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:
Sep. 17, 2024

Filed:

Apr. 27, 2021
Applicant:

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

Inventors:

Rahul Ramakrishnan, Ames, IA (US);

Aziz Alibasic, Waukee, IA (US);

Thomas Antony, Ames, IA (US);

Venkata Rama Karthik Paga, Ames, IA (US);

Assignee:

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

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
B60W 60/00 (2020.01); G06N 3/08 (2023.01); G06V 10/764 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06V 20/58 (2022.01);
U.S. Cl.
CPC ...
B60W 60/00274 (2020.02); B60W 60/001 (2020.02); G06N 3/08 (2013.01); G06V 10/764 (2022.01); G06V 10/803 (2022.01); G06V 10/82 (2022.01); G06V 20/58 (2022.01); B60W 2420/403 (2013.01); B60W 2420/408 (2024.01); B60W 2554/4049 (2020.02);
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, and tracking objects from on-board sensors configured with the autonomous machinery as it performs activities in either an agricultural setting or a transportation environment. The framework generates commands for navigational control of autonomously-operated vehicles in response to detected objects and predicted tracks thereof for safe operation in the performance of those activities. The framework processes image data and range data in multiple fields of view around the autonomously-operated to discern and track objects in a deep learning to accurately interpret this data for determining and effecting such navigational control.


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