Self-learning industrial robotic system
US11554482B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 16, 2020 |
| Grant date | Jan 17, 2023 |
| Priority date | — |
| Expiry date | Mar 23, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG05B2219/40499
- WIPO fieldHandling
- WIPO sectorMechanical engineering
Abstract
Example implementations described herein are directed to a simulation environment for a real world system involving one or more robots and one or more sensors. Scenarios are loaded into a simulation environment having one or more virtual robots corresponding to the one or more robots, and one or more virtual sensors corresponding to the one or more virtual system to train a control strategy model from reinforcement learning, which is subsequently deployed to the real world environment. In cases of failure of the real world environment, the failures are provided to the simulation environment to generate an updated control strategy model for the real world environment.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.