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. 11, 2023

Filed:

Aug. 31, 2020
Applicant:

Nvidia Corporation, Santa Clara, CA (US);

Inventors:

Michael Kroepfl, Kirkland, WA (US);

Amir Akbarzadeh, San Jose, CA (US);

Ruchi Bhargava, Redmond, WA (US);

Vaibhav Thukral, Bellevue, WA (US);

Neda Cvijetic, East Palo Alto, CA (US);

Vadim Cugunovs, Bellevue, WA (US);

David Nister, Bellevue, WA (US);

Birgit Henke, Seattle, WA (US);

Ibrahim Eden, Redmond, WA (US);

Youding Zhu, Sammamish, WA (US);

Michael Grabner, Redmond, WA (US);

Ivana Stojanovic, Berkeley, CA (US);

Yu Sheng, San Diego, CA (US);

Jeffrey Liu, Bellevue, WA (US);

Enliang Zheng, Redmond, WA (US);

Jordan Marr, Santa Clara, CA (US);

Andrew Carley, Kenmore, WA (US);

Assignee:

NVIDIA Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01C 21/00 (2006.01); G06N 3/02 (2006.01); G01C 21/16 (2006.01);
U.S. Cl.
CPC ...
G01C 21/3841 (2020.08); G01C 21/1652 (2020.08); G01C 21/3811 (2020.08); G01C 21/3867 (2020.08); G01C 21/3878 (2020.08); G01C 21/3896 (2020.08); G06N 3/02 (2013.01);
Abstract

An end-to-end system for data generation, map creation using the generated data, and localization to the created map is disclosed. Mapstreams—or streams of sensor data, perception outputs from deep neural networks (DNNs), and/or relative trajectory data—corresponding to any number of drives by any number of vehicles may be generated and uploaded to the cloud. The mapstreams may be used to generate map data—and ultimately a fused high definition (HD) map—that represents data generated over a plurality of drives. When localizing to the fused HD map, individual localization results may be generated based on comparisons of real-time data from a sensor modality to map data corresponding to the same sensor modality. This process may be repeated for any number of sensor modalities and the results may be fused together to determine a final fused localization result.


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