LAUSR

One-off construction is characterized by a multiplicity of manual manufacturing processes whereby it is based on consistent use of digital models. Since the actual state of construction does not match the digital models without manually updating them, the authors propose a method to automatically detect deviations and reposition the model data according to reality. The first essential method is based on the “Segmentation of Unorganized Points and Recognition of Simple Algebraic Surfaces” presented by Marek Vanco (2003). The second method is the customization of the iterative closest point (ICP) algorithm. The authors present the overall structure of the implemented software, based on open source and relate it to the general reverse engineering (RE) framework by Buonamici et al. (2017). A highlight will be given on.• The general architecture of the software prototype.• A customized segmentation and clustering of unorganized points and recognition of simple algebraic surfaces.• The deviation analysis with a customized iterative closest point (CICP) algorithm.Especially in the field of one-off construction, characterized by small and medium companies, automated assessment of 3D scan data during the design process is still in its infancy. By using an open source environment progress for consistent use of digital models could be accelerated.