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:
Nov. 26, 2024

Filed:

Mar. 17, 2022
Applicant:

GM Cruise Holdings Llc, San Francisco, CA (US);

Inventor:

Feng Tian, Foster City, CA (US);

Assignee:

GM CRUISE HOLDINGS LLC, San Francisco, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
B60W 50/02 (2012.01); B60W 60/00 (2020.01); G06V 10/98 (2022.01); G06V 20/56 (2022.01);
U.S. Cl.
CPC ...
B60W 50/0205 (2013.01); B60W 50/0225 (2013.01); B60W 60/001 (2020.02); G06V 10/98 (2022.01); G06V 20/56 (2022.01);
Abstract

The subject disclosure relates to techniques for filtering perception-related artifacts. The disclosed technology can include receiving, by a machine learning model, a first output generated by a perception system model onboard an autonomous vehicle, wherein the first output is based on sensor data received from sensors of the autonomous vehicle at a first time and includes an inaccurate perception of an environment around the autonomous vehicle, receiving, by the machine learning model, a second output generated by the perception system model onboard the autonomous vehicle, wherein the second output is based on sensor data received from sensors of the autonomous vehicle at a second time after the first time and includes an accurate perception of the environment around the autonomous vehicle, and altering, by the machine learning model, the inaccurate perception of the environment from the first output based on the accurate perception of the environment in the second output.


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