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:
Apr. 16, 2024

Filed:

Nov. 11, 2020
Applicant:

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

Inventors:

Ankit Laddha, Pittsburgh, PA (US);

Meet Pragnesh Shah, San Francisco, CA (US);

Zhiling Huang, Pittsburgh, PA (US);

Duncan Blake Barber, Pittsburgh, PA (US);

Matthew A. Langford, Pittsburgh, PA (US);

Carlos Vallespi-Gonzalez, Wexford, PA (US);

Sida Zhang, San Francisco, CA (US);

Assignee:

UATC, LLC, San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G05D 1/02 (2020.01); G01S 13/86 (2006.01); G05D 1/00 (2006.01); G06F 18/2413 (2023.01); G06F 18/25 (2023.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01); G01S 13/00 (2006.01);
U.S. Cl.
CPC ...
G05D 1/0221 (2013.01); G01S 13/865 (2013.01); G05D 1/0088 (2013.01); G05D 1/0257 (2013.01); G06F 18/24147 (2023.01); G06F 18/251 (2023.01); G06N 5/041 (2013.01); G06N 20/00 (2019.01);
Abstract

Systems and methods for trajectory prediction are provided. A method can include obtaining LIDAR data, radar data, and map data; inputting the LIDAR data, the radar data, and the map data into a network model; transforming, by the network model, the radar data into a coordinate frame associated with a most recent radar sweep in the radar data; generating, by the network model, one or more features for each of the LIDAR data, the transformed radar data, and the map data; combining, by the network model, the one or more generated features to generate fused feature data; generating, by the network model, prediction data based at least in part on the fused feature data; and receiving, as an output of the network model, the prediction data. The prediction data can include a respective predicted trajectory for a future time period for one or more detected objects.


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