Systems and methods for training a machine learned model for agent navigation
US11436441B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 17, 2019 |
| Grant date | Sep 6, 2022 |
| Priority date | — |
| Expiry date | Aug 19, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computer-implemented method is disclosed for training one or more machine-learned models. The method can include inputting a first image frame and a second image frame into a feature disentanglement model and receiving, as an output of the machine-learned feature disentanglement model, a state feature and a perspective feature. The method can include inputting the state feature and the perspective feature into a machine-learned decoder model and receiving, as an output of the machine-learned decoder model, the reconstructed image frame. The method can include comparing the reconstructed image frame with a third image frame corresponding with the location and the perspective orientation. The method can include adjusting one or more parameters of the machine-learned feature disentanglement model based on the comparison of the reconstructed image frame and the third image frame.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.