The present invention relates to a system and method for automated service at a retail location suitable for combining brick-and-mortar and online shopping methods and systems. In particular, the present invention relates to a retail location providing a combination automated and self-service shopping experience.
Since its invention by Clarence Saunders in 1916 (U.S. Pat. No. 1,242,872), the self-service store has come to dominate the retail landscape to such an extent that one hundred years later the generic word “store” means a self-service store by default. Indeed, it is difficult for many people, especially retailers, to even imagine a different form of brick-and-mortar retail model or system.
Since the emergence of the Internet in the late 1990's, the advantages of e-commerce, especially as practiced by online retailers such as Amazon, Inc., have convinced consumers to shift a steadily increasing proportion of their shopping to online systems. After only twenty years, e-commerce in general has become so disruptive to in person retail shopping that such online services are now seen by many experts to pose an existential threat to brick-and-mortar retailing operating under the self-service model.
However, both brick-and-mortar locations and online shopping methods and systems experience some shortcomings. For brick-and-mortar locations, the self-service store model is antiquated with the creation of the Internet, and retailers are losing market share to online retailers that can offer reduced prices and convenience when shopping online. There are a number of compelling advantages to online shopping over self-service stores. For example, customers can simply place an order(s) electronically, without having to go to the store, and the retailer (not the customer) is responsible for picking and shipping the items, to fulfill the order. As a result, online shopping enables an additional benefit of eliminating the need to endure the universally despised checkout line, which is a necessary evil of the self-service model. Additional advantages of shopping online are that customers can order any time of day from any location, product assortment can be vastly larger because fulfillment centers have far more storage capacity than individual brick-and-mortar stores, and because more “longer-tailed” products can be stocked economically to serve aggregated demand from a much larger pool of customers than would shop at a single store, an array of powerful decision-support tools are available to shoppers online, especially product-reviews, and orders can be delivered to the customers' homes, which is usually highly convenient for the customer.
For online retailers, the penetration of online orders is non-uniform across different product and store categories, with a dramatically lower penetration in food than in all other major categories. Part of the reason for this difference certainly has to do with food-perishability constraints and the resulting logistical complexity with the delivery function. A more fundamental reason, however, is that the relative advantages of a brick-and-mortar store vs. online are far more important in food than any other category.
In particular, from a customer perspective, brick-and-mortar retailing has a number of advantages over online retailing, including (1) immediacy, order-fulfillment can occur very quickly from locally stored picking stock; (2) the opportunity for the customer to physically examine products before purchasing them (e.g., non-fungible, damage, etc.); (3) the availability of retail associates in the store to provide service; and (4) the opportunity to provide stimulating in-store experiences and social interactions that customers value.
In attempt to bridge the gap between online shopping and in-person self-service shopping, brick-and-mortar retailers have expanded into e-commerce and offer customers the opportunity to place their orders online and either pick them up at stores or have them delivered to their homes. The online ordering methodology implemented by self-service retailers, however, requires the retailer to incur the cost of picking orders (a task that self-service customers normally perform at no cost to the retailer) and are constrained by competitive pressures from raising prices to cover these additional costs. Moreover, picking these orders in-store is so inefficient and disruptive to self-service customers that even relatively small sales volumes force retailers to move fulfillment to dedicated facilities. Brick-and-mortar retailers offering online sales commonly experience increases in both variable and fixed costs without increasing sales (i.e., people don't eat more because they order online). This “multi-channel” model is ultimately, therefore, a complex strategy and difficult to implement successfully. The more successful a retailer's move online, the faster that retailer will be forced to close stores, or go bankrupt.
There is a need for a system and method capable of implementing an optimized shopping experience for customers at brick-and-mortar locations that can compete with online retailers. The present invention is directed toward further solutions to address this need, in addition to having other desirable characteristics. Specifically, the present invention enables an automated-service operating model implemented at brick-and-mortar store locations that is demonstrably superior to both self-service brick-and-mortar retail models and to online retailer models, in terms of both customer experience and retailer profitability. In particular, the present invention provides retailers, including food retailers, with a method and system for converting self-service model retail locations into highly automated order-fulfillment centers for all or a portion of goods.
In accordance with example embodiments of the present invention, an automated store is provided. The automated store includes a building having an automated fulfillment section and a shopping section including a checkout section, and a delivery section. The shopping section includes a mock marketplace presenting fungible goods to customers for order selection, one or more shopping terminals for selecting one or more fungible goods from the mock marketplace, and one or more picking stations presenting one or more non-fungible goods for custom-picked selection. The automated fulfillment section includes an automated fulfillment system. The automated fulfillment system includes a storage structure including a plurality of rack modules separated by aisles and having a plurality of storage levels, the storage structure storing a plurality of totes that are empty when empty storage totes, contain eaches when storage totes, contain orders when order totes, or combinations thereof. The automated fulfillment system also includes at least one mobile robot capable of storing and retrieving totes from the storage structure, wherein the automated fulfillment system picks the one or more fungible goods and organizes the one or more fungible goods into one or more order totes for delivery to the customers. The checkout section includes one or more non-fungible goods drop-off stations receiving one or more non-fungible goods picked from the one or more picking stations and one or more checkout terminals having a configuration enabling the customers to render payment for the one or more fungible goods and the one or more non-fungible-goods. The delivery section includes a merge module that combines the one or more fungible goods from the automated fulfillment section with the one or more non-fungible goods picked from the shopping section into a delivery bundle and a pickup station receiving the delivery bundle and storing the delivery bundle in an assigned location until the customers arrive to take delivery of the delivery bundle.
In accordance with aspects of the present invention, the mock marketplace includes virtual or tangible displays of the one or more fungible goods that are scannable, images, or codes.
In accordance with aspects of the present invention, the one or more shopping terminals present purchasable goods to customers for order selection.
In accordance with aspects of the present invention, the picking stations enable the customers to directly hand-pick non-fungible goods. The picking stations can also include pickers that custom-pick non-fungible goods based on instruction from the customers, where the pickers are human and/or the pickers are robots.
In accordance with aspects of the present invention, the drop-off stations include assessment tools configured to identify the one or more non-fungible goods. The assessment tools include a scale for determining weight and an optical scanner for reading images, and labels, or codes.
In accordance with aspects of the present invention, the one or more non-fungible goods are placed in one or more totes in the shopping section. The one or more non-fungible goods drop-off stations receive totes containing the one or more non-fungible goods. The delivery bundle comprises one or more shopping bags containing the one or more fungible goods, the one or more non-fungible goods, or both. The delivery bundle can include one or more shopping bags.
In accordance with aspects of the present invention, the merge module removes the one or more non-fungible goods and the one or more fungible goods from totes and combines them into shopping bags in a preferred arrangement. An example arrangement is based on weight of items with heavier items placed on the bottom of the shopping bags and lighter items placed at the top. An example arrangement is also based on contents of items in such a way that food items are placed together in the shopping bags and non-food items are placed together in the shopping bags separate from the food items. An example arrangement is further based on crushability of packaging of items.
In accordance with aspects of the present invention, the shopping section is on a ground level of the automated store and the automated fulfillment section is above the shopping section.
In accordance with aspects of the present invention, the automated fulfillment section is on a ground level of the automated store and the shopping section is above the automated fulfillment section.
In accordance with aspects of the present invention, the automated fulfillment section includes an inventory of fungible goods in a storage system configured for automated picking by a plurality of robots. The fungible goods can be disposed in totes stored in rack modules of the automated fulfillment system.
In accordance with aspects of the present invention, the at least one mobile robot propels itself horizontally and vertically throughout the storage structure, placing totes into the storage structure, removing totes from the storage structure, and transporting totes.
In accordance with example embodiments of the present invention, a method for automated order fulfillment at an automated store is provided. The method includes receiving at least one order for one or more goods at the automated store from a customer and initiating a plurality of robots to pull the one or more goods from inventory for picking at a picking station. The method also includes the plurality of robots configured to pull inventory totes including goods for the one or more goods in the at least one order from inventory and deliver the totes to the picking station and pickers at the picking station pulling the one or more goods from the delivered totes. The method further includes packing the one or more goods in an order-tote associated with the at least one order and delivering completed the completed order-tote to the customer.
In accordance with example embodiments of the present invention, at least one order is one of an online order originating from a remote location and an in person order originating from the automated store. The initiating the plurality of robots for each order of the at least one order can be prioritized based on an origination of an order.
In accordance with example embodiments of the present invention, a system for implementing an automated store service model is provided. The system includes an order processing tool configured to receive at least one order from at least one customer and a non-fungible goods fulfillment tool configured to tally one or more non-fungible goods hand-picked by the at least one customer. The system also includes an automated service fulfillment tool configured to instruct automated robots to pick one or more fungible goods included within the at least one order and a delivery fulfillment tool configured to verify the one or more non-fungible goods, receive payment for the one or more non-fungible goods and the one or more fungible goods form the at least one customer, and deliver the one or more fungible goods to the at least one customer.
In accordance with example embodiments of the present invention, a method of shopping at an automated store is provided. The method includes selecting one or more fungible goods for automated fulfillment utilizing a shopping terminal, collecting and tallying one or more non-fungible goods in a non-fungible goods fulfillment section, verifying and paying for the one or more fungible goods and the one or more non-fungible goods, and receiving delivery of the one or more fungible goods.
In accordance with example embodiments of the present invention, an automated store is provided. The automated store includes a shopping, section. The shopping section includes one or more shopping terminals having a configuration enabling customers to browse and select one or more fungible goods for fulfillment by an automated fulfillment system and a non-fungible goods fulfillment section having a configuration enabling the customers to browse and select one or more non-fungible goods for hand-picked selection by the customers. The automated store also includes a fulfillment section. The fulfillment section includes the automated fulfillment system that picks the one or more fungible goods for delivery to the customers, one or more checkout kiosks having a configuration enabling the customers to render payment for the one or more fungible goods and the one or more non-fungible goods, and a delivery fulfillment section where the one or more fungible goods are delivered by the automated fulfillment system to the customers.
In accordance with example embodiments of the present invention, an automated store includes a shopping section. The shopping section includes product selection mechanisms having a configuration enabling customers to browse and select one or more fungible goods for fulfillment by an automated fulfillment system and a non-fungible goods fulfillment section having a configuration enabling the customers to browse and select one or more non-fungible goods. The automated store also includes a fulfillment section. The fulfillment section includes the automated fulfillment system that picks the selected one or more fungible goods for delivery to the customers, a payment system having a configuration enabling the customers to render payment for the one or more fungible goods and the one or more non-fungible goods, and a delivery fulfillment section where the one or more fungible goods are delivered by the automated fulfillment system to the customers.
In accordance with example embodiments of the present invention, the product selection mechanisms comprise one or more of a representative product packaging, a scannable product image, or virtual electronically displayed and selectable product user interface.
In accordance with example embodiments of the present invention, the payment system comprises one or more interactive kiosks. The payment system can also include a virtual payment system accessed by customer devices to execute payment.
In accordance with example embodiments of the present invention, an automated store. The automated store includes a shopping section including a customer shopping area in which customers provide indications of one or more goods for purchase; and a fulfillment section. The fulfillment section includes an automated fulfillment system that picks the selected one or more goods for delivery to the customers at the automated store.
In accordance with example embodiments of the present invention, the shopping section includes product selection mechanisms having a configuration enabling customers to browse and select one or more fungible goods for fulfillment by the automated fulfillment system. The shopping section can also include a non-fungible goods fulfillment section having a configuration enabling the customers to browse and select one or more non-fungible goods for purchase.
In accordance with example embodiments of the present invention, the automated store further comprises a payment system having a configuration enabling the customers to render payment for the one or more fungible goods and the one or more non-fungible goods. The automated store can also include a delivery fulfillment section where the one or more fungible goods are delivered by the automated fulfillment system to the customers.
These and other characteristics of the present invention will be more fully understood by reference to the following detailed description in conjunction with the attached drawings, in which:
An illustrative embodiment of the present invention relates to a combination automated-service and self-service store for implementation at brick-and-mortar retail locations. The store and corresponding method of implementation is an automated-service model in which robots, deployed at the brick-and-mortar location, fill orders for fungible goods (e.g., pre-packaged goods) placed by customers either online or in-store. The store at the brick-and-mortar location is provided including a front-end shopping section for non-fungible goods or automated service of “fresh” items (e.g., fresh goods, produce, etc.) that customers prefer to pick out by hand. The store further includes a back end automated order fulfillment section for other goods (e.g., packaged goods, dry goods, etc.). In accordance with an example embodiment, a customer places an order for package goods to be picked using the automated system and hand picks non-fungible goods. The two sets of goods are merged (following checkout and payment) for transfer at a transfer station at the brick-and-mortar location to the customer or a delivery proxy for transport to the customer at a local or remote location.
In an illustrative example of food retailing, there is an important distinction between non-fungible goods, such as meat and produce normally located in “perimeter departments” of the store, and fungible goods normally located on shelves throughout the center of the store. That difference in the goods relates to item interchangeability, or “fungibility”. With fungible goods, all “eaches” of a given stock-keeping unit (SKU) are essentially identical to each other in all respects important to customers, and are therefore fungible from a customer perspective. For this reason, customers are content to let the retailer select all of their fungible goods. However, with non-fungible goods, the customer prefers to do their own picking, because eaches of a given SKU can vary in attributes that are important to customers, such as marbling in meats and blemishes, color, and degree of ripeness in produce. Many customers (though not all) therefore prefer to select their own non-fungible goods rather than relinquish selection to the retailer. This preference to select produce via in-person inspection is a contributing factor as to why the penetration of online retailing has been so much slower in food than in nearly all other categories of trade.
For purposes of this disclosure, when individual item units or eaches of a given good or product are sufficiently identical that the customer is indifferent as to which specific each is selected from inventory, the eaches of that good can be considered to be “fungible”. Conversely, if individual eaches of a given good are different one from another in such a way that a customer might have a preference as to which specific each is selected, then those goods are considered to be “non-fungible”. In the context of a retail store, the self-service model adds little value to the customer experience with respect to fungible products, whereas stores implementing automated-service, as discussed with respect to the present invention, adds significant value by eliminating the need for customers to pick their own eaches of fungible goods. For many customers, on most occasions, however, self-service actually adds value to the customer experience with respect to non-fungible products by giving them full control over the selection of specific eaches, and so would be the preferred method of order-fulfillment. For other customers or on other occasions, the convenience of automated service adds more value than self-selection, and so will be the preferred fulfillment method.
Customer experience in the automated-service model of the present invention is maximized by (a) automating the fulfillment of all orders for fungible-goods and virtualizing the fungible goods market entirely, (b) providing a self-service non-fungible goods market that enables customers to select the specific eaches of those goods that they wish to hand select, and (c) optionally enabling customers to order non-fungible goods online and fulfill those orders by either manual, automated picking, or a combination thereof. The automated-service model of the present invention is feasible only if there is an automated order-fulfillment (“each-picking”) technology that can meet the demanding requirements of this model. As such, prior systems have been unable to effectively operate an end to end retail system that can leverage automated robots for order-fulfillment in the manner described herein.
As would be appreciated by one skilled in the art, the automated-service model can be implemented in any type of retail store. For example, the automated-service model can be implemented in grocery stores, in home improvement stores, in craft stores, in consumer product stores, or in a combination thereof (e.g., superstores). In each of the types of retail stores, goods can be classified as fungible and non-fungible as described in accordance with the present invention. In particular, the fungible goods are goods that are suitable for automated fulfillment in which customers do not typically care if they pick those goods themselves and non-fungible goods are goods that customers prefer to inspect and hand pick themselves. For example, in a home improvement store, the shopper selected non-fungible goods can include items such as lumber, select building materials (e.g., drywall, plywood, etc.), specialized hardware items, plants, etc. Continuing the home improvement example, the tangible goods equivalent can include pre-packaged hardware items, fixtures, pipe fittings, light bulbs, etc. As would be appreciated by one skilled in the art, some goods can have a display or sample item for individual inspection but still be fulfilled as a fungible item. For example, the store can have samples or display items for flooring, carpet, tile, etc. that customers may want to touch and inspect before purchasing.
Another example retail store ideal for implementation of the automated-service model of the present invention is grocery stores. While the disclosure of the present invention focuses on grocery stores, one skilled in the art will appreciate that the present invention can be implemented in numerous other mass-merchandising brick-and-mortar formats (e.g., home improvement stores, consumer product stores, technology stores, etc.), without departing from the scope of the present disclosure. Such other implementations are contemplated for use in conjunction with the present invention.
In accordance with an example embodiment of the present invention, non-fungible goods fulfillment 104 includes the process, system, and method for shopping for non-fungible goods with specific goods being selected by customers within a store 300. The non-fungible goods are made available to the customers for visual inspection, physical inspection, and selection of the inherently non-identical goods. The non-fungible goods fulfillment 104 process, system, and method is carried out within a shopping section 302 including storage containers (e.g., display cases of stands 606) of non-fungible goods (e.g., produce, meat, etc.) and customer fulfillment tools (e.g., order placement, payment or checkout kiosks 618, etc.) to enable customers to pick their own goods. As would be appreciated by one skilled in the art, the “non-fungible” goods are non-identical goods which can be picked by the customers in a similar fashion as traditional non-fungible goods models and/or a modified non-fungible goods model configured to operate optimally within the automated service model 100.
The automated order fulfillment 106 includes the process, system, and method for providing automated order fulfillment of fungible goods to customers at a store 300. The automated order fulfillment 106 process, system, and method is carried out within an automated fulfillment section 304 that houses inventory suitable for automated picking (e.g., storage totes of fungible goods) using an automated inventory management system for picking the fungible goods. In accordance with an example embodiment of the present invention, the automated inventory management system is a system including automated mobile robots 226 (e.g., Alphabot™ robots) configured to provide the automated order fulfillment 106 from the inventory stored in the automated fulfillment section 304. The automated fulfillment section 304 includes all of the resources for providing automated fulfillment. Additionally, the automated fulfillment section 304 includes storage racks 612 for storing inventory and providing guiderails for robots 226 retrieving the inventory stored on the storage racks 612, transportation to pickers at picking workstations 614, and returning the totes to inventory once the pickers have removed the appropriate goods from the totes. For example, the automated fulfillment section 304 includes storage racks 612 holding totes of goods and robots 226 configured to provide the automated order fulfillment 106. Examples of such configurations are disclosed in detail in U.S. Pat. No. 9,139,363, U.S. Patent Application Publication No. 2014/0288696 U.S. patent application Ser. No. 15/171,802, all of which are incorporated by reference herein.
In accordance with an example embodiment of the present invention, delivery fulfillment 108 includes the process, system, and method for providing all ordered and picked goods to the customers. The delivery of the goods by the process, system, and method of delivery fulfillment 108 can include delivery of any combination of automated fulfilled orders of fungible goods and customer picked non-fungible goods orders as well as in person orders and online orders. Additionally, the delivery fulfillment 108 can include any level of delivery, including but not limited to in-store delivery, customer vehicle delivery, and at home delivery.
In accordance with an example embodiment of the present invention, the automated service system 202 can include a computing device 204 having a processor 206, a memory 208, an input output interface 210, input and output devices 212 and a storage system 214. Additionally, the computing device 204 can include an operating system configured to carry out operations for the applications installed thereon. As would be appreciated by one skilled in the art, the computing device 204 can include a single computing device, a collection of computing devices in a network computing system, a cloud computing infrastructure, or a combination thereof, as would be appreciated by those of skill in the art. Similarly, as would be appreciated by one of skill in the art, the storage system 214 can include any combination of computing devices configured to store and organize a collection of data. For example, storage system 214 can be a local storage device on the computing device 204, a remote database facility, or a cloud computing storage environment. The storage system 214 can also include a database management system utilizing a given database model configured to interact with a user for analyzing the database data.
Continuing with
In accordance with an example embodiment of the present invention, the system 200 includes a plurality of user devices 224 and robots 226 configured to communicate with the automated service system 202 over a telecommunication network(s) 228. The automated service system 202 can act as a centralized host, for the user devices 224 and robots 226, providing the functionality of the tools 216, 218, 220, 222 sharing a secured network connection. As would be appreciated by one skilled in the art, the plurality of user devices 224 can include any combination of computing devices, as described with respect to the automated service system 202 computing device 204. For example, the computing device 204 and the plurality of user devices 224 can include any combination of servers, personal computers, laptops, tablets, smartphones, etc. In accordance with an example embodiment of the present invention, the computing devices 204, the user devices 224, and the robots 226 are configured to establish a connection and communicate over telecommunication network(s) 228 to carry out aspects of the present invention. As would be appreciated by one skilled in the art, the telecommunication network(s) 228 can include any combination of known networks. For example, the telecommunication network(s) 228 may be combination of a mobile network, WAN, LAN, or other type of network. The telecommunication network(s) 228 can be used to exchange data between the computing devices 204, the user devices 224, and the robots 226 exchange data with the storage system 214, and/or to collect data from additional sources.
In accordance with an example embodiment of the present invention, the order processing tool 216 is configured to handle all the processing for order processing 102. In particular, the order processing tool 216 is configured to receive customer order information (e.g., in person or remotely) and allocate the orders accordingly (e.g., dispatch automated order fulfillment), as discussed in greater detail herein. In accordance with an example embodiment of the present invention, the non-fungible goods fulfillment tool 218 is configured to handle all the processing related to non-fungible goods fulfillment 104. In particular, the non-fungible goods fulfillment tool 218 handles all of the operations at a front end of a store 300 including managing customer orders, payment, and other services, as discussed in greater detail herein. In accordance with an example embodiment of the present invention, the automated order fulfillment tool 220 is configured to handle all the processing related to automated order fulfillment 106. In particular, the automated order fulfillment tool 220 is configured to handle the operations at a backend of the store 300 including automated order picking, inventory management, etc., as discussed in greater detail herein. In accordance with an example embodiment of the present invention, the delivery fulfillment tool 222 is configured to handle all the processing related to delivery fulfillment 108. In particular, the delivery fulfillment tool 222 is configured to handle the processing related to delivering fulfilled customer orders to the customer at a particular destination, as discussed in greater detail herein.
In accordance with an example embodiment, the automated service model 100 is implemented within a brick-and-mortar retail store 300 configured for use in accordance with the present invention. The store 300 can be any retail store that provides goods available for sale to customers. In accordance with an example embodiment of the present invention, the store 300 is a grocery store providing groceries and other goods traditionally found at grocery stores to customers. The store 300 of the present invention differs from conventional stores in how customers obtain goods from the store 300. In particular, the store 300 includes a shopping section 302 enabling customers to hand pick goods, as done in traditional grocery stores, or otherwise select goods for automated fulfillment (such as by interactive display, scanning a tag, image, or code, or the like) and the automated fulfillment section 304 with an automated each-picking system that can pick most or all of the items that customers designate within an order (either an online or in person order).
The novel combination of the store 300 and the automated service model 100 alleviates customers from having to pick entire orders of goods, as in a traditional self-service store. Instead, utilizing the automated service model 100, customers can order some or all of goods the customer wishes to buy electronically through some form of digital device either in the store or remotely, and have the automated order fulfillment 106 pick the goods and deliver the order to the customer at the store 300 location. Simultaneously, the customer can pick any non-fungible goods from the shopping section 302 of the store 300 to be combined with the automated delivered goods at a checkout point within a delivery fulfillment section 308, as depicted in
Customer orders to be fulfilled by the automated order fulfillment 106 will be processed by the automated system within automated fulfillment section 304, as discussed in greater detail herein. When the automated order fulfillment 106 has been completed, the automated picked goods will be provided 406 to the delivery fulfillment section 308, as discussed in greater detail herein. Similarly, when customers have completed picking non-fungible goods within the shopping section 302, the customers will provide 408 the goods to the delivery fulfillment section 308, as discussed in greater detail herein. For example, the customers can place a tote or basket with their goods through a window to the delivery fulfillment section 308 as depicted in
Continuing with
In accordance with an example embodiment of the present invention, the store 300 of the automated-service model 100 includes a “front end” including an entry lobby, the shopping section 302 for non-fungible-goods, and associated work areas. As would be appreciated by one skilled in the art, the front end does not necessarily need to be located at a front of the store 300 or on a ground level of the store 300. The vast majority of floor space within the shopping section 302 is devoted to a non-fungible-goods market (e.g., produce, fresh goods and other non-fungible goods) and associated work spaces, which can be the focal point of the store 300 from a customer perspective. The shopping section 302 includes “non-fungible” goods such as produce, meat, seafood, many cheeses (primarily random-weight), deli, floral, bakery, and prepared foods. Typically, non-fungible goods will be sold from display fixtures or cases 606 with as many as three different pricing methods, including but not limited to “random dollar” (fungible with a price barcode), random weight (loose items, especially produce, priced based on item weight), and random count (loose items priced based on number of eaches). These non-fungible goods can also be sold at service counters that offer the customer more opportunity to customize ordered products according to their individual tastes and preferences.
In accordance with an example embodiment of the present invention, the shopping section 302 of the store 300 is similar in appearance to perimeter departments within traditional self-service grocery stores with technology enhancements, related to the automated-service model 100, to improve customer convenience and reduce retailer operating costs. The technological improvements for the shopping section 302 are primarily related to how customers shop for goods and exchange funds for those goods. One such technological improvement is the implementation of shopping terminals to be utilized in combination with the automated-service model 100. The shopping terminals are devices utilized by customers as the primary interface to select, scan, enter, and/or store goods for an order to be placed during shopping trip, including an exchange of funds for the order. In particular, the shopping terminals can be utilized to place orders for both fungible goods (to be picked by the automated order fulfillment 106) and non-fungible goods within the non-fungible goods fulfillment 104.
As would be appreciated by one skilled in the art, the shopping terminals can be any device configured to identify a particular good (e.g., via scan, photo, etc.) to be added to a shopping list. For example, the shopping terminals can be a portable scanning device or one or more fixed touch screens located within the shopping section 302. Additionally, user devices 224 (e.g., smart phones) of customers can be configured as shopping terminals by executing a mobile application associated with the store 300 on the mobile device. For purposes of this disclosure, the term “shopping terminal” is defined to include an application running on a user device 224 or a standalone specialized shopping terminal device (e.g., portable scanner, stationary screen, or a combination thereof). In operation, the shopping terminal interacts with the customer and communicates with the central automated service system 202 to support a broad set of functions involved in the shopping process. Each shopping terminal has a unique internal identifier that is included in messages, and the process of obtaining a shopping terminal includes a step in which the customer's identity is captured, e.g. via a radio frequency identification (RFID) key fob or an near field communication (NFC) chip in the customer's smart phone, or by entry of information at, e.g., a checkout kiosk 618 or service desk. The shopping terminal associated with the customer is used to pick the items desired for their shopping order to be picked by the automated order fulfillment 106 and by the customer within the non-fungible goods fulfillment 104.
In accordance with an example embodiment of the present invention, the shopping section 302 includes screens 602 representing a virtual fungible-goods market for ordering fungible goods to be picked by the automated order fulfillment 106. In particular, the virtual fungible-goods market combines the order processing 102 and non-fungible goods fulfillment 104 to enable a customer to select an order of goods to be picked by the automated order fulfillment 106. In accordance with an example embodiment of the present invention, the shopping section 302 includes a mock marketplace 600 with demo or sample products with SKUs (e.g., empty boxes, pictures, etc.) on physical shelving units (as typically found in a traditional market), or images of such goods made available for browsing of goods (electronic display, or tangible images or illustrations). Example implementations of the mock marketplace 600 are depicted in
In accordance with an example embodiment of the present invention, the mock marketplace 600 is limited to picking the goods available via the virtual marketplace. The virtual marketplace includes a plurality of screens (e.g., shopping terminals) 602 mounted on walls or panel floor-stands, which display a combination of selectable fungible goods and non-fungible goods available in inventory. The customer utilizes the screen(s) 602 to browse and select which goods they want to add to their shopping order.
In accordance with an example embodiment of the present invention, the mock marketplace 600 can include ordering goods for automated order fulfillment 106 through a combination of virtual shopping screens 602, a physical mock marketplace 600, and a non-fungible goods marketplace. For example, customers can order fungible goods from aisles of shelving 604 containing mock fungible goods, as depicted in
Additionally, the smaller screens 602 can be utilized for the cross-promotion of goods. For example, screens 602 attached to the display cases or stands 606 containing vegetables can display content promoting salad dressing configured enable customers to order the related fungible goods directly through the associated screens 602 (e.g., scanning an RFID tag). In this example embodiment, the fungible goods are completely virtualized and the non-fungible goods marketplace is not, and customers order fungible goods via screens in the store in much the same way in similar manner to shopping remotely on in-home or mobile devices. For example, the store 300 can include a primary set of large screens 602 mounted along a wall to minimize floor-space requirements with additional screens 602 (typically smaller) positioned throughout the non-fungible goods market. Accordingly, regardless of a customer's location within the store 300, the customers can initiate the process of ordering fungible goods on the screens 602 by using a portable shopping terminal to read an identifying tag (e.g. RFID tag or barcode) on an available screen 602, which would then activate an ordering session on the screen 602.
In accordance with an example embodiment of the present invention, the order of goods provided by the screens 602 are processed by an order processing tool 216 and provided to an automated order fulfillment tool 220 for execution through the automated order fulfillment 106. The automated order fulfillment 106 processes the order and delivers the completed order of goods to the customer at a later time period (e.g., at the delivery fulfillment section 308), as discussed in greater detail herein. As would be appreciated by one skilled in the art, the non-fungible goods fulfillment 104 can also be selected in a similar manner, for automated fulfillment, in which a customer selects non-fungible goods from a pool of uniquely identifiable goods displayed on the screens 602. Thereafter, the selection of the non-fungible goods can be picked for the customer using either an automated means or a third party proxy to do the picking (e.g., at a picking workstation 614). Additionally, the order processing 102 can provide feedback to the customer as to a status of the order, a list of goods within the order, a total cost of the order, and other information related to the order. For example, the order processing tool 216 provides a reasonably accurate estimate of the wait time before completion of the order, and then notifies customers the status of the order (e.g., via the personal shopping terminals). When the order is completed, the customer can be notified (e.g., via an application on a portable shopping terminal, an in store status screen, email or short message service (SMS), etc.) that the order is ready for pickup and/or delivery.
In accordance with an example embodiment of the present invention, the shopping section 302 of the store 300 includes a non-fungible market for goods (e.g., produce) which customers prefer to physically inspect, handle, and pick the non-fungible goods themselves (e.g., unautomated). For purposes of this disclosure these types of goods are referred to as non-fungible goods and/or fungible goods. For example, customers can browse non-fungible produce sections for fruits and vegetables as they would in a traditional self-service grocery store. Additionally, customers can order non-fungible goods from various stations included within the shopping section 302. The stations can include, but are not limited to, a deli service counter, a seafood service counter, a bakery, a prepared foods and restaurant station(s), meal kits, etc. Non-fungible goods can be handled in multiple modes: a proxy manual picker (e.g., a store employee picks non-fungible goods on behalf of a customer, typically via an online order), customer selection of non-fungible goods (in person or online), customers at stations (e.g., deli, bakery, seafood, etc.), or customer in store non-fungible goods selection. The customer can tally and add the non-fungible goods to an order through non-fungible goods selection in the shopping section 302 by utilizing a combination of scales 608, as depicted in
In accordance with an example embodiment of the present invention, the non-fungible goods fulfillment 104 provides another technological improvement with a process, system, and method for how customers tally non-fungible items in the shopping section 302, compared to the checkout process in conventional marketplaces. The tallying process of the present invention enables customers to tally goods they wish to purchase in a simple and efficient manner across all pricing methods. In particular, the shopping section 302 provides the customer a simplified and efficient manner for customers to order/pick-out non-fungible goods (e.g., tally) and pay for those goods utilizing a combination of shopping terminals in combination with wireless scales 608 positioned at locations throughout the store 300 for convenient use. For example, the section of the shopping section 302 containing fruits will include checkout kiosks 618 and scales 608 for the customer to enter a quantity and weight of a particular fruit item(s) to be added to the customer's order. Once the non-fungible goods are tallied and weighed, they can be added to the customer's order (e.g., via the shopping terminal) such that all customer handpicked goods and automated picked goods will be reflected within a single shopping order. As would be appreciated by one skilled in the art, a customer order can be updated with a tally for each item added to a customer basket or cart while the user shops in the shopping section 302. During a checkout process, the tally and weight of the items in the customer baskets/carts can be verified and processed.
In accordance with an example embodiment, the customer picked non-fungible goods verification process can take place at a checkout kiosk 618 within the shopping section 302 or the customer can pass the non-fungible goods through 408 to the delivery fulfillment section 308 for weight, verification, and consolidation with an automated fulfillment order from the automated fulfillment section 304. In this case, the combined order will be delivered 410 to the customer at the delivery fulfillment section 308.
In an exemplary example, picking random-dollar items are the simplest goods to tally, requiring only that the customer use the shopping terminal to scan the price barcode on the item. (the weight of random-dollar items will either be embedded within the price barcode or derived from the barcoded price based on the known unit price of the item.). To tally and purchase random-weight items, once they have bagged the item units they wish to purchase, customers can perform a simple and intuitive three-step process (in any sequence): (1) the shopping terminal is used to scan an RFID tag located on the item's unit-price sign, which identifies the item, (2) the bag is placed on a conveniently located wireless scale 608, and (3) the shopping terminal is used to scan an RFID tag 609 located on the scale 608, which identifies the scale 608. The system-control software then tallies the item price by reading the item weight from the designated scale 608 and applying the item's unit price. Similarly, to purchase random-count items, customers follow the same three-step process described above for random-weight items, plus a fourth step of either inputting the number of eaches being purchased or confirming the estimated number of eaches the system has calculated by dividing the item weight by an average weight per each for that SKU.
In accordance with an example embodiment of the present invention, non-fungible goods can both be virtually selected by customers to be fulfilled by the automated order fulfillment 106 and/or a third party proxy. To virtually select non-fungible, the customer can utilize a remote online display of the available goods or an in store shopping terminal screen 602. The virtual marketplace display(s) on the screens 602 can provide the customer with a variety of visual and measured information about the goods to be selected. For example, the virtual marketplace display(s) can provide digital images for each unique non-fungible goods with associated measured information. The measured information can include, but is not limited to, a weight, a degree of ripeness (e.g., as determined through a spectrograph), a level of firmness (e.g., as determined through automated tactile sensing), etc. Relying on the visual and measured information, the customer can virtually “hand pick” each unique non-fungible good to be picked for delivery by the automated order fulfilment 106.
In accordance with an example embodiment of the present invention, the automated fulfillment section 304 includes inventory of fungible goods for picking by automated fulfillment robots 226. In particular, the automated fulfillment section 304 includes storage racks 612 of inventory in which robots 226 navigate to pull goods to be picked to fulfill orders placed by customers. For example, the automated fulfillment section 304 includes the system described in the examples of such configurations disclosed in U.S. Pat. No. 9,139,363, U.S. Patent Application Publication No. 2014/0288696 U.S. patent application Ser. No. 15/171,802. As would be appreciated by one skilled in the art, any combination of automated inventory management system can be utilized within the automated fulfillment section 304 without departing from the scope of the present invention. Additionally, the automated fulfillment section 304 can also include varied temperature zones for storing goods with different temperature requirements. For example, the automated fulfillment section 304 can include three main temperature zones for ambient temperature, chilled, and frozen goods. As would be appreciated by one skilled in the art, within the chilled zone, there may be additional sub-zones for optimal storage of meats, dairy, and various types of produce.
In accordance with an example embodiment of the present invention, the automated fulfillment section 304 includes a manual-pick area for fungible goods that are not capable of or not ideal to be handled by the automated robots 226 (e.g., uglies), automated tote-consolidation stations, and decanting stations (if this function is performed in the store). In the example automated robot picking design, picking stock is stored in containers called “totes” and while the vast majority of goods can be contained in totes, a few goods are too large in at least one dimension (e.g. brooms, mops, large bags of pet food or cat litter, etc.), and so must be picked manually. In addition, it may be more cost-efficient to pick some high-volume/high-cube goods manually than with automated robots 226 (e.g. bulky paper products, bulk bottled water, etc.), even though dimensionally a tote could hold some small number of eaches of those goods. Instead of being picked by robots 226, all uglies type goods are picked manually, are stored temporarily in a “special-items” holding area, and then delivered by store associates to customers at order-transfer stations 610. Additionally, the automated fulfillment section 304 also includes intermediate storage for completed orders pending delivery to customers.
In operation, the automated order fulfillment 106 fulfills all customer orders for fungible goods. The goods in the order to be fulfilled are provided by the order processing 102 and can include an order of selected fungible goods except for the uglies, and optionally orders for non-fungible goods that have been “pre-packed” in a barcoded package and inducted into the automated order fulfillment 106 system (e.g., cuts of meat). The robots 226 within the automated fulfillment section 304 are responsible for pulling totes eaches from inventory to be provided for picking by human or robotic operator (“pickers”) at picking workstations 614. Ordered eaches are packed into “bags” contained within order-totes (“O-totes”) by the pickers at the picking workstations 614.
Once an automated order has been completed (e.g., all eaches from an order picked into one or more O-totes 702 at a picking workstation 614), the filled O-totes 702 are either placed into a storage rack 612 subsystem for temporary storage pending delivery to the customer (e.g. if the order was placed online), or discharged from the system immediately for delivery to the customer within the store 300 at the delivery fulfillment section 308 (e.g. if the order was placed in the store). O-totes 702 are placed into storage regardless of the order type and are held until a customer is available to pick-up the order. The automated order fulfillment 106 can store O-totes 702 in the appropriate temperature storage environment. For example, frozen or refrigerated goods will be designated to be stored in a freezer or refrigerator environment while fungible goods can be stored at an ambient temperature of the store 300. Additionally, the stored goods of an order can contain fungible items, or perhaps even special order prepared (e.g., cooked, decorated cake) that can be all picked up together. In particular, when a customer is ready to pick-up an order, all of the O-totes 702 and other products are delivered from the various storage environments to the customer at a designated delivery area.
Additionally, orders may be distributed across multiple O-totes 702. For example, large orders that require more than three traditional bags 704 will be spread across at least two O-totes 702, and orders that include eaches from multiple temperature zones and require intermediate storage before delivery to the customer will require at least one O-tote 702 for each zone. As would be appreciated by one skilled in the art, with orders that are placed in-store for immediate delivery without intermediate storage, eaches of goods from multiple temperature zones can generally be combined into a single O-tote 702, in the same way that such eaches are bagged together during checkout in a traditional self-service store. Counterintuitively, it is usually more capital efficient for O-totes 702 to contain eaches from only a single order. While multi-order O-totes 702 would enable a somewhat greater density in the intermediate storage of online orders, the resulting capex savings will typically be offset by the need for additional bots to perform an order-consolidation process prior to shipping most orders. Order consolidation would also degrade service level by delaying delivery of the order to the customer.
In the automated-service model 100 of the present invention, the checkout process is simply the termination of the shopping process and payment for the goods within the order. The customers can checkout using the shopping terminal or at a checkout kiosk 618 with each payment system having certain restrictions. For example, a checkout kiosk 618 is available for customers paying with cash, by inserting a physical payment card, or if they wish to redeem paper coupons. A shopping terminal is available to customers designating a pre-registered credit/debit card or other form of payment (e.g., using a smart phone via NFC communication with the shopping terminal) associated with the customer. While the simplified checkout transactions will primarily be completed purely electronically via the shopping terminals, the checkout kiosks 618 are available to customers if physical objects are required as part of the checkout process (e.g., cash, credit cards, coupons, etc.). As would be appreciated by one skilled in the art, each checkout kiosk 618 includes a cash-handling mechanism, a debit/credit card reader, a paper-coupon hander, a receipt printer, and a user interface that could be as simple as a touch-screen display (similar to a traditional self-checkout terminal). In operation, each checkout kiosk 618 is configured with an RFID tag reader that enables a customer to read RFID tag information (e.g., order summary) into the shopping terminal to initiate the checkout process. Additionally, for customers utilizing the electronic shopping terminal checkout, a separate bank of receipt printers are available for printing a receipt for the electronically paid order. On each printer is an RFID tag that a customer would read into the shopping terminal in order to initiate printing of the receipt.
In accordance with an example embodiment of the present invention, the customers pay before receiving the goods provided by the automated order fulfillment 106. Once paid, the goods are provided to the customer after exiting the store at a designated order-transfer station 610 (e.g., at the delivery fulfillment section 308). Similarly, the customer can pay for and validate non-fungible order goods that were picked by the customer in the shopping section 302. As discussed herein, the customer tallied each item picked and inserted into their cart, including a product selection (e.g., manually entered, scanned, etc.) and weight (e.g., provided by the wireless scales 608) and a cost is automatically associated with each tallied item in the order. The system 200 can verify a final order of customer picked items by a weight to confirm that the checkout weight of the non-fungible produce matches the total of the tallied weights entered by the customer during shopping. Once the weight is verified, the total cost of the customer's order, including any automated fulfilled orders, can be tallied and applied to the balance for payment.
In accordance with an example embodiment of the present invention, the customers are required to transfer totes including their hand-picked non-fungible goods orders from the shopping section 302 to the delivery fulfillment section 308 (e.g., through 408). At the delivery fulfillment section 308, the tote including the non-fungible goods received from the customer will be consolidated and combined with the O-totes 702 deliver from the automated fulfillment section 304. In particular, the robots 226 deliver totes from the shopping section 302 and the automated fulfillment section 304 to a combination station at the delivery fulfillment section 308 for consolidation prior to delivery to the customer. The delivery fulfillment section 308 includes a merge module that combines the one or more fungible goods from the automated fulfillment section 304 with the one or more non-fungible-goods picked from the shopping section 302 into a delivery bundle. Once all the goods have been combined/consolidated the totes are ready for delivery at an order transfer station 610. The delivery bundle is transported to the pickup station, which receives and stores the delivery bundle in an assigned location until the customers arrive to take delivery of the delivery bundle. As would be appreciated by one skilled in the art, if the customer has selected non-fungible goods only, then there is no need to consolidate the customer's non-fungible goods with an automated order and the customer can exit the store 300 with the non-fungible products after validating the non-fungible goods at a checkout kiosk 618. Accordingly, non-fungible goods only orders do not require the customer to transfer the non-fungible goods back to the delivery fulfillment section 308.
In accordance with an example embodiment of the present invention, the customers can place online orders for pickup or delivery without having to step foot inside the store 300. The online order process can include any combination of the ordering methods discussed herein including searching fungible and non-fungible goods and designating which goods the customer would like to order. Additionally, as discussed herein, customers can virtually hand pick non-fungible goods utilizing the combination of methods and systems discussed herein. Alternatively, the customer can elect to have a proxy picker (e.g., a store employee) pick the non-fungible goods according to the customer's preferences. In this example, the customer can provide instructions for the proxy picker specifying various qualities of the non-fungible goods that they desire (e.g., color, firmness, weight, etc.). The proxy picker will pick the non-fungible goods according to the customer's instructions and add those goods to the automated fulfilled order provide by the automated order fulfillment 106.
In addition to the goods being ordered, the customer specifies a pickup or delivery methods for the order. For example, the customer can specific a scheduled pickup or a scheduled delivery. Additionally, the store 300 can utilize a combination of delivery options including but not limited to a store run delivery fleet or coordinating with a third party service to deliver the goods (e.g., taxi or private car service). The system 200 can provide the customer with multiple pickup and delivery options as well as estimated time of fulfillment for the pickup and delivery options. As would be appreciated by one skilled in the art, the estimated times will vary depending on the type of goods (e.g., non-fungible or fungible), the types of picking process (e.g., automated fulfillment, proxy fulfillment, etc.), a time of day (e.g., peak or off peak shopping periods), the type of delivery method, etc. For automated fulfilled orders only, the time of fulfillment can be realized in as little as ten minutes, based on a number of robots 226 available in the automated fulfillment section 304, providing near on demand latency.
In accordance with an example embodiment of the present invention, the order processing 102, automated order fulfillment 106, and delivery fulfillment 108 can be optimized based on a combination of customer schedules and locations. In particular, the system 200 optimizes customer delivery fulfillment 108 of the order tote fulfillment queue based on delivery/arrival times an. The system 200, can use global positioning system (GPS) information of consumers to manage when the robots 226 pulling orders as well as scheduling a lane to receive delivery of the order for order management and traffic management. For example, the system 200 can prioritize order fulfillment from highest to lowest with the highest prioritization for in store customers, then customers located within a nearby location of the store 300 for pickup, then scheduled home delivery, etc. Similarly, the system 200 can determine when a customer in headed to the store to pick up an order (e.g., based on location information from a customer application) and initiate a dispatch of the customer's order tote(s) to a designated customer pick up location. Additionally, the system 200 can track historical customer behaviors when determining which customer order to prioritize. For example, if a customer frequently changes an order fulfillment time, then the system 200 will give that customer a lower priority to a customer who consistently picks up their order on time. Additionally, the system 200 can offer incentives to customers to accept off-peak delivery/pickup times. The implementation of providing incentives to customers for accepting off peak pickup/delivery will smooth out peaks for optimization.
In accordance with an example embodiment of the present invention, the prioritization tasks will vary based on the “needs” of the store through robot 226 load balancing. As the robots 226 perform order delivery fulfillment 108 and inventory replenishment, the system 200 is scheduled to balance the robot 226 utilization. For example, to system can load balance the robots 226 to perform inventory replenishment during off-peak customer time periods. Also the system 200 can schedule order fulfillment for online orders for next day pickup during night hours when the store 300 is closed to customers. During periods of peak throughput, it is very important to distribute bot workload such that efficient utilization of the robot 226 capacity is maximize in order to satisfy demand and deliver satisfactory service levels to customers. Accordingly, in accordance with an example embodiment, the robots 226 tasks receive the follows prioritization of importance (from highest to lowest priority): deliveries of orders to transfer stations 610, emergency replenishments of picking stocks, picking orders placed by in-store customers, picking orders placed online (further prioritized by scheduled or expected time of pickup), routine replenishment of picking stock.
The final step in the order-fulfillment process in the automated-service model 100 is the transfer of the ordered eaches to the customer (or a delivery proxy) at the delivery fulfillment section 308. In accordance with an example embodiment of the present invention, the delivery fulfillment 108 is responsible for scheduling when the orders are delivered to the respective order-transfer stations 610 within the delivery fulfillment section 308. Delivery fulfillment 108 takes place at designated transfer stations 610 inside (e.g., within the shopping section 302) and/or outside the store 300 at the delivery fulfillment section 308. The eaches picked by the robots 226 are contained in bags 704 inside O-totes 702, and these O-totes 702 are delivered to the transfer stations 610 by the robots 226. Additionally, the manually picked uglies can also be delivered to the same transfer stations 610 by a store associate or picked up by the customer at a dedicated pickup location.
In accordance with an example embodiment of the present invention, the order-transfer stations 610 are structures with a set of shelves that hold O-totes 702.
In accordance with an example embodiment of the present invention, the store 300 includes two sets of order-transfer stations 610. In particular, the store 300 includes one set of order-transfer stations 610 to be used by in-store customers and the second set of order-transfer stations 610 to be used by customers that are visiting the store only to pick up their orders and do not go inside the store 300 (e.g., outside order-transfer stations 610). The transfer stations 610 used by in-store customers further include a parking platform for a shopping cart, which can optionally be instrumented to weigh each cart placed on it for checkout, as discussed in greater detail herein. Depending on specific site attributes and store 300 configuration, it is also possible for exterior transfer stations 610 to be used by both in-store and pickup-only customers. For example, the outside order-transfer stations 610 will be installed within the parking lot or parking structure to enable the robots 226 to deliver orders directly to transfer stations 610 located at customers' parked cars.
In accordance with an example embodiment of the present invention, the order-transfer stations 610 can operate bi-directionally, i.e. it is possible for a customer to place the bags containing his/her self-selected non-fungible-goods into an empty O-tote 702 on the shelf of a transfer station 610 so that a robot 226 can place it into (chilled) storage within the robot system. This capability enables in-store customers to leave an order at the store temporarily and pick it up or have it delivered to home at a later time. Similarly, returns can be provided by inserting a returned item into an O-tote 702 during a return transaction. For example, the returned item(s) will go alone in an empty tote, the tote will be returned to a picking work station 614 while simultaneously bringing out product containers from inventory and picking from return container to the product container.
In accordance with an example embodiment of the present invention, the robots 226, can place the completed O-totes 702 containing an order into delivery carts. The delivery carts can be transported to a customer's car or a customer can pick-up a cart at the order-transfer stations 610 and bring the cart to their car themselves.
At step 904, the customer collects and tallies non-fungible goods in the shopping section 302, if any. As discussed herein, the customer can hand pick non-fungible produce and tally/weigh the produce to be added to the customer order via the shopping terminal(s). The system incentivizes customers to order fungible goods initially (automated fulfillment) by having the automated fulfilled order ready for delivery when the customer is done picking non-fungible goods in the shopping section 302. Shopping for non-fungible goods can include utilizing a cart or tote to select loose produce (random weight), pre-packed (random dollar), and goods from service counters.
At step 906, the customer can perform checkout. In particular, as discussed herein, the customer can utilize the portable shopping terminal or checkout kiosk 618 to check out the combination of the non-fungible goods and the fungible goods. During the checkout, the weight of any tallied non-fungible goods are tallied and verified against the user input and the goods in the automated order are confirmed by the customer. The customer can pay utilizing any combination of cash, credit, virtual payment, etc.
At step 908, the customer receives delivery of the order. The delivery fulfillment provided to the customer includes both the non-fungible goods picked and verified by the customer and the fungible goods picked by the automated order fulfillment 106. As discussed herein, the delivery can take place in the store or outside of the store at the customer's car. Optionally, the customer can select a delayed checkout and leave the completed and paid for order at the store for future pickup or delivery. Checkout on a portable shopping terminal or checkout kiosk 618.
Any suitable computing device can be used to implement the computing devices 202, 204, 222, 224 and methods/functionality described herein and be converted to a specific system for performing the operations and features described herein through modification of hardware, software, and firmware, in a manner significantly more than mere execution of software on a generic computing device, as would be appreciated by those of skill in the art. One illustrative example of such a computing device 1000 is depicted in
The computing device 1000 can include a bus 1010 that can be coupled to one or more of the following illustrative components, directly or indirectly: a memory 1012, one or more processors 1014, one or more presentation components 1016, input/output ports 1018, input/output components 1020, and a power supply 1024. One of skill in the art will appreciate that the bus 1010 can include one or more busses, such as an address bus, a data bus, or any combination thereof. One of skill in the art additionally will appreciate that, depending on the intended applications and uses of a particular embodiment, multiple of these components can be implemented by a single device. Similarly, in some instances, a single component can be implemented by multiple devices. As such,
The computing device 1000 can include or interact with a variety of computer-readable media. For example, computer-readable media can include Random Access Memory (RAM); Read Only Memory (ROM); Electronically Erasable Programmable Read Only Memory (EEPROM); flash memory or other memory technologies; CDROM, digital versatile disks (DVD) or other optical or holographic media; magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices that can be used to encode information and can be accessed by the computing device 1000.
The memory 1012 can include computer-storage media in the form of volatile and/or nonvolatile memory. The memory 1012 may be removable, non-removable, or any combination thereof. Exemplary hardware devices are devices such as hard drives, solid-state memory, optical-disc drives, and the like. For example, the memory 1012 may be cloud based data storage accessible by the automated service system 202. The computing device 1000 can include one or more processors that read data from components such as the memory 1012, the various I/O components 1016, etc. Presentation component(s) 1016 present data indications to a user or other device. Exemplary presentation components include a display device, speaker, printing component, vibrating component, etc.
The I/O ports 1018 can enable the computing device 1000 to be logically coupled to other devices, such as I/O components 1020. Some of the I/O components 1020 can be built into the computing device 1000. Examples of such I/O components 1020 include a microphone, joystick, recording device, game pad, satellite dish, scanner, printer, wireless device, networking device, and the like.
As utilized herein, the terms “comprises” and “comprising” are intended to be construed as being inclusive, not exclusive. As utilized herein, the terms “exemplary”, “example”, and “illustrative”, are intended to mean “serving as an example, instance, or illustration” and should not be construed as indicating, or not indicating, a preferred or advantageous configuration relative to other configurations. As utilized herein, the terms “about” and “approximately” are intended to cover variations that may existing in the upper and lower limits of the ranges of subjective or objective values, such as variations in properties, parameters, sizes, and dimensions. In one non-limiting example, the terms “about” and “approximately” mean at, or plus 10 percent or less, or minus 10 percent or less. In one non-limiting example, the terms “about” and “approximately” mean sufficiently close to be deemed by one of skill in the art in the relevant field to be included. As utilized herein, the term “substantially” refers to the complete or nearly complete extend or degree of an action, characteristic, property, state, structure, item, or result, as would be appreciated by one of skill in the art. For example, an object that is “substantially” circular would mean that the object is either completely a circle to mathematically determinable limits, or nearly a circle as would be recognized or understood by one of skill in the art. The exact allowable degree of deviation from absolute completeness may in some instances depend on the specific context. However, in general, the nearness of completion will be so as to have the same overall result as if absolute and total completion were achieved or obtained. The use of “substantially” is equally applicable when utilized in a negative connotation to refer to the complete or near complete lack of an action, characteristic, property, state, structure, item, or result, as would be appreciated by one of skill in the art.
Numerous modifications and alternative embodiments of the present invention will be apparent to those skilled in the art in view of the foregoing description. Accordingly, this description is to be construed as illustrative only and is for the purpose of teaching those skilled in the art the best mode for carrying out the present invention. Details of the structure may vary substantially without departing from the spirit of the present invention, and exclusive use of all modifications that come within the scope of the appended claims is reserved. Within this specification embodiments have been described in a way which enables a clear and concise specification to be written, but it is intended and will be appreciated that embodiments may be variously combined or separated without parting from the invention. It is intended that the present invention be limited only to the extent required by the appended claims and the applicable rules of law.
It is also to be understood that the following claims are to cover all generic and specific features of the invention described herein, and all statements of the scope of the invention which, as a matter of language, might be said to fall therebetween.
The present application is a continuation of U.S. patent application Ser. No. 15/816,832, filed on Nov. 17, 2017, entitled “AUTOMATED-SERVICE RETAIL SYSTEM AND METHOD,” which application claims priority to U.S. Provisional Patent Application No. 62/423,614, filed on Nov. 17, 2016, entitled “AUTOMATED-SERVICE RETAIL SYSTEM AND METHOD,” which applications are incorporated by reference herein in their entirety.
Number | Name | Date | Kind |
---|---|---|---|
3927773 | Bright | Dec 1975 | A |
4007843 | Lubbers et al. | Feb 1977 | A |
4221076 | Ozawa | Sep 1980 | A |
4415975 | Burt | Nov 1983 | A |
4428708 | Burt | Jan 1984 | A |
5143246 | Johnson et al. | Sep 1992 | A |
5179329 | Nishikawa et al. | Jan 1993 | A |
5186281 | Jenkins | Feb 1993 | A |
5433293 | Sager | Jul 1995 | A |
5472309 | Bernard et al. | Dec 1995 | A |
5501295 | Muller et al. | Mar 1996 | A |
5526940 | Shea et al. | Jun 1996 | A |
5551823 | Maruyama | Sep 1996 | A |
5595264 | Trotta, Jr. | Jan 1997 | A |
5636966 | Yon et al. | Jun 1997 | A |
5642976 | Konstant | Jul 1997 | A |
5890136 | Kipp | Mar 1999 | A |
5953234 | Singer et al. | Sep 1999 | A |
5996316 | Kirschner | Dec 1999 | A |
6026376 | Kenney | Feb 2000 | A |
6289260 | Bradley et al. | Sep 2001 | B1 |
6325586 | Loy | Dec 2001 | B1 |
6386448 | Addy | May 2002 | B1 |
6494313 | Trescott | Dec 2002 | B1 |
6539876 | Campbell et al. | Apr 2003 | B1 |
6671580 | Campbell et al. | Dec 2003 | B2 |
6729836 | Stingel, III et al. | May 2004 | B2 |
6744436 | Chirieleison, Jr. et al. | Jun 2004 | B1 |
6805526 | Stefani | Oct 2004 | B2 |
6895301 | Mountz | May 2005 | B2 |
7054832 | Vallabh | May 2006 | B1 |
7101139 | Benedict | Sep 2006 | B1 |
7110855 | Leishman | Sep 2006 | B2 |
7139637 | Waddington et al. | Nov 2006 | B1 |
7246706 | Shakes et al. | Jul 2007 | B1 |
7255525 | Smith et al. | Aug 2007 | B2 |
7381022 | King | Jun 2008 | B1 |
7532947 | Waddington et al. | May 2009 | B2 |
7591630 | Lert, Jr. | Sep 2009 | B2 |
7603299 | Dewey, Jr. et al. | Oct 2009 | B1 |
7640863 | Minges | Jan 2010 | B2 |
7751928 | Antony et al. | Jul 2010 | B1 |
7774234 | Kopelman | Aug 2010 | B1 |
7861844 | Hayduchok et al. | Jan 2011 | B2 |
7894932 | Mountz et al. | Feb 2011 | B2 |
7894933 | Mountz et al. | Feb 2011 | B2 |
7896243 | Herskovitz | Mar 2011 | B2 |
7931431 | Benedict et al. | Apr 2011 | B2 |
7938324 | Tamarkin et al. | May 2011 | B2 |
7991505 | Lert, Jr. et al. | Aug 2011 | B2 |
8104601 | Hayduchok et al. | Jan 2012 | B2 |
8201737 | Palacios Durazo et al. | Jun 2012 | B1 |
8276740 | Hayduchok et al. | Oct 2012 | B2 |
8311902 | Mountz et al. | Nov 2012 | B2 |
8327609 | Krizmanic et al. | Dec 2012 | B2 |
8425173 | Lert et al. | Apr 2013 | B2 |
8447665 | Schoenharl et al. | May 2013 | B1 |
8483869 | Wurman et al. | Jul 2013 | B2 |
8527325 | Atreya et al. | Sep 2013 | B1 |
8579574 | Hanel | Nov 2013 | B2 |
8594835 | Lert et al. | Nov 2013 | B2 |
8622194 | DeWitt et al. | Jan 2014 | B2 |
8626335 | Wurman et al. | Jan 2014 | B2 |
8639531 | Hasan et al. | Jan 2014 | B2 |
8690510 | Razumov | Apr 2014 | B1 |
8694152 | Cyrulik et al. | Apr 2014 | B2 |
8718814 | Clark et al. | May 2014 | B1 |
8721250 | Razumov | May 2014 | B2 |
8721251 | Razumov | May 2014 | B1 |
8734079 | Razumov | May 2014 | B1 |
8738177 | Van Ooyen et al. | May 2014 | B2 |
8740538 | Lert et al. | Jun 2014 | B2 |
8831984 | Hoffman et al. | Sep 2014 | B2 |
8892240 | Vliet et al. | Nov 2014 | B1 |
8965562 | Wurman et al. | Feb 2015 | B1 |
8972045 | Mountz et al. | Mar 2015 | B1 |
8983647 | Dwarakanath et al. | Mar 2015 | B1 |
9008828 | Worsley | Apr 2015 | B2 |
9008829 | Worsley | Apr 2015 | B2 |
9008830 | Worsley | Apr 2015 | B2 |
9010517 | Hayduchok et al. | Apr 2015 | B2 |
9020632 | Naylor | Apr 2015 | B2 |
9037286 | Lert | May 2015 | B2 |
9051120 | Lert et al. | Jun 2015 | B2 |
9096375 | Lert et al. | Aug 2015 | B2 |
9111251 | Brazeau | Aug 2015 | B1 |
9120622 | Elazary et al. | Sep 2015 | B1 |
9129250 | Sestini et al. | Sep 2015 | B1 |
9139363 | Lert | Sep 2015 | B2 |
9147208 | Argue et al. | Sep 2015 | B1 |
9216857 | Kalyan et al. | Dec 2015 | B1 |
9242798 | Guan | Jan 2016 | B2 |
9242799 | O'Brien et al. | Jan 2016 | B1 |
9260245 | Este et al. | Feb 2016 | B2 |
9321591 | Lert et al. | Apr 2016 | B2 |
9330373 | Mountz et al. | May 2016 | B2 |
9334113 | Naylor | May 2016 | B2 |
9334116 | DeWitt et al. | May 2016 | B2 |
9378482 | Pikler et al. | Jun 2016 | B1 |
9409664 | Vliet et al. | Aug 2016 | B1 |
9423796 | Sullivan et al. | Aug 2016 | B2 |
9428295 | Vliet et al. | Aug 2016 | B2 |
9452883 | Wurman et al. | Sep 2016 | B1 |
9466045 | Kumar | Oct 2016 | B1 |
9487356 | Aggarwal | Nov 2016 | B1 |
9505556 | Razumov | Nov 2016 | B2 |
9527669 | Hanssen et al. | Dec 2016 | B1 |
9550624 | Khodl | Jan 2017 | B2 |
9558472 | Tubilla Kuri | Jan 2017 | B1 |
9626709 | Koch et al. | Apr 2017 | B2 |
9630777 | Yamashita | Apr 2017 | B2 |
9733646 | Nusser et al. | Aug 2017 | B1 |
9751693 | Battles et al. | Sep 2017 | B1 |
9815625 | DeWitt et al. | Nov 2017 | B2 |
9821959 | Hognaland | Nov 2017 | B2 |
9827683 | Hance et al. | Nov 2017 | B1 |
9852396 | Jones et al. | Dec 2017 | B2 |
9978036 | Eller | May 2018 | B1 |
10127514 | Napoli | Nov 2018 | B2 |
10179700 | Lert, Jr. | Jan 2019 | B2 |
10189641 | Hognaland | Jan 2019 | B2 |
10192195 | Brazeau | Jan 2019 | B1 |
10229385 | Evers et al. | Mar 2019 | B2 |
10336543 | Sills et al. | Jul 2019 | B1 |
10360531 | Stallman et al. | Jul 2019 | B1 |
10482421 | Ducrou et al. | Nov 2019 | B1 |
10579965 | Meurer | Mar 2020 | B2 |
11142402 | Lert, Jr. | Oct 2021 | B2 |
20020059121 | Schneider et al. | May 2002 | A1 |
20020077937 | Lyons | Jun 2002 | A1 |
20020082887 | Boyert | Jun 2002 | A1 |
20020133415 | Zarovinsky | Sep 2002 | A1 |
20020143669 | Scheer | Oct 2002 | A1 |
20030110104 | King et al. | Jun 2003 | A1 |
20030197061 | Din | Oct 2003 | A1 |
20040010337 | Mountz | Jan 2004 | A1 |
20040010339 | Mountz | Jan 2004 | A1 |
20040024730 | Brown et al. | Feb 2004 | A1 |
20040111337 | Feeney et al. | Jun 2004 | A1 |
20040238629 | Buchholz | Dec 2004 | A1 |
20040249497 | Saigh | Dec 2004 | A1 |
20040254825 | Hsu et al. | Dec 2004 | A1 |
20050035694 | Stevens | Feb 2005 | A1 |
20050043850 | Stevens et al. | Feb 2005 | A1 |
20050047895 | Lert | Mar 2005 | A1 |
20050060246 | Lastinger et al. | Mar 2005 | A1 |
20050096936 | Lambers | May 2005 | A1 |
20050108114 | Kaled | May 2005 | A1 |
20050149226 | Stevens et al. | Jul 2005 | A1 |
20050182695 | Lubow et al. | Aug 2005 | A1 |
20050256787 | Wadawadigi et al. | Nov 2005 | A1 |
20050267791 | LaVoie et al. | Dec 2005 | A1 |
20050278062 | Janert et al. | Dec 2005 | A1 |
20060020366 | Bloom | Jan 2006 | A1 |
20060108419 | Som | May 2006 | A1 |
20060182548 | Gretsch | Aug 2006 | A1 |
20060257236 | Stingel, III et al. | Nov 2006 | A1 |
20070011053 | Yap | Jan 2007 | A1 |
20070016496 | Bar et al. | Jan 2007 | A1 |
20070127691 | Lert, Jr. | Jun 2007 | A1 |
20070162353 | Borders et al. | Jul 2007 | A1 |
20070210164 | Conlon et al. | Sep 2007 | A1 |
20070244758 | Xie | Oct 2007 | A1 |
20070276535 | Haag | Nov 2007 | A1 |
20070293978 | Wurman et al. | Dec 2007 | A1 |
20070294029 | D'Andrea et al. | Dec 2007 | A1 |
20080040244 | Ricciuti et al. | Feb 2008 | A1 |
20080041947 | Hollister et al. | Feb 2008 | A1 |
20080131241 | King | Jun 2008 | A1 |
20080131255 | Hessler et al. | Jun 2008 | A1 |
20080181753 | Bastian et al. | Jul 2008 | A1 |
20080215180 | Kota | Sep 2008 | A1 |
20090074545 | Lert, Jr. | Mar 2009 | A1 |
20090149985 | Chirnomas | Jun 2009 | A1 |
20090157472 | Burazin et al. | Jun 2009 | A1 |
20090249749 | Schill et al. | Oct 2009 | A1 |
20090272799 | Skor et al. | Nov 2009 | A1 |
20090276264 | Pandit et al. | Nov 2009 | A1 |
20100010902 | Casey | Jan 2010 | A1 |
20100060455 | Frabasile | Mar 2010 | A1 |
20100076591 | Lert, Jr. | Mar 2010 | A1 |
20100114790 | Strimling et al. | May 2010 | A1 |
20100234980 | Lapre | Sep 2010 | A1 |
20100262278 | Winkler | Oct 2010 | A1 |
20100310344 | Hinnen | Dec 2010 | A1 |
20100316468 | Lert et al. | Dec 2010 | A1 |
20100316469 | Lert et al. | Dec 2010 | A1 |
20100316470 | Lert et al. | Dec 2010 | A1 |
20100322746 | Lert | Dec 2010 | A1 |
20100322747 | Lert et al. | Dec 2010 | A1 |
20110008138 | Yamashita | Jan 2011 | A1 |
20110238207 | Bastian, II et al. | Sep 2011 | A1 |
20110243707 | Dumas et al. | Oct 2011 | A1 |
20110320034 | Dearlove et al. | Dec 2011 | A1 |
20120029683 | Keller et al. | Feb 2012 | A1 |
20120029685 | Keller | Feb 2012 | A1 |
20120101627 | Lert | Apr 2012 | A1 |
20120143427 | Hoffman et al. | Jun 2012 | A1 |
20120150340 | Suess et al. | Jun 2012 | A1 |
20120173351 | Hanson | Jul 2012 | A1 |
20120186942 | Toebes et al. | Jul 2012 | A1 |
20120195720 | Sullivan et al. | Aug 2012 | A1 |
20120219397 | Baker | Aug 2012 | A1 |
20120298688 | Stiernagle | Nov 2012 | A1 |
20120330458 | Weiss | Dec 2012 | A1 |
20130087610 | Shin et al. | Apr 2013 | A1 |
20130181586 | Hognaland | Jul 2013 | A1 |
20130226718 | Ascarrunz | Aug 2013 | A1 |
20130235206 | Smith et al. | Sep 2013 | A1 |
20130246229 | Mountz et al. | Sep 2013 | A1 |
20130310967 | Olson et al. | Nov 2013 | A1 |
20130317642 | Asaria et al. | Nov 2013 | A1 |
20130346204 | Wissner-Gross et al. | Dec 2013 | A1 |
20140003727 | Lortz et al. | Jan 2014 | A1 |
20140040075 | Perry et al. | Feb 2014 | A1 |
20140052498 | Marshall | Feb 2014 | A1 |
20140058822 | Sobecks et al. | Feb 2014 | A1 |
20140062699 | Heine et al. | Mar 2014 | A1 |
20140088758 | Lert et al. | Mar 2014 | A1 |
20140100769 | Wurman et al. | Apr 2014 | A1 |
20140100999 | Mountz et al. | Apr 2014 | A1 |
20140136218 | Bolene et al. | May 2014 | A1 |
20140143099 | Wilkins | May 2014 | A1 |
20140156553 | Leach et al. | Jun 2014 | A1 |
20140212249 | Kawano | Jul 2014 | A1 |
20140244026 | Neiser | Aug 2014 | A1 |
20140257555 | Bastian, II | Sep 2014 | A1 |
20140271063 | Lert et al. | Sep 2014 | A1 |
20140279294 | Field-Darragh et al. | Sep 2014 | A1 |
20140288696 | Lert | Sep 2014 | A1 |
20140308098 | Lert et al. | Oct 2014 | A1 |
20140324491 | Banks et al. | Oct 2014 | A1 |
20140330603 | Corder | Nov 2014 | A1 |
20140336814 | Moore et al. | Nov 2014 | A1 |
20140343717 | Dorval et al. | Nov 2014 | A1 |
20140350715 | Gopalakrishnan et al. | Nov 2014 | A1 |
20140351101 | Danelski | Nov 2014 | A1 |
20140365341 | MacLaurin | Dec 2014 | A1 |
20150032252 | Galluzzo et al. | Jan 2015 | A1 |
20150051994 | Ward et al. | Feb 2015 | A1 |
20150058178 | Chirnomas | Feb 2015 | A1 |
20150071743 | Lert | Mar 2015 | A1 |
20150112826 | Crutchfield, Jr. | Apr 2015 | A1 |
20150134490 | Collin | May 2015 | A1 |
20150154535 | Wappler et al. | Jun 2015 | A1 |
20150170256 | Pettyjohn et al. | Jun 2015 | A1 |
20150178671 | Jones et al. | Jun 2015 | A1 |
20150178673 | Penneman | Jun 2015 | A1 |
20150206224 | Ouimet | Jul 2015 | A1 |
20150220896 | Carr | Aug 2015 | A1 |
20150266672 | Lert et al. | Sep 2015 | A1 |
20150286967 | Lert et al. | Oct 2015 | A1 |
20150291357 | Razumov | Oct 2015 | A1 |
20150294333 | Avegliano et al. | Oct 2015 | A1 |
20150307279 | Almada et al. | Oct 2015 | A1 |
20150310447 | Shaw | Oct 2015 | A1 |
20150375938 | Lert et al. | Dec 2015 | A9 |
20160016733 | Lert | Jan 2016 | A1 |
20160031644 | Schubilske | Feb 2016 | A1 |
20160055452 | Qin | Feb 2016 | A1 |
20160063604 | Shaffer | Mar 2016 | A1 |
20160075512 | Lert | Mar 2016 | A1 |
20160086255 | Sainfort | Mar 2016 | A1 |
20160101940 | Grinnell et al. | Apr 2016 | A1 |
20160107838 | Swinkels | Apr 2016 | A1 |
20160110702 | Landers, Jr. | Apr 2016 | A1 |
20160129592 | Saboo et al. | May 2016 | A1 |
20160140488 | Lindbo | May 2016 | A1 |
20160145045 | Mountz et al. | May 2016 | A1 |
20160167227 | Wellman et al. | Jun 2016 | A1 |
20160171592 | Pugh | Jun 2016 | A1 |
20160223339 | Pellow et al. | Aug 2016 | A1 |
20160236867 | Brazeau et al. | Aug 2016 | A1 |
20160244262 | O'Brien et al. | Aug 2016 | A1 |
20160253740 | Goulart | Sep 2016 | A1 |
20160260158 | High | Sep 2016 | A1 |
20160299782 | Jones et al. | Oct 2016 | A1 |
20160304281 | Elazary et al. | Oct 2016 | A1 |
20160307153 | Løken | Oct 2016 | A1 |
20160311617 | Van Den Berk | Oct 2016 | A1 |
20160314431 | Quezada | Oct 2016 | A1 |
20160325933 | Stiernagle et al. | Nov 2016 | A1 |
20160327941 | Stiernagle et al. | Nov 2016 | A1 |
20160347545 | Lindbo et al. | Dec 2016 | A1 |
20160355337 | Lert et al. | Dec 2016 | A1 |
20160364786 | Wankhede | Dec 2016 | A1 |
20160371650 | Schmidt | Dec 2016 | A1 |
20170036798 | Prahlad et al. | Feb 2017 | A1 |
20170043953 | Battles et al. | Feb 2017 | A1 |
20170066592 | Bastian, II et al. | Mar 2017 | A1 |
20170068973 | Sinkel | Mar 2017 | A1 |
20170088360 | Brazeau et al. | Mar 2017 | A1 |
20170113910 | Becchi et al. | Apr 2017 | A1 |
20170132559 | Jones et al. | May 2017 | A1 |
20170137222 | Lert, Jr. | May 2017 | A1 |
20170137223 | Lert, Jr. | May 2017 | A1 |
20170158430 | Raizer | Jun 2017 | A1 |
20170166356 | Tubilla Kuri | Jun 2017 | A1 |
20170166399 | Stubbs et al. | Jun 2017 | A1 |
20170185933 | Adulyasak et al. | Jun 2017 | A1 |
20170185955 | Hufschmid et al. | Jun 2017 | A1 |
20170200108 | Au et al. | Jul 2017 | A1 |
20170206480 | Naumann et al. | Jul 2017 | A1 |
20170213186 | Grifoni | Jul 2017 | A1 |
20170220995 | Paulweber et al. | Aug 2017 | A1 |
20170228701 | Wosk et al. | Aug 2017 | A1 |
20170260008 | DeWitt et al. | Sep 2017 | A1 |
20170267452 | Goren et al. | Sep 2017 | A1 |
20170269607 | Fulop | Sep 2017 | A1 |
20170278047 | Welty et al. | Sep 2017 | A1 |
20170285648 | Welty et al. | Oct 2017 | A1 |
20170297820 | Grinnell et al. | Oct 2017 | A1 |
20170301004 | Chirnomas | Oct 2017 | A1 |
20170313514 | Lert, Jr. et al. | Nov 2017 | A1 |
20170316233 | Kherani et al. | Nov 2017 | A1 |
20170320102 | McVaugh et al. | Nov 2017 | A1 |
20170322561 | Stiernagle | Nov 2017 | A1 |
20170323250 | Lindbo et al. | Nov 2017 | A1 |
20170330142 | Kanellos et al. | Nov 2017 | A1 |
20170330270 | Kanellos | Nov 2017 | A1 |
20170334646 | High et al. | Nov 2017 | A1 |
20170369244 | Battles et al. | Dec 2017 | A1 |
20180005173 | Elazary et al. | Jan 2018 | A1 |
20180005174 | Dixon et al. | Jan 2018 | A1 |
20180029797 | Hance et al. | Feb 2018 | A1 |
20180032949 | Galluzzo | Feb 2018 | A1 |
20180068368 | Mattingly | Mar 2018 | A1 |
20180130015 | Jones et al. | May 2018 | A1 |
20180134492 | Lert, Jr. | May 2018 | A1 |
20180137452 | Khatravath et al. | May 2018 | A1 |
20180182054 | Yao et al. | Jun 2018 | A1 |
20180211203 | Greenberg | Jun 2018 | A1 |
20180237221 | Lindbo et al. | Aug 2018 | A1 |
20180237222 | Issing et al. | Aug 2018 | A1 |
20180300680 | Undernehr et al. | Oct 2018 | A1 |
20180314991 | Grundberg | Nov 2018 | A1 |
20180319590 | Lindbo et al. | Nov 2018 | A1 |
20180342031 | Tada et al. | Nov 2018 | A1 |
20190026770 | Murugesan | Jan 2019 | A1 |
20190139637 | Ceh | May 2019 | A1 |
20190197451 | Balasingham | Jun 2019 | A1 |
20190389659 | Grinnell et al. | Dec 2019 | A1 |
20210032034 | Kalouche | Feb 2021 | A1 |
20220274776 | Lert, Jr. | Sep 2022 | A1 |
Number | Date | Country |
---|---|---|
101790740 | Jul 2010 | CN |
3624033 | Aug 1987 | DE |
102012100354 | Jul 2013 | DE |
0302205 | Feb 1989 | EP |
1348646 | Oct 2003 | EP |
2650237 | Nov 2014 | EP |
2995579 | Mar 2016 | EP |
2651786 | May 2016 | EP |
2651787 | May 2016 | EP |
3056454 | Aug 2016 | EP |
3542327 | Sep 2019 | EP |
S4715872 | Jun 1972 | JP |
H0642810 | Jun 1994 | JP |
H08161612 | Jun 1996 | JP |
H1135107 | Feb 1999 | JP |
2002160813 | Jun 2002 | JP |
2004139194 | May 2004 | JP |
2007246226 | Sep 2007 | JP |
2009535285 | Oct 2009 | JP |
2020514203 | May 2020 | JP |
7137562 | Sep 2022 | JP |
2022171728 | Nov 2022 | JP |
0068856 | Nov 2000 | WO |
0169552 | Sep 2001 | WO |
2005097550 | Oct 2005 | WO |
2007067868 | Jun 2007 | WO |
2010100513 | Sep 2010 | WO |
20100118412 | Oct 2010 | WO |
2014166640 | Oct 2014 | WO |
2015005873 | Jan 2015 | WO |
2016172793 | Nov 2016 | WO |
2016199033 | Dec 2016 | WO |
2017064401 | Apr 2017 | WO |
2018094286 | May 2018 | WO |
Entry |
---|
Office Action dated Sep. 14, 2022 in Japanese Patent Application No. 2019-546194. |
Final Office Action dated Oct. 20, 2021 in U.S. Appl. No. 16/594,647. |
Response to Office Action filed Aug. 24, 2020 in U.S. Appl. No. 15/951,956. |
Office Action dated Mar. 13, 2023 in U.S. Appl. No. 17/745,627. |
English language Abstract for WO2017064401 published Apr. 20, 2017. |
Non-Final Rejection dated Sep. 3, 2014 in U.S. Appl. No. 14/213,187. |
Amendment filed Feb. 27, 2015 in U.S. Appl. No. 14/213,187. |
Notice of Allowance and Fees Due dated May 20, 2015 in U.S. Appl. No. 14/213, 187. |
Non-Final Rejection dated Jan. 12, 2016 in U.S. Appl. No. 14/860,410. |
Amendment filed Apr. 8, 2016 in U.S. Appl. No. 14/860,410. |
Non-Final Rejection dated Jul. 20, 2016 in U.S. Appl. No. 14/860,410. |
Amendment filed Sep. 27, 2016 in U.S. Appl. No. 14/860,410. |
Notice of Allowance and Fees Due dated Nov. 10, 2016 in U.S. Appl. No. 14/860,410. |
Non-Final Rejection dated Apr. 10, 2017 in U.S. Appl. No. 15/421,208. |
Amendment filed Sep. 11, 2017 in U.S. Appl. No. 15/421,208. |
Supplemental Amendment filed Oct. 12, 2017 in U.S. Appl. No. 15/421,208. |
Notice of Allowance and Fee{s) Due dated Oct. 5, 2017 in U.S. Appl. No. 15/421,239. |
International Search Report dated Oct. 7, 2016 in International Application No. PCT/US2016/035547. |
Restriction Requirement dated Nov. 3, 2017 in U.S. Appl. No. 15/171,802, filed Jun. 2, 2016. |
International Search Report and Written Opinion dated Sep. 6, 2017 in International Patent Application No. PCTUS2017/032171. |
U.S. Appl. No. 15/699,700, filed Sep. 8, 2017. |
English language Abstract for WO2014166640 published Oct. 16, 2014. |
Response to Restriction Requirement filed Nov. 20, 2017 in U.S. Appl. No. 15/171,802. |
U.S. Appl. No. 15/826,045, filed Nov. 29, 2017. |
Notice of Allowance and Fee(s) Due dated Dec. 8, 2017 in U.S. Appl. No. 15/421,209. |
Notice of Allowance and Fee(s) Due dated Jan. 19, 2018 in U.S. Appl. No. 15/421,239. |
Office Action dated Feb. 12, 2018 in U.S. Appl. No. 15/171,802. |
International Search Report for International Application No. PCT/US2017/062423 dated Feb. 5, 2018. |
Notice of Allowance and Fee(s) Due dated Jan. 16, 2018 in U.S. Appl. No. 15/699,700. |
International Search Report for International Application No. PCT/US2018/013203 dated Apr. 5, 2018. |
International Search Report for International Application No. PCT/US2018/19537 dated Apr. 13, 2018. |
Response to Office Action filed May 9, 2018 in U.S. Appl. No. 15/171,802. |
Final Office Action dated Aug. 7, 2018 in U.S. Appl. No. 15/171,802. |
Notice of Allowance and Fee(s) Due dated Aug. 31, 2018 in U.S. Appl. No. 15/978,423. |
Response to Office Action filed Sep. 12, 2018 in U.S. Appl. No. 15/171,802. |
Notice of Allowance and Fee(s) Due dated Oct. 9, 2018 in U.S. Appl. No. 15/171,802. |
Response to Office Action filed Nov. 13, 2018 in U.S. Appl. No. 15/421,208. |
Notice of Allowance dated Jan. 17, 2019 in U.S. Appl. No. 15/421,208. |
Notice of Allowance and Fee(s) Due dated Jan. 29, 2019 in U.S. Appl. No. 15/171,802. |
Notice of Allowance dated Mar. 20, 2019 in U.S. Appl. No. 15/421,208. |
Office Action dated Jun. 21, 2019 in U.S. Appl. No. 15/867,373. |
Brittain Ladd, “A Beautiful Way to Save Woolworths”, www.linkedin.com/pulse, May 17, 2016. |
Bill Bishop, “The Automated Supermarket: Part 1”, www.brickmeetsclick.com, Jul. 23, 2013. |
Bill Bishop, “The Automated Supermarket: Part 2”, www.brickmeetsclick.com, Jul. 29, 2013. |
Response to Office Action filed Sep. 23, 2019 in European Patent Application No. 16804451.9. |
Response to Office Action filed Oct. 21, 2019 in U.S. Appl. No. 15/867,373. |
Response to Office Action filed Oct. 29, 2019 in U.S. Appl. No. 15/826,045. |
Office Action dated Nov. 20, 2019 in U.S. Appl. No. 15/826,045. |
Office Action dated Dec. 5, 2019 in U.S. Appl. No. 15/867,373. |
Preliminary Amendment filed Dec. 20, 2019 in U.S. Appl. No. 16/594,647. |
Response to Office Action filed Jan. 24, 2020 in U.S. Appl. No. 15/951,956. |
Response to Office Action filed Mar. 5, 2020 in U.S. Appl. No. 15/867,373. |
Office Action dated Dec. 5, 2022 in Japanese Patent Application No. 2021-156451. |
Office Action dated Feb. 2, 2023 in U.S. Appl. No. 17/223,714. |
Final Office Action dated Mar. 24, 2020 in U.S. Appl. No. 15/591,956. |
Response to Office Action filed Jan. 24, 2020 in U.S. Appl. No. 15/591,956. |
Office Action dated Nov. 18, 2019 in U.S. Appl. No. 15/903,993. |
Response to Office Action filed Apr. 16, 2020 in U.S. Appl. No. 15/903,993. |
Notice of Allowance and Fee(s) Due dated May 15, 2020 in U.S. Appl. No. 15/903,993. |
Qi Xu, “Improving Responsiveness of Supply Chain through RFID Visibility Technology”, 2009 IEEE/INFORMS International Conference on Service Operations, Logistics and Informatics, Chicago, IL, Jul. 22-24, 2009, pp. 513-517. |
Harrison et al., “Intelligent distribution and logistics”, IEE Proceedings—Intelligent Transport Systems, vol. 153, No. 2, pp. 167-180, Jun. 2006. |
N. Viswanadham, “The past, present, and future of supply-chain automation”, IEE Robotics & Automation Magazine, vol. 9, No. 2, pp. 48-56, Jun. 2002. |
C. Prasse et al., “How IoT will change the design and operation of logistics systems”, 2014 International Conference on the Internet of Things (IOT), Oct. 6-8, 2014, pp. 55-60. |
Leung et al., “Design of a Case-Based Multi-Agent Wave Picking Decision Support System for Handling E-Commerce Shipments”, 2016 Portland International Conference on Management of Engineering and Technology (PICMET), Sep. 4-8, 2016, pp. 2248-2256. |
Final Office Action dated Jun. 18, 2020 in U.S. Appl. No. 15/826,045. |
Response to Office Action filed Mar. 6, 2020 in European Patent Application No. 18702006.0. |
Office Action dated Mar. 20, 2020 in U.S. Appl. No. 15/867,373. |
Extended European Search Report dated Mar. 13, 2020 in European Patent Application No. 19217215.3. |
Final Office Action dated Mar. 24, 2020 in U.S. Appl. No. 15/951,956. |
Response to Office Action filed Apr. 15, 2020 in U.S. Appl. No. 15/826,045. |
Response to Office Action filed Apr. 17, 2020 in European Patent Application No. 18709235.8. |
Response to Office Action filed Jul. 20, 2020 in U.S. Appl. No. 15/867,373. |
Office Action dated Aug. 11, 2020 in Japanese Patent Application No. 2018-515183. |
Notice of Allowance and Fee(s) Due dated Aug. 19, 2020 in U.S. Appl. No. 15/867,373. |
Office Action dated Aug. 20, 2020 in U.S. Appl. No. 16/121,212. |
English language Abstract for DE3624033 published Aug. 6, 1987. |
Office Action dated Sep. 14, 2020 in U.S. Appl. No. 15/591,956. |
Office Action dated Sep. 14, 2020 in U.S. Appl. No. 15/903,993. |
International Search Report and Written Opinion dated Sep. 4, 2020 in International Patent Application No. PCT/US2020/033250. |
Response to Office Action filed Nov. 2, 2020, with English machine translation, in Chinese Patent Application No. 201780042943.2. |
Response to Office Action filed Dec. 18, 2020, with English language translation of claims as amended, in Japanese Patent Application No. 2018-515183. |
Office Action dated Dec. 24, 2020, with English language translation, in Japanese Patent Application No. 2020-038556. |
Office Action dated Nov. 25, 2020, with English language translation, in Japanese Patent Application No. 2019-526569. |
Office Action dated Dec. 24, 2020 in U.S. Appl. No. 16/273,449. |
Notice of Allowance and Fee(s) Due dated Feb. 11, 2021 in U.S. Appl. No. 15/903,993. |
C. Wurll, “Mixed Case Palletizing with Industrial Robots,” Proceedings of ISR 2016: 47st International Symposium on Robotics, Munich, Germany, pp. 1-6, Jun. 21-22, 2016. |
Extended European Search Report dated May 12, 2021 in European Patent Application No. 21163777.2. |
Response to Office Action filed May 17, 2021 in U.S. Appl. No. 16/273,449. |
Supplemental Response to Office Action filed May 26, 2021 in U.S. Appl. No. 16/273,449. |
Office Action dated Jun. 18, 2021 in U.S. Appl. No. 15/903,993. |
Office Action dated May 4, 2018 in U.S. Appl. No. 15/816,832. |
Response to Office Action filed Aug. 2, 2018 in U.S. Appl. No. 15/816,832. |
Final Office Action dated Nov. 2, 2018 in U.S. Appl. No. 15/816,832. |
Response to Final Office Action filed Mar. 22, 2019 in U.S. Appl. No. 15/816,832. |
Office Action dated Apr. 15, 2019 in U.S. Appl. No. 15/816,832. |
Response to Office Action filed Aug. 12, 2019 in U.S. Appl. No. 15/816,832. |
Final Office Action dated Nov. 1, 2019 in U.S. Appl. No. 15/816,832. |
Response to Final Office Action filed Mar. 30, 2020 in U.S. Appl. No. 15/816,832. |
Office Action dated Apr. 30, 2020 in U.S. Appl. No. 15/816,832. |
Response to Office Action filed Aug. 31, 2020 in U.S. Appl. No. 15/816,832. |
Final Office Action dated Oct. 19, 2020 in U.S. Appl. No. 15/816,832. |
Response to Final Office Action filed Mar. 19, 2021 in U.S. Appl. No. 15/816,832. |
Notice of Allowance and Fee(s) Due dated Apr. 1, 2021 in U.S. Appl. No. 15/816,832. |
Notice of Allowance and Fee(s) Due dated Jun. 9, 2021 in U.S. Appl. No. 15/816,832. |
Notice of Allowance and Fee(s) Due dated Jul. 30, 2021 in U.S. Appl. No. 15/816,832. |
Office Action dated Apr. 19, 2023 in U.S. Appl. No. 17/240,777. |
Kate Taylor, “Walmart, Lowe's, and Whole Foods are banking on this to compete with Amazon”, Business Insider, (Sep. 18, 2016), URL: https://www.businessinsider.nl/retail-companies-invest-in-automation-2016-9/?international=true&r=US, (Jan. 24, 2018), XP055444003. |
CIPO; App. No. 3,043,896; Office Action and Examination Search Report dated Jan. 19, 2023; (3 pages). |
IPA; App. No. 2017362508; Examination Report dated Aug. 22, 2022; (6 pages). |
IMPI; App. No. MX/a/2019/005740; Office Action dated Mar. 31, 2023; (18 pages). |
PCT; App. No. PCT/US2017/062423; International Search Report and Written Opinion dated Feb. 5, 2018; (15 pages). |
CNIPA; App. No. 201780083818.6; Office Action dated Aug. 29, 2022; (29 pages). |
CNIPA; App. No. 201780083818.6; First Search dated Aug. 19, 2022; (2 pages). |
EPO; App. No. 17817396.9; Communication Pursuant to Rules 161(1) and 162 EPC dated Jul. 5, 2019; (3 pages). |
EPO; App. No. 17817396.9; Communication Pursuant to Article 94(3) EPC dated Feb. 25, 2021; (7 pages). |
EPO; App. No. 17817396.9; Communication Pursuant to Article 94(3) EPC dated Jun. 27, 2023; (8 pages). |
IMPI; App. No. MX/a/2019/005740; Office Action dated Jan. 6, 2023; (11 pages). |
JPO; App. No. 2019-526569; Decision to Grant dated Jul. 8, 2022; (2 pages). |
JPO; App. No. 2019-526569; Office Action dated Aug. 19, 2021; (4 pages). |
JPO; App. No. 2019-526569; Office Action dated Nov. 25, 2020; (7 pages). |
IPI; App. No. 201927023909; First Examination Report dated Jun. 18, 2021; (7 pages). |
Non-Final Office Action dated Mar. 23, 2021 in U.S. Appl. No. 16/594,647. |
Response to Office Action filed Aug. 24, 2020 in U.S. Appl. No. 15/591,956. |
Taylor, Kate; “Walmart, Lowe's, and Whole Foods are banking on this to compete with Amazon”; https://www.businessinsider.nl/retail-companies-invest-in-automation-2016-9/? international=true&r=US; Sep. 18, 2016; pp. 1-8. |
IMPI; App. No. MX/a/2019/005740; Office Action dated Aug. 31, 2023; (6 pages). |
Number | Date | Country | |
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20220036295 A1 | Feb 2022 | US |
Number | Date | Country | |
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62423614 | Nov 2016 | US |
Number | Date | Country | |
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Parent | 15816832 | Nov 2017 | US |
Child | 17499783 | US |