DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 10/22/2025 has been entered.
Status of Claims
This action is in reply to the RCE filed on 12/03/2025.
Claims 1, 3-4, 6-7, 9, 11-14, 16-18, and 21-27 are currently pending and have been examined.
Claims 1, 3, 9, 11-12, 14, 16-18, and 25 have been amended.
Claims 26-27 have been added.
Claims 5 and 8 have been cancelled.
Claims 1, 3-4, 6-7, 9, 11-14, 16-18, and 21-27 are currently rejected.
This action is made NON-FINAL.
Response to Arguments
Applicant’s arguments filed 12/03/2025 have been fully considered but they are not persuasive.
Applicant’s arguments appear to be primarily to the inherency attributed to the teachings of Roberge as well as the currently amended limitations of the claims. In response to these arguments the examiner has removed Roberge and replaced it with Hamilton in the updated rejections below to teach what was previously taught by Roberge as well as the amended limitations to the independent claims.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 4, 6-7, 9, 11-13, 17-18, and 21-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Vandike et. al. (US 2021/0029878), herein Vandike in view of Hamilton et. al. (US 2023/0049727), herein Hamilton (previously cited 09/16/2025).
Regarding claim 1:
Vandike teaches:
An agricultural windrowing system (windrowers [0003]) comprising:
a communication system (communication system 206 [0039]) configured to receive an information map (receive prior information map 258 [0040]) that includes values of a characteristic (an optical characteristic map [0040]) corresponding to a plurality of different geographic locations in a worksite (The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field [0006]);
a geographic position sensor (geographic position sensor 204 [0039]) configured to detect a geographic location of a mobile windrowing machine (Geographic position sensor 204 illustratively senses or detects the geographic position or location of agricultural harvester 100 [0042]);
one or more in-situ sensors (one or more in-situ sensors 208 [0039]), configured to detect a value of each additional characteristic of one or more additional characteristics (that sense one or more agricultural characteristics of a field [0039]) corresponding to a geographic area (concurrent with a harvesting operation [0039]; examiner notes that the data would correspond to the location of the machine at the time the data is collected.), the one or more additional characteristics including at least one characteristic of the mobile windrowing machine (geographic position sensor 204 [0067]);
one or more processors (one or more processors or servers 201 [0039]); and
memory (data store 202) storing computer executable instructions that, when executed by the one or more processors, cause the one or more processors (any or all of the systems, components, logic and interactions may be implemented by software that is loaded into a memory and is subsequently executed by a processor [0112]) to:
generate a functional predictive [windrow shape quality] map of the worksite (to generate a functional predictive map 263 [0045]) that maps a plurality of predictive values of [windrow shape quality] to the plurality of different geographic locations in the worksite (predictive map generator 212 generates a predictive map 264 that predicts the value of the yield [0047]), wherein each predictive value, of the plurality of predictive values of [windrow shape quality], is mapped to a respective geographic location, of the plurality of different geographic locations (he one or more information maps map one or more agricultural characteristic values at different geographic locations of a field [0006]), and is based on:
the value of the characteristic in the information map (The predictive model can also be generated based on optical characteristic values from the prior information map 258 [0046]) corresponding to the respective geographic location in the worksite (at different locations across the field [0047]), and the value of each additional characteristic of the one or more additional characteristics detected by the one or more in-situ sensors corresponding to the geographic area (and multiple in-situ data values generated by in-situ sensors 208 [0046])
control the mobile windrowing machine based on the functional predictive windrow shape quality map (which generates control signals based upon the predictive map 264 [0056]).
Vandike does not explicitly teach, however Hamilton teaches:
generate a functional predictive windrow shape quality (to estimate a predicted condition of a windrow formed by the windrower 10 at certain operating parameters [0037])
wherein each predictive value, of the plurality of predictive values of windrow shape quality (The controller 17 may determine the crop yield and moisture content using information from the sensor(s) 19, and optionally, from other sources (e.g., weather conditions, power consumed by the header 14, historical data such as measurements of prior harvests, planting data, irrigation data, soil quality data, etc.). The controller 17 may use the measured crop yield and moisture content, as well as predicted or current local weather conditions [0037]; at certain operating parameters (e.g., positions of the swathboard 24 and/or the forming shields 22, speed of the header 14, roll pressure of the conditioner rolls 20, ground speed of the windrower 10, etc.) [0037]), is mapped to a respective geographic location (In block 76, the yield and moisture content of the crop material is detected. In block 78, an operating parameter of the agricultural machine is changed in response to the detected yield and moisture content. [0042]), of the plurality of different geographic locations (examiner notes that Hamilton is measuring the area it was about to harvest so therefore the determination is being made in real time in regards to the area it is currently in and therefore the characteristics are specific to that location of the many locations that make up an entire field.), and is based on:
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Vandike to include the teachings as taught by Hamilton with a reasonable expectation of success. The combination of Vandike and Hamilton would have been obvious to one having ordinary skill in the art at the time of effective filing because the combination is combining prior art elements according to known methods to yield predictable results. Vandike teaches a windowing machine that can control the machine based off of a prediction map generated from sensor data. Vandike does not explicitly teach detecting windrow shape quality but Hamilton does teach the ability to determine windrow shape quality and adjust the control based on a response to that determination. Using the prediction map as taught by Vandike to automatically control and predict the windrow shape quality of Hamilton would yield the predictable result of the claimed invention. Additionally substituting one value taught by Hamilton into the prediction model as taught by Vandike is simple substitution of one known element for another to obtain a predictable result. Hamilton also teaches the benefit of “The controller 17 may use the measured crop yield and moisture content, as well as predicted or current local weather conditions, to estimate a predicted condition of a windrow formed by the windrower 10 at certain operating parameters [Hamilton, 0037]”
Regarding claim 4:
Vandike in view of Hamilton teaches all the limitations of claim 1, upon which this claim is dependent.
Vandike further teaches:
controlling a cutter actuator of the mobile windrowing machine (One or more actuators 107 drive movement of header 102 about axis 105 in the direction generally indicated by arrow 109 [0026]).
Regarding claim 6:
Vandike in view of Hamilton teaches all the limitations of claim 1, upon which this claim is dependent.
Hamilton further teaches:
controlling a forming shield actuator of the mobile windrowing machine (The controller 17 may adjust the position of the swathboard 24 and/or the forming shields 22, the ground speed of the tractor 12, the header speed, or other operating parameters as crop yield and moisture change [0038]).
Regarding claim 7:
Vandike in view of Hamilton teaches all the limitations of claim 1, upon which this claim is dependent.
Hamilton further teaches:
controlling a swath flap actuator of the mobile windrowing machine (The controller 17 may adjust the position of the swathboard 24 and/or the forming shields 22, the ground speed of the tractor 12, the header speed, or other operating parameters as crop yield and moisture change [0038]).
Regarding claim 9:
Vandike in view of Hamilton teaches all the limitations of claim 1, upon which this claim is dependent.
Vandike further teaches:
generate a predictive [windrow shape quality] model indicative of a relationship between values of the characteristic in the information map (a model that is indicative of a relationship between the values sensed by the in-situ sensor 208 and a value mapped to the field by the prior information map 258 [0044]) and [values of windrow shape quality] based on the [value of the windrow shape quality] corresponding to the geographic area (a model that is indicative of a relationship between the values sensed by the in-situ sensor 208 and a value mapped to the field by the prior information map 258 [0044]) and a value of the first characteristic in the information map corresponding to the geographic area (a value mapped to the field by the prior information map 258 [0044]); and
generate the functional predictive [windrow shape quality] map (generate a functional predictive map 263 [0045]) based on the predictive [windrow shape quality] model (the optical characteristic values in prior information map 258 [0045]) and based on the values of the first characteristic in the information map at the different geographic locations in the worksite (Predictive map generator 212 can use the model generated by predictive model generator 210 and the optical characteristic values in prior information map 258, to generate a functional predictive map 263 that predicts the characteristic at different locations in the field. [0045]).
Hamilton further teaches:
generate a windrow shape quality value (to estimate a predicted condition of a windrow formed by the windrower 10 at certain operating parameters [0037]) corresponding to the geographic area (In block 76, the yield and moisture content of the crop material is detected. In block 78, an operating parameter of the agricultural machine is changed in response to the detected yield and moisture content. [0042]) based on the value of each additional characteristic of the one or more additional characteristics corresponding to the geographic area (The controller 17 may determine the crop yield and moisture content using information from the sensor(s) 19, and optionally, from other sources (e.g., weather conditions, power consumed by the header 14, historical data such as measurements of prior harvests, planting data, irrigation data, soil quality data, etc.). The controller 17 may use the measured crop yield and moisture content, as well as predicted or current local weather conditions [0037]; at certain operating parameters (e.g., positions of the swathboard 24 and/or the forming shields 22, speed of the header 14, roll pressure of the conditioner rolls 20, ground speed of the windrower 10, etc.) [0037]); and
windrow shape quality (to estimate a predicted condition of a windrow formed by the windrower 10 at certain operating parameters [0037])
Regarding claim 11:
Vandike in view of Hamilton teaches all the limitations of claim 1, upon which this claim is dependent.
Vandike further teaches:
a topographic map that maps, as the values of the characteristic, topographic characteristic values to the different geographic locations in the worksite (examiner is interpreting this limitation in the alternative which does not require it to be taught by the applied art.);
a vegetative index map that maps, as the values of the characteristic, vegetative index values to the different geographic locations in the worksite (A vegetative index map illustratively maps vegetative index values (which may be indicative of vegetative growth or other characteristics) across different geographic locations in a field of interest [0022]);
a crop genotype map that maps, as the values of the characteristic, crop genotype values to the different geographic locations in the worksite (examiner is interpreting this limitation in the alternative which does not require it to be taught by the applied art.);
a soil type map that maps, as the values of the characteristic, soil type values to the different geographic locations in the worksite (examiner is interpreting this limitation in the alternative which does not require it to be taught by the applied art.);
a soil moisture map that maps, as the values of the characteristic, soil moisture values to the different geographic locations in the worksite (examiner is interpreting this limitation in the alternative which does not require it to be taught by the applied art.);
a soil nutrient map that maps, as the values of the characteristic, soil nutrient values to the different geographic locations in the worksite (examiner is interpreting this limitation in the alternative which does not require it to be taught by the applied art.); or
an optical map that maps, as the values of the characteristic, optical characteristic values to the different geographic locations in the worksite (Optical characteristic maps can be generated using satellite images, optical sensors on flying vehicles such as UAVS, or optical sensors on a ground-based system, such as another agricultural work machine operating in the field before the harvesting operation. [0021]).
Regarding claim 12:
Vandike teaches:
A computer implemented (the processors and servers include computer processors with associated memory [0108]) method (methods [0017]) of controlling a mobile windrowing machine (windrowers [0003]), the method comprising:
receiving an information map (receive prior information map 258 [0040]) that maps values of a first characteristic (an optical characteristic map [0040]) to a plurality of different geographic locations in a worksite (The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field [0006]);
detecting, with a first in-situ sensor (one or more in-situ sensors 208 [0039]), a value of a second agricultural characteristic (that sense one or more agricultural characteristics of a field [0039]) corresponding to a geographic area (Geographic position sensor 204 illustratively senses or detects the geographic position or location of agricultural harvester 100 [0042]);
detecting, with a second in-situ sensor (one or more in-situ sensors 208 [0039]), a value of a third characteristic corresponding to the geographic area (that sense one or more agricultural characteristics of a field [0039]), the third characteristic different than the first characteristic and the second characteristic (In-situ sensors 208 may sense, without limitation, soil characteristic, a crop moisture, a weed intensity, weed location, weed type, a yield, a biomass, a crop state, a power characteristic, a speed, a machine orientation (pitch, roll, direction), tailings characteristics, grain quality, internal material distribution, stalk characteristic, crop height, residue, cleaning fan speed, power usage, etc. In-situ data include data taken from a sensor on-board the agricultural harvester or taken by any sensor where the data are detected during the harvesting operation. [0043]);
generating a functional predictive map (to generate a functional predictive map 263 [0045]) of the field that maps predictive [dry down values] to the different geographic locations in the worksite (predictive map generator 212 generates a predictive map 264 that predicts the value of the yield [0047]) based on the values of the first characteristic in the information map at the different geographic locations in the worksite (The predictive model can also be generated based on optical characteristic values from the prior information map 258 [0046]), the value of the second characteristic detected by the first in-situ sensor corresponding to the geographic area (In-situ sensors 208 may sense, without limitation, soil characteristic, a crop moisture, a weed intensity, weed location, weed type, a yield, a biomass, a crop state, a power characteristic, a speed, a machine orientation (pitch, roll, direction), tailings characteristics, grain quality, internal material distribution, stalk characteristic, crop height, residue, cleaning fan speed, power usage, etc. In-situ data include data taken from a sensor on-board the agricultural harvester or taken by any sensor where the data are detected during the harvesting operation. [0043]), and the value of the third characteristic detected by the second in-situ sensor corresponding to the geographic area (In-situ sensors 208 may sense, without limitation, soil characteristic, a crop moisture, a weed intensity, weed location, weed type, a yield, a biomass, a crop state, a power characteristic, a speed, a machine orientation (pitch, roll, direction), tailings characteristics, grain quality, internal material distribution, stalk characteristic, crop height, residue, cleaning fan speed, power usage, etc. In-situ data include data taken from a sensor on-board the agricultural harvester or taken by any sensor where the data are detected during the harvesting operation. [0043]); and
controlling the mobile windrowing machine based on the functional predictive map (which generates control signals based upon the predictive map 264 [0056]).
Hamilton also teaches:
based on: the value of the first characteristic in the information map at the respective geographic location in the worksite (other sources (e.g., weather conditions, power consumed by the header 14, historical data such as measurements of prior harvests, planting data, irrigation data, soil quality data, etc.) [0037]);
the value of the second characteristic detected by the first in-situ sensor corresponding to the geographic area (one or more sensors 19a-19c configured to detect properties of the crop material being cut, such as yield (mass of crop) and moisture content [0030]);
the value of the third characteristic detected by the second in-situ sensor corresponding to the geographic area (one or more sensors 19a-19c configured to detect properties of the crop material being cut, such as yield (mass of crop) and moisture content [0030]); and
controlling the mobile windrowing machine based on the functional predictive dry down map (the controller 17 can determine how to adjust the operating parameters to make the windrow have a selected moisture content at a preselected future time, typically a time for baling or raking. Appropriate operating parameters may be determined based on yield, moisture, drying models, and weather predictions. [0037]).
Vandike does not explicitly teach, however Hamilton teaches:
generating a functional predictive dry down [map] (to estimate a predicted condition of a windrow formed by the windrower 10 at certain operating parameters [0037]) of the worksite that maps a plurality of predictive dry down values (the controller 17 can determine how to adjust the operating parameters to make the windrow have a selected moisture content at a preselected future time, typically a time for baling or raking [0037]) to the plurality of different geographic locations in the worksite (examiner notes that the adjustments/predictions are made to each area of the worksite independently and therefore are detecting a plurality of different locations.), wherein each predictive dry down value, of the plurality of predictive fry down values, is mapped to a respective geographic location, of the plurality of different geographic locations (The controller 17 may determine the crop yield and moisture content using information from the sensor(s) 19, and optionally, from other sources (e.g., weather conditions, power consumed by the header 14, historical data such as measurements of prior harvests, planting data, irrigation data, soil quality data, etc.) [0037]), and is based on:
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Vandike to include the teachings as taught by Hamilton with a reasonable expectation of success. The combination of Vandike and Hamilton would have been obvious to one having ordinary skill in the art at the time of effective filing because the combination is combining prior art elements according to known methods to yield predictable results. Vandike teaches a windowing machine that can control the machine based off of a prediction map generated from sensor data. Vandike does not explicitly teach detecting windrow shape quality but Hamilton does teach the ability to determine windrow shape quality and adjust the control based on a response to that determination. Using the prediction map as taught by Vandike to automatically control and predict the windrow shape quality of Hamilton would yield the predictable result of the claimed invention. Additionally substituting one value taught by Hamilton into the prediction model as taught by Vandike is simple substitution of one known element for another to obtain a predictable result. Hamilton also teaches the benefit of “The controller 17 may use the measured crop yield and moisture content, as well as predicted or current local weather conditions, to estimate a predicted condition of a windrow formed by the windrower 10 at certain operating parameters [Hamilton, 0037]”
Regarding claim 13:
Vandike in view of Hamilton teaches all the limitations of claim 12, upon which this claim is dependent.
Vandike further teaches:
controlling the mobile windrowing machine (control [0018]) comprises one or more of:
controlling an actuator to control a position of a component of the mobile windrowing machine (control the position of the header of the agricultural harvester relative to the field surface [0018]); and
controlling an actuator to control a speed or direction of movement of a component of the mobile windrowing machine (examiner is interpreting this limitation in the alternative.).
Regarding claim 16:
Vandike in view of Hamilton teaches all the limitations of claim 12, upon which this claim is dependent.
Vandike further teaches:
generating (a predictive model or relationship generator (collectively referred to hereinafter as “predictive model generator 210”) [0039]), with a processing system, [dry down value] corresponding to the geographic area based on the value of the second characteristic (that sense one or more agricultural characteristics of a field [0039]) detected by the first in-situ sensor (one or more in-situ sensors 208 [0039]) corresponding to the geographic area (Geographic position sensor 204 illustratively senses or detects the geographic position or location of agricultural harvester 100 [0042]) and based on the value of the third characteristic (that sense one or more agricultural characteristics of a field [0039]) detected by the second in-situ sensor (one or more in-situ sensors 208 [0039]) corresponding to the geographic area (Geographic position sensor 204 illustratively senses or detects the geographic position or location of agricultural harvester 100 [0042]);
generating a predictive [dry down] model (a predictive model or relationship generator (collectively referred to hereinafter as “predictive model generator 210”) [0039]) indicative of a relationship between values of the first characteristic and dry down values based on the generated dry down value corresponding to the geographic area and a value of the first characteristic in the information map corresponding to the geographic area (a model that is indicative of a relationship between the values sensed by the in-situ sensor 208 and a value mapped to the field by the prior information map 258 [0044]); and
wherein generating the functional predictive map (generate a functional predictive map 263 [0045]) comprises generating the functional predictive based on the values of the first characteristic in the information map at the different geographic locations (Predictive map generator 212 can use the model generated by predictive model generator 210 and the optical characteristic values in prior information map 258, to generate a functional predictive map 263 that predicts the characteristic at different locations in the field. [0045]) and the predictive [dry down] model (Predictive map generator 212 can use the model generated by predictive model generator 210 [0045]).
Hamilton further teaches:
a processing system configured to generate a dry down value (the controller 17 can determine how to adjust the operating parameters to make the windrow have a selected moisture content at a preselected future time, typically a time for baling or raking [0037]) corresponding to the geographic area (to estimate a predicted condition of a windrow formed by the windrower 10 at certain operating parameters [0037]) based on the values of the respective characteristics detected by the one or more in-situ sensors corresponding to the geographic area (one or more sensors 19a-19c configured to detect properties of the crop material being cut, such as yield (mass of crop) and moisture content [0030]); and
predictive dry down (windrow have a selected moisture content at a preselected future time)
Regarding claim 17:
Vandike teaches:
An agricultural windrowing system (windrowers [0003]) comprising:
a communication system (communication system 206 [0039]) configured to receive an information map (receive prior information map 258 [0040]) that includes values of a characteristic (an optical characteristic map [0040]) corresponding to different geographic locations in a worksite (The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field [0006]);
one or more in-situ sensors (one or more in-situ sensors 208 [0039]), configured to detect a value of each additional characteristic of one or more additional characteristics (that sense one or more agricultural characteristics of a field [0039]) corresponding to a geographic area (concurrent with a harvesting operation [0039]; examiner notes that the data would correspond to the location of the machine at the time the data is collected.), the one or more additional characteristics including at least one characteristic of the mobile windrowing machine (geographic position sensor 204 [0067]);
one or more processors (one or more processors or servers 201 [0039]); and
memory (data store 202) storing computer executable instructions that, when executed by the one or more processors, cause the one or more processors (any or all of the systems, components, logic and interactions may be implemented by software that is loaded into a memory and is subsequently executed by a processor [0112]) to:
generating a predictive model (a predictive model or relationship generator (collectively referred to hereinafter as “predictive model generator 210”) [0039]) indicative of a relationship between values of the characteristic (a model that is indicative of a relationship between the values sensed by the in-situ sensor 208 and a value mapped to the field by the prior information map 258 [0044]) and [dry down or windrow shape quality] based on the value of each additional characteristic of the plurality of additional characteristics detected by the one or more in-situ sensors corresponding to the geographic area and a value of the characteristic in the information map corresponding to the geographic area (a model that is indicative of a relationship between the values sensed by the in-situ sensor 208 and a value mapped to the field by the prior information map 258 [0044]);
generate a functional predictive map of the worksite (to generate a functional predictive map 263 [0045]) that maps a plurality of predictive values of [dry down or windrow shape quality] to the plurality of different geographic locations in the worksite (predictive map generator 212 generates a predictive map 264 that predicts the value of the yield [0047]), wherein each predictive value, of the plurality of predictive values, is mapped to a respective geographic location, of the plurality of different geographic locations (he one or more information maps map one or more agricultural characteristic values at different geographic locations of a field [0006]), and is based on the value of the characteristic in the information map (The predictive model can also be generated based on optical characteristic values from the prior information map 258 [0046]) corresponding to the respective geographic location and based on the predictive model (Predictive map generator 212 can use the model generated by predictive model generator 210 [0045])
control the agricultural windrowing machine based on the functional predictive map (which generates control signals based upon the predictive map 264 [0056]).
Vandike does not explicitly teach, however Hamilton teaches:
a plurality of predictive values of dry down or windrow shape quality (to estimate a predicted condition of a windrow formed by the windrower 10 at certain operating parameters [0037])
wherein each predictive value, of the plurality of predictive values (The controller 17 may determine the crop yield and moisture content using information from the sensor(s) 19, and optionally, from other sources (e.g., weather conditions, power consumed by the header 14, historical data such as measurements of prior harvests, planting data, irrigation data, soil quality data, etc.). The controller 17 may use the measured crop yield and moisture content, as well as predicted or current local weather conditions [0037]; at certain operating parameters (e.g., positions of the swathboard 24 and/or the forming shields 22, speed of the header 14, roll pressure of the conditioner rolls 20, ground speed of the windrower 10, etc.) [0037]), is mapped to a respective geographic location (In block 76, the yield and moisture content of the crop material is detected. In block 78, an operating parameter of the agricultural machine is changed in response to the detected yield and moisture content. [0042]), of the plurality of different geographic locations (examiner notes that Hamilton is measuring the area it was about to harvest so therefore the determination is being made in real time in regards to the area it is currently in and therefore the characteristics are specific to that location of the many locations that make up an entire field.)
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Vandike to include the teachings as taught by Hamilton with a reasonable expectation of success. The combination of Vandike and Hamilton would have been obvious to one having ordinary skill in the art at the time of effective filing because the combination is combining prior art elements according to known methods to yield predictable results. Vandike teaches a windowing machine that can control the machine based off of a prediction map generated from sensor data. Vandike does not explicitly teach detecting windrow shape quality but Hamilton does teach the ability to determine windrow shape quality and adjust the control based on a response to that determination. Using the prediction map as taught by Vandike to automatically control and predict the windrow shape quality of Hamilton would yield the predictable result of the claimed invention. Additionally substituting one value taught by Hamilton into the prediction model as taught by Vandike is simple substitution of one known element for another to obtain a predictable result. Hamilton also teaches the benefit of “The controller 17 may use the measured crop yield and moisture content, as well as predicted or current local weather conditions, to estimate a predicted condition of a windrow formed by the windrower 10 at certain operating parameters [Hamilton, 0037]”
Regarding claim 18:
Vandike in view of Hamilton teaches all the limitations of claim 17, upon which this claim is dependent.
Vandike further teaches:
wherein the computer executable instructions, when executed by the one or more processors, cause the one or more processors to control the agricultural windowing machine by controlling (control [0018]) one or more of:
an actuator to control a position of a component of the agricultural windrowing machine (control the position of the header of the agricultural harvester relative to the field surface [0018]);
Hamilton further teaches:
an actuator to control a speed of movement of a component of the agricultural windrowing machine (speed of the header 14, roll pressure of the conditioner rolls 20, ground speed of the windrower 10 [0037]); and
an actuator to control a direction of movement of a component of the agricultural windrowing machine (positions of the swathboard 24 and/or the forming shields 22 [0037]).
Regarding claim 21:
Vandike in view of Hamilton teaches all the limitations of claim 17, upon which this claim is dependent.
Vandike further teaches:
wherein the at least one characteristic corresponding to the agricultural windrowing machine comprises at least one of:
(i) a force used to drive a cutting component of a header of the agricultural windrowing machine (threshing rotor drive force [0018]);
(ii) a speed of a merger belt of the header of the agricultural windrowing machine (examiner is interpreting this limitation in the alternative);
(iii) a position of the merger belt of the header of the agricultural windrowing machine (examiner is interpreting this limitation in the alternative);
(iv) a force used to drive a component of the header of the agricultural windrowing machine, the component different than the cutting component (examiner is interpreting this limitation in the alternative);
(v) an orientation of the agricultural windrowing machine (machine heading [0037]); and
(vi) a height of the cutting component of the header of the agricultural windrowing machine (a vertical position of header 102 (the header height) above ground 111 [0026]).
Regarding claim 22:
Vandike in view of Hamilton teaches all the limitations of claim 21, upon which this claim is dependent.
Hamilton further teaches:
wherein the plurality of additional characteristics further comprise one or more of:
windrow width (a density, height, width, or shape of a windrow formed, or a predicted condition at a future time of a windrow formed by the windrower 10 [0041]);
windrow height (a density, height, width, or shape of a windrow formed, or a predicted condition at a future time of a windrow formed by the windrower 10 [0041]);
windrow density (a density, height, width, or shape of a windrow formed, or a predicted condition at a future time of a windrow formed by the windrower 10 [0041]);
cut quality (examiner is interpreting this limitation in the alternative); and
conditioning quality (form a windrow that is expected to be within a selected moisture range at a future baling time [0040]).
Regarding claim 23:
Vandike in view of Hamilton teaches all the limitations of claim 21, upon which this claim is dependent.
Vandike further teaches:
wherein the characteristic comprises one of vegetative index (vegetative index [0047]), a topographic characteristic (characteristics of a field such as slope [0037]), genotype (examiner is interpreting this limitation in the alternative), soil type (soil type [0037]), soil moisture (soil moisture [0037]), soil nutrient (examiner is interpreting this limitation in the alternative), or an optical characteristic (weed intensity, weed type [0037]).
Regarding claim 24:
Vandike in view of Hamilton teaches all the limitations of claim 1, upon which this claim is dependent.
Vandike further teaches:
wherein the at least one characteristic of the agricultural windrowing machine comprises at least one of:
(i) a force used to drive a cutting component of a header of the agricultural windrowing machine (threshing rotor drive force [0018]);
(ii) a speed of a merger belt of the header of the agricultural windrowing machine (examiner is interpreting this limitation in the alternative);
(iii) a position of the merger belt of the header of the agricultural windrowing machine (examiner is interpreting this limitation in the alternative);
(iv) a force used to drive a component of the header of the agricultural windrowing machine, the component different than the cutting component (examiner is interpreting this limitation in the alternative);
(v) an orientation of the agricultural windrowing machine (machine heading [0037]); and
(vi) a height of the cutting component of the header of the agricultural windrowing machine (a vertical position of header 102 (the header height) above ground 111 [0026]) and
Hamilton further teaches:
wherein the plurality of additional characteristics further comprise one or more of:
windrow width (a density, height, width, or shape of a windrow formed, or a predicted condition at a future time of a windrow formed by the windrower 10 [0041]);
windrow height (a density, height, width, or shape of a windrow formed, or a predicted condition at a future time of a windrow formed by the windrower 10 [0041]);
windrow density (a density, height, width, or shape of a windrow formed, or a predicted condition at a future time of a windrow formed by the windrower 10 [0041]);
cut quality (examiner is interpreting this limitation in the alternative); and
conditioning quality (form a windrow that is expected to be within a selected moisture range at a future baling time [0040]).
Regarding claim 25:
Vandike in view of Hamilton teaches all the limitations of claim 12, upon which this claim is dependent.
Vandike further teaches:
wherein each the second characteristic and third characteristic comprise a different one of:
cut height (a vertical position of header 102 (the header height) above ground 111 [0026]);
machine orientation (machine heading [0037]);
merger belt speed (examiner is interpreting this limitation in the alternative);
merger belt position (examiner is interpreting this limitation in the alternative);
mass flow (examiner is interpreting this limitation in the alternative); and
rotary material flow (examiner is interpreting this limitation in the alternative).
Hamilton further teaches:
windrow width (a density, height, width, or shape of a windrow formed, or a predicted condition at a future time of a windrow formed by the windrower 10 [0041]);
windrow height (a density, height, width, or shape of a windrow formed, or a predicted condition at a future time of a windrow formed by the windrower 10 [0041]);
windrow density (a density, height, width, or shape of a windrow formed, or a predicted condition at a future time of a windrow formed by the windrower 10 [0041]);
cut quality (examiner is interpreting this limitation in the alternative); and
conditioning quality (form a windrow that is expected to be within a selected moisture range at a future baling time [0040]).
Regarding claim 27:
Vandike in view of Hamilton teaches all the limitations of claim 1, upon which this claim is dependent.
Vandike further teaches:
wherein the geographic location of the mobile windrowing machine comprises a first geographic location at a current operation of the mobile windrowing machine (a current geographical location of device 16 [0123]),
the one or more in-situ sensors detect the value of each additional characteristic, of the one or more additional characteristics, during the current operation of the mobile windrowing machine at the first geographic location (In-situ sensors 208 may sense, without limitation, soil characteristic, a crop moisture, a weed intensity, weed location, weed type, a yield, a biomass, a crop state, a power characteristic, a speed, a machine orientation (pitch, roll, direction), tailings characteristics, grain quality, internal material distribution, stalk characteristic, crop height, residue, cleaning fan speed, power usage, etc. In-situ data include data taken from a sensor on-board the agricultural harvester or taken by any sensor where the data are detected during the harvesting operation. [0043]),
the plurality of different geographic locations comprises a second geographic location in the worksite (different locations in the field [0006]), and
the instructions, when executed by the one or more processors, cause the one or more processors to control the mobile windrowing machine at the second geographic location (The predictive map can be output and used in automated machine control. [0006]) based on the predictive value of windrow shape quality mapped to the second geographic location in the functional predictive windrow shape quality map (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 [0006]).
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Vandike et. al. (US 2021/0029878), herein Vandike in view of Hamilton et. al. (US 2023/0049727), herein Hamilton (previously cited 09/16/2025) in further view of Stephens (US 11,930,737), herein Stephens.
Regarding claim 3:
Vandike in view of Hamilton teaches all the limitations of claim 1, upon which this claim is dependent.
Vandike further teaches:
a propulsion subsystem of the mobile windrowing machine (which generates control signals based upon the predictive map 264 [0056]), or
Hamilton further teaches:
a conditioner actuator of the mobile windrowing machine (The controller 17 may adjust the position of the swathboard 24 and/or the forming shields 22, the ground speed of the tractor 12, the header speed, or other operating parameters as crop yield and moisture change [0038]).
Vandike does not explicitly teach, however Stephens teaches:
controlling a merger subsystem of the mobile windrowing machine (an application specific controller that controls the merger system 20 [col 5, lines 36-37]).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Vandike in view of Hamilton to include the teachings as taught by Stephens with a reasonable expectation of success. The combination of Vandike and Stephens would have been obvious to one having ordinary skill in the art at the time of effective filing because the combination is combining prior art elements according to known methods to yield predictable results. Vandike teaches a windowing machine that can control the machine based off of a prediction map generated from sensor data. Vandike does not explicitly teach adjusting the specific features claimed but Stephens does teach the ability to automatically control the claimed feature. Using the prediction map as taught by Vandike to automatically control the actuator of Stephens would yield the predictable result of the claimed invention.
Claim(s) 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Vandike et. al. (US 2021/0029878), herein Vandike in view of Hamilton et. al. (US 2023/0049727), herein Hamilton (previously cited 09/16/2025) in further view of Kemmer et. al. (US 2022/0210975), herein Kemmer.
Regarding claim 14:
Vandike in view of Hamilton teaches all the limitations of claim 12, upon which this claim is dependent.
Vandike further teaches:
wherein controlling the mobile windrowing machine comprises controlling the mobile windrowing machine based on the functional predictive map (which generates control signals based upon the predictive map 264 [0056])
Vandike in view of Hamilton does not explicitly teach, however Kemmer teaches:
obtaining follow-on machine (depend on the machine that is used to pick up the windrow [col 1, lines 11-12]) and operation data (For instance, a combine harvester equipped with a pickup header may be guided to follow a windrow such that the observable center of the windrow is aligned with the center of the header. A baler, on the other hand, may be guided to follow a windrow in a way that enables the material compaction pressure to be distributed equally across the width of the bale. [col 1, lines 12-15) and wherein controlling the mobile windrowing machine comprises controlling the mobile windrowing machine based on the [functional predictive map] and the follow-on machine (selection of an optimal drive path to pick up windrows [col 1, lines 10-12]) and operation data (For instance, a combine harvester equipped with a pickup header may be guided to follow a windrow such that the observable center of the windrow is aligned with the center of the header. A baler, on the other hand, may be guided to follow a windrow in a way that enables the material compaction pressure to be distributed equally across the width of the bale. [col 1, lines 12-15).
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Vandike in view of Hamilton to include the teachings as taught by Kemmer with a reasonable expectation of success. Kemmer teaches the benefits of “different machines may use different drive paths to collect the windrow to optimize downstream processing [Kemmer, col 2, lines 12-16]”.
Claim(s) 26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Vandike et. al. (US 2021/0029878), herein Vandike in view of Hamilton et. al. (US 2023/0049727), herein Hamilton (previously cited 09/16/2025) in further view of Childs et. al. (US 2023/0376041), herein Childs.
Regarding claim 26:
Vandike in view of Hamilton teaches all the limitations of claim 1, upon which this claim is dependent.
Vandike further teaches:
control the mobile windrowing machine to form a windrow based on the functional predictive windrow shape quality map (see quality map as taught by Vandike.) and the follow-on machine (see Childs below.) and operation data (The controller 17 may be configured to adjust the actuators 30, 38, to change the position of the swathboard 24 and/or the forming shields 22 in response to yield and moisture content as detected by the sensor(s) 19 [0036]).
Vandike in view of Hamilton does not explicitly teach, however Childs teaches:
obtain follow-on machine and operation data representing operational characteristics of one or more follow-on machines, different than the mobile windrowing machine, configured to perform a windrow processing operation on the windrow formed by the mobile windrowing machine (Controller 123 can communicate with controller 115, so that controller 115 outputs information to the display of input/output device 120 of work vehicle 100, thereby informing a user of various conditions of baler 101 and bales 110 forming or formed therein [0029]); and
It would have been obvious to one of ordinary skill in the art at the time of the effective filing date of the claimed invention to have modified Vandike in view of Hamilton to include the teachings as taught by Childs with a reasonable expectation of success. The references are all in the same field of endeavor of controlling agricultural equipment. Childs teaches the benefits of “The baler controller sends this information to the tractor controller, which can output to a user interface whether the bale in the bale chamber of the baler is properly forming in terms of its shape and size. For instance, if the forming bale has a larger diameter on the left side compared to the right side, then to obtain a balanced bale the operator, using this information from the user interface, can steer the tractor and thus also the baler rightward so as to cause more crop material from the windrow to fill the right side of the bale chamber compared to the left side of the bale chamber [Childs, 0004]”.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Faust (US 2021/0045283) discloses A crop windrow monitoring system includes an image sensor positioned to include a field of view facing a rearward direction of a power unit, and a visual monitor operable to display an image. A computing device is operable to determine an intended direction of movement of the power unit. The image is displayed on the visual monitor in a first mode having a first magnification when the intended direction of movement includes the rearward direction. The image is displayed on the visual monitor in a second mode having a second magnification and overlaid with indicia indicating a width of the windrow when the intended direction of movement includes the forward direction. The second magnification may be larger than the first magnification.
Bollinger (US 2020/0205345) discloses a system, comprising: an interface configured to receive input defining a target windrow; a windrower comprising a windrow forming assembly configured to form a windrow; one or more sensors; and a computing system configured to control formation of the windrow according to the target windrow based on the input and further based on input from the one or more sensors.
Dilts (US 2019/0084764) discloses A windrow chute assembly includes a plurality of movable chute sections. A first chute section has a first proximal end for receiving material, and a first distal end opposite the first proximal end. The second chute section has a second proximal end for receiving material, and a second distal end opposite the second proximal end. The first and second proximal ends define a transverse axis therebetween. The first and second chute sections are displaceable toward one another to a closed or partially closed configuration to control the width and placement of each windrow. The first and second chute sections are also displaceable away from one another to an open configuration to provide access to rear areas of the combine.
Ferrari (EP 3871481) discloses Agriculture vehicle (1) wherein a vehicle body (3) is provided with a front LIDAR sensor (5) configured to scan an field ahead (Fah) that is the area in front of the vehicle towards which the vehicle is moving and a rear LIDAR sensor (6) configured to scan an a field behind (Fbh) that is a rear area on which the vehicle has previously moved. The vehicle (1) is provided with a GPS system (8) configured to provide position and coordinates of the scanned field ahead (Fah) and of the scanned field behind (Fbh). An electronic unit (10) is configured to compare images of the field ahead (Fah) and of field behind (Fbh) to provide autonomous guidance to the agricultural vehicle and/or to automatize the agricultural operations performed by the agricultural vehicle.
Rotole (EP3315011) discloses A work vehicle (10) for working a swath of crop is disclosed. The work vehicle (10) comprising: at least one ground-engaging wheel (14, 16) or track mounted to the work vehicle (10) and movable in a travel direction (T) along a tread path (40); a first redistribution device mounted to the work vehicle (10) to move crop that is ahead of the at least one ground-engaging wheel (14, 16) or track relative to the travel direction (T); and a second redistribution device mounted to the work vehicle (10) to move crop that is behind the at least one ground-engaging wheel (14, 16) or track relative to the travel direction (T); wherein the first redistribution device is configured to open the swath of crop along substantially only the tread path (40) ahead of the at least one ground-engaging wheel (14, 16) or track relative to the travel direction (T) and the second redistribution device is configured to close the swath of crop along the tread path (40) behind the at least one ground-engaging wheel (14, 16) or track relative to the travel direction (T). Further, a work vehicle train with a lead vehicle (10) and a follower vehicle (62) is disclosed.
Hamilton (US 2022/0207622) discloses a method for use in a farming operation comprising plural stages grouped over a first time period, the farming operation implemented over at least the first time period and a second time period, the method comprising: during the first time period: receiving first parameter information and first field position information corresponding to the first parameter information concerning a first stage; receiving second parameter information and second field position information corresponding to the second parameter information concerning a second stage, the first and second parameter information comprising quality information; determining a difference between the first and second parameter information; and effecting or recommending a change in the farming operation based on the difference.
Patton (US 2015/0089912) discloses An agricultural combine (100) has a windrow control circuit that controls the profile of windrow (154) based upon signals received from a sensor (152).
Franet (US 2003/0024228) discloses A windrow merging implement with a pick-up, a conveyor and a connecting hitch or structure is provided in combination with a mowing vehicle, with the connecting hitch being releasably secured to a rear end of the vehicle chassis. The mowing vehicle is operative to form windrows of crop in one or more of three locations, namely, a central location passing longitudinally between the wheels of the vehicle and one on each side of the vehicle. The windrow merging implement may be positioned at either side of the vehicle for picking up the windrow deposited there, and includes a conveyor structure for either depositing the picked up windrow upon or alongside the centrally deposited windrow. Also disclosed is an embodiment where the windrow merging implement picks up and displaces transversely the centrally deposited windrow. A further embodiment discloses two windrow merging implements which respectively pick up the windrows at the opposite sides of the vehicle and convey them inwardly so as to be combined with the centrally located windrow.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Scott R Jagolinzer whose telephone number is (571)272-4180. The examiner can normally be reached M-Th 8AM - 4PM Eastern.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Christian Chace can be reached at (571)272-4190. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Scott R. Jagolinzer
Examiner
Art Unit 3665
/S.R.J./Examiner, Art Unit 3665 /CHRISTIAN CHACE/Supervisory Patent Examiner, Art Unit 3665