Controlling position of robot by determining goal proposals by using neural networks
US11958529B2 · kind B2 · utility
3Cited by
4References
24Claims
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Key dates
| Filing date | Aug 20, 2020 |
| Grant date | Apr 16, 2024 |
| Priority date | — |
| Expiry date | Dec 29, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A framework for offline learning from a set of diverse and suboptimal demonstrations operates by selectively imitating local sequences from the dataset. At least one embodiment recovers performant policies from large manipulation datasets by decomposing the problem into a goal-conditioned imitation and a high-level goal selection mechanism.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.