Training multiple neural networks of a vehicle perception component based on sensor settings
US10984257B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 31, 2018 |
| Grant date | Apr 20, 2021 |
| Priority date | — |
| Expiry date | Aug 19, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/59
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for controlling a vehicle based on sensor data having variable sensor parameter settings includes receiving sensor data generated by a vehicle sensor while the sensor is configured with a first sensor parameter setting. The method also includes receiving an indicator specifying the first sensor parameter setting, and selecting, based on the received indicator, one of a plurality of neural networks of a perception component, each neural network having been trained using training data corresponding to a different sensor parameter setting. The method also includes generating signals descriptive of a current state of the environment using the selected neural network and based on the received sensor data. The method further includes generating driving decisions based on the signals descriptive of the current state of the environment, and causing one or more operational subsystems of the vehicle to maneuver the vehicle in accordance with the generated driving decisions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.