公开(公告)号：US20240242145A1

公开(公告)日：2024-07-18

申请号：US18156347

申请日：2023-01-18

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Haochen Luo ,  Eric Hermann ,  Rishab Saraf ,  Abhinav Darbari ,  Teodor Lefter ,  Jason Sanchez ,  Jagannath Putrevu

IPC: G06Q10/0631 ,  G06Q10/0639 ,  G06Q10/0835 ,  G06Q10/087 ,  G06Q30/0202 ,  G06Q30/0601

CPC classification number: G06Q10/063118 ,  G06Q10/06398 ,  G06Q10/08355 ,  G06Q10/087 ,  G06Q30/0202 ,  G06Q30/0635

Abstract: An online concierge shopping system fulfills orders using workers who pick items at a warehouse to complete an order and workers to deliver the orders to a customer's location. To optimize the staffing of workers for each task, the system uses a trained model to predict the number of workers needed to achieve an optimal outcome based on an input set of contextual information. The system also schedules specific workers to various shifts using the predicted number of workers needed and then searching a feasibility space for an optimal solution. The trained model may be updated based on performance observations.

公开(公告)号：US20240202694A1

公开(公告)日：2024-06-20

申请号：US18169012

申请日：2023-02-14

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Ganglu Wu ,  Shiyuan Yang ,  Xiao Zhou ,  Qi Wang ,  Qunwei Liu ,  Youming Luo

IPC: G06Q20/20 ,  G06K7/14 ,  G06Q30/0601 ,  G06T3/40 ,  G06V10/25

CPC classification number: G06Q20/208 ,  G06K7/1443 ,  G06Q30/0633 ,  G06Q30/0641 ,  G06T3/40 ,  G06V10/25

Abstract: An automated checkout system modifies received images of machine-readable labels to improve the performance of a label detection model that the system uses to decode item identifiers encoded in the machine-readable labels. For example, the automated checkout system may transform subregions of an image of a machine-readable label to adjust for distortions in the image's depiction of the machine-readable label. Similarly, the automated checkout system may identify readable regions within received images of machine-readable labels and apply a label detection model to those readable regions. By modifying received images of machine-readable labels, these techniques improve on existing computer-vision technologies by allowing for the effective decoding of machine-readable labels based on real-world images using relatively clean training data.

公开(公告)号：US20240177226A1

公开(公告)日：2024-05-30

申请号：US18072487

申请日：2022-11-30

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Andrew Peters ,  Dominic Cocchiarella ,  Brandon Leonardo ,  David McIntosh ,  Varouj Chitilian

IPC: G06Q30/0601 ,  G06Q30/0207 ,  G06Q30/0251 ,  G06T13/40 ,  H04W4/021

CPC classification number: G06Q30/0643 ,  G06Q30/0209 ,  G06Q30/0255 ,  G06Q30/0261 ,  G06Q30/0271 ,  G06Q30/0631 ,  G06T13/40 ,  H04W4/021

Abstract: A computing platform may receive, from a user device, historical shopping information indicating previously purchased items and/or previous routes within shopping environments for a first user of the user device. The computing platform may input, into a shopping gamification model, the historical shopping information, which may output shopping recommendation information indicating one or more of: recommended items or recommended routes within a first shopping environment. The computing platform may send, to the user device, a shopping gamification interface that includes the shopping recommendation information and one or more commands directing the user device to display the shopping gamification interface. The computing platform may receive, from the user device, user feedback information indicating acceptance or rejection of the shopping recommendation information by the first user. The computing platform may update, based on the user feedback information, the shopping gamification model.

公开(公告)号：US20240104569A1

公开(公告)日：2024-03-28

申请号：US17955228

申请日：2022-09-28

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Rohit Turumella ,  Yehonatah Afek ,  Chun-Che Wang ,  Leslie McFadden ,  Thomas Doan

IPC: G06Q20/40 ,  G06Q30/06

CPC classification number: G06Q20/4016 ,  G06Q30/0617 ,  G06Q30/0635

Abstract: An online concierge system facilitates a checkout bypass process for shoppers. The online concierge system detects when the shopper procuring an order for a customer is ready to exit the warehouse after obtaining the items in the order. The online concierge system applies a trained risk model to automatically determining whether to initiate an audit of the shopper. Responsive to determining to initiate the audit, the online concierge system invokes an auditing process. The online concierge system receives, via an auditor application, verification of the order from the auditor mobile application. Responsive to the verification, the online concierge system completes the order and generates routing instructions via the shopper mobile application for facilitating delivery by the shopper to the customer.

公开(公告)号：US20240104493A1

公开(公告)日：2024-03-28

申请号：US17935091

申请日：2022-09-24

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Reza Faturechi ,  Dylan Wang ,  Brian Duggan ,  Xianlei Qiu ,  Atul Gupte ,  Bing Hong Leonard How

IPC: G06Q10/08 ,  G06Q10/06

CPC classification number: G06Q10/087 ,  G06Q10/06312 ,  G06Q10/0639

Abstract: An online concierge system generates order batches for pickers and offers those order batches. The online concierge system generates a set of candidate order batches, which are subsets of a received set of orders. The online concierge system generates a set of order batch scores for each of a set of candidate pickers, and offers the candidate order batches to the candidate pickers for the candidate pickers to service based on the set of order batch scores. If a candidate picker accepts the offered order batch, the online concierge system identifies candidate order batches with overlapping orders with the order batch accepted by the candidate picker, and rescinds the offer for each of the candidate pickers to service the order batches.

公开(公告)号：US20240070746A1

公开(公告)日：2024-02-29

申请号：US17899483

申请日：2022-08-30

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Girija Narlikar ,  Sharath Rao Karikurve

IPC: G06Q30/06 ,  G06N20/00 ,  G06Q30/02

CPC classification number: G06Q30/0631 ,  G06N20/00 ,  G06Q30/0201 ,  G06Q30/0633

Abstract: A method implemented at a computer system includes, responsive to identifying an opportunity to present content to a target user, accessing a machine learning model trained on a dataset containing input features of a plurality of users and labels indicating openness metrics of the respective plurality of users. The machine learning model is then applied to a set of features of the target user to output an openness metric that predicts a loss in the target user's response rate when contextual relevance is not considered in selection of recommendation for the target user. A recommendation is then selected from a plurality of candidate recommendations based on the openness metric and sent for display to the target user.

公开(公告)号：US20240070393A1

公开(公告)日：2024-02-29

申请号：US17821889

申请日：2022-08-24

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Shishir Kumar Prasad ,  Cameron Nicholas Taylor ,  John Salaveria ,  Joey Loi ,  Kevin McCullough

IPC: G06F40/284 ,  G06Q30/06

CPC classification number: G06F40/284 ,  G06Q30/0621

Abstract: An online concierge system generates suggested instructions for presentation to a user. The online concierge system access instruction examples corresponding to a target item category and generates candidate instruction representations based on instruction messages within each instruction example. The online concierge system generates preliminary scores for the candidate instruction representations that are directly related to an intra-category frequency of use of the instruction tokens of the candidate instruction representation within the target item category. The online system normalizes these preliminary scores for the candidate instruction representations based on the inter-category frequency of use of the instruction tokens in all item categories to generate final scores for the candidate instruction representations. The online concierge system selects a set of instruction representations based on these final scores and generates suggested instructions based on the set of instruction representations.

公开(公告)号：US20240054449A1

公开(公告)日：2024-02-15

申请号：US17936232

申请日：2022-09-28

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Lin Gao ,  Yilin Huang ,  Shiyuan Yang ,  Hao Wu ,  Ganglu Wu ,  Xiao Zhou

IPC: G06Q10/08 ,  G06V20/52

CPC classification number: G06Q10/087 ,  G06V20/52

Abstract: An online concierge system may use images received from shopping carts within retailers to determine the availability of items within those retailers. A shopping cart includes externally-facing cameras that automatically capture images of the area around the shopping cart as the shopping cart travels through a retailer. The online concierge system receives these images, which depict displays within the retailers from which a picker or a retailer patron can collect items. The online concierge system determines which items should be depicted in the images and which items are actually depicted in the images. The online concierge system identifies which items should be depicted, but are not depicted, and determines that these items are unavailable (e.g., out of stock) at that retailer. The online concierge system updates an availability database to indicate that these items are unavailable and may notify the retailer that the item is unavailable.

公开(公告)号：US20240034381A1

公开(公告)日：2024-02-01

申请号：US17936226

申请日：2022-09-28

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Lin Gao ,  Yilin Huang ,  Shiyuan Yang ,  Jianbo Meng ,  Yakun Li ,  Linhua Luo ,  Weiting Chen

IPC: B62B5/00 ,  B62B3/14 ,  G06Q30/06

CPC classification number: B62B5/0096 ,  B62B3/1424 ,  G06Q30/06

Abstract: An automated checkout system uses a shopping cart that is automatically charged when stacked into another shopping cart. Each shopping cart has a front charging connector and a rear charging connector. When a first shopping cart is stacked into a second shopping cart, the front charging connector of the first shopping cart connects with the rear charging connector of the second shopping cart. Electrical power can flow to the first shopping cart via the second shopping cart to charge a battery of the first shopping cart. The second shopping cart may be similarly stacked into a third shopping cart, wherein the second shopping cart receives electrical power from the third shopping cart. The second shopping cart may use this electrical power to charge its own battery or may provide some or all of the electrical power to the first shopping cart to charge the first shopping cart's battery.

公开(公告)号：US20240013185A1

公开(公告)日：2024-01-11

申请号：US17874987

申请日：2022-07-27

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Lin Gao ,  Yilin Huang ,  Shiyuan Yang ,  Ganglu Wu ,  Yang Wang ,  Wentao Pan

IPC: G06Q20/20 ,  G06V10/80 ,  G01G19/40 ,  G01G19/12

CPC classification number: G06Q20/208 ,  G06V10/803 ,  G01G19/40 ,  G01G19/12

Abstract: A smart shopping cart includes internally facing cameras and an integrated scale to identify objects that are placed in the cart. To avoid unnecessary processing of images that are irrelevant, and thereby save battery life, the cart uses the scale to detect when an object is placed in the cart. The cart obtains images from a cache and sends those to an object detection machine learning model. The cart captures and sends a load curve as input to the trained model for object detection. Labeled load data and labeled image data are used by a model training system to train the machine learning model to identify an item when it is added to the shopping cart. The shopping cart also uses weight data and the image data from a timeframe associated with the addition of the item to the cart as inputs.