Abstract: A pallet loading and validation system provides several features that are particularly beneficial in the context of a conveyor product distribution system, such as a pallet loading system, although some features are not exclusive to a conveyor system. In some aspects, the techniques described herein relate to a method for identifying a SKU of a package using a computer system having at least one processor, the method including: (a) taking at least one image of a package on a conveyor; (b) receiving the at least one image in the computer system; and (c) based upon the at least one image, the computer system determining a SKU associated with the package.

Abstract: A computer system for validating trays loaded with products receives at least one image of products in at least one tray of a plurality of trays in an imaging area. A type of the products in the at least one tray is determined based upon the at least one image. The type of products in the at least one tray is compared to at least one order. A confirmation or error is indicated based upon the comparison. In some examples, the products are bakery products of different types loaded in plastic, stackable bakery trays. In one example method, a plurality of stacks of loaded bakery trays are imaged from a front or rear of the trays. In another example method, the plurality of stacks are imaged from overhead as the trays are loaded onto the stacks.

Abstract: An imaging system and method uses grouping and elimination to label images of unknown items. The items may be stacked together with known or unknown items. The items may be packages, such as packages of beverage containers. A machine learning model may be used to infer skus of the packages. The machine learning model is trained on known skus but is not trained on unknown skus. Multiple images of the same unknown sku are grouped using the machine learning model. Elimination based upon lists of expected skus is used to label each group of unknown skus.

Abstract: A delivery system may include a pallet wrapper system having a turntable, a camera directed toward an area above the turntable, and a stretch wrap dispenser adjacent the turntable. A computer receives images from the camera of multiple sides of a pallet loaded with packages on the turntable. The computer stitches images from different sides of the stack of packages that correspond to the same package. At least one machine learning model may be used to infer SKUs of each package. Optical character recognition may be performed in parallel on the images. The determination of the SKU of each package may be based upon the inferred SKUs and on the OCR.

Abstract: A pallet wrapper and imaging system a pallet loaded with containers to calculate a sustainability based upon a type of the pallet and the containers on the pallet. The system also determines the stability of the pallet and containers, a speed at which the pallet and containers can be wrapped, and an amount of stretch film needed to secure the load for transport. After validation by the imaging system (with or without a wrapper), a QC bot assists a QC worker in remedying or checking any detected errors or potential errors.

Abstract: A delivery system may include a pallet wrapper system having a turntable, a camera directed toward an area above the turntable, and a stretch wrap dispenser adjacent the turntable. A computer receives images from the camera of multiple sides of a pallet loaded with packages on the turntable. The computer stitches images from different sides of the stack of packages that correspond to the same package. At least one machine learning model may be used to infer SKUs of each package. Optical character recognition may be performed in parallel on the images. The determination of the SKU of each package may be based upon the inferred SKUs and on the OCR.

Abstract: A pallet wrapper and imaging system a pallet loaded with containers to calculate a sustainability based upon a type of the pallet and the containers on the pallet. The system also determines the stability of the pallet and containers, a speed at which the pallet and containers can be wrapped, and an amount of stretch film needed to secure the load for transport. After validation by the imaging system (with or without a wrapper), a QC bot assists a QC worker in remedying or checking any detected errors or potential errors.

Abstract: An imaging system and method uses grouping and elimination to label images of unknown items. The items may be stacked together with known or unknown items. The items may be packages, such as packages of beverage containers. A machine learning model may be used to infer skus of the packages. The machine learning model is trained on known skus but is not trained on unknown skus. Multiple images of the same unknown sku are grouped using the machine learning model. Elimination based upon lists of expected skus is used to label each group of unknown skus.

Abstract: An imaging system and method uses grouping and elimination to label images of unknown items. The items may be stacked together with known or unknown items. The items may be packages, such as packages of beverage containers. A machine learning model may be used to infer skus of the packages. The machine learning model is trained on known skus but is not trained on unknown skus. Multiple images of the same unknown sku are grouped using the machine learning model. Elimination based upon lists of expected skus is used to label each group of unknown skus.

Abstract: A delivery system may include a pallet wrapper system having a turntable, a camera directed toward an area above the turntable, and a stretch wrap dispenser adjacent the turntable. A computer receives images from the camera of multiple sides of a pallet loaded with packages on the turntable. The computer stitches images from different sides of the stack of packages that correspond to the same package. At least one machine learning model may be used to infer SKUs of each package. Optical character recognition may be performed in parallel on the images. The determination of the SKU of each package may be based upon the inferred SKUs and on the OCR.

Abstract: A pallet wrapper and imaging system a pallet loaded with containers to calculate a sustainability based upon a type of the pallet and the containers on the pallet. The system also determines the stability of the pallet and containers, a speed at which the pallet and containers can be wrapped, and an amount of stretch film needed to secure the load for transport. After validation by the imaging system (with or without a wrapper), a QC bot assists a QC worker in remedying or checking any detected errors or potential errors.

Abstract: A delivery system may include a pallet wrapper system having a turntable, a camera directed toward an area above the turntable, and a stretch wrap dispenser adjacent the turntable. A computer receives images from the camera of multiple sides of a pallet loaded with packages on the turntable. The computer stitches images from different sides of the stack of packages that correspond to the same package. At least one machine learning model may be used to infer SKUs of each package. Optical character recognition may be performed in parallel on the images. The determination of the SKU of each package may be based upon the inferred SKUs and on the OCR.

Abstract: A pallet sled includes a pair of tines extending forward from a base. A camera is mounted on the pallet sled and is configured to record images, such as video, as the pallet sled brings pallets of items from a truck into a store. At least one processor is used to analyze the images from the pallet sled. The images are used to determine inventory levels in the store, conditions of the store, conditions of the pathways of the pallet sled. An accelerometer on the pallet sled detects hard braking and accidents.

Abstract: Several embodiments of turntable systems for loaded pallets are disclosed. In some embodiments, a first ramp leads up to the turntable and a second ramp leads down from the turntable on the opposite side. In other embodiments, at least two turntables are positioned adjacent one another, optionally with a bridge surface connecting them so that a pallet lift can be driven from one turntable to the other to place one pallet on one turntable and another pallet on the other turntable according to a method disclosed herein. A validation system without a turntable includes a plurality of cameras about a periphery of a platform weight sensor.

Abstract: A pick assist system may include a pallet destacker storing a front column of pallets and a back column of pallets. At least one rfid reader is configured to read an rfid tag on a pallet in or below at least one of the front column of pallets or the back column of pallets. The pick assist system may include a pallet sled including a display indicating a product to be retrieved. The pallet sled may determine that the product has been placed in a center of a pallet on the pallet sled. A method for verifying a pallet may include identifying skus on exterior products in a layer in a stack of products. Based upon that determination, the skus of the interior products may also be determined. For example, it may be determined that the interior products were part of a layer pick.

Abstract: A delivery system may include a pallet wrapper system having a turntable, a camera directed toward an area above the turntable, and a stretch wrap dispenser adjacent the turntable. A computer receives images from the camera of multiple sides of a pallet loaded with packages on the turntable. The computer stitches images from different sides of the stack of packages that correspond to the same package. At least one machine learning model may be used to infer SKUs of each package. Optical character recognition may be performed in parallel on the images. The determination of the SKU of each package may be based upon the inferred SKUs and on the OCR.

Abstract: Several embodiments of turntable systems for loaded pallets are disclosed. In some embodiments, a first ramp leads up to the turntable and a second ramp leads down from the turntable on the opposite side. In other embodiments, at least two turntables are positioned adjacent one another, optionally with a bridge surface connecting them so that a pallet lift can be driven from one turntable to the other to place one pallet on one turntable and another pallet on the other turntable according to a method disclosed herein. A validation system without a turntable includes a plurality of cameras about a periphery of a platform weight sensor.

Abstract: An imaging system and method uses grouping and elimination to label images of unknown items. The items may be stacked together with known or unknown items. The items may be packages, such as packages of beverage containers. A machine learning model may be used to infer skus of the packages. The machine learning model is trained on known skus but is not trained on unknown skus. Multiple images of the same unknown sku are grouped using the machine learning model. Elimination based upon lists of expected skus is used to label each group of unknown skus.

Abstract: A semantic similarity fingerprint is generated for an image by inferring a plurality of SKUs each at an associated first weight based upon analysis of the image using the machine learning models. The associated first weights for each of the classifications based upon each machine learning model is the semantic similarity fingerprint. The semantic similarity fingerprint may be compared to previously generated semantic similarity fingerprints. If a match is found with a semantic similarity fingerprint that has previously been identified as a particular.

Abstract: A pallet wrapper and imaging system a pallet loaded with containers to calculate a sustainability based upon a type of the pallet and the containers on the pallet. The system also determines the stability of the pallet and containers, a speed at which the pallet and containers can be wrapped, and an amount of stretch film needed to secure the load for transport. After validation by the imaging system (with or without a wrapper), a QC bot assists a QC worker in remedying or checking any detected errors or potential errors.