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:
Mar. 17, 2020

Filed:

Aug. 26, 2016
Applicant:

Ford Global Technologies, Llc, Dearborn, MI (US);

Inventors:

Alexander Groh, Detroit, MI (US);

Kay Kunes, Maranz, AZ (US);

Sarah Houts, Mountain View, CA (US);

Assignee:

FORD GLOBAL TECHNOLOGIES, LLC, Dearborn, MI (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2006.01); G06N 3/04 (2006.01); G09B 9/54 (2006.01); G06F 17/50 (2006.01); G06N 7/00 (2006.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06F 17/5009 (2013.01); G06F 17/5095 (2013.01); G06N 3/04 (2013.01); G06N 3/0454 (2013.01); G06N 7/005 (2013.01); G09B 9/54 (2013.01); G06F 2217/10 (2013.01);
Abstract

A machine learning module may generate a probability distribution from training data including labeled modeling data correlated with reflection data. Modeling data may include data from a LIDAR system, camera, and/or a GPS for a target environment/object. Reflection data may be collected from the same environment/object by a radar and/or an ultrasonic system. The probability distribution may assign reflection coefficients for radar and/or ultrasonic systems conditioned on values for modeling data. A mapping module may create a reflection model to overlay a virtual environment assembled from a second set of modeling data by applying the second set to the probability distribution to assign reflection values to surfaces within the virtual environment. Additionally, a test bench may evaluate an algorithm, for processing reflection data to generate control signals to an autonomous vehicle, with simulated reflection data from a virtual sensor engaging reflection values assigned within the virtual environment.


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