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:
Sep. 06, 2022

Filed:

Mar. 27, 2019
Applicant:

Nvidia Corporation, San Jose, CA (US);

Inventors:

Clement Farabet, Mill Valley, CA (US);

John Zedlewski, San Francisco, CA (US);

Zachary Taylor, Santa Cruz, CA (US);

Greg Heinrich, Nice, FR;

Claire Delaunay, Menlo Park, CA (US);

Mark Daly, Eagle, ID (US);

Matthew Campbell, Surf City, NC (US);

Curtis Beeson, Irwin, PA (US);

Gary Hicok, Mesa, AZ (US);

Michael Cox, Menlo Park, CA (US);

Rev Lebaredian, Los Gatos, CA (US);

Tony Tamasi, Portola Valley, CA (US);

David Auld, Saratoga, CA (US);

Assignee:

NVIDIA Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2006.01); G06N 3/04 (2006.01); G06N 20/00 (2019.01); G06F 9/455 (2018.01); G06N 3/063 (2006.01); G06K 9/62 (2022.01); G06V 10/44 (2022.01); G06V 20/56 (2022.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06F 9/455 (2013.01); G06K 9/6271 (2013.01); G06N 3/0454 (2013.01); G06N 3/063 (2013.01); G06N 20/00 (2019.01); G06V 10/454 (2022.01); G06V 20/56 (2022.01);
Abstract

In various examples, physical sensor data may be generated by a vehicle in a real-world environment. The physical sensor data may be used to train deep neural networks (DNNs). The DNNs may then be tested in a simulated environment—in some examples using hardware configured for installation in a vehicle to execute an autonomous driving software stack—to control a virtual vehicle in the simulated environment or to otherwise test, verify, or validate the outputs of the DNNs. Prior to use by the DNNs, virtual sensor data generated by virtual sensors within the simulated environment may be encoded to a format consistent with the format of the physical sensor data generated by the vehicle.


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