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:
Feb. 11, 2025

Filed:

May. 26, 2022
Applicant:

National Yang Ming Chiao Tung University, Hsinchu, TW;

Inventors:

Mang Ou-Yang, Hsinchu, TW;

Yung-Jhe Yan, Taipei, TW;

Ming-Da Jiang, Dalin Township, TW;

Ta-Fu Hsu, Taoyuan, TW;

Shao-Chun Yeh, Taoyuan, TW;

Kun-Hsiang Chen, Kaohsiung, TW;

Tzung-Cheng Chen, Tainan, TW;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 10/82 (2022.01); B64C 39/02 (2023.01); G01C 21/00 (2006.01); G05D 1/00 (2006.01); G06V 10/56 (2022.01); G06V 10/762 (2022.01); G06V 10/80 (2022.01); G06V 20/58 (2022.01); G08G 5/00 (2006.01);
U.S. Cl.
CPC ...
G06V 10/803 (2022.01); B64C 39/024 (2013.01); G01C 21/005 (2013.01); G05D 1/106 (2019.05); G06V 10/56 (2022.01); G06V 10/762 (2022.01); G06V 10/82 (2022.01); G06V 20/58 (2022.01); G08G 5/003 (2013.01); G08G 5/0069 (2013.01); B64U 2201/10 (2023.01);
Abstract

A method for searching a path by using a 3D reconstructed map includes: receiving 3D point-cloud map information and 3D material map information; clustering the 3D point-cloud map information with a clustering algorithm to obtain clustering information, and identifying material attributes of objects in the 3D point-cloud map information with a material neural network model to obtain material attribute information; fusing the those map information based on their coordinate information, thereby outputting fused map information; identifying obstacle areas and non-obstacle areas in the fused map information based on an obstacle neural network model, the clustering information, and the material attribute information; and generating 3D path information according to the non-obstacle areas. Since the 3D path information is generated based on those map information, the obstacle areas and flight spaces are effectively determined to generate an accurate flight path.


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