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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.

Patent No.:

US 12272160 B1

PDFFull Text
Date of Patent:
Apr. 08, 2025

Filed:

Dec. 02, 2022

Systems and methods for estimating grip intensity on a steering wheel

Applicant:

Woven BY Toyota, Inc., Tokyo, JP;

Inventors:

Manuel Ludwig Kuehner, Mountain View, CA (US);

Hiroshi Yasuda, San Francisco, CA (US);

Assignee:

Woven by Toyota, Inc., Tokyo, JP;

Attorneys:

Christopher G. Darrow

Darrow Mustafa PC

Primary Examiner:

Isaac G Smith

Assistant Examiner:

Nikki Marie M undefined Molina

Int. Cl.
CPC ...
G06V 20/59 (2022.01); B60R 1/29 (2022.01); B60W 50/06 (2006.01); B60W 50/08 (2020.01); B60W 50/14 (2020.01); B62D 15/00 (2006.01); G01L 5/22 (2006.01); G06T 7/50 (2017.01); G06V 10/774 (2022.01); G06V 40/10 (2022.01);
U.S. Cl.
CPC ...
G06V 20/597 (2022.01); B60R 1/29 (2022.01); B60W 50/06 (2013.01); B60W 50/087 (2013.01); B60W 50/14 (2013.01); B62D 15/00 (2013.01); G01L 5/221 (2013.01); G06T 7/50 (2017.01); G06V 10/774 (2022.01); G06V 40/11 (2022.01); G06V 40/15 (2022.01); B60W 2420/00 (2013.01); B60W 2420/403 (2013.01); B60W 2422/00 (2013.01); G06T 2207/10048 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30196 (2013.01); G06T 2207/30268 (2013.01);
Abstract

Systems, methods, and other embodiments described herein relate to implementing and calibrating a learning model for inferring operator intent by estimating grip intensity. In one embodiment, a method includes estimating, using a learning model during a driving scenario, first grip intensity on a steering device for a vehicle according to initial image data depicting a hand of an operator gripping outside the set areas that have pressure sensors. The method also includes calibrating the learning model for the operator and the steering device using grip measurements and additional image data acquired from gripping inside the set areas. The method also includes computing, using the learning model during the driving scenario, second grip intensity outside the set areas on the steering device according to hand images acquired about the operator. The method also includes adapting a vehicle parameter of the vehicle according to the second grip intensity.

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