Machine-learned model for optimizing selection sequence for items in a warehouse
US11775926B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 29, 2018 |
| Grant date | Oct 3, 2023 |
| Priority date | — |
| Expiry date | Feb 27, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An online shopping concierge system sorts a list of items to be picked in a warehouse by receiving data identifying a warehouse and items to be picked by a picker in the warehouse. The system retrieves a machine-learned model that predicts a next item of a picking sequence of items. The model was trained, using machine-learning, based on sets of data that each include a list of picked items, an identification of a warehouse from which the items were picked, and a sequence in which the items were picked. The system identifies an item to pick first and a plurality of remaining items. The system predicts, using the model, a next item to be picked based on the remaining items, the first item, and the warehouse. The system transmits data identifying the first item and the predicted next item to be picked to the picker in the warehouse.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.