Patent · US Active

Neural networks with attention al bottlenecks for trajectory planning

US11565715B2 · kind B2 · utility

0Cited by
0References
17Claims
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Assignee

Inventors

Key dates

Filing dateSep 14, 2020
Grant dateJan 31, 2023
Priority date
Expiry dateOct 11, 2040

Classification

  • Technology area (CPC B)Performing Operations; Transporting
  • CPC primaryB60W2555/60
  • WIPO fieldMeasurement
  • WIPO sectorInstruments

Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for planning a trajectory of a vehicle. One of the methods includes obtaining input data for planning a driving trajectory for a vehicle, the input data comprising an intended route for the vehicle and data characterizing an environment in a vicinity of the vehicle; processing the input data using an input encoder neural network to generate feature data that includes a respective feature representation for each of a plurality of locations in the environment; applying spatial attention to the feature representations to generate a respective attention weight for each of the plurality of locations; generating a respective attended feature representation for each of the plurality of locations; generating a bottlenecked representation of the attended feature representations; and generating a planned future trajectory from at least the bottlenecked representation.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.