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:
Aug. 22, 2023

Filed:

Jan. 10, 2020
Applicant:

Raven Industries, Inc., Sioux Falls, SD (US);

Inventors:

Colin Josh Hurd, Ames, IA (US);

Rahul Ramakrishnan, Ames, IA (US);

Mark William Barglof, Burt, IA (US);

Quincy Calvin Milloy, Ames, IA (US);

Thomas Antony, Ames, IA (US);

Assignee:

Raven Industries, Inc., Sioux Falls, SD (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G05D 1/02 (2020.01); G05D 1/00 (2006.01); B60W 10/20 (2006.01); B60W 10/18 (2012.01); B60W 10/04 (2006.01); B60W 10/10 (2012.01); G06K 9/00 (2022.01); G06K 9/62 (2022.01); G06N 20/00 (2019.01); G06V 10/82 (2022.01); G06V 20/58 (2022.01); G06F 18/24 (2023.01); G06F 18/214 (2023.01); G06F 18/21 (2023.01); G06F 18/25 (2023.01); G06V 10/143 (2022.01);
U.S. Cl.
CPC ...
G06V 10/82 (2022.01); B60W 10/04 (2013.01); B60W 10/10 (2013.01); B60W 10/18 (2013.01); B60W 10/20 (2013.01); G05D 1/0088 (2013.01); G05D 1/0214 (2013.01); G05D 1/0246 (2013.01); G05D 1/0248 (2013.01); G06F 18/214 (2023.01); G06F 18/217 (2023.01); G06F 18/24 (2023.01); G06F 18/251 (2023.01); G06N 20/00 (2019.01); G06V 10/143 (2022.01); G06V 20/58 (2022.01); B60W 2300/15 (2013.01); B60W 2420/42 (2013.01); B60W 2554/00 (2020.02); B60W 2710/10 (2013.01); B60W 2710/18 (2013.01); B60W 2710/20 (2013.01); B60W 2720/106 (2013.01); G05D 2201/0201 (2013.01);
Abstract

A framework for safely operating autonomous machinery, such as vehicles and other heavy equipment, in an in-field or off-road environment, includes detecting, identifying, classifying and tracking objects and/or terrain characteristics from on-board sensors that capture images in front and around the autonomous machinery as it performs agricultural or other activities. The framework generates commands for navigational control of the autonomous machinery in response to perceived objects and terrain impacting safe operation. The framework processes image data and range data in multiple fields of view around the autonomous equipment to discern objects and terrain, and applies artificial intelligence techniques in one or more neural networks to accurately interpret this data for enabling such safe operation.


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