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:
Jan. 07, 2025

Filed:

Apr. 27, 2022
Applicant:

Snap Inc., Santa Monica, CA (US);

Inventors:

David G. Fliszar, Manhattan Beach, CA (US);

Russell Douglas Patton, Playa Vista, CA (US);

Assignee:

Snap Inc., Santa Monica, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G08G 5/00 (2006.01); B64C 39/02 (2023.01); B64U 50/19 (2023.01); B64U 101/30 (2023.01);
U.S. Cl.
CPC ...
G08G 5/0039 (2013.01); B64C 39/024 (2013.01); G08G 5/006 (2013.01); G08G 5/0069 (2013.01); G08G 5/0091 (2013.01); B64U 50/19 (2023.01); B64U 2101/30 (2023.01); B64U 2201/10 (2023.01);
Abstract

Systems, computer readable medium and methods for navigation correction for excessive wind in an autonomous drone are disclosed. Excessive winds can be a particular problem for small autonomous drones as safety and retrieval of the autonomous drones is important and the autonomous drones often have limited thrust and batteries. Autonomous drones are disclosed that detect and correct flight plans when excessive winds are detected. The autonomous drone determines based on the severity of the excessive winds whether to return to a home position which is typically a position of a user of the autonomous drone or to land in place. If the excessive winds subside, then the autonomous drone returns to its original flight plan at the point where the autonomous drone was blown off course by the excessive winds. The autonomous drone detects excessive winds either directly by sensor data or inferentially by unanticipated movement of the autonomous drone.


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