US 12,240,644 B2
Bud sorting and packaging apparatus, systems and methods
Michael Marseglia, Webster, NY (US); Steven T. Gizzi, Webster, NY (US); Scott Baube, Webster, NY (US); and Jeffrey S. Clough, Webster, NY (US)
Assigned to InTunes Products, LLC, Webster, NY (US)
Filed by InTunes Products, LLC, Webster, NY (US)
Filed on Oct. 27, 2022, as Appl. No. 17/975,182.
Claims priority of provisional application 63/355,395, filed on Jun. 24, 2022.
Prior Publication US 2023/0415943 A1, Dec. 28, 2023
Int. Cl. B25J 9/16 (2006.01); B07C 5/28 (2006.01); B25J 9/00 (2006.01); B25J 13/08 (2006.01); B65B 5/06 (2006.01); B65B 5/08 (2006.01); B65B 35/16 (2006.01); B65B 57/14 (2006.01); B65B 57/18 (2006.01); G06V 10/764 (2022.01); G06V 10/778 (2022.01); G06V 10/88 (2022.01)
CPC B65B 57/14 (2013.01) [B07C 5/28 (2013.01); B25J 9/0093 (2013.01); B25J 9/1687 (2013.01); B25J 9/1697 (2013.01); B25J 13/08 (2013.01); B65B 5/06 (2013.01); B65B 5/08 (2013.01); B65B 35/16 (2013.01); B65B 57/18 (2013.01); G06V 10/764 (2022.01); G06V 10/778 (2022.01); G06V 10/88 (2022.01)] 23 Claims
OG exemplary drawing
 
1. A system for packaging cannabis buds into individual containers each having a predetermined loaded target weight, comprising:
a) a bud pick and place robot having an arm with a free end including a plurality of individual bud pickers;
b) a bud picking tray adapted to receive and present for picking by said plurality of individual bud pick and place elements a plurality of cannabis buds; and
c) a computer vision system electronically connected to said bud picker robot, said computer vision system including a processor in communication with a non-transitory memory storing computer readable instructions executable by the processor for performing a method, the method comprising the steps of:
i) acquiring a digital image of a plurality of product items having a product type;
ii) identifying each of the plurality of product items in the digital image, resulting in one or more identified product items;
iii) determining a pixel-based area for each of the one or more identified product items;
iv) predicting a weight of each of the one or more identified product items based on a size thereof, the determined pixel-based area and a predetermined density based on the product type, the step of predicting resulting in a plurality of predicted weights;
v) grouping, based on the plurality of predicted weights, the one or more identified product items into a plurality of groups, each group satisfying the predetermined loaded target weight; and
vi) automatedly picking and placing each of the plurality of groups into a product item container.