Graph-based heuristics for recognition of machined features from a 3D solid model
Computer-Aided Design
Automatic recognition and representation of shape-based features in a geometric modeling system
Computer Vision, Graphics, and Image Processing
Generative geometric design and boundary solid grammars
Generative geometric design and boundary solid grammars
An Analysis of Some Graph Theoretical Cluster Techniques
Journal of the ACM (JACM)
IEEE Computer Graphics and Applications
Geometric Reasoning for Recognition of Three-Dimensional Object Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric Reasoning for Recognition of Three-Dimensional Object Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Designing inner hood panels through a shape grammar based framework
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Languages and semantics of grammatical discrete structures
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
A fuzzy configuration multi-agent approach for product family modelling in conceptual design
Journal of Intelligent Manufacturing
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The introduction of features concept enables the association of shape and knowledge in understanding a CAD model. Grammar is considered potentially powerful formalism by its ability to represent and generate features. However, effective methods of computational must consider both feature modeling and feature learning in order to update the feature language. This paper presents an approach for the inference of Feature Grammars including three main phases. In the first phase, based on the hypothesis of the robustness, we search for terminals of features structures. In the second phase, from the terminals and their interrelationship, we represent the structures of features by corresponding canonical matrices. In the third phase, we infer the production rules of Features Grammars. Production rules are inferred based on the clustering of features structures as well as on their ordering relation. Examples and application illustrate the steps involved and the advantages of this approach.