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 .
Status of Claims
This final action is in response to Applicant’s amended filing of 04/13/2026.
Claims 1-10 and 12-21 are currently pending and have been examined. Applicant has amended claims 1-3, 8-10, 14, and 17-18; cancelled claim 11; and added new claim 21.
Response to Arguments
Applicant’s arguments with respect to claims 1-20 rejected under 35 USC § 102(a)(1) and 103 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claims 1-3, 5-6, 9-10, 12, 15, 17-19, and 21 are rejected under 35 U.S.C. 103 as unpatentable over Debbaut (US 20180325014 A1) in view of Meltzer et al. (US 20210287001 A1).
Regarding claim 1, Debbaut discloses an agricultural system (see at least abstract) comprising:
one or more processors (see at least ¶ [0050] disclosing a computer program running on a computer embodied as a processor);
and memory storing instructions (see at least ¶ [0050] disclosing a computer program stored on memory running on a computer embodied as a processor), executable by the one or more processors, that, when executed by the one or more processors, cause the one or more processors to perform a computer implemented harvest readiness monitoring method (claim 9) comprising:
obtaining one or more of historical data or worksite data (see at least ¶ [0090-0097] disclosing an unmanned aerial vehicle (UAV) gathering “first pass” overview field data from a first altitude as the basis for controlling the UAV during a “second pass” gathering secondary field data from a second altitude, the overview and secondary field data including objects of the field, the boundaries of the field, and crop location, width, height, and shape data);
identifying one or more monitoring locations at a worksite to be monitored for the one or more harvest readiness attributes based on the one or more of historical data or worksite data (see at least ¶ [0090-0097] disclosing an unmanned aerial vehicle (UAV) gathering “first pass” overview field data from a first altitude as the basis for controlling the UAV during a “second pass” gathering secondary field data from a second altitude, the secondary field data including crop location, width, height, and shape data);
and controlling one or more drones based on the one or more monitoring locations to detect one or more harvest readiness attributes corresponding to each of the one or more monitoring locations (see at least ¶ [0090-0095] disclosing an unmanned aerial vehicle (UAV) gathering “first pass” overview field data from a first altitude as the basis for controlling the UAV during a “second pass” gathering secondary field data from a second altitude, where an associated controller determines vehicle control instructions to follow a vehicle route based on crop location).
Debbaut does not explicitly disclose selecting, based on the one or more of historical data or worksite data, one or more harvest readiness attributes to be monitored from a set of harvest readiness attributes.
However, Meltzer suggests selecting, based on the one or more of historical data or worksite data, one or more harvest readiness attributes to be monitored from a set of harvest readiness attributes (see at least ¶ [0069], [0127], and [0165-0168] disclosing a system to train and predict crop size and yield based on historical information of a UAV collecting images of a given fruit and comparing their size by position in the plot).
It would be obvious to one of ordinary skill in the art before the effective filing date of the present invention to incorporate the historical size comparison of Meltzer into the field monitoring and data collecting methods of Debbaut with a reasonable expectation of success because both inventions are directed toward using UAVs to operate and collect agricultural field information to facilitate harvesting. This would allow the harvesting system to anticipate when crops are ready to be harvested and can more readily harvest the ripe crops at the earliest possibility.
Regarding claim 9, Debbaut discloses a computer implemented harvest readiness monitoring method (see at least abstract) comprising:
identifying one or more monitoring locations at a worksite to be monitored for one or more harvest readiness attributes based on the values corresponding to the plurality of different locations of the worksite (see at least ¶ [0090-0097] disclosing an unmanned aerial vehicle (UAV) gathering “first pass” overview field data from a first altitude as the basis for controlling the UAV during a “second pass” gathering secondary field data from a second altitude, the secondary field data including crop location, width, height, and shape data);
and controlling one or more drones based on the one or more monitoring locations to detect one or more harvest readiness attributes corresponding to each of the one or more monitoring locations (see at least ¶ [0090-0095] disclosing an unmanned aerial vehicle (UAV) gathering “first pass” overview field data from a first altitude as the basis for controlling the UAV during a “second pass” gathering secondary field data from a second altitude, where an associated controller determines vehicle control instructions to follow a vehicle route based on crop location).
Debbaut does not explicitly disclose obtaining historical data including values corresponding to a plurality of different locations of a worksite, wherein the values comprise one or more of:
historical crop moisture values;
historical material application values;
historical planting values;
historical tillage values;
historical operating parameter values;
or historical harvest readiness values.
However, Meltzer suggests obtaining historical data including values corresponding to a plurality of different locations of a worksite, wherein the values comprise one or more of:
historical crop moisture values;
historical material application values;
historical planting values;
historical tillage values;
historical operating parameter values;
or historical harvest readiness values (see at least ¶ [0069], [0127], and [0165-0168] disclosing a system to train and predict crop size and yield based on historical information of a UAV collecting images of a given fruit and comparing their size by position in the plot).
It would be obvious to one of ordinary skill in the art before the effective filing date of the present invention to incorporate the historical size comparison of Meltzer into the field monitoring and data collecting methods of Debbaut with a reasonable expectation of success because both inventions are directed toward using UAVs to operate and collect agricultural field information to facilitate harvesting. This would allow the harvesting system to anticipate when crops are ready to be harvested and can more readily harvest the ripe crops at the earliest possibility.
Regarding claim 17, Debbaut discloses an agricultural system (see at least abstract) comprising:
one or more processors (see at least ¶ [0050] disclosing a computer program running on a computer embodied as a processor);
and memory storing instructions (see at least ¶ [0050] disclosing a computer program stored on memory running on a computer embodied as a processor), executable by the one or more processors, that, when executed by the one or more processors, cause the one or more processors to:
obtain data corresponding to a worksite (see at least ¶ [0090-0097] disclosing an unmanned aerial vehicle (UAV) gathering “first pass” overview field data from a first altitude as the basis for controlling the UAV during a “second pass” gathering secondary field data from a second altitude, the overview and secondary field data including objects of the field, the boundaries of the field, and crop location, width, height, and shape data);
identify a monitoring location at the worksite to be monitored for one or more harvest readiness attributes based on data corresponding to the worksite (see at least ¶ [0090-0097] disclosing an unmanned aerial vehicle (UAV) gathering “first pass” overview field data from a first altitude as the basis for controlling the UAV during a “second pass” gathering secondary field data from a second altitude, the overview and secondary field data including objects of the field, the boundaries of the field, and crop location, width, height, and shape data);
and control a drone during a worksite sensing operation based on the monitoring location to detect one or more harvest readiness attributes corresponding to the monitoring location and to generate harvest readiness sensor data indicative of the one or more harvest readiness attributes corresponding to the monitoring location (see at least ¶ [0090-0095] disclosing an unmanned aerial vehicle (UAV) gathering “first pass” overview field data from a first altitude as the basis for controlling the UAV during a “second pass” gathering secondary field data from a second altitude, where an associated controller determines vehicle control instructions to follow a vehicle route based on crop location);
determine readiness for harvesting based on the harvest readiness sensor data (see at least ¶ [0058-0064] and [0077] disclosing using field data to control a machine for picking up crop material based on prioritizing crop material with particular characteristics such as height, width, cross-sectional area, volume, or shape).
Debbaut does not explicitly disclose the data corresponding to the worksite comprises values generated prior to the worksite sensing operation performed by the drone.
However, Meltzer suggests the data corresponding to the worksite comprises values generated prior to the worksite sensing operation performed by the drone (see at least ¶ [0069], [0127], and [0165-0168] disclosing a system to train and predict crop size and yield based on historical information of a UAV collecting images of a given fruit and comparing their size by position in the plot).
It would be obvious to one of ordinary skill in the art before the effective filing date of the present invention to incorporate the historical size comparison of Meltzer into the field monitoring and data collecting methods of Debbaut with a reasonable expectation of success because both inventions are directed toward using UAVs to operate and collect agricultural field information to facilitate harvesting. This would allow the harvesting system to anticipate when crops are ready to be harvested and can more readily harvest the ripe crops at the earliest possibility.
Regarding claim 2, Debbaut discloses the one or more of historical data or worksite data includes one or more of:
vegetation index values corresponding to different locations of the worksite;
topographic attribute values corresponding to different locations of the worksite;
yield values corresponding to different locations of the worksite (see at least ¶ [0077] and [0090-0097] disclosing an unmanned aerial vehicle (UAV) gathering “second pass” secondary field data from a second altitude, secondary field data including crop location, width, height, and shape);
or soil attribute values corresponding to different locations of the worksite.
Regarding claim 3, Debbaut does not explicitly disclose the one or more of historical data or worksite data includes one or more of:
historical crop moisture values corresponding to different locations of the worksite;
historical material application values corresponding to different locations of the worksite;
historical planting values corresponding to different locations of the worksite;
historical tillage values corresponding to different locations of the worksite;
historical operating parameter values corresponding to different locations of the worksite;
or historical harvest readiness values corresponding to different locations of the worksite.
However, Meltzer suggests historical harvest readiness values corresponding to different locations of the worksite (see at least ¶ [0069], [0127], and [0165-0168] disclosing a system to train and predict crop size and yield based on historical information of a UAV collecting images of a given fruit and comparing their size by position in the plot).
It would be obvious to one of ordinary skill in the art before the effective filing date of the present invention to incorporate the historical size comparison of Meltzer into the field monitoring and data collecting methods of Debbaut with a reasonable expectation of success because both inventions are directed toward using UAVs to operate and collect agricultural field information to facilitate harvesting. This would allow the harvesting system to anticipate when crops are ready to be harvested and can more readily harvest the ripe crops at the earliest possibility.
Regarding claim 5, Debbaut discloses the one or more harvest readiness attributes include one or more crop readiness attributes indicative of a readiness of crop plants of the worksite for harvesting (see at least ¶ [0058-0064] and [0077] disclosing using field data to control a machine for picking up crop material based on prioritizing crop material with particular characteristics such as height, width, cross-sectional area, volume, or shape).
Regarding claims 6 and 12, Debbaut discloses controlling travel of a drone, of the one or more drones, relative to a monitoring location, of the one or more monitoring locations, to detect, with one or more harvest readiness sensors on the drone, one or more harvest readiness attributes corresponding to the monitoring location (see at least ¶ [0058-0064], [0067], [0077], and [0097] disclosing controlling the UAV to collect field data via a camera to determine crop material with particular characteristics such as height, width, cross-sectional area, volume, or shape).
Regarding claim 10, Debbaut does not explicitly disclose controlling the one or more drones comprises controlling the one or more drones in a current harvest season, wherein the historical data comprises data obtained prior to the current harvest season.
However, Meltzer suggests controlling the one or more drones comprises controlling the one or more drones in a current harvest season, wherein the historical data comprises data obtained prior to the current harvest season (see at least ¶ [0069], [0127], and [0165-0168] disclosing a system to train and predict crop size and yield based on historical information of a UAV collecting images of a given fruit and comparing their size by position in the plot).
It would be obvious to one of ordinary skill in the art before the effective filing date of the present invention to incorporate the historical size comparison of Meltzer into the field monitoring and data collecting methods of Debbaut with a reasonable expectation of success because both inventions are directed toward using UAVs to operate and collect agricultural field information to facilitate harvesting. This would allow the harvesting system to anticipate when crops are ready to be harvested and can more readily harvest the ripe crops at the earliest possibility.
Regarding claim 15, Debbaut discloses controlling travel of a drone, of the one or more drones, relative to a monitoring location, of the one or more monitoring locations, to detect, as one or more harvest readiness attributes corresponding to the monitoring location, one or more crop readiness attributes corresponding to the monitoring location (see at least ¶ [0058-0064], [0067], [0077], and [0097] disclosing controlling the UAV to collect field data via a camera to determine crop material with particular characteristics such as height, width, cross-sectional area, volume, or shape).
Regarding claim 18, Debbaut discloses control travel of the drone relative to the monitoring location, to detect, with one or more harvest readiness sensors on the drone, one or more harvest readiness attributes corresponding to the monitoring location (see at least ¶ [0058-0064], [0067], [0077], and [0097] disclosing controlling the UAV to collect field data via a camera to determine crop material with particular characteristics such as height, width, cross-sectional area, volume, or shape).
Regarding claim 19, Debbaut discloses the one or more harvest readiness attributes include one or more crop plant readiness attributes corresponding to the monitoring location and wherein the instructions, when executed by the one or more processors, cause the one or more processors to determine readiness for harvesting by determining readiness of crop plants corresponding to the monitoring location for harvesting based on the one or more crop plant readiness attributes corresponding to the monitoring location (see at least ¶ [0058-0064], [0067], [0077], and [0097] disclosing controlling the UAV to collect field data via a camera to determine crop material with particular characteristics such as height, width, cross-sectional area, volume, or shape).
Regarding claim 21, Debbaut does not explicitly disclose the historical data comprises data obtained from a source other than the one or more drones.
However, Meltzer suggests the historical data comprises data obtained from a source other than the one or more drones (see at least ¶ [0069], [0073-0074], [0086], [0127], and [0165-0168] disclosing a system to train and predict crop size and yield based on historical information of a UAV collecting images of a given fruit and comparing their size by position in the plot, where that data is stored in memory devices in servers).
It would be obvious to one of ordinary skill in the art before the effective filing date of the present invention to incorporate the historical size comparison of Meltzer into the field monitoring and data collecting methods of Debbaut with a reasonable expectation of success because both inventions are directed toward using UAVs to operate and collect agricultural field information to facilitate harvesting. This would allow the harvesting system to anticipate when crops are ready to be harvested and can more readily harvest the ripe crops at the earliest possibility.
Claims 4, 16, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Debbaut in view of Meltzer et al., as applied in claims 1, 9, and 17 above, and in view of Benkert et al. (US 20160019560 A1).
Regarding claim 4, the combination of Debbaut and Meltzer does not explicitly disclose the one or more harvest readiness attributes include one or more worksite readiness attributes indicative of a readiness of the worksite for harvesting.
However, Benkert suggests the one or more harvest readiness attributes include one or more worksite readiness attributes indicative of a readiness of the worksite for harvesting (see at least ¶ [0045] and [0050-0051] disclosing an agricultural situational awareness tool embodied as an unmanned aerial vehicle (UAV) that performs a crop survey of a field, collecting and/or retrieving from a server weather data present at a farm).
It would be obvious to one of ordinary skill in the art before the effective filing date of the present invention to incorporate the weather data considerations of Benkert into the combination of Debbaut and Meltzer with a reasonable expectation of success because all inventions are directed toward using UAVs to operate and collect agricultural field information to facilitate harvesting. It would be clear to one of ordinary skill in the art to take inclement weather conditions into account as part of determining whether a field is ready to be harvested.
Regarding claim 16, the combination of Debbaut and Meltzer does not explicitly disclose controlling travel of a drone, of the one or more drones, relative to a monitoring location, of the one or more monitoring locations, to detect, as one or more harvest readiness attributes corresponding to the monitoring location, one or more worksite readiness attributes corresponding to the monitoring location.
However, Benkert suggests controlling travel of a drone, of the one or more drones, relative to a monitoring location, of the one or more monitoring locations, to detect, as one or more harvest readiness attributes corresponding to the monitoring location, one or more worksite readiness attributes corresponding to the monitoring location (see at least ¶ [0045] and [0050-0051] disclosing an agricultural situational awareness tool embodied as an unmanned aerial vehicle (UAV) that performs a crop survey of a field, collecting and/or retrieving from a server weather data present at a farm).
It would be obvious to one of ordinary skill in the art before the effective filing date of the present invention to incorporate the weather data considerations of Benkert into the combination of Debbaut and Meltzer with a reasonable expectation of success because all inventions are directed toward using UAVs to operate and collect agricultural field information to facilitate harvesting. It would be clear to one of ordinary skill in the art to take inclement weather conditions into account as part of determining whether a field is ready to be harvested.
Regarding claim 20, the combination of Debbaut and Meltzer does not explicitly disclose the one or more harvest readiness attributes include one or more worksite readiness attributes of an area of the worksite corresponding to the monitoring location and wherein the instructions, when executed by the one or more processors, cause the one or more processors to determine readiness for harvesting by determining readiness of the area of the worksite corresponding to the monitoring location for harvesting based on the one or more worksite readiness attributes corresponding to area of the worksite corresponding to the monitoring location.
However, Benkert suggests the one or more harvest readiness attributes include one or more worksite readiness attributes of an area of the worksite corresponding to the monitoring location and wherein the instructions, when executed by the one or more processors, cause the one or more processors to determine readiness for harvesting by determining readiness of the area of the worksite corresponding to the monitoring location for harvesting based on the one or more worksite readiness attributes corresponding to area of the worksite corresponding to the monitoring location (see at least ¶ [0045] and [0050-0051] disclosing an agricultural situational awareness tool embodied as an unmanned aerial vehicle (UAV) that performs a crop survey of a field, collecting and/or retrieving from a server weather data present at a farm).
It would be obvious to one of ordinary skill in the art before the effective filing date of the present invention to incorporate the weather data considerations of Benkert into the combination of Debbaut and Meltzer with a reasonable expectation of success because all inventions are directed toward using UAVs to operate and collect agricultural field information to facilitate harvesting. It would be clear to one of ordinary skill in the art to take inclement weather conditions into account as part of determining whether a field is ready to be harvested.
Claims 7-8 and 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over Debbaut in view of Meltzer et al., as applied in claims 1 and 9 above, and in view of Maor et al. (US 20220046859 A1).
Regarding claims 7 and 13, the combination of Debbaut and Meltzer does not disclose controlling travel of a drone, of the one or more drones, relative to a monitoring location, of the one or more monitoring locations, to exert a force on a crop plant corresponding to the monitoring location and to detect, with one or more harvest readiness sensors on the drone, one or more harvest readiness attributes corresponding to the monitoring location after exertion of force on the crop plant.
However, Maor suggests controlling travel of a drone, of the one or more drones, relative to a monitoring location, of the one or more monitoring locations, to exert a force on a crop plant corresponding to the monitoring location and to detect, with one or more harvest readiness sensors on the drone, one or more harvest readiness attributes corresponding to the monitoring location after exertion of force on the crop plant (see at least ¶ [0017] and [0020-0023] disclosing UAVs configured to harvest ripe fruit based on detection and tactile feedback to determine if the fruit is ready to be plucked, wherein a pruning arm is used to apply force to the branch to disconnect the fruit from it).
It would be obvious to one of ordinary skill in the art before the effective filing date of the present invention to incorporate the plucking functionality of Maor into the combination of Debbaut and Meltzer with a reasonable expectation of success because all inventions are directed toward using UAVs to operate and collect agricultural field information to facilitate harvesting. While Debbaut does not explicitly disclose the UAV operations facilitating direct harvesting, both inventions gather data to determine if crops/fruits are ready to be harvested, in order to facilitate said harvesting. Maor simply demonstrates the next step in the process and harvests said crops/fruits after determining they are ready to harvest.
Regarding claims 8 and 14, Debbaut discloses sensing, with one or more harvest readiness sensors, the material of the crop plant to detect one or more harvest readiness attributes (see at least ¶ [0058-0064], [0067], [0077], and [0097] disclosing controlling the UAV to collect field data via a camera to determine crop material with particular characteristics such as height, width, cross-sectional area, volume, or shape).
The combination of Debbaut and Meltzer does not explicitly disclose controlling travel of a drone, of the one or more drones, relative to a monitoring location, of the one or more monitoring locations, to remove material of a crop plant from the crop plant.
However, Maor suggests disclose controlling travel of a drone, of the one or more drones, relative to a monitoring location, of the one or more monitoring locations, to remove material of the crop plant from the crop plant (see at least ¶ [0017] and [0020-0023] disclosing UAVs configured to harvest ripe fruit based on detection and tactile feedback to determine if the fruit is ready to be plucked, wherein a pruning arm is used to apply force to the branch to disconnect the fruit from it).
It would be obvious to one of ordinary skill in the art before the effective filing date of the present invention to incorporate the plucking functionality of Maor into the combination of Debbaut and Meltzer with a reasonable expectation of success because all inventions are directed toward using UAVs to operate and collect agricultural field information to facilitate harvesting. While Debbaut does not explicitly disclose the UAV operations facilitating direct harvesting, both inventions gather data to determine if crops/fruits are ready to be harvested, in order to facilitate said harvesting. Maor simply demonstrates the next step in the process and harvests said crops/fruits after determining they are ready to harvest.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JARED C BEAN whose telephone number is (571)272-5255. The examiner can normally be reached 7:30AM - 5:00PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Navid Z Mehdizadeh can be reached at (571) 272-7691. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/J.C.B./Examiner, Art Unit 3669
/NAVID Z. MEHDIZADEH/Supervisory Patent Examiner, Art Unit 3669
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