AGENT-BASED OPTIMIZATION OF MULTI-BUILDING SITE LAYOUTS

    公开(公告)号:US20240104255A1

    公开(公告)日:2024-03-28

    申请号:US18167032

    申请日:2023-02-09

    Applicant: AUTODESK, INC.

    CPC classification number: G06F30/13 G06F30/20

    Abstract: One embodiment of the present invention sets forth a technique for generating a multi-building layout for a site. The technique includes instantiating a plurality of agents representing a plurality of buildings located on the site based on a set of boundary conditions associated with the site. The techniques also include iteratively updating a plurality of states associated with the plurality of agents based on the set of boundary conditions and a plurality of behaviors associated with the plurality of agents. The techniques further include generating a layout for the site based on the plurality of states, wherein the layout comprises a plurality of building footprints for the plurality of buildings.

    TECHNIQUES FOR ANALYZING VEHICLE DESIGN DEVIATIONS USING DEEP LEARNING WITH NEURAL NETWORKS

    公开(公告)号:US20230061993A1

    公开(公告)日:2023-03-02

    申请号:US18045809

    申请日:2022-10-11

    Applicant: AUTODESK, INC.

    Abstract: A design application is configured to generate a latent space representation of a fleet of pre-existing vehicles. The design application encodes vehicle designs associated with the fleet of pre-existing vehicles into the latent space representation to generate a first latent space location. The first latent space location represents the characteristic style associated with the fleet of pre-existing vehicles. The design application encodes a sample design provided by a user into the latent space representation to produce a second latent space location. The design application then determines a distance between the first latent space location and the second latent space location. Based on the distance, the design application generates a style metric that indicates the aesthetic similarity between the sample design and the vehicle designs associated with the fleet of pre-existing vehicles. The design application can also generate new vehicle designs based on the latent space representation and the sample design.

    GENERATING BUILDING DESIGNS WHILE COMPUTATIONALLY OPTIMIZING FOR WORK CONDITIONS

    公开(公告)号:US20210150105A1

    公开(公告)日:2021-05-20

    申请号:US17098228

    申请日:2020-11-13

    Applicant: AUTODESK, INC.

    Abstract: Various embodiments set forth systems and techniques for generating work condition values for a building layout. The techniques include receiving a building layout specifying, for each workspace of a plurality of workspaces included in the workplace, a respective location of the workspace; selecting one or more work condition elements from a plurality of work condition elements based at least on the plurality of workspaces; for each work condition element of the one or more work condition elements: evaluating the plurality of workspaces based on the work condition element; based on the evaluating the plurality of workspaces, generating an element value corresponding to the work condition element; and computing, based on element values corresponding to the one or more work condition elements, an overall work condition value associated with the building layout.

    GENERATIVE DESIGN PIPELINE FOR URBAN AND NEIGHBORHOOD PLANNING

    公开(公告)号:US20190147116A1

    公开(公告)日:2019-05-16

    申请号:US16181224

    申请日:2018-11-05

    Applicant: AUTODESK, INC.

    Abstract: An urban design pipeline automatically generates design options for an urban design project. The urban design pipeline includes a geometry engine and an evaluation engine. The geometry engine analyzes design criteria and design objectives associated with the urban design project and then generates numerous candidate designs that meet the design criteria and optimize the design objectives to varying degrees. The evaluation engine evaluates each candidate design to generate a set of metrics. The geometry engine modifies the candidate designs based on corresponding metrics to generate candidate designs that better meet the design criteria and more effectively achieve the design objectives.

    AUTOMATED GENERATION AND EVALUATION OF ARCHITECTURAL DESIGNS

    公开(公告)号:US20190065633A1

    公开(公告)日:2019-02-28

    申请号:US16112562

    申请日:2018-08-24

    Applicant: AUTODESK, INC.

    Abstract: A design engine is configured to interact with potential occupants of a structure in order to generate data that defines the usage preferences of those occupants. The design engine generates multiple candidate designs for the structure via a generative design process, and then evaluates each candidate design using a set of metrics determined relative to the usage preferences. Based on these evaluations, the design engine selects at least one candidate design that optimizes the set of metrics across all potential occupants.

    GENERATIVE SPACE PLANNING IN ARCHITECTURAL DESIGN FOR EFFICIENT DESIGN SPACE EXPLORATION

    公开(公告)号:US20190026401A1

    公开(公告)日:2019-01-24

    申请号:US15956685

    申请日:2018-04-18

    Applicant: AUTODESK, INC.

    Abstract: A design engine generates a spectrum of design options to solve an architectural design problem. When generating a given design option, the design engine processes a set of design objectives and design constraints to generate an initial design plan. The initial design plan defines generative regions where geometry can be created and non-generative regions where geometry creation is restricted. The design engine generates a set of pathways that divide the design plan into multiple parcels and then divides each parcel further to produce a collection of cells. The design engine selects specific cells for major programs and merges these cells with adjacent cells until program space requirements are met. The design engine distributes minor programs within the remaining unoccupied cells of the design plan, thereby producing the design option.

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