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. 27, 2022

Filed:

Dec. 13, 2019
Applicant:

Uatc, Llc, San Francisco, CA (US);

Inventors:

Eric Lloyd Wilkinson, San Francisco, CA (US);

Michael Lee Phillips, Pittsburgh, PA (US);

David Mcallister Bradley, Pittsburgh, PA (US);

Zakary Warren Littlefield, Pittsburgh, PA (US);

Aum Jadhav, San Francisco, CA (US);

Utku Eren, Pittsburgh, PA (US);

Samuel Philip Marden, Pittsburgh, PA (US);

Colin Jeffrey Green, Pittsburgh, PA (US);

Assignee:

UATC, LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G05D 1/00 (2006.01); B60W 30/095 (2012.01); G05D 1/02 (2020.01);
U.S. Cl.
CPC ...
G05D 1/0088 (2013.01); B60W 30/0956 (2013.01); G05D 1/0214 (2013.01); G05D 1/0221 (2013.01); B60W 2520/12 (2013.01); G05D 2201/0213 (2013.01);
Abstract

Systems and methods for vehicle motion planning based on uncertainty are provided. A method can include obtaining scene data descriptive of one or more objects within a surrounding environment of the autonomous vehicle. The method can include determining one or more subproblems based at least in part on the scene data. In some implementation, each of the one or more subproblems can correspond to at least one object within the surrounding environment of the autonomous vehicle. The method can include generating one or more branching policies based at least in part on the one or more subproblems. In some implementations, each of the one or more branching policies can include scene data associated with the autonomous vehicle and one or more objects within the surrounding environment of the autonomous vehicle. The method can include determining one or more costs associated each of the one or more branching policies. The method can include selecting a motion plan based at least in part on the one or more costs associated with each of the one or more branching policies. The method can include providing the motion plan for use in controlling a motion of the autonomous vehicle.


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