Abstract: Provided are various systems and processes for improving last-mile delivery of real-time, on-demand orders for perishable goods. In one aspect, an automated vehicle (AV) comprises a body including a storage compartment for storing perishable goods. The storage compartment is accessible by a user upon authentication of the user. The AV further comprises a sensor module for receiving data for navigating the AV. The sensor module is positioned above the body on a support structure at a predetermined height above the ground, such as three to five feet. The data includes one or more of the following: audio data, video data, radio waves, and backscattered light waves. The AV further comprises an onboard computer system configured to process the data to navigate the AV along motor vehicle routes and pedestrian routes. The AV may be configured to interface with an automated locker system to retrieve or deposit the perishable goods.

Abstract: A central server computer can process the data in real time by using an event-based data (i.e., event data) platform. Event-based data can be actions performed by entities providing the data to the central server computer. Storing the event-based data can allow the central server computer to store a transaction data in a granular manner according to different events, which can help with verification and traceability.

Abstract: A method includes a computer receiving a fulfillment request associated with one or more items. Responsive to receiving the fulfillment request, the computer determines estimated weight data based on the one or more items in the fulfillment request. The computer obtains actual weight data associated with the fulfillment request for one or more items. The computer verifies that the actual weight data corresponds to the estimated weight data. The computer performs additional processing based on verifying.

Abstract: The present disclosure generally pertains to systems and methods of order fulfillment using a fulfillment engine, which optimizes the allocation of client or user orders to third party merchants for fulfillment through the use of linear programming or machine learning. This optimization occurs by loading a series of relevant merchant attributes and client attributes into an optimizer with the order and analyzing the attributes to determine an optimal allocation of client orders to third party merchants. These orders are issued to the merchants and where necessary the system arranges delivery of the orders to the client. The system may also automatically update future orders in response to client feedback.

Abstract: Systems, methods, and computer-readable media for providing a signaling location beacon are provided. Specifically, a collection location for collecting, by an agent, an item is determined. Also, a physical beacon associated with the pickup location can be identified. Further, an interaction between the physical beacon and the agent can be detected. For example, the interaction can occur based on the physical beacon and the agent being in physical proximity to each other during a process of the agent collecting the item at the collection location. As follows, in response to the interaction, transmission of a sensory signal to the agent can be facilitated to provide perceivable direction information associated with the physical location to the agent. The sensory signal can be specific to the agent based on the interaction between the physical beacon and the agent.

Abstract: This disclosure relates to verifying possession of a card via a tap gesture of the card in relation to a mobile device supporting Near-Field Communication (NFC) functionality.

Abstract: Provided are various systems and processes for improving last-mile delivery of real-time, on-demand orders for perishable goods. In one aspect, a method for operating an autonomous vehicle comprises receiving real-time perception data at a planner module located on the autonomous vehicle, and generating an initial motion plan based on the real-time perception data. The autonomous vehicle is maneuvered along a constrained route based on the initial motion plan without user input. An alert condition is detected from the real-time perception data, and a notification is displayed at an operator device. The notification includes a request for user input to adjust the initial motion plan. User input is received at the planner module and a modified motion plan is generated by adjusting the initial motion plan based on the user input. A virtual representation of objects identified by the AV is locally rendered for display at the operator device.

Abstract: Provided are various systems and processes for improving last-mile delivery of real-time, on-demand orders for perishable goods. In one aspect, an automated vehicle (AV) comprises a body including a storage compartment for storing perishable goods. The storage compartment is accessible by a user upon authentication of the user. The AV further comprises a sensor module for receiving data for navigating the AV. The sensor module is positioned above the body on a support structure at a predetermined height above the ground, such as three to five feet. The data includes one or more of the following: audio data, video data, radio waves, and backscattered light waves. The AV further comprises an onboard computer system configured to process the data to navigate the AV along motor vehicle routes and pedestrian routes. The AV may be configured to interface with an automated locker system to retrieve or deposit the perishable goods.

Abstract: Described herein are various systems and processes for vehicles for delivery of real-time, on-demand orders for perishable goods, and operations thereof. The automated delivery vehicle may include a food transport container and various sensors configured to determine the location and/or surroundings of the vehicle. The automated delivery vehicle may further include a display and/or other output source configured to provide outputs to persons surrounding the automated delivery vehicle. Such outputs may include, for example, an information graphical representation (e.g., provided on a display), an audio output, and/or data communicated to a wireless device.

Abstract: Provided are various systems and processes for improving last-mile delivery of real-time, on-demand orders for perishable goods. In one aspect, a method for operating an autonomous vehicle comprises receiving real-time perception data at a planner module located on the autonomous vehicle, and generating an initial motion plan based on the real-time perception data. The autonomous vehicle is maneuvered along a constrained route based on the initial motion plan without user input. An alert condition is detected from the real-time perception data, and a notification is displayed at an operator device. The notification includes a request for user input to adjust the initial motion plan. User input is received at the planner module and a modified motion plan is generated by adjusting the initial motion plan based on the user input. A virtual representation of objects identified by the AV is locally rendered for display at the operator device.

Abstract: Techniques for optimizing a food service configured to receive food orders from multiple customers, and consolidate orders based on respective days, times, and locations associated therewith. The food orders may include deliveries, customer pick-ups, and dine-in options for eating at a restaurant. The optimized food service may be configured to assign a restaurant to the consolidated orders and send a preparation instruction to the restaurant to prepare the consolidated orders for a designated pick-up or dining time. The optimized food service may additionally instruct an order supervisor to travel to the restaurant to assist in preparation of the consolidated orders. The order supervisor may additionally serve a food order, such as for a dine-in option or full service, catered delivery. For delivery orders, the optimized food service may assign a courier and, in some examples, a delivery assistant, to deliver the orders to respective customers.

Abstract: In some examples, a computer may receive, from a buyer application on a buyer device, an indication that the buyer has accessed information related to a first merchant of a plurality of merchants. The computer may send a communication to a merchant application on a merchant computing device of the first merchant to determine a current backlog of orders for the first merchant. Based at least partially on receiving an indication that the current backlog exceeds a threshold, the computer may send, to the buyer application, item information that causes the buyer application to present, in a user interface, information indicating availability of a meal kit for a menu item offered by the first merchant. The computer may receive a selection via the user interface indicating an order for the meal kit and may send a communication to the merchant application to indicate the order for the meal kit.

Abstract: A system includes a carousel apparatus, a support structure configured to hold a receptacle, and a linear actuator apparatus configured to move the support structure. The carousel apparatus includes: a holder in which a first plurality of openings and a second plurality of openings are formed, and a first motor coupled to the holder and adapted to rotate the holder around an axis. A linear actuator apparatus includes: a linear guide which extends underneath the holder and is coupled to the support structure, and a second motor coupled to the linear guide and adapted to move the support structure along the linear guide underneath the holder.

Abstract: Described herein are various systems and processes for vehicles for delivery of real-time, on-demand orders for perishable goods, and operations thereof. The automated delivery vehicle may include a food transport container and various sensors configured to determine the location and/or surroundings of the vehicle. The automated delivery vehicle may further include a display and/or other output source configured to provide outputs to persons surrounding the automated delivery vehicle. Such outputs may include, for example, an information graphical representation (e.g., provided on a display), an audio output, and/or data communicated to a wireless device.

Abstract: In some examples, a system receives, from a courier device, an indicated geographic location of the courier device determined at least in part from a satellite positioning system receiver associated with the courier device. The system may determine an amount of an item possessed by the courier and may further determine a plurality of past delivery locations within a threshold courier travel time of the indicated geographic location of the courier device. In addition, the system may determine a plurality of buyer devices associated with the plurality of past delivery locations, and may send, to the plurality of buyer devices, respective electronic communications indicting that the item is available for delivery from the courier located within the threshold courier travel time of a respective buyer location.

Abstract: Methods and systems for time series forecasting using ensemble machine learning are disclosed. A computer system (distributed or otherwise) can instantiate, train, and use a plurality of machine learning models to generate time series forecasts. These can include both different types of machine learning models, as well as similar machine learning models that have different configurations. Embodiments of the present disclosure can use a novel modification of k-folds cross validation techniques that preserves the order of temporal data. Time series data can be partitioned into segments and folds and used to train and test the plurality of machine learning models. Forecasts produced by the trained machine learning models, along with historical time series data (or “actuals”) can be used to train an ensemble machine learning model to produce an ensemble forecast based on forecasts generated by the trained machine learning models.

Abstract: Techniques for optimizing a food service configured to receive food orders from multiple customers, and consolidate orders based on respective days, times, and locations associated therewith. The food orders may include deliveries, customer pick-ups, and dine-in options for eating at a restaurant. The optimized food service may be configured to assign a restaurant to the consolidated orders and send a preparation instruction to the restaurant to prepare the consolidated orders for a designated pick-up or dining time. The optimized food service may additionally instruct an order supervisor to travel to the restaurant to assist in preparation of the consolidated orders. The order supervisor may additionally serve a food order, such as for a dine-in option or full service, catered delivery. For delivery orders, the optimized food service may assign a courier and, in some examples, a delivery assistant, to deliver the orders to respective customers.

Abstract: An automated food making apparatus is described. An automated food making apparatus can include: a carousel; a dispensing apparatus shared among a plurality of canisters on the carousel, wherein at least one canister includes a paddle; and wherein the dispensing apparatus is configured to rotate the canister's paddle to dispense ingredients stored in the canister. A dispensing mechanism for an automated food making apparatus can include: an actuator arm; a motor that is adapted to rotate the actuator arm; one or more magnets embedded in the actuator arm; and one or more sensors configured to detect position of the actuator arm; wherein the actuator arm dispenses ingredients by rotating a pin located on a canister.

Abstract: A system includes a carousel apparatus including: first openings concentrically arranged around axis to hold first containers adapted to hold first food ingredients, second openings concentrically arranged inside the first openings to hold second containers adapted to hold second food ingredients, a holder in which the first openings and the second openings are formed, and which is adapted to support the first containers and the second containers, and a first motor coupled to the holder and adapted to rotate the holder around the axis; support structure configured to hold a receptacle; and a linear actuator apparatus configured to move the support structure and including: a linear guide which extends underneath the holder and is coupled to the support structure, and a second motor coupled to the linear guide and adapted to move the support structure along the linear guide underneath the first openings and the second openings.

Abstract: A method is disclosed. The method includes receiving, by a server computer comprising a machine learning model, a fulfillment request including an address from an end user device operated by an end user. The method also includes determining an address type associated with the address, and performing, by the server computer, further processing based upon the address type.