Abstract: A system-directed single line pick batching is described. In an example implementation, the system may receive data describing a set of orders including SKU identifiers associated with items in the orders, identify an eligible cart, and assign a location to a task queue of the cart based on the location being associated with a particular SKU identifier. In some instances, the location or SKU identifier may be determined based on an order with a certain quantity of different SKU identifiers. In some instances, the system may navigate the cart to the location and instruct the item to be picked from the location. In response to completion of the pick of the item, the system may navigate the cart to an end point.

Abstract: The technology includes an example method for determining matching items. In some implementations, the method may determine a first set and second set of attributes and attribute types associated with a first and second item, respectively, based on description data associated with the items. The method may determine an attribute-type indicator for a pairing of a first attribute of the first set with a second attribute of the second set based on attribute types of the attributes, compute an attribute value for the pairing based on a similarity between the first and second attribute, and compute a match score for a combination of the first and second items based on the attribute value and attribute-type indicator. The method may also, in response to receiving a data query identifying the first item, provide a graphical user interface including a graphical element representing the second item based on the match score.

Abstract: In an example embodiment, a method may generate an item layout map for a shelving unit, where the shelving unit stores item types associated with a product category. The method may determine product attributes associated with the product category and divider configurations of the shelving unit, where a divider configuration divides the shelving unit into one or more candidate regions. The method may generate an ontology entry associated with a product attribute and the divider configuration based on the item layout map and the divider configuration of the shelving unit, the ontology entry indicating a regional entropy values of a product attribute for the candidate regions generated by the divider configuration. In some instances, the method may generate a guidance instruction related to the product attribute of the product category based on the ontology entry and provide the guidance instruction to a user.

Abstract: A hybrid modular storage fetching system is described. In an example implementation, an automated guided vehicle of the hybrid modular storage fetching system includes a drive unit that provides motive force to propel the automated guided vehicle within an operating environment. The automated guided vehicle may also include a container handling mechanism including an extender and a carrying surface, the container handling mechanism having three or more degrees of freedom to move the carrying surface along three or more axes. The container handling mechanism may retrieve an item from a first target shelving unit using the carrying surface and the three or more degrees of freedom and place the item on a second target shelving unit. The automated guided vehicle may also include a power source coupled to provide power to the drive unit and the container handling mechanism.

Abstract: A release logic system for releasing cartons into a fulfillment system is described. In an example implementation, a release logic engine may receive carton data representing a set of cartons and indicating picks for each the set of cartons. The release logic engine may determine a score for a carton of the set of cartons based on a location of a first pick of the carton in a pick-to-cart area of a fulfillment center. In some implementations, the release logic engine may assign the carton to a cart adapted to transport cartons based on the score determined for the carton, and may induct the carton into the fulfillment center for the first pick using the cart.

Abstract: Technology for optimizing automated inventory management is described. In an example implementation, a method, implemented using one or more computing devices, may generate unit identifier sets based on affinities between items uniquely identified by the unit identifiers, determine first and second contribution values for each of the unit identifier sets, and calculate a difference between the first and the second contribution values for each of the unit identifier sets. The method may further calculate an incremental carton and expense prevention opportunity (ICEPO) value for the unit identifier sets, calculate an adjusted fulfillment center stocking score using the ICEPO value and the difference between the first and the second contribution values for each of the unit identifier sets, select a subset of the unit identifier sets based on the adjusted fulfillment center stocking score, and output the subset to an inventory replenishment system that manages stocking of items.

Abstract: An automated belt-based diverter system is described in some implementations. In an example implementation, the system may include a belt, which includes a closed loop of material, coupled with a pulley and a motor that provides motive force to the belt, for example, using the pulley. In some implementations, one or more diverter arms may be coupled with the belt. A diverter arm may include a body with a first arm end, a second arm end, and a pushing surface. A diverter arm may be coupled at the first end with the belt so that the second end extends away from the belt and the pushing surface may contact an object to push the item. The system may also include a controller coupled with the motor to rotate the belt in defined directions or distances based on instructions.

Abstract: A system-directed robotic cart picking system is described. In an example implementation, the system may generate a picking itinerary including pick-to-cart routing based on locations of items in an order fulfillment center and received order data identifying the items, and may transport the carts in the order fulfillment center according to the pick-to-cart routing. The system may determine a zone of the order fulfillment center to which to assign a picker based on the picking itinerary and may determine tasks, such as picking at least one item from the locations to the carts, for the picker located in the zone. In some instances, the system may output pick instructions to a picker client device directing the picker to perform the tasks and may transport the carts to a defined point in the order fulfillment center in response to completion of the tasks.

Abstract: An automated sorting and packing system is described. In an example implementation, the system may include a transfer station that transfers an item into a shipping carton, one or more conveyors that convey the item and/or carton to a transfer station, a scanner that scans the item, and a processor communicatively coupled with the scanner and the one or more conveyors. According to some implementations, the system may perform operations including determining a carton identifier associated with a carton based on an order, assigning a transfer station to the order and the carton identifier based on scan data identifying an item, transporting the item to the transfer station using a conveyor, and transferring the item from the conveyor to a carton associated with the carton identifier using the transfer station.

Abstract: A system and method for providing a mobile interface for marking and organizing images is described herein. In some instances, the system may present, on a display device, an image region that displays a capturable image that is capturable by an image sensor of the wireless mobile electronic device and a preview region including a series of one or more annotatable image previews. The system may receive an input instructing the wireless mobile electronic device to capture a second image using the image sensor of the wireless mobile electronic device, generate a second image preview representing the second image, and update the graphical user interface to include the second image preview at the preview region. The system may receive an input including an annotation using an input device of the wireless mobile electronic device and update the graphical user interface to represent the annotation at the preview region.

Abstract: An automated packing system, which may include a transfer station is described. In an example implementation, system may include an item-consolidation area that receives items, a carton receiving area that receives a carton, and a structure that holds the item-consolidation area vertically higher than the carton-receiving area. The system may also include a passage between the item-consolidation area and the carton-receiving area. The passage that may allow the items to pass from the item-consolidation area and the carton in the carton-receiving area. The system may include an actuation mechanism that controls movement of the items between the item-consolidation area and the carton-receiving area.

Abstract: A hybrid modular storage fetching system is described. In an example implementation, the system may include a warehouse execution system adapted to generate a picking schedule for picking pick-to-cart and high-density storage items, and an AGV dispatching system adapted to dispatch a cart automated guided vehicle and a modular storage fetching automated guided vehicle based on the picking schedule. The cart automated guided vehicle may be adapted autonomously transport a carton through a pick-to-cart area and to a pick-cell station. The modular storage fetching automated guided vehicle may be adapted to synchronously autonomously transport a modular storage unit containing items to be placed in the cartons from a high-density storage area to the pick-cell station.

Abstract: A system and method for dynamic allocation of delivery resources is described. In an example implementation, the system may determine floating and static geographic areas based on delivery data, generate an initial mapping associating the static geographic area with addresses and/or routes, and generate one or more periodic routes based on the initial mapping. In some instances, the system may compute a route-value target for each of the periodic routes based on a load of the periodic routes and may then assign one or more floating addresses located in the one or more geographic regions to the periodic routes based on the route-value target. In some instances, the system may determine a delivery vehicle load plan based on the assignment to the routes and may automatically perform a defined operation using the delivery vehicle load plan.

Abstract: A restocking hub with interchangeable buttons mapped to item identifiers is described herein. In some instances, a local hub may receive an actuation signal from a particular interchangeable button communicatively coupled with the local hub. The actuation signal may include a button ID that identifies the particular interchangeable button and may indicating an actuation of the particular interchangeable button. The local hub may generate an order signal identifying the button ID based on the actuation signal, and may transmit the order signal instructing a remote server to perform a defined operation using the button ID. In some instances, the local hub may output a confirmation notification based on data received from the remote server based on the defined operation.

Abstract: A hybrid modular storage fetching system is described. In an example implementation, an automated guided vehicle of the hybrid modular storage fetching system includes a drive unit that provides motive force to propel the automated guided vehicle within an operating environment. The automated guided vehicle may also include a container handling mechanism including an extender and a carrying surface, the container handling mechanism having three or more degrees of freedom to move the carrying surface along three or more axes. The container handling mechanism may retrieve an item from a first target shelving unit using the carrying surface and the three or more degrees of freedom and place the item on a second target shelving unit. The automated guided vehicle may also include a power source coupled to provide power to the drive unit and the container handling mechanism.

Abstract: A hybrid modular storage fetching system with a robot execution system (REX) is described. In an example implementation, a REX may induct, into the hybrid modular storage fetching system, an order identifying items to be fulfilled by automated guided vehicles (AGVs) at an order fulfillment facility. The REX may generate at task list including tasks for a first and second AGV, instruct the first AGV to retrieve a first item in the order from a first storage area based on the task list and deliver the first item to a pick-cell station. The REX may also instruct the second AGV to retrieve a second item of the order from a second storage area and deliver the second item to the pick-cell station. The REX may communicate with other components of the hybrid modular storage fetching system to coordinate the paths of the AGVs to fulfill the order.

Abstract: A method determines a processing cluster including one or more stock keeping units (SKUs); divides the processing cluster into a first cluster and a second cluster based on SKU affinities between the one or more SKUs in the processing cluster; determines a first SKU of the first cluster to be replicated to the second cluster based on a demand correlation between the first SKU of the first cluster and a second SKU of the second cluster; replicates the first SKU of the first cluster to the second cluster; responsive to replicating the first SKU of the first cluster to the second cluster, determines whether the first cluster and the second cluster satisfy a defined constraint; and responsive to determining that the first cluster and the second cluster satisfy the defined constraint, assigns the first cluster to a first physical location and assigning the second cluster to a second physical location.

Abstract: An automated guided vehicle (AGV) is described. In an example implementation, the AGV may include an AGV body; one or more elevator mechanisms coupled to the AGV body; a support surface coupled to the AGV body and vertically movable along the AGV body by the one or more elevator mechanisms, the support surface supporting an object from underneath the object when the object is placed on the support surface; one or more arms coupled to the AGV body and vertically movable along the AGV body by the one or more elevator mechanisms, the one or more arms articulating to move the object from a first position of the object and place the object on the support surface; and an AGV controller configured to control one or more operations of the AGV.

Abstract: In an example implementation, a smart cart system may include a cart including a frame and an item holder supported by the frame and configured to transition between an open position and a storage position that is more compact than the open position. The smart cart system may include a motivator configured to provide a motive force to the cart, a power source coupled with the motivator, and a charging interface attached to the frame of the cart and that interacts with a cart charging system of a cart storage rack to charge the power source. The smart cart system may also include a user interface device, a computing device, and a smart cart controller operable on the computing device to receive information describing an attribute of an item and provide information describing the attribute of the item for presentation by the user interface device.

Abstract: In an example embodiment, a method determines a container containing one or more items associated with one or more item types, the container located at a current position in a storage facility; determines one or more order likelihoods of the one or more item types contained in the container; determines a container utilization likelihood of the container based on the one or more order likelihoods of the one or more item types contained in the container; determines an optimal position for the container in the storage facility based on the container utilization likelihood of the container, the optimal position being different from the current position of the container; and instructing an automated guided vehicle (AGV) to transport the container from the current position of the container to the optimal position of the container in the storage facility.