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. 09, 2024

Filed:

Dec. 29, 2021
Applicant:

Midea Group Co., Ltd., Foshan, CN;

Inventor:

Ke Huang, San Jose, CA (US);

Assignee:

MIDEA GROUP CO., LTD., Foshan, CN;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G05D 1/00 (2024.01); G06T 7/11 (2017.01); G06T 7/593 (2017.01); G06T 7/70 (2017.01); G06V 20/58 (2022.01);
U.S. Cl.
CPC ...
G06V 20/58 (2022.01); G05D 1/0214 (2013.01); G05D 1/0231 (2013.01); G06T 7/11 (2017.01); G06T 7/593 (2017.01); G06T 7/70 (2017.01); G06T 2207/10024 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/10032 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20092 (2013.01);
Abstract

The method and system disclosed herein presents a method and system for capturing, by a depth-perception device on a mobile robot moving in an environment, depth-perception information at a first location within a portion of the environment. The method includes capturing, by a camera device on the mobile robot, an image frame at the first location within the portion of the environment, generating a three-dimensional point cloud representing the portion of the environment based on the depth-perception information and the image frame, extracting semantic information by providing the frame and the point cloud to a neural network model configured to perform semantic segmentation, associating the semantic information to the three-dimensional point cloud, projecting the three-dimensional point cloud onto a two-dimensional plane to form a first two-dimensional map; and demarcating the first two-dimensional map with a plurality of different regions based on the semantic information.


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