustIterativeClosestPoint.