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:
Apr. 28, 2026

Filed:

Sep. 27, 2023
Applicant:

Mitsubishi Electric Research Laboratories, Inc., Cambridge, MA (US);

Inventors:

Chiori Hori, Lexington, MA (US);

Jonathan Le Roux, Arlington, MA (US);

Devesh Jha, Cambridge, MA (US);

Siddarth Jain, Cambridge, MA (US);

Radu Ioan Corcodel, Cambridge, MA (US);

Diego Romeres, Boston, MA (US);

Puyuang Peng, Austin, TX (US);

Xinyu Liu, Province, RI (US);

David Harwath, Austin, TX (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G05D 1/00 (2024.01); G06V 10/82 (2022.01); G06V 20/40 (2022.01); G10L 15/02 (2006.01); G10L 15/16 (2006.01); G10L 15/18 (2013.01);
U.S. Cl.
CPC ...
G05D 1/0246 (2013.01); G06V 10/82 (2022.01); G06V 20/41 (2022.01); G06V 20/46 (2022.01); G06V 20/49 (2022.01); G10L 15/02 (2013.01); G10L 15/16 (2013.01); G10L 15/1815 (2013.01);
Abstract

A method, a system and a computer program product are provided for applying a neural network including an action sequence decoder for generating an action sequence for a robot to perform a task. The neural network is applied to generate the action sequence based on recordings demonstrating humans performing tasks. In an example, the method comprises collecting a recording and a sequence of captions describing scenes in the recording; extracting feature data from the recording; encoding the extracted feature data to produce a sequence of encoded features; and applying the action sequence decoder to produce a sequence of actions for the robot based on the sequence of encoded features having a semantic meaning corresponding to a semantic meaning of the sequence of captions. The feature data includes features of a video signal, an audio signal, and/or text transcription capturing a performance of the task.


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