Distributing and rebalancing crewless vehicles (CV) by receiving a CV demand-availability gap, identifying candidate CV to relocate to close the CV demand-availability gap, identifying a candidate transport to relocate the CV to close the CV demand-availability gap, generating a candidate CV relocation plan, optimizing an overall CV relocation plan, and executing the overall CV relocation plan.

A method includes receiving, by machine-learning logic, observations indicative of a states associated with a first and second group of vehicles arranged within an engagement zone during a first interval of an engagement between the first and the second group of vehicles. The machine-learning logic determines actions based on the observations that, when taken simultaneously by the first group of vehicles during the first interval, are predicted by the machine-learning logic to result in removal of one or more vehicles of the second group of vehicles from the engagement zone during the engagement. The machine-learning logic is trained using a reinforcement learning technique and on simulated engagements between the first and second group of vehicles to determine sequences of actions that are predicted to result in one or more vehicles of the second group being removed from the engagement zone. The machine-learning logic communicates the plurality of actions to the first group of vehicles.

Systems, apparatus and methods may be configured to implement actively-controlled light emission from a robotic vehicle. A light emitter(s) of the robotic vehicle may be configurable to indicate a direction of travel of the robotic vehicle and/or display information (e.g., a greeting, a notice, a message, a graphic, passenger/customer/client content, vehicle livery, customized livery) using one or more colors of emitted light (e.g., orange for a first direction and purple for a second direction), one or more sequences of emitted light (e.g., a moving image/graphic), or positions of light emitter(s) on the robotic vehicle (e.g., symmetrically positioned light emitters). The robotic vehicle may not have a front or a back (e.g., a trunk/a hood) and may be configured to travel bi-directionally, in a first direction or a second direction (e.g., opposite the first direction), with the direction of travel being indicated by one or more of the light emitters.

An inventory management system includes pick stations, automated vehicles having an onboard power source, a first drive system configured to horizontally displace the vehicle, a second drive system configured to vertically displace the vehicle along a guide system, and a platform for supporting an item during displacement of the vehicle. A first plurality of storage locations store inventory items at a first zone of vehicle operation and a second plurality of storage areas store inventory items at a second zone of vehicle operation. A first pick station is closer to the first storage locations than to the second storage locations, Vehicles are configured to transfer a selected item from one of the second plurality of storage locations to the first pick station or to transfer the selected item from the second plurality of storage locations to the first plurality of storage locations.

Disclosed is a processing device that is mounted in a vehicle and is able to perform communication with a center server during a normal time. The processing device includes a controller configured to execute searching for one or a plurality of other vehicles with which a host vehicle is able to perform communication, in emergency where a situation of emergency occurs and communication with the center server is disrupted, inquiring the other vehicles searched by the search about whether or not to enable intervention control related to the situation, and deciding a center vehicle giving an instruction related to the intervention control from among the other vehicles replying to enable the intervention control and the host vehicle.

Systems and methods for a stand-alone self-driving material-transport vehicle are provided. A method includes: displaying a graphical map on a graphical user-interface device based on a map stored in a storage medium of the vehicle, receiving a navigation instruction based on the graphical map, and navigating the vehicle based on the navigation instruction. As the vehicle navigates, it senses features of an industrial facility using its sensor system, and locates the features relative to the map. Subsequently, the vehicle stores the updated map including the feature on the vehicle's storage medium. The map can then be shared with other vehicles or a fleet-management system.

A remote assistance management system is in communication with autonomous traveling vehicles for letting an operator provide remote assistance in response to an assistance request from a vehicle. The system predicts an occurrence of an assistance request in future based on operation states of the vehicles, and categorize a cause of an assistance request predicted to occur into a first category cause that lasts for a long time and a second category cause that lasts only for a short time. The system receives an assistance request from the vehicles. In response to acquiring a first assistance request of which the cause is the first category cause from a first vehicle, the system transmits a first command signal for the first vehicle that is decided by an operator to the first vehicle, and applies the first command signal to another vehicle from which the first assistance request is predicted to occur.

A remote assistance management system is in communication with a plurality of autonomous traveling vehicles for letting an operator provide remote assistance in response to an assistance request from a vehicle. The system predicts, for each vehicle, an occurrence of an assistance request in future based on an operation state of each vehicle and calculates a predicted assistance period for each assistance request predicted to occur. When more than a predetermined number of overlapping assistance requests of which predicted assistance periods overlap at the same time are predicted to occur, the system instructs to excess vehicles a change of a traveling mode from a first traveling mode being a normal traveling mode to a second traveling mode for avoiding or delaying the occurrence of an assistance request, the excess vehicles being vehicles in excess of the predetermined number among vehicles from which the overlapping assistance requests are predicted to occur.

A method for controlling a robot is provided. The method includes the steps of: acquiring information on a sound associated with a robot call in a serving place; determining a call target robot associated with the sound, among a plurality of robots in the serving place, on the basis of the acquired information; and providing feedback associated with the sound by the call target robot.

An automated storage and retrieval system includes: a storage grid having storage columns arranged in rows, in which storage containers are stacked one on top of another; a rail system having a first set of parallel rails arranged in a horizontal plane and extending in a first direction, and a second set of parallel rails arranged in the horizontal plane and extending in a second direction orthogonal to the first direction, which first and second sets of rails form a grid pattern in the horizontal plane having a plurality of adjacent grid cells; at least one container handling vehicle configured to move on the rail system, including a wheel arrangement configured to guide the at least one storage container vehicle along the rail system in at least one of the first direction and the second direction; and a service vehicle for movement on the rail system.