Training artificial networks for robotic picking
US11911901B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 8, 2020 |
| Grant date | Feb 27, 2024 |
| Priority date | — |
| Expiry date | Jan 16, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/047
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Various embodiments of the present technology generally relate to robotic devices and artificial intelligence. More specifically, some embodiments relate to an artificial neural network training method that does not require extensive training data or time expenditure. The few-shot training model disclosed herein includes attempting to pick up items and, in response to a failed pick up attempt, transferring and generalizing information to similar regions to improve probability of success in future attempts. In some implementations, the training method is used to robotic device for picking items from a bin and perturbing items in a bin. When no picking strategies with high probability of success exist, the robotic device may perturb the contents of the bin to create new available pick-up points. In some implementations, the device may include one or more Computer-vision systems.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.