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:
Oct. 13, 2020

Filed:

Sep. 12, 2018
Applicant:

Episys Science, Inc., Poway, CA (US);

Inventors:

Nadeesha Oliver Ranasinghe, Torrance, CA (US);

Bong Kyun Ryu, Poway, CA (US);

Wei-Min Shen, Rancho Palos Verdes, CA (US);

Assignee:

EpiSys Science, Inc., Poway, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04L 29/08 (2006.01); G07C 5/02 (2006.01); G07C 5/08 (2006.01); H04W 76/25 (2018.01); H04W 76/11 (2018.01); G05D 1/10 (2006.01); G06K 9/62 (2006.01); H04W 4/02 (2018.01); H04W 40/24 (2009.01); H04W 4/021 (2018.01); H04W 24/10 (2009.01); H04W 72/04 (2009.01); G06K 9/00 (2006.01); H04W 84/18 (2009.01); G05D 1/00 (2006.01); H04W 84/00 (2009.01);
U.S. Cl.
CPC ...
H04L 67/12 (2013.01); G05D 1/104 (2013.01); G06K 9/6284 (2013.01); G06K 9/6296 (2013.01); G07C 5/02 (2013.01); G07C 5/08 (2013.01); H04W 4/021 (2013.01); H04W 4/023 (2013.01); H04W 24/10 (2013.01); H04W 40/248 (2013.01); H04W 72/0406 (2013.01); H04W 76/11 (2018.02); H04W 76/25 (2018.02); G05D 1/00 (2013.01); G06K 9/00664 (2013.01); G06K 9/6297 (2013.01); H04W 84/005 (2013.01); H04W 84/18 (2013.01);
Abstract

A method and apparatus are provided for autonomously detecting and reporting anomalies in actions of an autonomous mobile node, or in behaviors of a swarm of autonomous mobile nodes to an operator. The autonomous mobile node may experience anomalies or unexpected situations due to various failures or external influence (e.g. natural weather phenomena, enemy threats). During a training phase a prediction model and a structured model may be established from measurement data received from one or more sensors of an autonomous mobile node or a swarm of nodes while executing an action or behavior under normal circumstances. A prediction model forecasts the expected outcome of an action or behavior, and structured model helps quantify the similarity of a learned action or behavior to the currently observed situation. Based on the measurement data applicable models can be used for an action or behavior for anomaly detection in the action or behavior.


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