Automatically generating training data for a lidar using simulated vehicles in virtual space
US11521009B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 4, 2019 |
| Grant date | Dec 6, 2022 |
| Priority date | — |
| Expiry date | Mar 5, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/588
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Automated training dataset generators that generate feature training datasets for use in real-world autonomous driving applications based on virtual environments are disclosed herein. The feature training datasets may be associated with training a machine learning model to control real-world autonomous vehicles. In some embodiments, an occupancy grid generator is used to generate an occupancy grid indicative of an environment of an autonomous vehicle from an imaging scene that depicts the environment. The occupancy grid is used to control the vehicle as the vehicle moves through the environment. In further embodiments, a sensor parameter optimizer may determine parameter settings for use by real-world sensors in autonomous driving applications. The sensor parameter optimizer may determine, based on operation of the autonomous vehicle, an optimal parameter setting of the parameter setting where the optimal parameter setting may be applied to a real-world sensor associated with real-world autonomous driving applications.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.