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:
Sep. 05, 2023

Filed:

Nov. 30, 2020
Applicant:

X Development Llc, Mountain View, CA (US);

Inventor:

Guy Satat, Sunnyvale, CA (US);

Assignee:

Google LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/60 (2022.01); B25J 9/16 (2006.01); B25J 19/02 (2006.01); G01N 21/359 (2014.01); G06F 18/21 (2023.01); G06F 18/24 (2023.01); H04N 23/10 (2023.01); H04N 23/56 (2023.01); H04N 23/90 (2023.01); H04N 23/695 (2023.01); G06V 10/58 (2022.01); B25J 5/00 (2006.01); G01N 21/55 (2014.01);
U.S. Cl.
CPC ...
B25J 9/1697 (2013.01); B25J 9/163 (2013.01); B25J 9/1664 (2013.01); B25J 19/023 (2013.01); G01N 21/359 (2013.01); G06F 18/21 (2023.01); G06F 18/24 (2023.01); G06V 10/60 (2022.01); H04N 23/10 (2023.01); H04N 23/56 (2023.01); H04N 23/695 (2023.01); H04N 23/90 (2023.01); B25J 5/007 (2013.01); G01N 2021/555 (2013.01); G06V 10/58 (2022.01);
Abstract

A method includes identifying a target surface in an environment of a robotic device. The method further includes controlling a moveable component of the robotic device to move along a motion path relative to the target surface, wherein the moveable component comprises a light source and a camera. The method additionally includes receiving a plurality of images from the camera when the moveable component is at a plurality of poses along the motion path and when the light source is illuminating the target surface. The method also includes determining bidirectional reflectance distribution function (BRDF) image data, wherein the BRDF image data comprises the plurality of images converted to angular space with respect to the target surface. The method further includes determining, based on the BRDF image data and by applying at least one pre-trained machine learning model, a material property of the target surface.


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