Fast feature recognition and mesh generation in structural design

A nontransitory computer readable storage medium comprising program instructions that, when executed by one or more processors, carries out a method of identifying a structural feature of a structure, the method comprising:

• obtaining a global point cloud representation of the structure;
• obtaining a target point cloud that represents a target structural feature, wherein the target point cloud is a subset of the global point cloud representation of the structure;
• supplying global structural information and the target point cloud to a feature clustering process and producing therefrom a clustered representation of the structure, wherein:
• the global structural information is derived from the global point cloud representation of the structure;
• a dataset size of the clustered representation of the structure is smaller than a dataset size of the global structural information;
• and
• the clustered representation of the structure comprises data points that are clustered around features of the structure that are estimated by the feature clustering process as having at least a predefined level of similarity to the target point cloud;
• and
• supplying the clustered representation of the structure and the target point cloud to a feature matching process that compares the target point cloud with clusters of datapoints within the clustered representation of the structure and produces therefrom one or more matching point clouds, wherein each of the one or more matching point clouds is a subset of the global point cloud representation of the structure.

A system for identifying a structural feature of a structure, the system comprising:

• one or more nontransitory memories having stored therein program instructions;
• and
• one or more processors configured to execute the program instructions and thereby to perform:
• obtaining a global point cloud representation of the structure;
• obtaining a target point cloud that represents a target structural feature, wherein the target point cloud is a subset of the global point cloud representation of the structure;
• supplying global structural information and the target point cloud to a feature clustering process and producing therefrom a clustered representation of the structure, wherein:
• the global structural information is derived from the global point cloud representation of the structure;
• a dataset size of the clustered representation of the structure is smaller than a dataset size of the global structural information;
• and
• the clustered representation of the structure comprises data points that are clustered around features of the structure that are estimated by the feature clustering process as having at least a predefined level of similarity to the target point cloud;
• and
• supplying the clustered representation of the structure and the target point cloud to a feature matching process that compares the target point cloud with clusters of datapoints within the clustered representation of the structure and produces therefrom one or more matching point clouds, wherein each of the one or more matching point clouds is a subset of the global point cloud representation of the structure.

A structural feature recognizer for use in computational engineering, wherein the structural feature recognizer is configured to identify a structural feature of a structure, the structural feature recognizer comprising:

• circuitry configured to obtain a global point cloud representation of the structure;
• circuitry configured to obtain a target point cloud that represents a target structural feature, wherein the target point cloud is a subset of the global point cloud representation of the structure;
• circuitry configured to supply global structural information and the target point cloud to a feature clustering process and to produce therefrom a clustered representation of the structure, wherein:
• the global structural information is derived from the global point cloud representation of the structure;
• a dataset size of the clustered representation of the structure is smaller than a dataset size of the global structural information;
• and
• the clustered representation of the structure comprises data points that are clustered around features of the structure that are estimated by the feature clustering process as having at least a predefined level of similarity to the target point cloud;
• and
• circuitry configured to supply the clustered representation of the structure and the target point cloud to a feature matching process that compares the target point cloud with clusters of datapoints within the clustered representation of the structure and produces therefrom one or more matching point clouds, wherein each of the one or more matching point clouds is a subset of the global point cloud representation of the structure.