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公开(公告)号：US20230315925A1
公开(公告)日：2023-10-05
申请号：US17713724
申请日：2022-04-05
Applicant: Autodesk, Inc.
Inventor： Mihai Stancu , Cosmin Paul Manoliu , Dan Florin Peticila , Pawel Piechnik , Mihai Vlad Catalina , Dragos Leonardo Olaru , Vlad Pavel , Dumitru Berteanu , Bogdan Orzea , Silviu Constantin Nita , Amalia Elena Constantin
CPC classification number: G06F30/12 , G06F30/13 , G06F30/17 , G06F2111/20
Abstract: A method and system provides the ability to connect steel elements. A design intent model is acquired and consists of a building information model of a skeleton of a building without connections between steel elements that have geometric characteristics. A structural analysis of the structure of the model is performed and generates output consisting of member end forces at intersections of the steel elements. Via a user interface, rules are defined, that associate a potential connection with a structural steel profile. Via a user interface, a script is defined, that dictate where connections should be placed by: identifying second geometric characteristics of the potential connection, identifying forces for steel elements to be connected, comparing the design intent model, the structural analysis output and the rules to the structural steel profile, and autonomously generating and placing, based on the comparison, connections on the BIM model at applicable intersections.
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公开(公告)号：US11776245B2
公开(公告)日：2023-10-03
申请号：US17719088
申请日：2022-04-12
Applicant: Autodesk, Inc.
Inventor： Shubham Goel , Charis Kaskiris , Patricia Keaney , Anand Rajagopal , Maryam Rezvani , Manu Venugopal , Xin Xu , Brad Lee Bitler
IPC: G06V10/82 , G06V20/00 , G06V20/20 , G06V10/764 , G06V20/13 , G06V20/17 , G06V20/52 , G06F18/24 , G05B9/02
CPC classification number: G06V10/82 , G06F18/24 , G06V10/764 , G06V20/13 , G06V20/17 , G06V20/20 , G06V20/35 , G06V20/52 , G05B9/02
Abstract: A computer-implemented method and system provide the ability to determine and provide a safety risk analysis for construction. Construction related data is obtained and includes textual data and a visual artifact for the construction project. A construction safety context is identified based on the construction related data. Based on the construction safety context, a safety participant risk score that assigns a numerical safety risk participant value to any entity involved in the construction project is determined. Based on the safety risk participant score, a safety project score that assigns a risk level on a per-project basis is determined. The safety risk analysis is presented based on the safety participant risk score and safety project score, via a graphical user interface.
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公开(公告)号：US11775709B2
公开(公告)日：2023-10-03
申请号：US16387526
申请日：2019-04-17
Applicant: AUTODESK, INC.
Inventor： James Stoddart , David Benjamin , Danil Nagy , Damon Lau , Daniel Noviello
CPC classification number: G06F30/23 , G06F30/15 , G06T19/00 , G06T2210/36
Abstract: In various embodiments, an automobile modeling application generates automobile designs. In operation, the automobile modeling application determines a first parameter value associated with a first instance of a first parameterized automobile component. The automobile modeling application then computes a second parameter value associated with a second instance of a second parameterized automobile component based on a structural relationship between the first instance and the second instance. Subsequently, the automobile modeling application generates a computer-aided design (CAD) geometry model for an automobile based on the first parameter value, the second parameter value, and one or more functional relationships defined between two or more instances included in a set of parameterized automobile component instances. Advantageously, because the automobile modeling application automatically propagates changes throughout the automobile design, the amount of time required to make significant changes to the automobile design can be substantially reduced.
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公开(公告)号：US20230298291A1
公开(公告)日：2023-09-21
申请号：US17832116
申请日：2022-06-03
Applicant: AUTODESK, INC.
Inventor： Dale ZHAO , David BENJAMIN , Rui WANG
CPC classification number: G06T19/20 , G06T15/08 , G06F30/20 , G06T2210/04 , G06T2219/2021 , G06T2219/2012 , G06T2200/24
Abstract: A voxel-based design approach enables the creating and modifying of a design model comprising a 3D grid of discrete voxels that is represented by a voxel data structure. The voxel data structure comprises voxel-level entries, each entry corresponding to a voxel based on the 3D location within the 3D grid. The voxel data structure includes a design-level entry for storing design-level performance metrics. The system updates the voxel data structure to reflect user modifications to the design model and renders a visualization of the updated design model. The system displays a per-voxel heat map for the design model for a selected performance metric based on the voxel data structure. The design system displays multiple optimized design solutions based on corresponding optimized voxel data structures. The system generates the multiple optimized design solutions based on a voxel-based optimization technique. The system also performs a voxel-based recommendation visualization technique.
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35.发明公开公开(公告)号：US20230281349A1
公开(公告)日：2023-09-07
申请号：US17687535
申请日：2022-03-04
Applicant: AUTODESK, INC.
Inventor： Yi WANG , Mehdi NOURBAKHSH , Dale ZHAO
Abstract: In various embodiments, an intent-driven layout application automatically generates design for floor spaces. The intent-driven layout application generates a logic formula based on a statement of a design intent and at least one fuzzy geometric predicate. The intent-driven layout application computes, for a first spatial object, a set of desirability values for a set of candidate placements within a first design based on the logic formula. Based on the set of desirability values, the intent-driven layout application selects a first candidate placement from the set of candidate placements. Subsequently, the intent-driven layout application generates a second design based on the first design, where the first spatial object has the first candidate placement within the second design.
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Patent Agency Ranking
公开(公告)号：US11748527B2
公开(公告)日：2023-09-05
申请号：US17820867
申请日：2022-08-18
Applicant: AUTODESK, INC.
Inventor： James Stoddart , Danil Nagy , David Benjamin , Lorenzo Villagi
IPC: G06F30/13
CPC classification number: G06F30/13
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.
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公开(公告)号：US20230267667A1
公开(公告)日：2023-08-24
申请号：US17677826
申请日：2022-02-22
Applicant: AUTODESK, INC.
Inventor： Frederik BRUDY , Fraser ANDERSON , Raimund DACHSELT , George FITZMAURICE , Justin Frank MATEJKA , Patrick REIPSCHLÄGER
CPC classification number: G06T13/40 , G06F3/011 , G06T19/006 , G06T7/70 , G06V40/23 , G06T2207/30196
Abstract: One embodiment of a computer-implemented method for analyzing human motion data includes receiving a set of motion data that indicates one or more movements of a first person within a real-world environment; generating a virtual avatar corresponding to the first person based on the set of motion data; determining a position of the virtual avatar within an extended reality (ER) scene based on the one or more movements; and displaying the virtual avatar in the ER scene according to the determined position.
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38.发明公开公开(公告)号：US20230260183A1
公开(公告)日：2023-08-17
申请号：US17673403
申请日：2022-02-16
Applicant: Autodesk, Inc.
Inventor： Fraser Anderson , George William Fitzmaurice , Cheng Yao Wang , Qian Zhou
CPC classification number: G06T13/40 , G06F3/011 , G06T7/251 , G06F16/743 , G06T2200/24
Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for providing editable keyframe-based animation data for applying to a character to animate motion of the character in three-dimensional space. Three-dimensional motion data is constructed from two-dimensional videos. The three-dimensional motion data represents movement of people in the two-dimensional videos and includes, for each person, a root of a three-dimensional skeleton of the person. The three-dimensional skeleton comprises multiple three-dimensional poses of the person during at least a portion of frames of a video from the two-dimensional videos. The three-dimensional motion data is converted into editable keyframe-based animation data in three-dimensional space and provided to animate motion.
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公开(公告)号：US11727166B2
公开(公告)日：2023-08-15
申请号：US16405761
申请日：2019-05-07
Applicant: AUTODESK, INC.
Inventor： David Benjamin , James Stoddart , Danil Nagy , Damon Lau
IPC: G06F16/90 , G06F30/17 , G06F3/04815 , G06F16/901 , G06F30/20 , G06F3/04845 , G06F3/0482 , G06F3/04847 , G06F111/02 , G06F111/20
CPC classification number: G06F30/17 , G06F3/04815 , G06F16/9024 , G06F30/20 , G06F3/0482 , G06F3/04845 , G06F3/04847 , G06F2111/02 , G06F2111/20
Abstract: A design analysis engine analyzes a CAD assembly to generate a topological model. The topological model is a graph of nodes coupled together via a set of edges. Each node represents a different CAD model in the CAD assembly and each edge represents a different connection between two such CAD models. The design analysis engine also analyzes the CAD assembly to generate a data model corresponding to the topological model. The data model is a structured dataset that includes component entries and connection entries. A component entry includes design data associated with a CAD model in the CAD assembly and a connection entry includes design data associated with a physical or logical connection between two or more such CAD models. A user interacts with the topological model to navigate the CAD assembly, obtain CAD model data, and initiate automatically-performed design tasks.
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公开(公告)号：US11694415B2
公开(公告)日：2023-07-04
申请号：US17083153
申请日：2020-10-28
Applicant: AUTODESK, INC.
Inventor： Ran Zhang , Morgan Fabian , Ebot Etchu Ndip-Agbor , Lee Morris Taylor
CPC classification number: G06T19/20 , G06N3/08 , G06T3/40 , G06T17/205 , G06T2219/2016 , G06T2219/2021
Abstract: In various embodiments, a training application trains a machine learning model to modify portions of shapes when designing 3D objects. The training application converts first structural analysis data having a first resolution to first coarse structural analysis data having a second resolution that is lower than the first resolution. Subsequently, the training application generates one or more training sets based on a first shape, the first coarse structural analysis data, and a second shape that is derived from the first shape. Each training set is associated with a different portion of the first shape. The training application then performs one or more machine learning operations on the machine learning model using the training set(s) to generate a trained machine learning model. The trained machine learning model modifies at least a portion of a shape having the first resolution based on coarse structural analysis data having the second resolution.
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