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:
Mar. 25, 2025

Filed:

Jun. 21, 2021
Applicant:

Honda Motor Co., Ltd., Tokyo, JP;

Inventors:

Harshayu Girase, Union City, CA (US);

Haiming Gang, San Jose, CA (US);

Srikanth Malla, Sunnyvale, CA (US);

Jiachen Li, Albany, CA (US);

Akira Kanehara, Utsunomiya, JP;

Chiho Choi, San Jose, CA (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
B60W 60/00 (2020.01); G01S 17/86 (2020.01); G01S 17/894 (2020.01); G06T 7/20 (2017.01);
U.S. Cl.
CPC ...
B60W 60/0027 (2020.02); G01S 17/86 (2020.01); G01S 17/894 (2020.01); G06T 7/20 (2013.01); B60W 2420/403 (2013.01); B60W 2420/408 (2024.01); B60W 2554/4029 (2020.02); B60W 2554/4045 (2020.02); B60W 2556/10 (2020.02); G06T 2207/10024 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20072 (2013.01); G06T 2207/30196 (2013.01); G06T 2207/30236 (2013.01); G06T 2207/30241 (2013.01); G06T 2207/30252 (2013.01);
Abstract

A system and method for providing long term and key intentions for trajectory prediction that include receiving image data and LiDAR data associated with RGB images and LiDAR point clouds that are associated with a surrounding environment of an ego agent and processing a long term and key intentions for trajectory prediction dataset (LOKI dataset) that is utilized to complete joint trajectory and intention prediction for heterogeneous traffic agents. The system and method also include encoding a past observation history of each of the heterogeneous traffic agents and sampling a respective goal. The system and method further include decoding and predicting future trajectories associated with each of the heterogeneous traffic agents based on data included within the LOKI dataset, the encoded past observation history, and the respective goal.


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