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:
Nov. 25, 2025

Filed:

Dec. 27, 2023
Applicants:

Jining University, Jining, CN;

Shanghai University, Shanghai, CN;

Inventors:

Jun Liu, Jining, CN;

Hengyu Li, Shanghai, CN;

Lei Wan, Shanghai, CN;

Jingyi Liu, Shanghai, CN;

Yueying Wang, Shanghai, CN;

Shaorong Xie, Shanghai, CN;

Jun Luo, Shanghai, CN;

Assignees:

Jining University, Jining, CN;

Shanghai University, Shanghai, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/593 (2017.01); G06T 3/40 (2024.01); G06T 7/80 (2017.01); H04N 13/00 (2018.01); H04N 13/239 (2018.01); H04N 13/271 (2018.01); H04N 23/61 (2023.01); H04N 23/698 (2023.01);
U.S. Cl.
CPC ...
G06T 7/593 (2017.01); G06T 3/40 (2013.01); G06T 7/80 (2017.01); H04N 13/239 (2018.05); H04N 13/271 (2018.05); H04N 23/61 (2023.01); H04N 23/698 (2023.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30244 (2013.01); H04N 2013/0081 (2013.01);
Abstract

Disclosed is a method for constructing a bionic binocular active visual simultaneous localization and mapping (SLAM) system. The method includes: S1, constructing a binocular active visual system, peripheral vision is simulated using a panoramic camera, a panoramic value map is constructed based on the panoramic camera, and a binocular bionic eye gaze control strategy based on the panoramic value map is proposed; S2, designing a SLAM algorithm framework which is suitable for motion of the two bionic eyes, where relative pose optimization of left and right cameras based on a Perspective-n-Point algorithm and depth calculation for binocular matching points based on triangulation are adopted in a SLAM tracking thread; and S3, with the assistance of camera poses estimated by the SLAM system and sparse landmark point coordinates, training a self-supervised depth estimation network, to provide dense depth estimation for a mapping module of the SLAM system, achieving dense mapping.


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