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:
Jun. 06, 2023

Filed:

Dec. 28, 2021
Applicant:

Guangdong University of Technology, Guangzhou, CN;

Inventors:

Renquan Lu, Guangzhou, CN;

Hongxia Rao, Guangzhou, CN;

Yong Xu, Guangzhou, CN;

Yuru Guo, Guangzhou, CN;

Jie Tao, Guangzhou, CN;

Chang Liu, Guangzhou, CN;

Ye Kuang, Guangzhou, CN;

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/75 (2022.01); G06V 20/17 (2022.01); G06T 15/00 (2011.01); G06F 16/29 (2019.01); G06T 7/33 (2017.01); G06T 17/05 (2011.01); G06V 10/26 (2022.01); G08C 17/02 (2006.01); H04L 67/10 (2022.01); H04N 21/2187 (2011.01); G06V 10/44 (2022.01); G06V 10/25 (2022.01); G06V 10/82 (2022.01); G06V 10/88 (2022.01); G06V 10/20 (2022.01); G06V 10/766 (2022.01); G06V 20/56 (2022.01);
U.S. Cl.
CPC ...
G06V 10/443 (2022.01); G06V 10/25 (2022.01); G06V 10/255 (2022.01); G06V 10/766 (2022.01); G06V 10/82 (2022.01); G06V 10/88 (2022.01); G06V 20/56 (2022.01);
Abstract

The present invention discloses a cloud-edge-end cooperative control method of a 5G networked UAV for security rescue, including: an image acquisition step: performing, by a single-chip microcomputer, attitude resolution on data acquired by a detection sensor, to obtain image data; a sparse landmark map building step: performing, by a control platform, front-end feature point matching, local map building and optimization, loopback detection, and frame resolution on the image data, to generate a sparse landmark map; a three-dimensional dense map building step: generating, by an edge cloud, a three-dimensional dense map based on a key frame pose and key frame observation data of the sparse landmark map; a high-precision semantic map building step: obtaining a high-precision semantic map; and a UAV movement step: adjusting, by the driving mechanism, a pose of the UAV according to the three-dimensional dense map or the high-precision semantic map.


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