公开(公告)号：US20230162141A1

公开(公告)日：2023-05-25

申请号：US17534281

申请日：2021-11-23

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Benjamin Knight ,  Darren Johnson ,  Dan Haugh ,  Saumitra Maheshwari ,  Qi Xi ,  Conor Woods

IPC: G06Q10/08 ,  G06Q30/06

CPC classification number: G06Q10/087 ,  G06Q30/0629 ,  G06Q30/0641

Abstract: An online concierge system receives information from a warehouse including locations of items within the warehouse. When a shopper selects an order for fulfillment from the warehouse, the online concierge system sorts the items for the shopper to minimize the time spent in the warehouse using the received information. When the online concierge system does not receive a location of an item within the warehouse, the online concierge system obtains a taxonomy for the warehouse including multiple levels, with each level having a different level of specificity. The online concierge system determines a higher level in the taxonomy for the item and identifies other items offered by the warehouse having the determined category. The online concierge system infers a location of the item within the warehouse used for sorting items of the order from locations of the other items within the warehouse and times when shoppers retrieved the other items.

公开(公告)号：US12147938B2

公开(公告)日：2024-11-19

申请号：US17534281

申请日：2021-11-23

Applicant: Maplebear Inc.

Inventor： Benjamin Knight ,  Darren Johnson ,  Daniel Haugh ,  Saumitra Maheshwari ,  Qi Xi ,  Conor Woods

IPC: G06Q10/087 ,  G06Q30/0601 ,  G06Q30/06

Abstract: An online concierge system receives information from a warehouse including locations of items within the warehouse. When a shopper selects an order for fulfillment from the warehouse, the online concierge system sorts the items for the shopper to minimize the time spent in the warehouse using the received information. When the online concierge system does not receive a location of an item within the warehouse, the online concierge system obtains a taxonomy for the warehouse including multiple levels, with each level having a different level of specificity. The online concierge system determines a higher level in the taxonomy for the item and identifies other items offered by the warehouse having the determined category. The online concierge system infers a location of the item within the warehouse used for sorting items of the order from locations of the other items within the warehouse and times when shoppers retrieved the other items.

公开(公告)号：US20240005269A1

公开(公告)日：2024-01-04

申请号：US17855793

申请日：2022-07-01

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Benjamin Knight ,  Qi Xi ,  Saumitra Maheshwari ,  Salmaan Ayaz

IPC: G06Q10/08 ,  G06Q30/06

CPC classification number: G06Q10/087 ,  G06Q30/0633

Abstract: An online system performs a method. The method comprises obtaining historical pick data for items located in a warehouse, including data for each of the items picked and pick times between each of the items picked, and determining a taxonomy of items offered by the warehouse. The taxonomy identifies a plurality of product categories structured in a hierarchy, wherein each level of the hierarchy corresponds to a particular level of granularity of product data. The method further comprises applying the historical pick data to a machine learning model to generate pairwise relations between product categories at each level of the taxonomy and generating sequences of product categories based on the pairwise relations. An order for items offered by the warehouse is received and compared to the sequences for each level to generate a pick sequence for picking the items efficiently, which is outputted by the system to a mobile application.

公开(公告)号：US20250139574A1

公开(公告)日：2025-05-01

申请号：US18498016

申请日：2023-10-30

Applicant: Maplebear Inc.

Inventor： Shang Li ,  Ashish Sinha ,  Krishna Kumar Selvam ,  Qi Xi ,  Amirali Darvishzadeh ,  David Zandman ,  Christopher Billman

IPC: G06Q10/087 ,  G06N5/022

Abstract: A machine-learned predictive model is trained to predict potential for customer complaint. The model is part of an online concierge system. The online concierge system accesses a customer order that includes one or more items. The online concierge system determines input data for an item of the one or more items. The online concierge system determines a prediction value associated with potential for customer complaint for the item by applying the machine-learned prediction model to the input data. The online concierge system provides the prediction value to a picker client device associated with a picker who is assigned the item. The picker client device presents an alert to the picker based in part on the prediction value, and the alert includes a message that is customized to mitigate a cause of potential customer complaint for the item.

公开(公告)号：US20250037076A1

公开(公告)日：2025-01-30

申请号：US18916477

申请日：2024-10-15

Applicant: Maplebear Inc.

Inventor： Benjamin Knight ,  Darren Johnson ,  Daniel Haugh ,  Saumitra Maheshwari ,  Qi Xi ,  Conor Woods

IPC: G06Q10/087 ,  G06Q30/0601

Abstract: A method for optimizing order fulfillment in a warehouse by an online system. The system receives an item catalog from an inventory system, which includes item locations. The system also obtains a taxonomy that organizes items into hierarchical levels based on attributes. When an order is placed by a user, the system checks whether the item catalog contains location data for each item. If an item's location is missing, the system identifies alternative items from the taxonomy with shared attributes and uses the location of a selected alternative item as a proxy. The system determines a picking sequence for the items in the order, optimized to minimize travel distance within the warehouse, and transmits the sequence to a shopper's device for fulfillment.