US 11,672,203 B2
Predictive map generation and control
Nathan R. Vandike, Geneseo, IL (US); Bhanu Kiran Reddy Palla, Bettendorf, IA (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. 17/66,999.
Application 17/066,999 is a continuation in part of application No. 16/783,511, filed on Feb. 6, 2020.
Application 16/783,511 is a continuation in part of application No. 16/783,475, filed on Feb. 6, 2020.
Application 16/783,475 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. 16/171,978, filed on Oct. 26, 2018, granted, now 11,240,961.
Prior Publication US 2021/0029878 A1, Feb. 4, 2021
Int. Cl. A01D 41/127 (2006.01); G01C 21/00 (2006.01); G01N 21/25 (2006.01); G06N 20/00 (2019.01); G01N 33/00 (2006.01)
CPC A01D 41/127 (2013.01) [G01C 21/3807 (2020.08); G01C 21/3848 (2020.08); G01N 21/25 (2013.01); G01N 33/0098 (2013.01); G06N 20/00 (2019.01)] 21 Claims
OG exemplary drawing
 
1. An agricultural work machine, comprising:
a communication system that receives a prior information map that includes values of an optical 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 a value of an agricultural characteristic corresponding to the geographic location;
a predictive model generator that generates a predictive characteristic model that models a relationship between the optical characteristic and the agricultural characteristic based on a value of the optical characteristic in the prior information map at the geographic location and the value of the agricultural characteristic detected by the in-situ sensor corresponding to the geographic location; and
a predictive map generator that generates a functional predictive map of the field, that maps predictive values of the agricultural characteristic to the different geographic locations in the field, based on the values of the optical characteristic in the prior information map and based on the predictive characteristic model.