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. 04, 2023

Filed:

Feb. 10, 2021
Applicant:

Miso Robotics, Inc., Pasadena, CA (US);

Inventors:

Ryan W. Sinnet, Pasadena, CA (US);

Robert Anderson, Pasadena, CA (US);

Zachary Zweig Vinegar, Los Angeles, CA (US);

William Werst, Pasadena, CA (US);

David Zito, Pasadena, CA (US);

Sean Olson, Pacific Palisades, CA (US);

Assignee:

Miso Robotics, Inc., Pasadena, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); B25J 9/00 (2006.01); G05B 19/42 (2006.01); A23L 5/10 (2016.01); G06Q 50/12 (2012.01); G06K 9/62 (2022.01); G06Q 10/0631 (2023.01); G06T 7/73 (2017.01); G06T 7/70 (2017.01); A47J 36/32 (2006.01); A47J 37/06 (2006.01); A47J 37/12 (2006.01); G02B 27/01 (2006.01); G06Q 20/20 (2012.01); G06V 20/52 (2022.01); G06V 20/68 (2022.01);
U.S. Cl.
CPC ...
B25J 9/0081 (2013.01); A23L 5/10 (2016.08); A23L 5/15 (2016.08); A47J 36/32 (2013.01); A47J 37/06 (2013.01); A47J 37/12 (2013.01); G02B 27/017 (2013.01); G05B 19/42 (2013.01); G06K 9/6273 (2013.01); G06Q 10/06311 (2013.01); G06Q 20/202 (2013.01); G06Q 50/12 (2013.01); G06T 7/70 (2017.01); G06T 7/73 (2017.01); G06V 20/52 (2022.01); A23V 2002/00 (2013.01); G05B 2219/36184 (2013.01); G05B 2219/40391 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/10048 (2013.01); G06T 2207/20084 (2013.01); G06V 20/68 (2022.01);
Abstract

An automated kitchen assistant system inspects a food preparation area in the kitchen environment using a novel sensor combination. The combination of sensors includes an Infrared (IR) camera that generates IR image data and at least one secondary sensor that generates secondary image data. The IR image data and secondary image data are processed to obtain combined image data. A trained convolutional neural network is employed to automatically compute an output based on the combined image data. The output includes information about the identity and the location of the food item. The output may further be utilized to command a robotic arm, kitchen worker, or otherwise assist in food preparation. Related methods are also described.


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