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:
Dec. 10, 2024

Filed:

Sep. 27, 2021
Applicant:

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

Inventors:

Basel Alghanem, Pittsburgh, PA (US);

Benjamin David Ballard, Pittsburgh, PA (US);

Russell Schloss, Pittsburgh, PA (US);

Christian Höeppner, Munich, DE;

Mark Ollis, Pittsburgh, PA (US);

George Peter Kenneth Carr, Allison Park, PA (US);

Assignee:

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

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
B60W 30/09 (2012.01); B60W 60/00 (2020.01); G01S 17/58 (2006.01); G01S 17/89 (2020.01); G01S 17/931 (2020.01);
U.S. Cl.
CPC ...
B60W 30/09 (2013.01); B60W 60/0027 (2020.02); G01S 17/58 (2013.01); G01S 17/89 (2013.01); G01S 17/931 (2020.01); B60W 2420/408 (2024.01); B60W 2554/4042 (2020.02); B60W 2554/4043 (2020.02);
Abstract

Systems and methods are described for measuring velocity of an object detected by a light detection and ranging (lidar) system. According to some aspects a method may include receiving a lidar dataset generated by the lidar system, transforming the lidar dataset into a first layer dataset and a second layer dataset, and converting the first layer dataset into a first image and the second layer dataset into a second image. The method may also include performing a feature detection operation that identifies at least one feature in the first image and the same feature in the second image, locating a first location of the feature in the first image and a second location of the feature in the second image, and generating a velocity estimate of the feature based on a difference between the first location and the second location and a difference between the different time intervals.


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