US 12,250,894 B2
Machine learning optimization through randomized autonomous crop planting
Michael D. Stellpflug, Cary, NC (US); and Angela L. Bowman, Waukee, IA (US)
Assigned to DEERE & COMPANY, Moline, IL (US)
Filed by Deere & Company, Moline, IL (US)
Filed on Aug. 21, 2021, as Appl. No. 17/408,398.
Prior Publication US 2023/0054908 A1, Feb. 23, 2023
Int. Cl. A01B 69/04 (2006.01); A01C 7/06 (2006.01); A01C 21/00 (2006.01); A01G 25/09 (2006.01); A01G 25/16 (2006.01); A01M 7/00 (2006.01)
CPC A01B 69/008 (2013.01) [A01C 7/06 (2013.01); A01C 21/005 (2013.01); A01C 21/007 (2013.01); A01G 25/09 (2013.01); A01G 25/16 (2013.01); A01M 7/0089 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A method for cultivating a field, comprising:
planting each of a plurality of portions of the field, each portion of the field planted using one or more agricultural vehicles configured to randomly vary each of a plurality of planting parameters before or during planting the portion of the field, the planting parameters including at least a planting depth, a planting spacing, a type of treatment applied when planting, and an amount of treatment applied when planting;
determining, for each portion of the field, a resulting crop outcome across the portion of the field;
generating a training set of data comprising the varied planting parameters and the determined crop outcome for each of the portions of the field;
training a machine-learned model using the generated training set of data, the machine-learned model configured to predict a crop outcome for a portion of the field based on a set of planting parameters used to plant the portion of the field;
for a subsequent iteration, for a target portion of the field, applying the machine-learned model to identify a set of planting parameters for planting the target portion of the field to optimize a desired crop outcome;
identifying, for each of a plurality of sub-portions of the target portion, a set of randomly varied planting parameters based on the identified set of planting parameters for planting the target portion of the field; and
planting, in the subsequent iteration and for each of the plurality of sub-portions of the target portion, the sub-portion with the corresponding set of randomly varied planting parameters.