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:
Oct. 22, 2024

Filed:

Nov. 01, 2021
Applicant:

Aurora Operations, Inc., Pittsburgh, PA (US);

Inventors:

Anqi Joyce Yang, Toronto, CA;

Can Cui, Toronto, CA;

Ioan Andrei Bârsan, Toronto, CA;

Shenlong Wang, Toronto, CA;

Raquel Urtasun, Toronto, CA;

Assignee:

AURORA OPERATIONS, INC., Pittsburgh, PA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G05D 1/00 (2024.01); B60R 1/27 (2022.01); G01S 17/894 (2020.01);
U.S. Cl.
CPC ...
G05D 1/0251 (2013.01); B60R 1/27 (2022.01); G01S 17/894 (2020.01); G05D 1/0212 (2013.01); G05D 1/0248 (2013.01); B60R 2300/303 (2013.01); B60R 2300/304 (2013.01);
Abstract

Systems and methods for the simultaneous localization and mapping of autonomous vehicle systems are provided. A method includes receiving a plurality of input image frames from the plurality of asynchronous image devices triggered at different times to capture the plurality of input image frames. The method includes identifying reference image frame(s) corresponding to a respective input image frame by matching the field of view of the respective input image frame to the fields of view of the reference image frame(s). The method includes determining association(s) between the respective input image frame and three-dimensional map point(s) based on a comparison of the respective input image frame to the one or more reference image frames. The method includes generating an estimated pose for the autonomous vehicle the one or more three-dimensional map points. The method includes updating a continuous-time motion model of the autonomous vehicle based on the estimated pose.


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