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, 2026

Filed:

Aug. 25, 2021
Applicant:

Robert Bosch Gmbh, Stuttgart, DE;

Inventors:

Simon Passenheim, Berlin, DE;

Emiel Hoogeboom, Amsterdam, NL;

William Harris Beluch, Stuttgart, DE;

Assignee:

ROBERT BOSCH GMBH, Stuttgart, DE;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); B25J 9/02 (2006.01); B25J 9/16 (2006.01); G06N 3/0475 (2023.01); G16B 15/20 (2019.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); B25J 9/163 (2013.01); B25J 9/1671 (2013.01); B25J 9/023 (2013.01); G05B 2219/40499 (2013.01); G06N 3/0475 (2023.01); G16B 15/20 (2019.02);
Abstract

A computer-implemented method of estimating a reliability of control data for a computer-controlled system interacting with an environment. The control data is inferred from a model input by a machine learnable control model which is trained on a training dataset. The model input comprises at least one direction vector which is extracted from sensor data and which is associated with a component of the computer-controlled system or an object in the environment. The reliability is estimated using a generative model that is trained to generate synthetic model inputs representative of the training dataset, by applying an inverse of the generative model to the model input to determine a likelihood of the model input being generated according to the generative model. The generative model comprises a coupling layer comprising a circle transformation and one or more of an unconditional rotation and a conditional rotation.


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