IP Library › Granted Patent US 12,344,260
Granted Patent B2
US 12,344,260 · App. 18/408,216 · Granted Jul 1, 2025

Predictive machine control

Inventors: Andy B. Appleton (Cedar Falls, IA); Nohoon Ki (Cedar Falls, IA); Wissam H. El-Ratal (Waterloo, IA); Rui Zhang (Waterloo, IA); Justin T. Roth (Cedar Falls, IA)
Assignee: Deere & Company
B60W50/0097A01B69/008A01B79/005A01D41/1278G06Q10/047G06Q30/0284B60W2300/152
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Quick Facts
Patent No.
US 12,344,260
App. No.
18/408,216
Granted
Jul 1, 2025
Kind
B2
Abstract

A policy map is obtained that includes of prescribed machine settings values for controlling a machine to perform an operation at different locations in the field. Sensor signals indicating conditions that will be encountered by the machine in the future, as it moves through the site. A predictive model provides an expected machine response, based upon the a future condition and a prescribed machine setting value. Adjusted machine setting value is generated based on the expected machine response. Control signals are generated, based on the adjusted machine setting value, to control a set of controllable subsystems.

Claims (9)

1. An agricultural vehicle control system, comprising:

a setting prediction system that obtains a policy map of a field on which an operation is to be performed by an agricultural vehicle, prior to the agricultural vehicle performing the operation at the field, the policy map including a prescribed machine route and prescribed machine settings values at different locations along the machine route, the prescribed machine settings values each defining a setting for a controllable subsystem;

a future condition sensor that generates, as the agricultural vehicle is performing the operation, a sensor signal indicative of a future condition that the agricultural vehicle will encounter, at a future location, in performing the operation;

a predictive vehicle model that models the agricultural vehicle in performing the operation and that receives the sensor signal indicative of the future condition that the agricultural vehicle will encounter at the future location, identifies a prescribed machine setting value, from the policy map, corresponding to the future location, and generates an expected vehicle response output indicative of expected vehicle response characteristics based on the sensor signal indicative of the future condition that the agricultural vehicle will encounter at the future location and the prescribed machine setting value, from the policy map, corresponding to the future location;

an adjustment component that determines that an adjustment is to be made to the prescribed machine setting value, from the policy map, corresponding to the future location based on the expected vehicle response output, generates a plurality of different potential adjusted machine setting values for controlling the machine at the future location based on an operator selected control strategy, and generates a cost for each potential adjusted machine setting value of the plurality of different potential adjusted machine setting values;

a selector that selects, as a selected adjusted machine setting value, one of the plurality of different potential adjusted machine setting values based on the cost for each potential adjusted machine setting value of the plurality of different machine setting values; and

a control signal generator that generates a control signal to control the agricultural vehicle based on the selected adjusted machine setting value.

2. The agricultural vehicle of claim 1 , wherein the future condition sensor comprises a load weight sensor.

3. The agricultural vehicle of claim 1 , wherein the future condition sensor comprises a traction sensor.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 10, 2024
From: APPLETON, ANDY B.; KI, NOHOON; EL-RATAL, WISSAM H.; ZHANG, RUI; ROTH, JUSTIN T.
To: DEERE & COMPANY
Reel/Frame 066074/0820 →
Continuity (2)
Division 16668478 · Oct 30, 2019
Related Publication 20240140446A1 · May 2, 2024
References Cited (35)
US 5995895A · Watt · 1999 [cited by examiner]
US 9235214B2 · Anderson · 2016 [cited by applicant]
US 9656656B2 · Xing et al. · 2017 [cited by applicant]
US 9891629B2 · Murray et al. · 2018 [cited by applicant]
US 10801935B2 · Ki et al. · 2020 [cited by applicant]
US 10814856B2 · Kumar · 2020 [cited by examiner]
US 11079725B2 · Palla et al. · 2021 [cited by applicant]
US 20030018423A1 · Saller · 2003 [cited by examiner]
US 20150232097A1 · Luther · 2015 [cited by examiner]
US 20160298306A1 · de Kontz · 2016 [cited by examiner]
US 20160299111A1 · de Kontz · 2016 [cited by examiner]
US 20160299511A1 · de Kontz · 2016 [cited by examiner]
US 20160355198A1 · Dulmage · 2016 [cited by examiner]
US 20190188031A1 · Balachandran · 2019 [cited by examiner]
US 20200033890A1 · Sugaki · 2020 [cited by examiner]
US 20200079443A1 · Sauvageau · 2020 [cited by examiner]
US 20200150673A1 · Qiu · 2020 [cited by examiner]
US 20200181876A1 · Mahrenholz · 2020 [cited by examiner]
US 20200278680A1 · Schulz · 2020 [cited by examiner]
US 20210007277A1 · Anderson · 2021 [cited by applicant]
US 20210129853A1 · Appleton et al. · 2021 [cited by applicant]
CN 105045098 · 2015 [cited by applicant]
CN 105045098A · 2015 [cited by examiner]
CN 105045098B · 2017 [cited by examiner]
CN 106643719 · 2020 [cited by applicant]
CN 106643719B · 2020 [cited by examiner]
CN 109247324 · 2020 [cited by applicant]
CN 109247324B · 2020 [cited by examiner]
CN 112154447A · 2020 [cited by examiner]
DE 102017221134A1 · 2019 [cited by examiner]
DE 112019001832 · 2021 [cited by applicant]
DE 112019001832T5 · 2021 [cited by examiner]
EP 3578031A1 · 2019 [cited by examiner]
JP 2013228821A · 2013 [cited by examiner]
German Search Report issued in counterpart application No. 102020212106.0 dated May 31, 2021, 12 pages. [cited by applicant]
Cited By (2)
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