US-12626237-B2 - Self-checkout anti-theft vehicle systems and methods

US12626237B2US 12626237 B2US12626237 B2US 12626237B2US-12626237-B2

Abstract

Disclosed herein relates to a self-checkout anti-theft vehicle system, comprising: a self-checkout vehicle having a plurality of sensors and components implemented thereon, the self-checkout vehicle being used by shoppers for storing selected merchandises in a retail environment; and a centralized computing device. The centralized computing device is configured to: obtain information related to each merchandise selected and placed into the self-checkout vehicle by a shopper by exchanging data with the plurality of sensors and components via a first communication network, identify each merchandise via a second, different communication network based at least upon the information obtained from the plurality of sensors and components, and process payment information of each merchandise.

Inventors

Lin Gao
YILIN HUANG
Shiyuan Yang
Ahmed Beshry

Assignees

MAPLEBEAR INC.

Dates

Publication Date: 20260512
Application Date: 20240103

Claims (10)

1 . A method comprising: receiving, by a processor coupled to a self-checkout vehicle, an image captured by a camera coupled to the self-checkout vehicle, wherein the image depicts an item; receiving, by the processor of the self-checkout vehicle, location data associated with the image of the item, the location data describing a location within a store where the image was captured and wherein the location data is captured by a location sensor coupled to the self-checkout vehicle; identifying, by the processor of the self-checkout vehicle, a set of candidate items located near the location where the image was captured based on the location data captured by the location sensor coupled to the self-checkout vehicle, wherein the set of candidate items are identified by: filtering a set of items at the store based on whether each item in the set of items is within a threshold distance of the location within the store where the image was captured; calculating, by the processor of the self-checkout vehicle, a score for each of the set of candidate items based on the location data and the image, wherein the score for a candidate item represents a likelihood that the candidate item is depicted in the image, wherein calculating the score for a candidate item of the set of candidate items comprises: generating a set of features describing the image, and applying a classifier to the set of features to compute the score; identifying, by the processor of the self-checkout vehicle, the item depicted in the image based on the calculated scores of the set of candidate items; and updating a display of the self-checkout vehicle based on the identified item.
2 . The method of claim 1 , wherein the location data is received from a global positioning system device.
3 . The method of claim 1 , wherein the location where the image was captured is one of a side of an aisle of a store, or a counter location of a deli department of a store.
4 . The method of claim 1 , wherein receiving location data describing comprises: receiving a set of signals from one or more sensors coupled to the self-checkout vehicle; and calculating a triangulated position of the self-checkout vehicle using the set of signals, wherein a portion of the set of signals is broadcasted by different base stations located within the store.
5 . The method of claim 4 , wherein the triangulated position of the self-checkout vehicle is calculated based on a speed at which the set of signals broadcasted by the different base stations are processed by the one or more sensors.
6 . The method of claim 1 , wherein identifying a set of candidate items located near the location of the self-checkout vehicle comprises: identifying items within a threshold distance to the location where the image was captured.
7 . The method of claim 1 , wherein the set of candidate items are identified based on item layout information of the store.
8 . The method of claim 1 , wherein identifying the item in the image based on the calculated scores of the set of items comprises: comparing the calculated scores of the set of items; and responsive to identifying an item with a highest score, determining the item with the highest score as the item that is depicted in the image.
9 . The method of claim 1 , further comprising: receiving a weight measurement of an item from a weight sensor coupled to the self-checkout vehicle; and calculating a score for each of the set of items based on the weight measurement of the item and the location data associated with the image of the item.
10 . The method of claim 1 , further comprising: receiving a user's shopping history; and calculating a score for each of the set of items based on the user's shopping history and the location data associated with the image of the item.

Description

CROSS REFERENCE TO RELATED APPLICATION This application is a continuation of U.S. patent application Ser. No. 17/129,437, filed Dec. 21, 2020, which is a continuation of U.S. patent application Ser. No. 15/956,159, filed Apr. 18, 2018, which claims the benefit of U.S. Provisional Patent Application No. 62/537,140, filed Jul. 26, 2017, the contents of which are incorporated by reference herein in their entireties. TECHNICAL FIELD The present disclosure relates generally to self-checkout anti-theft systems and methods, and more specifically, to network connections, sensor fusion and the mechanical structure of a self-checkout vehicle. BACKGROUND Currently, an increasing number of convenience stores, grocery markets and retail outlets utilize self-checkout kiosks to allow customers to self-service their checkout. The benefit of self-checkout is apparent: grocers are able to save cashier labor while helping to reduce customer wait time by opening additional cash wrap. Despite its benefits, shoppers often encounter technical difficulties, require staff assistance and still line up at self-checkout registers at busy times. In order to provide a better shopping environment for customers in physical stores, a seamless self-checkout format is needed. Since customers conventionally use a shopping cart or a shopping basket during their store visit, it is more desirable if customers can directly purchase and bag their purchased goods in their shopping vehicles and directly walk out of the store thereafter. In the meantime, necessary anti-theft measures need to be implemented in such self-checkout vehicles to ensure the interests of the grocers are protected. BRIEF SUMMARY OF THE INVENTION The self-checkout anti-theft systems and methods disclosed herein provide a holistic checkout experience that also prevents theft. In one aspect, the disclosed system contemplates, among other features, a centralized computing device that communicates with all the sensors and mechanical structures in the self-checkout vehicle and acts as the command center. The centralized computing device may be connected to an in-store and/or external network through wireless connection devices, including but not limited to Wi-fi, Bluetooth, Zigbee and the like. The external network connection may allow the centralized computing device to, including but not limited to: I) send or receive timely information updates relating to inventory, coupon, promotions, stock availability and the like; 2) verify payment status of merchandise in the cart; 3) payment processing; 4) identify item information based on image processing; and 5) send or receive customer information and receipts. The centralized computing device may also communicate with internal sensors or mechanical devices through wired connections or wireless connection devices via an internal network such as Wi-Fi, Bluetooth, Zigbee and the like. The internal network connection may allow the centralized computing device to, including but not limited to: 1) send or receive data from sensors for further processing; 2) communicate between the sensors to triangulate merchandise information; 3) update status of vehicle components; and 4) send or receive mechanical commands to trigger a specific action in the self-checkout vehicle. In accordance with aspects of the present application, a self-checkout anti-theft vehicle system is disclosed. The system comprises: a self-checkout vehicle having a plurality of sensors and components implemented thereon, the self-checkout vehicle being used by shoppers for storing selected merchandises in a retail environment; and a centralized computing device. The centralized computing device is configured to: obtain information related to each merchandise selected and placed into the self-checkout vehicle by a shopper by exchanging data with the plurality of sensors and components via a first communication network, identify each merchandise via a second, different communication network based at least upon the information obtained from the plurality of sensors and components, and process payment information of each merchandise. BRIEF DESCRIPTION OF THE FIGURES For a more complete understanding of the example aspects, references are made to the following descriptions taken in connection with the accompanying drawings in which: FIG. 1 illustrates a self-checkout anti-theft system, in accordance with aspects of the present disclosure; FIG. 2 illustrates a perspective view of a self-checkout vehicle, in accordance with an example aspect of the present disclosure; FIG. 3 illustrates another perspective view of a self-checkout vehicle, in accordance with an example aspect of the present disclosure; FIG. 4 illustrates a deep learning neural network of a self-checkout anti-theft system, in accordance with an example aspect of the present disclosure; and FIG. 5 illustrates an example computer system through which the disclosed aspects of the systems and methods may be implemented. T