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:
Sep. 10, 2024

Filed:

Aug. 26, 2022
Applicant:

Toyota Research Institute, Inc., Los Altos, CA (US);

Inventors:

Guy Rosman, Newton, MA (US);

Daniel J. Brooks, Arlington, MA (US);

Simon A. I. Stent, Cambridge, MA (US);

Tiffany Chen, San Jose, CA (US);

Emily Sarah Sumner, Mountain View, CA (US);

Shabnam Hakimi, San Francisco, CA (US);

Jonathan DeCastro, Arlington, MA (US);

Deepak Edakkattil Gopinath, Chicago, IL (US);

Assignees:
Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
B60W 50/14 (2020.01); B25J 9/16 (2006.01); B25J 11/00 (2006.01); B60W 40/09 (2012.01); B60W 50/00 (2006.01); B60W 60/00 (2020.01); G06N 3/04 (2023.01);
U.S. Cl.
CPC ...
B60W 50/14 (2013.01); B25J 9/161 (2013.01); B25J 9/163 (2013.01); B25J 11/008 (2013.01); B60W 40/09 (2013.01); B60W 50/0097 (2013.01); B60W 60/0015 (2020.02); G06N 3/04 (2013.01); B60W 2050/0083 (2013.01); B60W 2050/143 (2013.01); B60W 2050/146 (2013.01); B60W 2556/10 (2020.02);
Abstract

Systems and methods for learning and managing robot user interfaces are disclosed herein. One embodiment generates, based on input data including information about past interactions of a particular user with a robot and with existing HMIs of the robot, a latent space using one or more encoder neural networks, wherein the latent space is a reduced-dimensionality representation of learned behavior and characteristics of the particular user, and uses the latent space as input to train a decoder neural network associated with (1) a new HMI distinct from the existing HMIs or (2) a particular HMI among the existing HMIs to alter operation of the particular HMI. The trained first decoder neural network is deployed in the robot to control, at least in part, operation of the new HMI or the particular HMI in accordance with the learned behavior and characteristics of the particular user.


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