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. 06, 2022

Filed:

Dec. 17, 2019
Applicant:

University of Washington, Seattle, WA (US);

Inventors:

Santosh Devasia, Seattle, WA (US);

Anuj Tiwari, Seattle, WA (US);

Assignee:

University of Washington, Seattle, WA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G05D 1/00 (2006.01); G08G 1/01 (2006.01); G08G 1/00 (2006.01); G05D 1/02 (2020.01); G08G 5/00 (2006.01);
U.S. Cl.
CPC ...
G05D 1/0088 (2013.01); G05D 1/0293 (2013.01); G05D 1/0295 (2013.01); G08G 1/0129 (2013.01); G08G 1/22 (2013.01); G08G 5/0069 (2013.01); G05D 2201/0213 (2013.01);
Abstract

The behavior of automated agents, such as autonomous vehicles, drones, and the like, can be improved by control systems and methods that implement a combination of neighbor following behavior, or neighbor-averaged information transfer, with delayed self-reinforcement by utilizing time-delayed movement data to modify course corrections of each automated agent. Disclosed herein are systems and methods by which a follower agent, or a multiple follower agents in formation with a plurality of automated agents, can be controlled by generating course correction data for each follower agent based on the movement of neighboring agents in formation, and augmenting the course correction data based on time-delayed movement data of the follower agent. The delayed self-reinforcement behavior can (i) increase the information-transfer rate between autonomous agents without requiring an increased, individual update-rate; and (ii) cause superfluid-like information transfer between the autonomous agents, resulting in improvements in formation-keeping performance of the autonomous agents.


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