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. 25, 2020

Filed:

May. 04, 2018
Applicant:

Hrl Laboratories, Llc, Malibu, CA (US);

Inventors:

Soheil Kolouri, Calabasas, CA (US);

Amir M. Rahimi, Malibu, CA (US);

Rajan Bhattacharyya, Sherman Oaks, CA (US);

Assignee:

HRL Laboratories, LLC, Malibu, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06T 7/262 (2017.01); G06T 7/277 (2017.01); G06N 3/00 (2006.01); G06N 20/00 (2019.01); G06K 9/00 (2006.01); A63B 69/00 (2006.01); G08G 5/00 (2006.01); G08G 9/00 (2006.01); A63B 24/00 (2006.01);
U.S. Cl.
CPC ...
G06T 7/262 (2017.01); G06K 9/00 (2013.01); G06K 9/0063 (2013.01); G06K 9/00335 (2013.01); G06K 9/00718 (2013.01); G06K 9/00744 (2013.01); G06K 9/6211 (2013.01); G06K 9/6214 (2013.01); G06K 9/6232 (2013.01); G06K 9/6245 (2013.01); G06K 9/6247 (2013.01); G06N 3/006 (2013.01); G06N 20/00 (2019.01); G06T 7/277 (2017.01); A63B 69/0071 (2013.01); A63B 2024/0056 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30196 (2013.01); G06T 2207/30221 (2013.01); G06T 2207/30241 (2013.01); G08G 5/0069 (2013.01); G08G 9/00 (2013.01);
Abstract

Described is a system for predicting multi-agent movements. A Radon Cumulative Distribution Transform (Radon-CDT) is applied to pairs of signature-formations representing agent movements. Canonical correlation analysis (CCA) components are identified for the pairs of signature-formations. Then, a relationship between the pairs of signature formations is learned using the CCA components. A counter signature-formation for a new dataset is predicted using the learned relationship and a new signature-formation. Control parameters of a device can be adjusted based on the predicted counter signature-formation.


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