The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 20, 2023

Filed:

Mar. 10, 2022
Applicant:

Autodesk, Inc., San Francisco, CA (US);

Inventors:

Hui Li, San Rafael, CA (US);

Evan Patrick Atherton, Castro Valley, CA (US);

Erin Bradner, San Francisco, CA (US);

Nicholas Cote, San Francisco, CA (US);

Heather Kerrick, Berkeley, CA (US);

Assignee:

AUTODESK, INC., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
B25J 9/16 (2006.01); G06N 20/00 (2019.01); G05B 19/418 (2006.01); G06N 3/08 (2023.01); G06F 30/20 (2020.01); G06N 3/044 (2023.01); G06T 17/00 (2006.01);
U.S. Cl.
CPC ...
B25J 9/1671 (2013.01); B25J 9/161 (2013.01); B25J 9/163 (2013.01); B25J 9/1605 (2013.01); G05B 19/41885 (2013.01); G06F 30/20 (2020.01); G06N 3/044 (2023.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06T 17/00 (2013.01); G05B 2219/32017 (2013.01); G05B 2219/35353 (2013.01);
Abstract

One embodiment of the present invention sets forth a technique for generating simulated training data for a physical process. The technique includes receiving, as input to at least one machine learning model, a first simulated image of a first object, wherein the at least one machine learning model includes mappings between simulated images generated from models of physical objects and real-world images of the physical objects. The technique also includes performing, by the at least one machine learning model, one or more operations on the first simulated image to generate a first augmented image of the first object. The technique further includes transmitting the first augmented image to a training pipeline for an additional machine learning model that controls a behavior of the physical process.


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