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:
Nov. 24, 2020

Filed:

May. 03, 2019
Applicant:

Brain Corporation, San Diego, CA (US);

Inventors:

Philip Meier, San Diego, CA (US);

Jean-Baptiste Passot, Solana Beach, CA (US);

Borja Ibarz Gabardos, London, GB;

Patryk Laurent, San Diego, CA (US);

Oleg Sinyavskiy, San Diego, CA (US);

Peter O'Connor, San Diego, CA (US);

Eugene Izhikevich, San Diego, CA (US);

Assignee:

Brain Corporation, San Diego, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
B25J 9/16 (2006.01); G06N 20/00 (2019.01); G06N 3/00 (2006.01); G05D 1/00 (2006.01); G05B 13/02 (2006.01);
U.S. Cl.
CPC ...
B25J 9/163 (2013.01); B25J 9/161 (2013.01); B25J 9/1602 (2013.01); B25J 9/1656 (2013.01); G05B 13/027 (2013.01); G05D 1/0033 (2013.01); G05D 1/0088 (2013.01); G06N 3/008 (2013.01); G06N 20/00 (2019.01); G05B 2219/40116 (2013.01); G05D 2201/02 (2013.01); Y10S 901/01 (2013.01); Y10S 901/46 (2013.01);
Abstract

Robots have the capacity to perform a broad range of useful tasks, such as factory automation, cleaning, delivery, assistive care, environmental monitoring and entertainment. Enabling a robot to perform a new task in a new environment typically requires a large amount of new software to be written, often by a team of experts. It would be valuable if future technology could empower people, who may have limited or no understanding of software coding, to train robots to perform custom tasks. Some implementations of the present invention provide methods and systems that respond to users' corrective commands to generate and refine a policy for determining appropriate actions based on sensor-data input. Upon completion of learning, the system can generate control commands by deriving them from the sensory data. Using the learned control policy, the robot can behave autonomously.


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