IP Library › Granted Patent US 12,295,288
Granted Patent B2
US 12,295,288 · App. 17/713,738 · Granted May 13, 2025

Predictive machine setting map generation and control system

Inventors: Nathan R. Vandike (Geneseo, IL); Bhanu Kiran Reddy Palla (Bettendorf, IA); Duane M. Bomleny (Geneseo, IL); Nathan E. Krehbiel (Bettendorf, IA); Troy M Heims (Davenport, IA)
Assignee: Deere &Company
A01D41/1278A01D41/02G05D1/0044G05D1/0274
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Quick Facts
Patent No.
US 12,295,288
App. No.
17/713,738
Granted
May 13, 2025
Kind
B2
Abstract

An information map is obtained by an agricultural system. The information map maps values of a characteristic to different geographic locations in a field. An in-situ sensor detects machine setting values as a mobile machine moves through the field. A predictive map generator generates a predictive map that predicts the machine setting at different locations in the field based on a relationship between the values of the characteristic and the machine setting values detected by the in-situ sensor. The predictive map can be output and used in automated machine control.

Claims (54)

1. An agricultural system comprising:

a geographic position sensor that detects a first geographic location of a mobile machine in a field;

an in-situ sensor that detects a machine setting value corresponding to the first geographic location in the field;

one or more processors;

memory storing instructions, executable by the one or more processors, that, when executed by the one or more processors, cause the one or more processors to:

obtain, as a first map, an information map that maps values of a characteristic to different geographic locations in the field;

generate a predictive machine setting model indicative of a relationship between the characteristic and the machine setting based on the machine setting value detected by the in-situ sensor corresponding to the first geographic location and a value of the characteristic in the information map corresponding to the first geographic location;

generate, as a second map, a functional predictive machine setting map of the field that maps a predictive machine setting value to a second geographic location in the field based on a value of the characteristic in the information map corresponding to the second geographic location and based on the predictive machine setting model; and

control the mobile machine based on the functional predictive machine setting map.

2. The agricultural system of claim 1 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to control the mobile machine based on the functional predictive machine setting map by controlling a controllable subsystem on the mobile machine based on the functional predictive machine setting map.

3. The agricultural system of claim 1 , wherein the in-situ sensor is an input sensor that detects the machine setting value by detecting an input into an input mechanism.

4. The agricultural system of claim 1 , wherein the in-situ sensor is a control system output sensor that detects the machine setting value by detecting an output of a control system that controls the mobile machine.

5. The agricultural system of claim 1 , wherein the machine setting value is indicative of a commanded operational set point of a component of the mobile machine.

6. The agricultural system of claim 1 , wherein the information map is one of:

a topographic map that maps, as the values of the characteristic, topographic characteristic values to the different geographic locations in the field;

a vegetative index map that maps, as the values of the characteristic, vegetative index values to the different geographic locations in the field;

an optical map that maps, as the values of the characteristic, optical characteristic values to the different geographic locations in the field;

a seeding map that maps, as the values of the characteristic, seeding characteristic values to the different geographic locations in the field;

a soil property map that maps, as the values of the characteristic, soil property values to the different geographic location in the field;

a prior operation map that maps, as the values of the characteristic, prior operation characteristic values to the different geographic locations in the field; or

a historical setting map that maps, as the values of the characteristic, historical setting values to the different geographic locations in the field.

7. The agricultural system of claim 1 , wherein the information map comprises two or more information maps, each of the two or more information maps mapping values of a respective characteristic to the different geographic locations in the field,

wherein the instructions, when executed by the one or more processors, cause the one or more processors to generate the predictive machine setting model indicative of a relationship between the two or more respective characteristics and the machine setting based on the machine setting value detected by the in-situ sensor corresponding to the first geographic location and values of the two or more respective characteristics in the two or more information maps corresponding to the first geographic location, and

wherein the functional predictive machine setting map maps a predictive machine setting value to the second geographic location in the field based on values of the two or more respective characteristics in the two or more information maps corresponding to the second geographic location and the predictive machine setting model.

8. The agricultural system of claim 1 , wherein the in-situ sensor detects, as the machine setting value, a machine setting value corresponding to a first component of the mobile machine,

wherein the instructions, when executed by the one or more processors, cause the one or more processors to generate the predictive machine setting indicative of a relationship between the characteristic and the machine setting corresponding to the first component of the mobile machine based on the machine setting value corresponding to the first component detected by the in-situ sensor corresponding to the first geographic location and the value of the characteristic in the information map corresponding to the first geographic location, and

wherein the functional predictive machine setting map maps a predictive machine setting value corresponding to the first component to the second geographic location in the field based on the value of the characteristic in the information map corresponding to the second geographic location and based on the predictive machine setting model.

9. The agricultural system of claim 8 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to control the mobile machine based on the functional predictive machine setting map by controlling an actuator corresponding to a second component of the mobile machine based on the functional predictive machine setting map.

10. The agricultural system of claim 9 , wherein the second component of the mobile machine is downstream of the first component of the mobile machine.

11. A computer implemented method comprising:

receiving an information map that maps values of a characteristic to different geographic locations in a field;

obtaining in-situ sensor data indicative of a value of a machine setting corresponding to a first geographic location in the field;

generating a predictive machine setting model indicative of a relationship between the characteristic and the machine setting based on the value of the machine setting corresponding to the first geographic location in the field and a value of the characteristic in the information map corresponding to the first geographic location in the field; and

controlling a predictive map generator to generate a functional predictive machine setting map of the field that maps a predictive value of the machine setting to a second geographic location in the field based on a value of the characteristic in the information map corresponding to the second geographic location and the predictive machine setting model; and

controlling a mobile machine based on the functional predictive machine setting map.

12. The computer implemented method of claim 11 , wherein controlling the mobile machine based on the functional predictive machine setting map comprises controlling a controllable subsystem on the mobile machine based on the functional predictive machine setting map.

13. The computer implemented method of claim 11 , wherein obtaining in-situ sensor data indicative of the value of the machine setting comprises one of: (i) detecting, with an input sensor, an input into an input mechanism; or (ii) detecting, with a control system output sensor, an output of a control system that controls the mobile machine.

14. The computer implemented method of claim 11 , wherein the machine setting corresponds to a first component of the mobile machine,

wherein generating the predictive machine setting model comprises generating the predictive machine setting model indicative of a relationship between the characteristic and the machine setting corresponding to the first component based on a value of the machine setting corresponding to the first component corresponding to the first geographic location and the value of the characteristic in the information map corresponding to the first geographic location, and

wherein generating the functional predictive machine setting map maps a predictive value of the machine setting corresponding to the first component to the second geographic location in the field based on the value of the characteristic in the information map corresponding to the second geographic location and the predictive machine setting model.

15. The computer implemented method of claim 14 , wherein controlling the mobile machine based on the functional predictive machine setting map comprises controlling a controllable subsystem corresponding to a second component based on the functional predictive machine setting map.

16. A mobile agricultural machine, comprising:

a geographic position sensor that is configured to detect a first geographic location of the mobile agricultural machine;

an in-situ sensor that is configured to detect a machine setting value corresponding to the first geographic location;

one or more processors;

memory storing instructions, executable by the one or more processors, that, when executed by the one or more processors, cause the one or more processors to:

obtain an information map that maps values of a characteristic to different geographic locations in a field;

generate a predictive machine setting model indicative of a relationship between values of the characteristic and machine setting values based on the machine setting value detected by the in-situ sensor corresponding to the first geographic location in the field and a value of the characteristic in the information map corresponding to the first geographic location in the field;

generate a functional predictive machine setting map of the field, that maps a predictive machine setting value to a second geographic location in the field, based on a value of the characteristic in the information map corresponding to the second geographic location and based on the predictive machine setting model; and

control the mobile agricultural machine based on the functional predictive machine setting map.

17. The mobile agricultural machine of claim 16 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to control the mobile agricultural machine based on the functional predictive machine setting map by controlling a controllable subsystem based on the functional predictive machine setting map.

18. The mobile agricultural machine of claim 17 , wherein controllable subsystem comprises an actuator that is controllable to adjust operation of a component of the mobile agricultural machine.

19. The mobile agricultural machine of claim 18 , wherein the predictive machine setting values correspond to a first component of the mobile agricultural machine and wherein the actuator corresponds to a second component of the mobile agricultural machine.

20. The mobile agricultural machine of claim 17 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to control the mobile agricultural machine based on the functional predictive machine setting map by controlling an interface mechanism of the mobile agricultural machine to generate a display indicative of the functional predictive machine setting map.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 5, 2022
From: VANDIKE, NATHAN R.; PALLA, BHANU KIRAN REDDY; BOMLENY, DUANE M.; KREHBIEL, NATHAN E.; HEIMS, TROY M.
To: DEERE & COMPANY
Reel/Frame 059609/0629 →
Continuity (1)
Related Publication 20230309449A1 · Oct 5, 2023
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