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:
Feb. 14, 2023

Filed:

Feb. 28, 2019
Applicant:

Honda Research Institute Europe Gmbh, Offenbach/Main, DE;

Inventors:

Mathias Franzius, Offenbach, DE;

Benjamin Metka, Offenbach, DE;

Ute Bauer-Wersing, Offenbach, DE;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/04 (2006.01); G06F 17/18 (2006.01); G06N 3/088 (2023.01); H04W 4/02 (2018.01); G05D 1/02 (2020.01);
U.S. Cl.
CPC ...
G06N 3/0472 (2013.01); G05D 1/0274 (2013.01); G06F 17/18 (2013.01); G06N 3/088 (2013.01); H04W 4/026 (2013.01); H04W 4/027 (2013.01); G05D 1/0272 (2013.01);
Abstract

A method of unsupervised learning of a metric representation and a corresponding system for a mobile device determines a metric position information for a mobile device from an environmental representation. The mobile device comprises at least one sensor for acquiring sensor data and an odometer system configured to acquire displacement data of the mobile device. An environmental representation is generated based on the acquired sensor data by applying an unsupervised learning algorithm. The mobile device moves along a trajectory and the displacement data and the sensor data are acquired while the mobile device is moving along the trajectory. A set of mapping parameters is calculated based on the environmental representation and the displacement data. A metric position estimation is determined based on a further environmental representation and the calculated set of mapping parameters.


Find Patent Forward Citations

Franzius, Mathias. (2023). Unsupervised learning of metric representations from slow features (U.S. Patent No. 11580364). U.S. Patent and Trademark Office. https://idiyas.com/patent/badge/11580364

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

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