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:
Jul. 01, 2025

Filed:

Dec. 30, 2021
Applicant:

Nvidia Corporation, Santa Clara, CA (US);

Inventors:

Neeraj Sajjan, Sunnyvale, CA (US);

Mehmet K. Kocamaz, San jose, CA (US);

Junghyun Kwon, Santa Clara, CA (US);

Sangmin Oh, San Jose, CA (US);

Minwoo Park, Saratoga, CA (US);

David Nister, Bellevue, WA (US);

Assignee:

NVIDIA Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G01S 7/53 (2006.01); G01S 13/89 (2006.01); G01S 13/931 (2020.01); G01S 15/931 (2020.01); G01S 17/89 (2020.01); G01S 17/931 (2020.01); G05D 1/00 (2006.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01);
U.S. Cl.
CPC ...
G05D 1/0248 (2013.01); G05D 1/0088 (2013.01); G05D 1/0219 (2013.01); G05D 1/0221 (2013.01); G05D 1/0251 (2013.01); G05D 1/0255 (2013.01); G05D 1/0257 (2013.01); G06N 3/08 (2013.01);
Abstract

In various examples, one or more output channels of a deep neural network (DNN) may be used to determine assignments of obstacles to paths. To increase the accuracy of the DNN, the input to the DNN may include an input image, one or more representations of path locations, and/or one or more representations of obstacle locations. The system may thus repurpose previously computed information—e.g., obstacle locations, path locations, etc.—from other operations of the system, and use them to generate more detailed inputs for the DNN to increase accuracy of the obstacle to path assignments. Once the output channels are computed using the DNN, computed bounding shapes for the objects may be compared to the outputs to determine the path assignments for each object. Additionally, a machine may perform control operations based at least on the path assignments.


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