DEFECT REMOVAL FROM MANUFACTURED OBJECTS HAVING MORPHED SURFACES

    公开(公告)号:US20210034961A1

    公开(公告)日:2021-02-04

    申请号:US16524912

    申请日:2019-07-29

    Applicant: Autodesk, Inc.

    Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided repair of physical structures include: generating a two dimensional difference image from a first three dimensional model of at least one actual three dimensional surface of a manufactured object, and a second three dimensional model of at least one source three dimensional surface used as input to a manufacturing process that generated the manufactured object; obtaining from an image-to-image translation based machine learning algorithm, trained using pairs of input images representing deformed and deformed plus surface defected added versions of a nominal three dimensional surface, a translated version of the two dimensional image; generating from the translated version of the two dimensional image a third three dimensional model of at least one morphed three dimensional surface corresponding to the at least one source three dimensional surface. Further, defects can be removed based on the third three dimensional model.

    DEFECT REMOVAL FROM MANUFACTURED OBJECTS HAVING MORPHED SURFACES

    公开(公告)号:US20230289596A1

    公开(公告)日:2023-09-14

    申请号:US18141262

    申请日:2023-04-28

    Applicant: Autodesk, Inc.

    CPC classification number: G06N3/08 G06F30/20 G05B19/4097 G05B2219/35134

    Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided repair of physical structures include: generating a two dimensional difference image from a first three dimensional model of at least one actual three dimensional surface of a manufactured object, and a second three dimensional model of at least one source three dimensional surface used as input to a manufacturing process that generated the manufactured object; obtaining from an image-to-image translation based machine learning algorithm, trained using pairs of input images representing deformed and deformed plus surface defected added versions of a nominal three dimensional surface, a translated version of the two dimensional image; generating from the translated version of the two dimensional image a third three dimensional model of at least one morphed three dimensional surface corresponding to the at least one source three dimensional surface. Further, defects can be removed based on the third three dimensional model.

    BUILDING INFORMATION DESIGN SYNTHESIS (BIDS)

    公开(公告)号:US20190228115A1

    公开(公告)日:2019-07-25

    申请号:US16254083

    申请日:2019-01-22

    Applicant: Autodesk, Inc.

    Abstract: A method, apparatus, system, and computer program product provide the ability to dynamically generate a digital building information model. Design data for various designs is received. The design data for each design is encoded into a graph. A knowledge base (consisting of a collection of the design data, actions taken on the design data, and interpretations of the received design data) is maintained. The knowledge base processes and stores the graph, and indexes and provides access to design knowledge. The knowledge base is iteratively trained based on the graph and updates to the graph, and translates user input for new design projects into actionable design models, documentation, and analytical data. User input (e.g., a sketch or bubble diagram) is received. As the user input is received, a layout floorplan is generated and displayed in real-time (based on the user input and the knowledge base).

    Defect removal from manufactured objects having morphed surfaces

    公开(公告)号:US11676007B2

    公开(公告)日:2023-06-13

    申请号:US16524912

    申请日:2019-07-29

    Applicant: Autodesk, Inc.

    CPC classification number: G06N3/08 G05B19/4097 G06F30/20 G05B2219/35134

    Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided repair of physical structures include: generating a two dimensional difference image from a first three dimensional model of at least one actual three dimensional surface of a manufactured object, and a second three dimensional model of at least one source three dimensional surface used as input to a manufacturing process that generated the manufactured object; obtaining from an image-to-image translation based machine learning algorithm, trained using pairs of input images representing deformed and deformed plus surface defected added versions of a nominal three dimensional surface, a translated version of the two dimensional image; generating from the translated version of the two dimensional image a third three dimensional model of at least one morphed three dimensional surface corresponding to the at least one source three dimensional surface. Further, defects can be removed based on the third three dimensional model.

    BUILDING INFORMATION DESIGN SYNTHESIS (BIDS)

    公开(公告)号:US20220180017A1

    公开(公告)日:2022-06-09

    申请号:US17681150

    申请日:2022-02-25

    Applicant: Autodesk, Inc.

    Abstract: A method, apparatus, system, and computer program product provide the ability to dynamically generate a digital building information model. Design data for various designs is received. The design data for each design is encoded into a graph. A knowledge base is maintained and defines a model of design intent while processing and storing the graph. First user input of a goal or constraint is received. The knowledge base generates solutions base don the input. Second user input based on the solutions is received and used to iteratively train the knowledge base. The solutions are then output.

    Building information design synthesis (BIDS)

    公开(公告)号:US11263360B2

    公开(公告)日:2022-03-01

    申请号:US16254083

    申请日:2019-01-22

    Applicant: Autodesk, Inc.

    Abstract: A method, apparatus, system, and computer program product provide the ability to dynamically generate a digital building information model. Design data for various designs is received. The design data for each design is encoded into a graph. A knowledge base (consisting of a collection of the design data, actions taken on the design data, and interpretations of the received design data) is maintained. The knowledge base processes and stores the graph, and indexes and provides access to design knowledge. The knowledge base is iteratively trained based on the graph and updates to the graph, and translates user input for new design projects into actionable design models, documentation, and analytical data. User input (e.g., a sketch or bubble diagram) is received. As the user input is received, a layout floorplan is generated and displayed in real-time (based on the user input and the knowledge base).

    LEARNING TO SIMULATE AND DESIGN FOR STRUCTURAL ENGINEERING

    公开(公告)号:US20210287138A1

    公开(公告)日:2021-09-16

    申请号:US17200546

    申请日:2021-03-12

    Applicant: Autodesk, Inc.

    Abstract: A method and system provide the ability to optimize a structural engineering design. A dataset is synthesized by acquiring a structural skeleton design of an entire building. The skeleton defines locations and connectivities of bars that represent columns or beams. The skeleton design is represented as a structural graph with each bar represented as a graph node and edges connecting graph nodes. Structural simulation results are computed for the synthetic dataset based on the structural graph, various loads, and a structural analysis. A simulation model and a size optimization model are trained based on the structural simulation results with the size optimization model determining cross-section sizes for the bars to satisfy a building mass objective, building constraints, and output from the simulation model. The structural engineering design is output from the size optimization model.

Patent Agency Ranking