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:
May. 30, 2023

Filed:

Feb. 12, 2021
Applicants:

Toyota Research Institute, Inc., Los Altos, CA (US);

The Board of Trustees of the Leland Stanford Junior University, Stanford, CA (US);

Inventors:

Haruki Nishimura, Stanford, CA (US);

Negar Zahedi Mehr, Champaign, IL (US);

Adrien David Gaidon, Mountain View, CA (US);

Mac Schwager, Stanford, CA (US);

Assignee:

Toyota Research Institute, Inc., Los Altos, CA (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G05D 1/02 (2020.01); B25J 9/16 (2006.01);
U.S. Cl.
CPC ...
G05D 1/0214 (2013.01); G05D 1/0287 (2013.01); B25J 9/163 (2013.01);
Abstract

Systems and methods described herein relate to controlling a robot. One embodiment receives an initial state of the robot, an initial nominal control trajectory of the robot, and a Kullback-Leibler (KL) divergence bound between a modeled probability distribution for a stochastic disturbance and an unknown actual probability distribution for the stochastic disturbance; solves a bilevel optimization problem subject to the modeled probability distribution and the KL divergence bound using an iterative Linear-Exponential-Quadratic-Gaussian (iLEQG) algorithm and a cross-entropy process, the iLEQG algorithm outputting an updated nominal control trajectory, the cross-entropy process outputting a risk-sensitivity parameter; and controls operation of the robot based, at least in part, on the updated nominal control trajectory and the risk-sensitivity parameter.


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