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:
Oct. 22, 2024

Filed:

Jun. 22, 2022
Applicant:

Tongji University, Shanghai, CN;

Inventors:

Bin He, Shanghai, CN;

Gang Li, Shanghai, CN;

Runjie Shen, Shanghai, CN;

Bin Cheng, Shanghai, CN;

Zhipeng Wang, Shanghai, CN;

Ping Lu, Shanghai, CN;

Zhongpan Zhu, Shanghai, CN;

Yanmin Zhou, Shanghai, CN;

Qiqi Zhu, Shanghai, CN;

Assignee:

TONGJI UNIVERSITY, Shanghai, CN;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 17/05 (2011.01); B64C 39/02 (2023.01); B64U 20/87 (2023.01); B64U 101/30 (2023.01); G01C 21/16 (2006.01); G01S 17/86 (2020.01); G01S 17/89 (2020.01); G05D 1/00 (2024.01); G06T 7/73 (2017.01); G06T 19/20 (2011.01);
U.S. Cl.
CPC ...
G06T 17/05 (2013.01); B64C 39/024 (2013.01); B64U 20/87 (2023.01); G01C 21/165 (2013.01); G01S 17/86 (2020.01); G01S 17/89 (2013.01); G05D 1/106 (2019.05); G06T 7/74 (2017.01); G06T 7/75 (2017.01); G06T 19/20 (2013.01); B64U 2101/30 (2023.01); G06T 2207/10028 (2013.01); G06T 2207/10032 (2013.01); G06T 2207/30181 (2013.01); G06T 2219/2016 (2013.01);
Abstract

The method includes: obtaining point cloud information collected by a depth camera, laser information collected by a lidar, and motion information of an unmanned aerial vehicle (UAV); generating a raster map based on the laser information, and obtaining pose information of the UAV based on the motion information; obtaining a map model through fusing the point cloud information, the raster map, and the pose information by a Bayesian fusion method; and correcting a latest map model by feature matching based on a previous map model.


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