IP Library › Granted Patent US 12,250,905
Granted Patent B2
US 12,250,905 · App. 17/066,887 · Granted Mar 18, 2025

Machine control using a predictive map

Inventors: Noel W. Anderson (Fargo, ND); Nathan R Vandike (Geneseo, IL); Bhanu Kiran Reddy Palla (Bettendorf, IA)
Assignee: Deere & Company
A01D41/1277A01B69/008A01D41/1272G06V20/188G06V40/10
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Quick Facts
Patent No.
US 12,250,905
App. No.
17/066,887
Filed
Oct 9, 2020
Granted
Mar 18, 2025
Kind
B2
Art Unit
3666
USPC
701/50
Abstract

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Claims (51)

1. An agricultural work machine for conducting a current operation at a field, the agricultural work machine comprising:

a geographic position sensor that detects a geographic location of the agricultural work machine in the field as the agricultural work machine conducts the current operation at the field;

an in-situ sensor that detects, as the agricultural work machine conducts the current operation at the field, a value of a first agricultural characteristic;

an in-situ pest sensor that detects, as the agricultural work machine conducts the current operation at the field, a value of a pest characteristic:

a controllable subsystem;

one or more processors;

memory; and

computer executable instructions stored in the memory, the computer executable instructions, when executed by the one or more processors, configure the one or more processors to:

obtain an information map that includes values of a second agricultural characteristic, different than the first agricultural characteristic, corresponding to different geographic locations in the field;

generate, as the agricultural work machine conducts the current operation at the field, a functional predictive pest characteristic map that maps predictive values of the pest characteristic corresponding to the different geographic locations in the field based on the values of the second agricultural characteristic in the information map and based on the value of the pest characteristic detected by the in-situ pest sensor;

generate, as the agricultural work machine conducts the current operation at the field, a functional predictive agricultural map of the field that maps predictive values of the first agricultural characteristic corresponding to the different geographic locations in the field based on the predictive values of the pest characteristic in the functional predictive pest characteristic map and based on the value of the first agricultural characteristic detected by the in-situ sensor; and

generate, as the agricultural work machine conducts the current operation at the field, a control signal to control the controllable subsystem based on the geographic location of the agricultural work machine and based on the functional predictive agricultural map.

2. The agricultural work machine of claim 1 , wherein the functional predictive agricultural map comprises a functional predictive yield map that maps, as the predictive values of the first agricultural characteristic, predictive yield values corresponding to the different geographic locations in the field.

3. The agricultural work machine of claim 2 , wherein the control signal controls the controllable subsystem to control a feed rate of material through the agricultural work machine.

4. The agricultural work machine of claim 1 , wherein the functional predictive agricultural map comprises a functional predictive grain quality map that maps, as the predictive values of the first agricultural characteristic, predictive grain quality values corresponding to the different geographic locations in the field.

5. The agricultural work machine of claim 4 , wherein the control signal controls the controllable subsystem to control a residue handling operation of the agricultural work machine.

6. The agricultural work machine of claim 1 wherein the controllable subsystem comprises a grain collector and wherein the control signal controls the grain collector to retain low quality, pest infected grain.

7. The agricultural work machine of claim 1 , wherein the control signal is indicative of an operator command and controls the controllable subsystem to execute the operator command.

8. The agricultural work machine of claim 1 , wherein the computer executable instructions, when executed by the one or more processors, further configure the one or more processors to:

generate, as the agricultural work machine conducts the current operation at the field, a predictive agricultural model that models a relationship between the pest characteristic and the first agricultural characteristic based on a predictive value of the pest characteristic in the functional predictive pest characteristic map and the value of the first agricultural characteristic detected by the in-situ sensor; and

generate, as the agricultural work machine conducts the current operation at the field, the functional predictive agricultural map based on the predictive values of the pest characteristic in the functional predictive pest characteristic map corresponding to the different geographic locations in the field and based on the predictive agricultural model.

9. The agricultural work machine of claim 1 , wherein the computer executable instructions, when executed by the one or more processors, further configure the one or more processors to:

generate, as the agricultural work machine conducts the current operation at the field, a user interface map representation of the functional predictive agricultural map, the user interface map representation comprising a field portion with a current location indicator indicating the geographic location of the agricultural work machine on the field portion and a pest characteristic symbol indicating a predictive value of the pest characteristic at one or more geographic locations on the field portion.

10. The agricultural work machine of claim 9 , wherein

the user interface map representation further includes an interactive display portion that displays a sensed characteristic display indicative of the first agricultural characteristic, an interactive threshold display portion indicative of an action threshold, and an interactive action indicator indicative of a control action to be taken when the first agricultural characteristic satisfies the action threshold, and

the computer executable instructions, when executed by the one or more processors, configure the one or more processors to generate the control signal to control the controllable subsystem based on the control action.

11. A computer implemented method of controlling an agricultural work machine during a current operation at a field, the computer implemented method comprising:

detecting a geographic location of the agricultural work machine during a current operation of the agricultural work machine at the field;

detecting, with an in-situ pest sensor as the agricultural work machine conducts the current operation at the field, a value of a pest characteristic;

detecting, with an in-situ sensor, a value of a first agricultural characteristic, as the agricultural work machine conducts the current operation at the field;

obtaining an information map of the field that includes values of a second agricultural characteristic, different than the first agricultural characteristic, corresponding to different geographic locations in the field;

generating, as the agricultural work machine conducts the current operation at the field, a functional predictive pest characteristic map of the field that maps predictive values of the pest characteristic corresponding to the different geographic locations in the field based on the values of the second agricultural characteristic in the information map and based on the value of the pest characteristic detected by the in-situ pest sensor;

generating, as the agricultural work machine conducts the current operation at the field, a functional predictive agricultural map of the field that maps predictive control values to the different geographic locations in the field based on the predictive values of the pest characteristic in the functional predictive pest characteristic map and based on the value of the first agricultural characteristic detected by the in-situ sensor; and

controlling, as the agricultural work machine conducts the current operation at the field, a controllable subsystem based on the detected geographic location of the agricultural work machine and based on t the functional predictive agricultural map.

12. The computer implemented method of claim 11 , wherein generating the functional predictive agricultural map comprises:

generating a functional predictive yield map that maps predictive yield values as the predictive control values.

13. The computer implemented method of claim 12 , wherein controlling the controllable subsystem comprises:

generating a feed rate control signal based on the detected geographic location of the agricultural work machine and the functional predictive yield map; and

controlling the controllable subsystem based on the feed rate control signal to control a feed rate of material through the agricultural work machine.

14. The computer implemented method of claim 11 , wherein generating the functional predictive agricultural map comprises:

generating a functional predictive grain quality map that maps predictive grain quality values as the predictive control values.

15. The computer implemented method of claim 14 , wherein controlling the controllable subsystem comprises:

generating a residue control signal based on the detected geographic location of the agricultural work machine and the functional predictive grain quality map; and

controlling the controllable subsystem based on the residue control signal to control, as the controllable subsystem, a residue handling subsystem of the agricultural work machine.

16. The computer implemented method of claim 11 , wherein generating the functional predictive agricultural map comprises:

generating a functional predictive operator command map that maps predictive operator commands as the predictive control values.

17. The computer implemented method of claim 16 , wherein controlling the controllable subsystem comprises:

generating an operator command control signal indicative of an operator command based on the detected geographic location of the agricultural work machine and the functional predictive operator command map; and

controlling the controllable subsystem based on the operator command control signal to execute the operator command.

18. The computer implemented method of claim 11 and further comprising:

generating, as the agricultural work machine conducts the current operation at the field, a predictive agricultural model that models a relationship between the pest characteristic and the first agricultural characteristic based on a predictive value of the pest characteristic in the information map and the value of the first agricultural characteristic detected by the in-situ sensor, wherein generating the functional predictive agricultural map comprises generating the functional predictive agricultural map based on the values of the pest characteristic in the functional predictive pest characteristic map map and based on the predictive agricultural model.

Assignments (2)
CORRECTIVE ASSIGNMENT TO CORRECT THE RECEIVING PARTY ZIP CODE PREVIOUSLY RECORDED AT REEL: 054081 FRAME: 0095. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Nov 4, 2020
From: ANDERSON, NOEL W.; VANDIKE, NATHAN R.; PALLA, BHANU KIRAN REDDY
To: DEERE & COMPANY
Reel/Frame 054303/0351 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 9, 2020
From: ANDERSON, NOEL W.; VANDIKE, NATHAN R.; PALLA, BHANU KIRAN REDDY
To: DEERE & COMPANY
Reel/Frame 054018/0095 →
Continuity (1)
Related Publication 20220110253A1 · Apr 14, 2022
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