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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.

Patent No.:

US 11861896 B1

PDFFull Text
Date of Patent:
Jan. 02, 2024

Filed:

Mar. 29, 2022

Autonomous aerial navigation in low-light and no-light conditions

Applicant:

Skydio, Inc., Redwood City, CA (US);

Inventors:

Samuel Shenghung Wang, Mountain View, CA (US);

Vladimir Nekrasov, Adelaide, AU;

Ryan David Kennedy, Redwood City, CA (US);

Gareth Benoit Cross, Mountain View, CA (US);

Peter Benjamin Henry, San Francisco, CA (US);

Kristen Marie Holtz, Menlo Park, CA (US);

Hayk Martirosyan, San Francisco, CA (US);

Abraham Galton Bachrach, Redwood City, CA (US);

Adam Parker Bry, Redwood City, CA (US);

Assignee:

Skydio, Inc., San Mateo, CA (US);

Attorney:

Young Basile Hanlon & MacFarlane, P.C.

Primary Examiner:

Clifford Hilaire

Int. Cl.
CPC ...
G06V 20/17 (2022.01); G06V 10/82 (2022.01); G06V 10/30 (2022.01); H04N 5/33 (2023.01); G06T 5/00 (2006.01); G06T 3/40 (2006.01); G05D 1/10 (2006.01); B64C 39/02 (2023.01); G06V 10/60 (2022.01); B64U 101/30 (2023.01);
U.S. Cl.
CPC ...
G06V 20/17 (2022.01); B64C 39/024 (2013.01); G05D 1/101 (2013.01); G06T 3/4038 (2013.01); G06T 5/008 (2013.01); G06V 10/30 (2022.01); G06V 10/60 (2022.01); G06V 10/82 (2022.01); H04N 5/33 (2013.01); B64U 2101/30 (2023.01); B64U 2201/10 (2023.01); G06T 2207/10024 (2013.01); G06T 2207/10032 (2013.01); G06T 2207/20024 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20182 (2013.01); G06T 2207/30252 (2013.01);
Abstract

Autonomous aerial navigation in low-light and no-light conditions includes using night mode obstacle avoidance intelligence, training, and mechanisms for vision-based unmanned aerial vehicle (UAV) navigation to enable autonomous flight operations of a UAV in low-light and no-light environments using infrared data.

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