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:
Jul. 21, 2020

Filed:

Dec. 18, 2017
Applicant:

Brain Corporation, San Diego, CA (US);

Inventors:

Filip Ponulak, San Diego, CA (US);

Moslem Kazemi, San Diego, CA (US);

Patryk Laurent, San Diego, CA (US);

Oleg Sinyavskiy, San Diego, CA (US);

Eugene Izhikevich, San Diego, CA (US);

Assignee:

Brain Corporation, San Diego, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
B25J 9/00 (2006.01); B25J 9/16 (2006.01); G05D 1/00 (2006.01); G05D 1/02 (2020.01); G06N 20/00 (2019.01); G06N 3/00 (2006.01); G06N 3/04 (2006.01);
U.S. Cl.
CPC ...
B25J 9/163 (2013.01); B25J 9/161 (2013.01); G05D 1/005 (2013.01); G05D 1/0088 (2013.01); G05D 1/0221 (2013.01); G05B 2219/36418 (2013.01); G05B 2219/36425 (2013.01); G05B 2219/40499 (2013.01); G05D 2201/02 (2013.01); G06N 3/008 (2013.01); G06N 3/049 (2013.01); G06N 20/00 (2019.01);
Abstract

Robotic devices may be trained by a trainer guiding the robot along a target trajectory using physical contact with the robot. The robot may comprise an adaptive controller configured to generate control commands based on one or more of the trainer input, sensory input, and/or performance measure. The trainer may observe task execution by the robot. Responsive to observing a discrepancy between the target behavior and the actual behavior, the trainer may provide a teaching input via a haptic action. The robot may execute the action based on a combination of the internal control signal produced by a learning process of the robot and the training input. The robot may infer the teaching input based on a comparison of a predicted state and actual state of the robot. The robot's learning process may be adjusted in accordance with the teaching input so as to reduce the discrepancy during a subsequent trial.


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