Apparatus for installing a solar panel array in parallel rows on panel support structure, as for solar farms, including a lift-and-place vehicle with characterizing features for moving between and along rows of support structure. Such vehicle includes a driven ground-engaging base, a lifting mast extending upwardly and in a fore/aft direction to define a panel-loading space therebeneath, a liftable trolley beam secured to the mast over the panel-loading space and extending laterally between adjacent rows, a traversing trolley movable along the beam, and a panel-placing carrier suspended from the trolley for up/down and lateral movement of carried panels. A panel-pallet vehicle is hitched to the lift-and-place vehicle, extends under the panel-loading space, and has a pallet carrier adjacent to the panel-loading space. Preferred embodiments include telescoping, tilting and angle adjustment of the mast, and the panel-placing carrier has panel supports movable between panel supporting and releasing orientations, and wireless control.

The present disclosure provides an end-to-end cargo handling system. The end-to-end cargo handling system comprises a transportation unit comprising a first sensing agent, a lift unit comprising a second sensing agent, and a control module in communication with the transportation unit and the lift unit via a network, wherein the transportation unit and the lift unit are configured to move a cargo unit from a first location to a second location autonomously.

An AMU system includes an Autonomous Mobile Unit (“AMU”), base station, lanyard, and Warehouse Management System (“WMS”) configured to communicate with one another over a network. The AMU includes a microphone configured to receive verbal commands from an individual. The individual can further provide verbal commands through the base station and the lanyard when worn by the individual. The lanyard can also provide a geo-fence around the individual where the AMU slows down to enhance safety.

Disclosed herein is an automated conveyance robot (ACR) for conveying movable platforms (MPs) in and out of trailers. A lift carriage at a first end of the ACR is configured to couple to the MP during movement and disengage after movement. A counterweight system at a second end of the ACR counterbalances the ACR during conveyance. The ACR comprises a front drive assembly and a rear drive assembly which are independently steerable to allow for different steering methods. The ACR can function fully automated or can be controlled

An automatic truck unloading apparatus and method are provided. The automatic truck unloading apparatus generates sensing information regarding the presence or absence of a pallet on the truck by implementing sensors installed in a region of a truck and a region of a storage area, and sets optimal transport paths for multiple unmanned forklift vehicles based on the sensing information, and unloads a pallet from the truck and moves and stores the pallet in the storage area by implementing an unmanned forklift vehicle.

A materials handling vehicle includes a camera, odometry module, processor, and drive mechanism. The camera captures images of an identifier for a racking system aisle and a rack leg portion in the aisle. The processor uses the identifier to generate information indicative of an initial rack leg position and rack leg spacing in the aisle, generate an initial vehicle position using the initial rack leg position, generate a vehicle odometry-based position using odometry data and the initial vehicle position, detect a subsequent rack leg using a captured image, correlate the detected subsequent rack leg with an expected vehicle position using rack leg spacing, generate an odometry error signal based on a difference between the positions, and update the vehicle odometry-based position using the odometry error signal and/or generated mast sway compensation to use for end of aisle protection and/or in/out of aisle localization.

A pallet detection assembly for a material handling vehicle is provided. The pallet detection assembly includes a body defining a cavity and having a proximity sensor housed at least partially within the cavity. The pallet detection assembly further includes an actuation plate having a tab coupled thereto and extending in a direction toward the body, and an actuator having a cylinder coupled to the body and a plunger slidably received within the cylinder and coupled to the actuation plate. The actuator is configured to movably couple the actuation plate to the body so that the actuation plate is configured to non-pivotally displace relative to the body.

A method for determining material-cage stacking, a computer device, and a storage medium are provided. The method includes the following. A material-cage image is obtained by photographing a first stacking apparatus of a first material cage and a second stacking apparatus of a second material cage. The stacking apparatuses of the two material cages in the material-cage image can be recognized respectively with two detection models. The first stacking result is obtained by obtaining location information of the stacking apparatuses of the two material cages with the first detection model, and the second stacking result is obtained with the second detection model.

A pallet position detection apparatus is provided. The detection apparatus and method checks information on a pallet disposed on a vehicle by recognizing an Radio Frequency Identification (RFID) tag or a Quick Response (QR) code attached to the truck, and recognizes an exact position of the pallet by detecting a reflector positioned on the pallet by a Lidar sensor, and unloads the pallet from the truck using an unmanned forklift vehicle based on the recognized position of the pallet.

A forklift includes a vehicle body, a loading device, a laser rangefinder, a first extractor configured to extract detection point candidates, a memory that stores at least one of dimension information, position information, and posture information of a container, a second extractor configured to extract at least two posture detection points by checking the detection point candidates against at least one of the dimension information, the position information, and the posture information, and a container posture detector configured to detect a relative angle between the forklift and the container in a vertical direction.