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:
Jun. 06, 2023

Filed:

Mar. 09, 2020
Applicant:

Honda Motor Co., Ltd., Tokyo, JP;

Inventor:

Yuji Hasegawa, Saitama, JP;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G05D 1/00 (2006.01); G05D 1/02 (2020.01); G06N 3/08 (2023.01); G06N 3/04 (2023.01); G06V 10/56 (2022.01); G06V 20/20 (2022.01); G06V 20/58 (2022.01); G06F 18/214 (2023.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 20/10 (2022.01);
U.S. Cl.
CPC ...
G05D 1/0221 (2013.01); G05D 1/0231 (2013.01); G06F 18/214 (2023.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06V 10/56 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 20/10 (2022.01); G06V 20/20 (2022.01); G06V 20/58 (2022.01);
Abstract

In an environment in which a plurality of second pedestrians moves along predetermined movement patterns, a plurality of movement routes when a first pedestrian moves toward a destination point is recognized. Data, in which an environmental image indicating a visual environment in front of a virtual robot when the virtual robot moves along each of the movement routes and a moving direction command indicating a moving direction of the virtual robot are combined, is generated as learning data. In the environmental image, colors corresponding to kinds of the moving objects are applied to at least a portion of moving object image regions indicating pedestrians (moving objects) present around a robot. Model parameters of a CNN (action model) is learned using the learning data, and a moving velocity command for the robot is determined using a learned CNN.


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