US 12,216,472 B2
Map generation and control system
Nathan R. Vandike, Geneseo, IL (US); Bhanu Kiran Reddy Palla, Bettendorf, IA (US); Federico Pardina-Malbran, Fort Collins, CO (US); Matthew T. Wold, Coal Valley, IL (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 Aug. 10, 2023, as Appl. No. 18/447,725.
Application 18/447,725 is a continuation of application No. 17/067,038, filed on Oct. 9, 2020, granted, now 11,983,009.
Prior Publication US 2023/0393577 A1, Dec. 7, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G05D 1/00 (2024.01); A01D 41/127 (2006.01); A01D 61/02 (2006.01); B60K 35/00 (2024.01); B60K 35/22 (2024.01); B60K 35/28 (2024.01); G01C 21/00 (2006.01); G01N 33/24 (2006.01); G05D 1/02 (2020.01); G05D 1/646 (2024.01); G06N 20/00 (2019.01); G01N 33/00 (2006.01)
CPC G05D 1/0212 (2013.01) [A01D 41/127 (2013.01); B60K 35/00 (2013.01); G01C 21/3807 (2020.08); G01C 21/3848 (2020.08); G05D 1/646 (2024.01); B60K 35/22 (2024.01); B60K 35/28 (2024.01); B60K 2360/166 (2024.01); G01N 33/0098 (2013.01); G01N 33/246 (2013.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. An agricultural work machine comprising;
a controllable subsystem;
a communication system configured to obtain an information map that includes yield values corresponding to different geographic locations in a field;
an in-situ sensor configured detects a value of an agricultural characteristic corresponding to a geographic location;
one or more processors;
memory; and
computer executable instructions, stored in the memory, that, when executed by the one or more processors, configure the one or more processors to:
generate a predictive agricultural model that models a relationship between the agricultural characteristic and yield based on the value of the agricultural characteristic, detected by the in-situ sensor, corresponding to the geographic location and a yield value in the information map corresponding to the geographic location; and
control the controllable subsystem based on the predictive agricultural model.