Deere & Company

Nathan R Vandike

Bhanu Kiran Reddy Palla

Noel Wayne Anderson

Duane M Bomleny

Federico Pardina-Malbran

Matthew T Wold

Nathan E Krehbiel

Bradley K Yanke

Stephen R Corban

Colin D Engel

Corwin Marcus Puryk

Cody W Best

Nathan Greuel

Benjamin M Lovett

Darin Ledru Roth

Garrick William Herbst

Todd E Van Hal

Michael A Waldo

Andrea M Agarwal

Nicholas A Ohrstrom

Alan David Sheidler

Volker Fuchs

Gurmukh H Advani

Michael T Meschke

Brian Joseph Gilmore

Andrew J Peterson

Scott N Clark

Troy M Heims

Alexander B Lassers

James Hershbarger

Adam J Donohoe

Bhanu Kiran Palla

Dinesh V Phatak

Mahesh S Bothe

David L Wells

Cary S Hubner

Ryan Patrick Mackin

Glenn Everett Pope

William Douglas Graham

Niels Dybro

Martin Rittershofer

Curtis R Hammer

Mark Michael Chaney

David A Hanson

Paul I Craig

Christopher J Faulkner

Jeremiah K Johnson

William D Todd

Steven Timothy Rieck

Jeffrey R Walter

Austin M Laugen

Nathaniel R Bernklau

Wentao W Yu

Nathan Ogden

Kevin A Thelen

Thomas Herlitzius

Brian Gorge

Andrew Wesley Keenan

Eric M Heien

Hrishikesh H Tupe

Jody I Eyestone

Adam J Beals

Zachary A Meyers

Mehul P Bhavsar

Derek J Franke

Martin Unterpaintner

Meghna Chandrasekaran

Brian J Gilmore

Travis J Auderer

Hans W Schaeffer

Stephan Kirstein

Sebastian Müller

Christian Korn

Michael W Derew

Megan L Winchell

Nathan Odgen

James Monroe Hershbarger

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.

Map generation and control system

An agricultural system comprises a stalk-diameter sensing system associated with a row unit and configured to sense diameter-related data of respective stalks and generate signals based on the diameter-related data. Deck plates associated with the row unit are spaced apart to define a deck plate spacing. A deck plate positioning system is coupled to at least one of the deck plates to adjust the deck plate spacing. A control system is configured to communicate with the stalk-diameter sensing system and the deck plate positioning system. The control system is configured to receive the signals, determine a statistical representative stalk diameter for a sample of stalks based on the diameter-related data, determine a target deck plate spacing based on the statistical representative stalk diameter, and output a control signal to command the deck plate positioning system to set the deck plate spacing based on the target deck plate spacing.

Agricultural system with deck plate positioning control

An agricultural system includes a control system. The control system obtains an input value of a characteristic corresponding to a geographic location. The control system further obtains a predictive power model, the predictive power model modeling a relationship between values of the characteristic and values of a power characteristic and configured to receive the input value of the characteristic corresponding to the geographic location and output an output value of the power characteristic corresponding to the geographic location. The control system generates a control signal to control a controllable subsystem of a mobile agricultural machine based on the output value of the power characteristic.

Systems and methods for predictive power requirements and control

A sensor senses wind direction and generates a sensor signal. A wind processor processes the sensor signal to identify a wind direction at a location of an agricultural harvester. An action signal is generated to control the agricultural harvester to avoid discharging residue from the agricultural harvester into unharvested crop, based upon the wind direction.

Residue spread control

Systems and methods for sensing accumulated residue on a transmission surface of a sensor of an agricultural machine and controlling a cleaning of the transmission surface. Using captured information obtained by the sensor through the transmission surface, a first cleanliness value can be derived and compared with a first threshold. If the first threshold is not satisfied, a cleaning system can be activated. Communication of signals generated using the captured information can also then be suspended or assigned a confidence value. Information subsequently captured by the sensor can be used to derive another cleanliness value for comparison to a second threshold. The subsequently derived cleanliness value can result in at least one of a change in the confidence value, resumption of communication of signals generated using captured information obtained by the sensor, deactivation of the cleaning system, and a change in the aggressiveness of the cleaning system.

Residue sensing and cleaning system

An agricultural harvesting system obtains a yield map that maps yield values to different geographic locations in a worksite and a speed map that maps agricultural harvester speed values to different geographic locations in the worksite. The agricultural harvesting system identifies a geographic location in the worksite at which the agricultural harvester will be full, at least to a threshold level, based on the yield map; identifies a geographic location in the worksite at which a material transfer operation is to start based on the geographic location at which the agricultural harvester will be full, at least to the threshold level; and identifies a time at which the agricultural harvester will arrive at the material transfer location, based on the speed map. The agricultural harvesting system can control one or more of the agricultural harvester and a receiving machine.

Systems and methods for predictive harvesting logistics

Control zones are identified on a thematic map and work machine actuator settings are identified for each control zone. A position of the work machine is sensed and actuators on the work machine are controlled based on the control zone that the work machine is in, and based upon the actuator settings corresponding to the control zone. The control zone is then divided, on a display, into a harvested portion of the control zone on which an observed condition value is shown, and control zone that has yet to be harvested, on which an estimated value of the condition is shown.

Mobile work machine control based on control zone map data

An agricultural harvesting system includes a harvesting logistics module that is configured to receive a map that maps values of a crop characteristic to different geographic locations in a field. The harvesting logistics module further configured to identify a crop characteristic threshold and to identify a mixture of crop material based on the map and based on the crop characteristic threshold. The harvesting logistics module configured to generate a route for a mobile machine, such as a receiving machine or a harvester, based on the identified mixture.

Predictive agricultural model and map generation

Predictive map generation and control system

A crop residue monitoring system may include a harvester, a camera to capture an image of crop residue generated by the harvester, an analytical unit to derive a value for a crop residue parameter of the crop residue based upon an optical analysis of the image and a control unit to adjust a subsequent field operation based upon the value of the crop residue parameter.

Crop residue based field operation adjustment

A residue distribution system includes a flow channel having a first lateral side and a second lateral side disposed. A spreader is positioned proximate a downstream end of the flow channel, and broadcasts the flow of the crop residue. A residue distributor is positioned within the flow channel and upstream of the spreader for directing the crop residue toward one of the first lateral side or the second lateral side of the flow channel to increase a mass of the crop residue that side of the spreader, whereby a discharge density of the crop residue on that side of the spreader is increased to overcome effects of a crosswind or an uphill side-slope on broadcast distribution of the crop residue.

Spreader distribution compensation through material flow manipulation

Predictive power map generation and control system

One or more information maps are obtained by an agricultural system. The one or more information maps map one or more characteristic values at different geographic locations in a worksite. An in-situ sensor detects a mass flow value as a mobile machine operates at the worksite. A predictive map generator generates a predictive map that maps predictive mass flow values or predictive yield values at different geographic locations in the worksite based on a relationship between the values in the one or more information maps and the mass flow value detected by the in-situ sensor or the yield value based on the detected mass flow value. The predictive map can be output and used in automated machine control.

Map based farming for windrower operation

One or more information maps are obtained by an agricultural system. The one or more information maps map one or more characteristic values at different geographic locations in a worksite. An in-situ sensor detects a weed value as a mobile machine operates at the worksite. A predictive map generator generates a predictive map that maps predictive weed values at different geographic locations in the worksite based on a relationship between the values in the one or more information maps and the weed value detected by the in-situ sensor. The predictive map can be output and used in automated machine control.

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Geneseo, IL, United States of America

Nathan R Vandike