Simulated annealing-based fitting of CAD models to point clouds of mechanical parts’ assemblies
Article dans une revue avec comité de lecture
Date
2020-02-18Journal
Engineering with ComputersAbstract
This paper introduces a new ftting approach to allow an efcient part-by-part reconstruction or update of editable CAD
models fitting the point cloud of a digitized mechanical parts′
assembly. The idea is to make use of parameterized CAD mod els whose dimensional parameters are to be optimized to match the acquired point cloud. Parameters may also be related to
assembly constraints, e.g. the distance between two parts. The optimization kernel relies on a simulated annealing algorithm
to fnd out the best values of the parameters so as to minimize the deviations between the point cloud and the CAD models
to be ftted. Both global and local ftting are possible. During the optimization process, the orientation and positioning of the
CAD parts are driven by an ICP algorithm. The modifcations are ensured by the batch calls to a CAD modeler which updates
the models as the ftting process goes on. The modeler also handles the assembly constraints. Both single and multiple parts
can be ftted, either sequentially or simultaneously. The evaluation of the proposed approach is performed using both real
scanned point clouds and as-scanned virtually generated point clouds which incorporate several artifacts that could appear
with a real scanner. Results cover several Industry 4.0 related application scenarios, ranging from the global ftting of a single
part to the update of a complete Digital Mock-Up embedding assembly constraints. The proposed approach demonstrates
good capacities to help maintaining the coherence between a product/system and its digital twin
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