Training trajectory scoring neural networks to accurately assign scores
US11586931B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 31, 2019 |
| Grant date | Feb 21, 2023 |
| Priority date | — |
| Expiry date | May 4, 2041 |
Classification
- Technology area (CPC B)Performing Operations; Transporting
- CPC primaryB60W60/0011
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a neural network having a plurality of sub neural networks to assign respective confidence scores to one or more candidate future trajectories for an agent. Each confidence score indicates a predicted likelihood that the agent will move along the corresponding candidate future trajectory in the future. In one aspect, a method includes using the first sub neural network to generate a training intermediate representation; using the second sub neural network to generate respective training confidence scores; using a trajectory generation neural network to generate a training trajectory generation output; computing a first loss and a second loss; and determining an update to the current values of the parameters of the first and second sub neural networks.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.