US 11,699,114 B2
Automated robotic pre-staging of prioritized pick up orders for non-notifying customers of a retail store
Brian Roth, Bentonville, AR (US); Paul Durkee, Centerton, AR (US); and Jason D. Shaffer, Bentonville, AR (US)
Assigned to Walmart Apollo, LLC, Bentonville, AR (US)
Filed by Walmart Apollo, LLC, Bentonville, AR (US)
Filed on Aug. 3, 2021, as Appl. No. 17/392,468.
Claims priority of provisional application 63/081,220, filed on Sep. 21, 2020.
Prior Publication US 2022/0092497 A1, Mar. 24, 2022
Int. Cl. G06Q 10/0631 (2023.01); G06Q 10/087 (2023.01); G06N 5/04 (2023.01); G06Q 30/0202 (2023.01); B65G 1/137 (2006.01)
CPC G06Q 10/06313 (2013.01) [B65G 1/137 (2013.01); G06N 5/04 (2013.01); G06Q 10/06311 (2013.01); G06Q 10/06315 (2013.01); G06Q 10/087 (2013.01); G06Q 30/0202 (2013.01); B65G 2201/0258 (2013.01)] 20 Claims
OG exemplary drawing
 
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.