Automated robotic pre-staging of prioritized pick up orders for non-notifying customers of a retail store

Patent metadata

Field	Value
Publication number	US-11699114-B2
Application number	US-202117392468-A
Country	US
Kind code	B2
Filing date	Aug 3, 2021
Priority date	Sep 21, 2020
Publication date	Jul 11, 2023
Grant date	Jul 11, 2023

Abstract

Examples provide a system and method for managing non-notifying customer orders for pickup. An order manager component identifies orders received from customers that typically do not provide advance notification prior to arrival at an order pickup location. A prioritization component assigns a priority to each order based on a per-customer confidence level. Customers providing notification and new customers receive the highest priority. Non-notifying customers having consistent pickup times associated with a threshold minimum number of previous orders receive a second highest priority. Non-notifying customers having inconsistent pickup arrival times and/or fewer than the threshold number of previous orders receive lower priority. A routing schedule is generated for pre-staging the orders based on the assigned priorities, pre-staging area capacity, and/or bot capacity. Totes are moved to the prestaging area based on instructions provided in the routing schedule.

First claim

What is claimed is:

1. A system comprising:
a memory;
a processor communicatively coupled to the memory;
an order manager component, executed by the processor, that:
obtains online order history data via a network, the online order history data associated with a plurality of remote order pickup locations,
analyzes the online order history data associated with individual users corresponding to each order in a plurality of pending orders at a local order pickup location,
determines a set of non-notifying orders from the plurality of pending orders based on the analysis and using a dynamic threshold of previous orders, the dynamic threshold dynamically adjusted by a machine learning component based on the online order history data and real-time order pickup data received via the network,
predicts an arrival time for an individual user associated with an individual order in the set of non-notifying orders based on online order history data;
calculates a per-customer confidence level for the predicted arrival time using the online order history data and the dynamic threshold,
assigns a per-order priority to each order within the set of non-notifying orders based at least in part on the calculated per-customer confidence level and the predicted arrival time, and
generates, by the processor, a routing schedule for pre-staging the set of non-notifying orders based on the assigned per-order priority, pre-staging area space capacity, and bot capacity, the routing schedule including a set of pre-staging routing instructions for pre-staging each order in the set of non-notifying orders based on the predicted arrival time of the individual user,
the order manager component sending, by the processor via the network, the generated routing schedule to an automated storage device at the local order pickup location, the automated storage device having a set of robotic devices, the set of robotic devices using the set of pre-staging routing instructions from the routing schedule to move totes storing items associated with a plurality of orders from a storage area to a pre-staging area within the automated storage device for user pickup at a dispensation area proximate to the pre-staging area.

2. The system of claim 1 , wherein the order manager component is further executed by the processor to:
analyze the online order history data associated with a customer originating an order in the plurality of pending orders to determine whether the customer is a returning customer or a new customer, and assign a highest priority to orders originated by new customers when assigning the per-order priority to each order within the set of non-notifying orders.

3. The system of claim 1 , wherein the predicted arrival time for the individual user is calculated using a number of previous orders and previous order pickup times for an individual user, the predicted arrival time weighted by the per-customer confidence level.

4. The system of claim 1 , wherein the assigned per-order priority for the set of non-notifying orders is further used to prioritize order picking and order induction into the automated storage device.

5. The system of claim 1 , wherein the order manager component is further executed by the processor to:
receive, from a customer device via a network, a customer check-in providing a customer-selected pickup time for an order in the set of non-notifying orders;
determine that the order is currently in the pre-staging area;
determine to move the order from the pre-staging area back to the storage area based on the customer-selected pickup time and cold-chain compliance rules;
generate new routing instructions for the order; and
send, by the processor via the network, the new routing instructions to the automated storage device at the local pickup location.

6. The system of claim 1 , the order manager component is further executed by the processor to:
receive, from a customer device via a network, a customer check-in providing a customer-selected pickup time for an order in the set of non-notifying orders;
determine that the order is currently in the pre-staging area;
determine that a higher priority order is currently waiting for the pre-staging area space capacity;
generate new routing instructions for the order based on the customer-selected pickup time and the determined higher priority order; and
send, by the processor via the network, the new routing instructions to the automated storage device at the local pickup location.

7. The system of claim 1 , wherein the set of robotic devices of the automated storage device include at least one robotic arm configured to move the totes within the automated storage device from the storage area to the pre-staging area.

8. The system of claim 1 , wherein the storage area of the automated storage device comprises a plurality of slots for storing the totes.

9. The system of claim 1 , wherein the online order history data identifies a number of previous orders made by a customer, whether the customer provided notification prior to arriving at an order pickup area to pickup a prior order in each of the number of previous orders, and a customer arrival time for each of the number of previous orders.

10. A computer-implemented method for managing non-notifying customer orders for pickup, the computer-implemented method comprising:
obtaining, by an order manager component executed by a processor, online order history data via a network, the online order history data associated with a plurality of remote order pickup locations;
analyzing, by the processor, the online order history data associated with individual users corresponding to each order in a plurality of pending orders at a local order pickup location;
determining, by the processor, a set of non-notifying orders from the plurality of pending orders based on the analysis and using a dynamic threshold of previous orders, the dynamic threshold adjusted based on online order history data and real-time order pickup data received via the network;
calculating, by the processor, a per-customer confidence level using the online order history data associated with the individual users corresponding to the set of non-notifying orders, the per-customer confidence level based at least in part on a predicted arrival time for an individual user;
assigning, by the processor, a per-order priority to each order within the set of non-notifying orders based on the calculated per-customer confidence level; and
generating, by the processor, a routing schedule for pre-staging the set of non-notifying orders based on the assigned per-order priorities, pre-staging area space capacity, and bot capacity, the routing schedule including a set of pre-staging routing instructions for pre-staging each order in the set of non-notifying orders based on the predicted arrival time of the individual user,
the order manager component sending, by the processor via the network, the generated routing schedule to an automated storage device at the local order pickup location, the automated storage device having a set of robotic devices, the set of robotic devices using the set of pre-staging routing instructions from the routing schedule to move totes storing items associated with a plurality of orders from a storage area to a pre-staging area within the automated storage device for user pickup at a dispensation area proximate to the pre-staging area.

11. The computer-implemented method of claim 10 , further comprising:
calculating, by the processor, the predicted arrival time for the individual user based on a number of previous orders and previous order pickup times, the predicted arrival time weighted by the per-customer confidence

Assignees

• Walmart Apollo Llc

Inventors

• Roth Brian
• Durkee Paul
• Shaffer Jason D

Classifications

• G06Q10/06311

  Scheduling, planning or task assignment for a person or group · CPC title

• B65G2201/0258

  Trays, totes or bins · CPC title

• G06N5/04

  Inference or reasoning models · CPC title

• B65G1/137

  with arrangements or automatic control means for selecting which articles are to be removed · CPC title

• G06Q10/087

  Inventory or stock management, e.g. order filling, procurement or balancing against orders · CPC title