Artificial intelligence system for learning robotic control policies
US10792810B1 · kind B1 · utility
34Cited by
2References
20Claims
0Family size
Assignee
Inventors
Key dates
| Filing date | Dec 14, 2017 |
| Grant date | Oct 6, 2020 |
| Priority date | — |
| Expiry date | Sep 2, 2038 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY10S901/03
- WIPO fieldHandling
- WIPO sectorMechanical engineering
Abstract
A machine learning system builds and uses computer models for controlling robotic performance of a task. Such computer models may be first trained using feedback on computer simulations of the robot performing the task, and then refined using feedback on real-world trials of the robot performing the task. Some examples of the computer models can be trained to automatically evaluate robotic task performance and provide the feedback. This feedback can be used by a machine learning system, for example an evolution strategies system or reinforcement learning system, to generate and refine the controller.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.