Predictive modeling of aircraft dynamics
US12360529B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 18, 2022 |
| Grant date | Jul 15, 2025 |
| Priority date | — |
| Expiry date | May 9, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG08G5/55
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Training adversarial aircraft controllers is provided. The method comprises inputting current observed states of a number of aircraft into a world model encoder, wherein each current state represents a state of a different aircraft, and wherein each current state comprises a missing parameter value. A number of adversarial control actions for the aircraft are input into the world model encoder concurrently with the current observed state, wherein the adversarial control actions are generated by competing neural network controllers. The world model encoder generates a learned observation from the current observed states and adversarial control actions, wherein the learned observation represents the missing parameter value from the current observed states. The learned observation and current observed states are input into the competing neural network controllers, wherein each current observed state is fed into a respective controller. The competing neural network controllers then generate next adversarial control actions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.