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. 08, 2025

Filed:

Apr. 29, 2022
Applicant:

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

Inventors:

Kuan-Hui Lee, San Jose, CA (US);

Charles Christopher Ochoa, San Francisco, CA (US);

Arjun Bhargava, San Francisco, CA (US);

Chao Fang, Sunnyvale, CA (US);

Kun-Hsin Chen, San Francisco, CA (US);

Assignees:
Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 10/82 (2022.01); G01S 7/41 (2006.01); G01S 13/86 (2006.01); G01S 13/931 (2020.01); G01S 17/86 (2020.01); G01S 17/89 (2020.01); G01S 17/931 (2020.01); G06V 10/20 (2022.01); G06V 10/62 (2022.01); G06V 10/80 (2022.01); G06V 20/56 (2022.01);
U.S. Cl.
CPC ...
G06V 10/82 (2022.01); G01S 7/417 (2013.01); G01S 13/865 (2013.01); G01S 13/931 (2013.01); G01S 17/86 (2020.01); G01S 17/89 (2013.01); G01S 17/931 (2020.01); G06V 10/255 (2022.01); G06V 10/62 (2022.01); G06V 10/80 (2022.01); G06V 10/806 (2022.01); G06V 20/56 (2022.01); G01S 13/862 (2013.01); G01S 13/867 (2013.01);
Abstract

Systems, methods, and other embodiments described herein relate to a multi-task model that integrates recurrent models to improve handling of multi-sweep inputs. In one embodiment, a method includes acquiring sensor data from multiple modalities. The method includes separately encoding respective segments of the sensor data according to an associated one of the different modalities to form encoded features using separate encoders of a network. The method includes accumulating, in a detector, sparse features associated with sparse sensor inputs of the multiple modalities to densify the sparse features into dense features. The method includes providing observations according to the encoded features and the sparse features using the network.


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