Patents/Assignees

AUTODESK, Inc.

216 patents in portfolio

US11798521utility2023
Computation Design of Acoustic Resonators
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US11789429utility2023
Computer Aided Generative Design with Tool Size Control to Facilitate 2.5-axis Subtractive Manufacturing Processes
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US11782396utility2023
Toolpath Generation by Reinforcement Learning for Computer Aided Manufacturing
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US11775709utility2023
Techniques for Generating Comprehensive Information Models for Automobile Designs
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US11772275utility2023
Generative Design Techniques for Robot Behavior
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US11776245utility2023
Architecture, Engineering and Construction (AEC) Construction Safety Risk Analysis System and Method for Interactive Visualization and Capture
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US11768974utility2023
Building Information Model (BIM) Element Extraction from Floor Plan Drawings Using Machine Learning
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US11762368utility2023
Computer Aided Generative Design with Layer Boundary Determination to Facilitate 2.5-axis Subtractive Manufacturing Processes
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US11763046utility2023
Techniques for Automatically Selecting Simulation Tools for and Performing Related Simulations on Computer-generated Designs
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US11748527utility2023
Automated Generation and Evaluation of Architectural Designs
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US11741084utility2023
High Frequency Data Management (HFDM)
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US11741662utility2023
Shaped-based Techniques for Exploring Design Spaces
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US11734227utility2023
Systems and Methods for Electronically Generating Submittal Registers
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US11734471utility2023
Topology Optimization for Subtractive Manufacturing Techniques
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US11726643utility2023
Techniques for Visualizing Probabilistic Data Generated When Designing Mechanical Assemblies
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US11727166utility2023
Techniques for Generating Graph-based Representations of Complex Mechanical Assemblies
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US11704016utility2023
Techniques for Interacting with Handheld Devices
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US11704456utility2023
Methods and Systems for Generating Lattice Recommendations in Computer-aided Design Applications
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US11698998utility2023
Computer Aided Design (CAD) Model Connection Propagation
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US11694415utility2023
Techniques for Training a Machine Learning Model to Modify Portions of Shapes When Generating Designs for Three-dimensional Objects
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