Delivery system

Patent metadata

Field	Value
Publication number	US-12373784-B2
Application number	US-202418604140-A
Country	US
Kind code	B2
Filing date	Mar 13, 2024
Priority date	Feb 25, 2019
Publication date	Jul 29, 2025
Grant date	Jul 29, 2025

Abstract

A delivery system generates a pick sheet containing a plurality of SKUs based upon an order. A loaded pallet is imaged to identify the SKUs on the loaded pallet, which are compared to the order prior to the loaded pallet leaving the distribution center. The loaded pallet may be imaged while being wrapped with stretch wrap. At the point of delivery, the loaded pallet may be imaged again and analyzed to compare with the pick sheet.

First claim

What is claimed is:

1. A validation system comprising:
at least one computer programmed to perform the steps of:
a) receiving at least one image of a product;
b) analyzing the at least one image to identify a package type of the product;
c) based upon the identified package type from step b) identifying a subset of possible brands of the product;
d) determining a brand of the product based upon the identified subset of brands from step c); and
e) identifying a SKU of the product based upon step d).

2. The validation system of claim 1 wherein the brand of the product indicates a specific flavor from a specific manufacturer.

3. The validation system of claim 1 wherein the at least one computer includes a machine learning model trained with images of cases of beverage containers.

4. The validation system of claim 3 wherein the machine learning model is trained to identify a plurality of available package types including reusable beverage crate, tray with translucent wrap, and fully enclosed box,
wherein the at least one computer is programmed to perform said step b) using the machine learning model.

5. The validation system of claim 4 wherein the brand of the product indicates a specific flavor from a specific manufacturer.

6. The validation system of claim 1 wherein the product is a case of beverage containers.

7. The validation system of claim 6 wherein the steps further include:
f) comparing the SKU identified in step e) to a desired SKUs on a pick sheet; and
g) indicating whether the SKU identified in step e) matches the SKU on the pick sheet based upon the comparison in step f).

8. The validation system of claim 6 further including at least one camera for generating the at least one image.

9. A validation system comprising:
a camera configured to generate at least one image of an item having an associated SKU; and
at least one computer programmed to:
a) analyze the at least one image to identify a package type of the item;
b) determine a brand of the item;
c) identify the associated SKU of item based upon steps a) and b); and
d) comparing the SKU identified in step c) to a pick sheet.

10. The validation system of claim 9 wherein the brand of the item indicates a specific flavor from a specific manufacturer.

11. The validation system of claim 9 wherein step a) is performed before step b).

12. The validation system of claim 11 wherein the at least one computer is further programmed to: e) based upon the identified package type from step a) identify a subset of possible brands of the item; and wherein step b) includes determining the brand of the item based upon the identified subset of brands from step e).

13. The validation system of claim 12 wherein the at least one computer includes at least one machine learning model trained on images of cases of beverage containers of a plurality of available package types including the package type of the item and of a plurality of available brands including the brand of the item.

14. The validation system of claim 13 wherein the at least one computer is programmed to determine the brand of the item in step b) by analyzing the at least one image.

15. The validation system of claim 14 wherein the item is a container of beverage containers.

16. The validation system of claim 15 wherein the brand of the item indicates a specific flavor from a specific manufacturer.

17. A validation system comprising:
at least one computer programmed to perform the steps of:
a) receiving a pick sheet for a plurality of SKUs, wherein each SKU has an associated package type and an associated branding;
b) receiving a plurality of images of an item, including a first image and a second image, wherein the plurality of images are taken from a plurality of sides of the item;
c) analyzing the first image to determine a first classification of the item at a first confidence level;
d) analyzing the second image to determine a second classification of the first item at a second confidence level;
e) determining the classification of the item based upon a higher of the first confidence level or the second confidence level;
f) determining the SKU associated with the item based upon the classification determined in step e); and
g) comparing the SKU determined in step f) to the plurality of SKUs on the pick sheet.

18. The validation system of claim 17 wherein the item is a container of beverage containers.

19. The validation system of claim 17 wherein the at least one computer includes at least one machine learning model trained with images of containers of beverage containers.

20. The validation system of claim 19 wherein the at least one computer is programmed to perform steps c) and d) using the at least one machine learning model.

21. The validation system of claim 20 wherein the first classification of the item indicates a first flavor from a first manufacturer.

22. The validation system of claim 21 wherein the second classification of the item indicates a second flavor from a second manufacturer.

23. The validation system of claim 22 wherein the item is a container of beverage containers.

24. The validation system of claim 20 wherein the first classification of the item indicates a first package type.

25. The validation system of claim 24 wherein the second classification of the item indicates a second package type.

26. The validation system of claim 25 wherein the item is a container of beverage containers.

27. The validation system of claim 26 wherein the first package type is selected from the group consisting of: reusable beverage crate, corrugated tray with translucent plastic wrap, fully enclosed cardboard, and paperboard box.

28. The validation system of claim 27 wherein the second package type is selected from the group consisting of: reusable beverage crate, corrugated tray with translucent plastic wrap, fully enclosed cardboard, and paperboard box.

29. The validation system of claim 28 wherein the container of beverage containers is on a pallet.

Assignees

• Rehrig Pacific Co

Inventors

• Martin Jr Robert Lee
• Mahesh Kalpana
• Herstad Rachel
• John Georgey
• Tatineni Hari Durga
• Agarwal Rahul
• Miller Jason Crawford
• Raghunathan Ravi
• Melendez Joseph
• Petrochilos Deanna
• Burden Charles

Classifications

• G06Q10/08

  Logistics, e.g. warehousing, loading or distribution; Inventory or stock management · CPC title

• G06V20/56

  exterior to a vehicle by using sensors mounted on the vehicle · CPC title

• G06V10/147 Primary

  Details of sensors, e.g. sensor lenses (fingerprint or palmprint sensors G06V40/13; vascular sensors G06V40/145; eye sensors G06V40/19) · CPC title

• G06V10/751

  Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching · CPC title

• G06K7/1447

  extracting optical codes from image or text carrying said optical code · CPC title