An autonomous advertising cart with display panels and speakers integrated into its navigation, movement and location tracking system. The cart displays advertising containing text, picture and video images, and speakers play sounds, music or other recordings. The cart selectively provides advertising communications depending on the items on the cart, where the cart is in the building, the time of day, the presence of people, etc., as the autonomous cart travels through its work environment. The advertisements are stored on-board the cart or received real-time via wireless communication. The cart preferably has microphones and customer observation cameras to collect real-time information about the working environment and customers to enhance the advertising experience and provide feedback about the advertising experience.

The present technology relates to an information processing system, an information processing method, and an information processing apparatus that are capable of assigning an appropriate operator to a vehicle on the basis of both the state of the vehicle to be remotely monitored and the state of the operator.

A vehicle state determination unit determines states of a plurality of vehicles to be remotely monitored. A monitoring state determination unit determines states of a plurality of operators regarding remote monitoring. An assignment unit assigns, on the basis of the states of the plurality of vehicles that are determined by the vehicle state determination unit and the states of the plurality of operators regarding remote monitoring that are determined by the monitoring state determination unit, one or more of the operators to each of the plurality of vehicles to remotely monitor the vehicle. The present technology is applicable to a management system, for example.

In some embodiments, a method of managing deliveries of orders by a fleet of unmanned aerial vehicles (UAVs) from retail fulfillment locations to delivery locations is provided. A fleet management computing system receives a request for delivery of an order from a retailer ordering computing system. The fleet management computing system transmits one or more package identifiers to be associated with one or more packages for the order. The fleet management computing system receives a notification that a package of the one or more packages for the order is ready for pickup at a retail fulfillment location. The fleet management computing system determines a navigation route for a UAV to the delivery location via the retail fulfillment location. The fleet management computing system transmits the navigation route to the UAV for autonomous navigation of the navigation route to the delivery location via the retail fulfillment location to deliver the package.

A method of operating a server is disclosed. The operation method of the disclosure, includes: identifying, by an product management module, a plurality of orders including a quantity of delivery item and a storage location of the delivery item; identifying, by a destination management module, a plurality of picking zones for loading each delivery item based on the storage location of the delivery item included in each of the plurality of orders; and selecting, by a task allocation module, at least one picking zone among the plurality of picking zones based on at least one of the quantity of delivery item matched to each of the plurality of picking zones, the number of picking stations included in each of the plurality of picking zones, and the location of the picking stations included in each of the plurality of picking zones.

Disclosed is a system for managing loads in a storage facility. The system comprises: a racking structure configured to store loads; mobile robot assembly(ies) (MRA(s)) operable to traverse within a storage facility, wherein MRA(s) comprises a mobile robot and a docking arrangement; and pick and drop robots (PDRs) operable to traverse along a height of storage facility for picking and dropping loads from racking structure, wherein PDRs comprise a latch arrangement and climb arrangement. Herein, MRA is operable to carry a PDR from amongst PDRs, PDR being operatively mounted on docking arrangement of MRA, wherein when MRA is at a first predefined distance from racking structure, PDR engages itself to racking structure via latch arrangement, and climb arrangement is configured to extend or retract vertically along a length of racking structure, for picking and dropping loads from racking structure upon engagement with racking structure.

A computing system may be configured as a fleet controller for autonomous mobile robots operating within a physical environment. The system may include a communication interface receiving sensor data from the robots including image data captured by visible light cameras located on the robots, an environment mapper determining a global scene graph representing the environment and identifying navigable regions of the environment, a workflow coordinator determining a workflow including tasks to be performed within the environment by one or more of the robots in cooperation with a human, and a route planner configured to determine routing information for the one or robots including a nominal route from a source location to a destination location. The robots may be configured to autonomously navigate the environment to execute the tasks based on the routing information.

An autonomous robot drive assembly includes a plurality of drive units. The plurality of drive units may allow for movement and control of the autonomous robot drive. Each of the plurality of drive units are configured to be oriented independent of the other drive units. Each drive unit may include a plurality of independently operable driven wheels. Each drive unit may further include a drive unit coupling, allowing for the drive unit to rotate independently of other portions of the autonomous robot. The drive unit coupling may not be driven and may be configured to freely rotate.

Disclosed are various embodiments for optimizing robot utilization in autonomous mobile robots by accounting for the battery charge state when assigning missions to be performed by the autonomous mobile robots in a material handling facility. In particular, mission data associated with one or more missions and robot data including a battery charge state associated with one or more robots can be analyzed to determine a robot mission assignment that accounts for battery state charge in order to maximize robot utilization and productivity of material handling tasks.

Aspects of the subject disclosure may include, for example, a drone orchestrator device, including: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of receiving instructions from a workflow manager to perform a job involving a payload; and sending a series of commands to a plurality of drones to orchestrate performance of the job autonomously. Other embodiments are disclosed.

A technique of camera exposure control for vision-based navigation of an unmanned aerial vehicle (UAV) includes acquiring an aerial image of a ground area below the UAV with an onboard camera system of the UAV, estimating a visual motion factor based on a speed of the UAV and an altitude of the UAV, and adjusting an exposure control setting of the onboard camera system based on the visual motion factor.