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:
Jul. 25, 2023

Filed:

Dec. 03, 2021
Applicant:

Zoox, Inc., Foster City, CA (US);

Inventors:

Cheng-Hsin Wuu, Pittsburgh, PA (US);

Subhasis Das, Menlo Park, CA (US);

Po-Jen Lai, Mountain View, CA (US);

Qian Song, San Mateo, CA (US);

Benjamin Isaac Zwiebel, Burlingame, CA (US);

Assignee:

Zoox, Inc., Foster City, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/70 (2022.01); G06V 20/58 (2022.01); G06V 20/40 (2022.01); G06V 20/56 (2022.01);
U.S. Cl.
CPC ...
G06V 10/70 (2022.01); G06V 20/41 (2022.01); G06V 20/582 (2022.01); G06V 20/584 (2022.01); G06V 20/588 (2022.01);
Abstract

Techniques for a perception system of a vehicle that can detect and track objects in an environment are described herein. The perception system may include a machine-learned model that includes one or more different portions, such as different components, subprocesses, or the like. In some instances, the techniques may include training the machine-learned model end-to-end such that outputs of a first portion of the machine-learned model are tailored for use as inputs to another portion of the machine-learned model. Additionally, or alternatively, the perception system described herein may utilize temporal data to track objects in the environment of the vehicle and associate tracking data with specific objects in the environment detected by the machine-learned model. That is, the architecture of the machine-learned model may include both a detection portion and a tracking portion in the same loop.


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