A baggage management system includes: a storage rack including a plurality of receptacles shaped and structured to retain one or more baggage items; a baggage transportation system including a plurality of automated guided vehicles (AGVs) configured to transport one or more baggage items between a pick up point, a drop off point, and the storage rack, each AGV including a a wireless communication unit and a controller configured to control movement of the specific AGV based on received control instructions; and a baggage administration server including a processor, a memory unit, and a wireless communication interface, and configured to receive a request to store or retrieve a baggage item from the storage rack, determine the position of the one or more AGVs, identify the one or more AGVs required to either store or retrieve a baggage item as defined in the request, and transmit control instructions to the AGVs.

A warehouse picking system and a warehouse picking method are provided. The warehouse picking system includes multiple cargo management stations and a management device. The management device receives multiple orders including at least one cargo, calculates an order score of each order by using an order score function; selects at least one order as a target order according to the order scores so as to determine a target cargo management station adapted for processing the target order; selects a cargo picking box storing at least one cargo in the target order from the cargo picking boxes of the target cargo management station to serve as candidate cargo picking boxes; and determines a target cargo picking box adapted for picking the cargo in the target order according to a workload of cargo picking equipment, a workload of cargo transportation equipment, and a disposition of each candidate cargo picking box.

In an environment in which a plurality of second pedestrians moves along predetermined movement patterns, a plurality of movement routes Rw when a first pedestrian moves toward a destination point is recognized. Data, in which an environmental image indicating a visual environment in front of a virtual robot when the virtual robot moves along each of the movement routes and a moving direction command indicating a moving direction of the virtual robot are combined, is generated as learning data. In the environmental image, colors corresponding to time-series displacement behaviors of a moving object image region is applied to at least a portion of the moving object image region indicating a pedestrian (moving object) present around a robot. Model parameters of a CNN (action model) is learned using the learning data, and a moving velocity command for a robot is determined using a learned CNN.

Dynamic allocation and coordination of auto-navigating vehicles uses robotic vehicles and centrally dispatched roaming order selectors to create a significantly more efficient, yet flexible, approach to picking goods within a warehouse. Robotic vehicles are configured to be loaded with goods from pick faces to fill orders. Each robotic vehicle follows a route that includes appropriate pick face locations. The robotic vehicles navigate from pick face to pick face where particular goods are located. Order selectors are dynamically and independently dispatched to meet the robotic vehicles at their pick face locations to load goods. Movement of the order selectors is orchestrated to increase efficiency in the order filling process within the warehouse.

A vehicle conveyance control apparatus for controlling a plurality of conveyance devices, includes a processor and a memory coupled to the processor. Each of the plurality of conveyance devices is configured to lift each tire of a vehicle to convey the vehicle from a predetermined area of a parking lot to a parking space. The processor is configured to perform: acquiring vehicle information including tire position information of each tire of the vehicle detected in the predetermined area; selecting conveyance devices to convey the vehicle from among the plurality of conveyance devices different in conveyance capacity for lifting each tire of the vehicle to convey the vehicle based on the tire position information of the vehicle acquired in the acquiring; and instructing the conveyance devices selected in the selecting to convey the vehicle from the predetermined area to the parking space.

Disclosed are systems and methods for dynamically re-routing a pick path to an alternate pick location in response to identifying a shorted product at a pick location. The dynamic decision to re-route an autonomous vehicle is based on completion scores representing a likelihood of completing order in an autonomous vehicle, a maximum remaining time, an additional pick time, and order priorities. Based on various weights for factors of the orders, a system may re-route the autonomous vehicle to fulfill a shorted order at an alternate location when no orders have a high likelihood of completion, the additional pick time associated with re-routing the autonomous vehicle to the alternate pick location is less than the maximum remaining time for each order on the autonomous vehicle, and/or none of the orders on the autonomous vehicle have a higher priority than the shorted order.

A traffic planning method for controlling a plurality of vehicles, wherein each vehicle occupies one node in a shared set of planning nodes and is movable to other nodes along predefined edges between pairs of the nodes in accordance with a finite set of motion commands. In the method, initial node occupancies of the vehicles are obtained, and a sequence of motion commands are determined by optimizing a state-action value function which depends on node occupancies s and the motion commands a to be given. The state-action value function includes a command-dependent term, which is updated in each iteration based on a reward function, and a command-independent term, which penalizes node occupancies with too small inter-vehicle gaps and is exempted from said updating.

A method includes receiving project information indicating a location of a worksite. The method also includes providing a first travel path to an electronic device associated with a mobile machine, wherein providing the first travel path to the electronic device causes at least part of the first travel path to be displayed via a display. The method further includes receiving location information indicating an initial location of the machine and one or more additional locations of the machine. Additionally, the method includes determining that the machine reached the worksite, and identifying, based at least in part on the location information, a second travel path extending from the initial location to the worksite. The method further includes determining whether the second travel path matches the first travel path, and storing at least one of the travel paths in a memory associated with a controller.

A method of using robotic units to provide security for a site, the method comprising: creating a digital twin of the site; using a pathing engine to model and determine possible robotic unit paths around the site; and using the digital twin and possible robotic unit paths to create numerous permutations of a security mission plan for the site.

A transportation system controls a fleet of autonomous vehicles to implement passenger transportation and coordinate delivery of baggage or other associated items using separate vehicles. The transportation system receives passenger data and associated item data via a user interface, and determines the number and type of autonomous vehicles to transport the passengers and items from selected pick-up locations to a destination. In various implementations, the transportation system may support different pick-up locations, pick-up times and/or delivery times for the passengers and associated items. The transportation system also may determine delayed item delivery options for different delivery times and modes of transportation. Based on the passenger and item data, along with input received via the user interface, the transportation system determines the vehicles to deploy and the delivery routes, and transmits instructions to the autonomous vehicles to provide the passenger transportation and perform the item delivery.