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. 09, 2024

Filed:

Jan. 31, 2022
Applicants:

Chongqing University, Chongqing, CN;

Star Institute of Intelligent Systems, Chongqing, CN;

Db (Chongqing) Intelligent Technology Research Institute Co., Ltd., Chongqing, CN;

Inventors:

Yongduan Song, Chongqing, CN;

Jie Zhang, Chongqing, CN;

Junfeng Lai, Chongqing, CN;

Huan Liu, Chongqing, CN;

Ziqiang Jiang, Chongqing, CN;

Li Huang, Chongqing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G05D 1/00 (2006.01); G06N 3/084 (2023.01); H04B 17/318 (2015.01);
U.S. Cl.
CPC ...
G05D 1/0088 (2013.01); G05D 1/0272 (2013.01); G05D 1/028 (2013.01); G06N 3/084 (2013.01); H04B 17/318 (2015.01); G05D 2201/0207 (2013.01);
Abstract

The present disclosure provides a neural network-based method for calibration and localization of an indoor inspection robot. The method includes the following steps: presetting positions for N label signal sources capable of transmitting radio frequency (RF) signals; computing an actual path of the robot according to numbers of signal labels received at different moments; computing positional information moved by the robot at a tmoment, and computing a predicted path at the tmoment according to the positional information; establishing an odometry error model with the neural network and training the odometry error model; and inputting the predicted path at the tmoment to a well-trained odometry error model to obtain an optimized predicted path. The present disclosure maximizes the localization accuracy for the indoor robot by minimizing the error of the odometer with the odometry calibration method.


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