US 11,946,747 B2
Crop constituent map generation and control system
Nathan R Vandike, Geneseo, IL (US); Noel W. Anderson, Fargo, ND (US); Bhanu Kiran Reddy Palla, Bettendorf, IA (US); Nathan Greuel, Le Claire, IA (US); and Alexander B. Lassers, Davenport, IA (US)
Assigned to Deere & Company, Moline, IL (US)
Filed by Deere & Company, Moline, IL (US)
Filed on Oct. 9, 2020, as Appl. No. 17/067,350.
Prior Publication US 2022/0113142 A1, Apr. 14, 2022
Int. Cl. G01C 21/32 (2006.01); A01B 79/00 (2006.01); G06F 16/28 (2019.01); G06F 16/29 (2019.01); G06V 20/10 (2022.01)
CPC G01C 21/32 (2013.01) [A01B 79/005 (2013.01); G06F 16/284 (2019.01); G06F 16/29 (2019.01); G06V 20/188 (2022.01)] 20 Claims
OG exemplary drawing
 
1. An agricultural work machine, comprising:
a communication system that receives a map that includes values of an 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 a value of a crop constituent corresponding to the geographic location;
a controllable subsystem;
one or more processors;
memory, wherein computer executable instructions are stored in the memory, the computer executable instructions, when executed by the one or more processors, configuring the one or more processors to:
generate a predictive agricultural model that models a relationship between the agricultural characteristic and the crop constituent based on a value of the agricultural characteristic in the map at the geographic location and the value of the crop constituent detected by the in-situ sensor corresponding to the geographic location;
generate a functional predictive agricultural map of the field that maps predictive values of the crop constituent to the different geographic locations in the field, based on the values of the agricultural characteristic in the map and based on the predictive agricultural model; and
generate a control signal to control the controllable subsystem based on the functional predictive agricultural map.