A control device controlling the movement route of a transportation vehicle calculates a movement route to a target position of the transportation vehicle and, in a case where an obstacle exists on the calculated movement route, counts the number of detours indicating the magnitude of an influence of the obstacle on movement route calculation, and calculates the movement route again so as to avoid the obstacle.

An autonomous moving apparatus control system including a range sensor, a reflection plate, and a control unit. The range sensor is installed in a cage of an elevator and detects a distance to an object by receiving reflected light of signal light applied to the object. The reflection plate is disposed in an elevator hall of a floor on which the elevator stops, and reflects the signal light. The control unit determines whether or not a mobile robot, which is an autonomous moving apparatus, can get on and off the elevator based on a detected distance, the detected distance being a distance to the reflection plate detected by the range sensor.

To load and unload a trailer, an autonomous mobile robot determines its location and the location of objects within the trailer relative to the trailer itself, rather than relative to a warehouse. The autonomous mobile robot determines its location the location of objects within the trailer relative to the trailer. The autonomous mobile robot navigates within the trailer and manipulates objects within the trailer from the trailer's reference frame. Additionally, the autonomous mobile robot uses a centerline heuristic to compute a path for itself within the trailer. A centerline heuristic evaluates nodes within the trailer based on how far away those nodes are from the centerline. If the nodes are further away from the centerline, they are assigned a higher cost. Thus, when the autonomous mobile robot computes a path, the path is more likely to stay near the centerline of the trailer rather than get closer to the sides.

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.

Provided is an automated guided vehicle that travels on a traveling path by loading at least one of a member required for a production work in which production equipment produces a product and a production tool detachable to the production equipment, and shares at least a portion of the traveling path with another automated guided vehicle, in which a traveling priority is variably set based on a work priority determined from a status of the production work, and when the traveling priority of the automated guided vehicle is higher than the traveling priority of the another automated guided vehicle, the automated guided vehicle is prioritized for traveling on the traveling path.

An automated storage and retrieval system includes a grid-based rail structure and a plurality of remotely operated vehicles arranged to operate on the grid-based rail structure. The automated storage and retrieval system includes a locking device arranged in a zone of the grid-based rail structure where a human and/or a robotic operator is permitted to interact with the remotely operated vehicle or contents of a storage container that the remotely operated vehicle is carrying. The locking device is arranged to lock the remotely operated vehicle against accidental displacement prior to interaction with the human and/or robotic operator, and wherein the locking device being arranged to unlock the remotely operated vehicle once interaction with the human and/or robotic operator is no longer required.

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.

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.