US 11,653,588 B2
Yield map generation and control system
Nathan R. Vandike, Geneseo, IL (US); Bhanu Kiran Reddy Palla, Bettendorf, IA (US); Matthew T. Wold, Bettendorf, IA (US); Cody W. Best, Silvis, IL (US); and Noel W Anderson, Fargo, ND (US)
Assigned to Deere & Company, Moline, IL (US)
Filed by Deere & Company, Moline, IL (US)
Filed on Oct. 9, 2020, as Appl. No. 17/67,483.
Application 17/067,483 is a continuation in part of application No. 16/380,531, filed on Apr. 10, 2019, granted, now 11,079,725.
Application 16/380,531 is a continuation in part of application No. 16/380,550, filed on Apr. 10, 2019.
Application 16/380,550 is a continuation in part of application No. 16/171,978, filed on Oct. 26, 2018, granted, now 11,240,961.
Prior Publication US 2021/0022283 A1, Jan. 28, 2021
Int. Cl. A01B 69/00 (2006.01); G05B 1/02 (2006.01); A01B 79/00 (2006.01); G05D 1/02 (2020.01)
CPC A01B 69/004 (2013.01) [A01B 79/005 (2013.01); G05D 1/0274 (2013.01); G05D 1/0278 (2013.01); G05D 2201/0201 (2013.01)] 21 Claims
OG exemplary drawing
 
1. An agricultural work machine, comprising:
a communication system that receives a prior information map that includes values of a first agricultural characteristic corresponding to different geographic locations in a field;
a geographic position sensor that detects a geographic location of the agricultural work machine;
an in-situ sensor that detects an agricultural yield as a second agricultural characteristic corresponding to the geographic location;
a predictive model generator that generates a predictive agricultural model that models a relationship between the first agricultural characteristic and the second agricultural characteristic based on a value of the first agricultural characteristic in the prior information map at the geographic location and a value of the second agricultural characteristic sensed by the in-situ sensor at the geographic location; and
a predictive map generator that generates a functional predictive agricultural map of the field that maps predictive values of the second agricultural characteristic to the different geographic locations in the field, based on the values of the first agricultural characteristic in the prior information map and based on the predictive agricultural model.