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. 06, 2023

Filed:

Dec. 07, 2020
Applicant:

Ford Global Technologies, Llc, Dearborn, MI (US);

Inventors:

Mokshith Voodarla, Santa Clara, CA (US);

Shubham Shrivastava, Sunnyvale, CA (US);

Punarjay Chakravarty, Campbell, CA (US);

Assignee:

Ford Global Technologies, LLC, Dearborn, MI (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 20/56 (2022.01); H04W 4/46 (2018.01); G06N 3/08 (2023.01); G06V 10/25 (2022.01); G06V 10/75 (2022.01); G06F 18/24 (2023.01); G06N 3/045 (2023.01); G06V 10/82 (2022.01); G06N 3/088 (2023.01); G06N 3/047 (2023.01);
U.S. Cl.
CPC ...
G06V 20/56 (2022.01); G06F 18/24 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06V 10/25 (2022.01); G06V 10/751 (2022.01); G06V 10/82 (2022.01); H04W 4/46 (2018.02); G06N 3/047 (2023.01); G06N 3/088 (2013.01);
Abstract

A plurality of temporally successive vehicle sensor images are received as input to a variational autoencoder neural network that outputs an averaged semantic birds-eye view image that includes respective pixels determined by averaging semantic class values of corresponding pixels in respective images in the plurality of temporally successive vehicle sensor images. From a plurality of topological nodes that each specify respective real-world locations, a topological node closest to the vehicle, and a three degree-of-freedom pose for the vehicle relative to the topological node closest to the vehicle, is determined based on the averaged semantic birds-eye view image. A real-world three degree-of-freedom pose for the vehicle is determined by combining the three degree-of-freedom pose for the vehicle relative to the topological node and the real-world location of the topological node closest to the vehicle.


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