locan.data.register.register_icp#

locan.data.register.register_icp(locdata, other_locdata, matrix=None, offset=None, pre_translation=None, max_correspondence_distance=1000, max_iteration=10000, verbose=True)[source]#

Register points or coordinates in locdata by an “Iterative Closest Point” algorithm using open3d.

Parameters:
  • locdata (Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]], LocData]) – Localization data representing the source on which to perform the manipulation.

  • other_locdata (Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]], LocData]) – Localization data representing the target.

  • matrix (Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]], None]) – Transformation matrix with shape (d, d) used as initial value. If None the unit matrix is used.

  • offset (Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]], None]) – Translation vector with shape (d,) used as initial value. If None a vector of zeros is used.

  • pre_translation (Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], bool, int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]], None]) – Values for translation of coordinates before registration.

  • max_correspondence_distance (float) – Threshold distance for the icp algorithm. Parameter is passed to open3d algorithm.

  • max_iteration (int) – Maximum number of iterations. Parameter is passed to open3d algorithm.

  • verbose (bool) – Flag indicating if transformation results are printed out.

Returns:

Matrix and offset representing the optimized transformation.

Return type:

Transformation