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:
Feb. 27, 2024

Filed:

Sep. 08, 2020
Applicant:

Embodied Intelligence, Inc., Berkeley, CA (US);

Inventors:

Yan Duan, Berkeley, CA (US);

Haoran Tang, Emeryville, CA (US);

Yide Shentu, Berkeley, CA (US);

Nikhil Mishra, Irvine, CA (US);

Xi Chen, Berkeley, CA (US);

Assignee:

Embodied Intelligence, Inc., Emeryville, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
B25J 9/16 (2006.01); B25J 15/06 (2006.01);
U.S. Cl.
CPC ...
B25J 9/161 (2013.01); B25J 9/163 (2013.01); B25J 9/1612 (2013.01); B25J 9/1653 (2013.01); B25J 15/0658 (2013.01);
Abstract

Various embodiments of the present technology generally relate to robotic devices and artificial intelligence. More specifically, some embodiments relate to an artificial neural network training method that does not require extensive training data or time expenditure. The few-shot training model disclosed herein includes attempting to pick up items and, in response to a failed pick up attempt, transferring and generalizing information to similar regions to improve probability of success in future attempts. In some implementations, the training method is used to robotic device for picking items from a bin and perturbing items in a bin. When no picking strategies with high probability of success exist, the robotic device may perturb the contents of the bin to create new available pick-up points. In some implementations, the device may include one or more Computer-vision systems.


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