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. 28, 2021

Filed:

Aug. 17, 2020
Applicant:

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

Inventors:

Gaurav Pandey, College Station, TX (US);

Ganesh Kumar, Santa Clara, CA (US);

Praveen Narayanan, San Jose, CA (US);

Jinesh Jain, Pacifica, CA (US);

Assignee:

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

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00805 (2013.01);
Abstract

A system comprises a computer that includes a processor and a memory. The memory stores instructions executable by the processor to estimate a first joint probability distribution of first data with respect to second data based on first and second marginal probability distributions of the first and second data, wherein the first data is from a first sensor based on a first sensor coordinate system, and the second data is from a second sensor based on a second sensor coordinate system, to estimate a second joint probability distribution of the first data with respect to the second data based on a projection of the first data onto a plane defined in the second sensor coordinate system, to estimate a rigid transformation between the first sensor coordinate system and the second sensor coordinate system by minimizing a distance between the first and second joint probability distributions, wherein the second joint probability distribution is a function of a set of extrinsic calibration parameters, and based on the set of the extrinsic calibration parameters, to detect an object in the first and second data.


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