DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
2. Applicant's arguments filed 01/29/2026 have been fully considered but they are not persuasive.
3. Applicant argues the amended claim(s) 1 is/are allowable over Stanhope et al. (US-20210300547-A1). Applicant continues, Stanhope has not been shown to disclose, the emended features of “identify a priority order of the one or more attributes in the one or more measurement areas lateral of the agricultural work machine; obtain, based at least in part on the priority order of the one or more attributes, the sensor data indicative of the one or more attributes in the one or more measurement areas lateral of the agricultural work machine,” as recited in amended independent claim 1.
4. Indeed, Stanhope does not teach the newly amended feature(s) mentioned above. As such, this amendment has necessitated additional reference Tamatani (US-20250068172-A1) which teaches, in brief, when generating a path to a field, or a path from a field to another place, based on the attribute information of each road on the map, the management device 600 generates as a path for the work vehicle 100 at least one of a path that gives priority to agricultural roads, a path that gives priority to roads following along a particular geographic feature, or a path that gives priority to roads on which satellite signals are properly received (Tamatani, in at least Fig. 1, and [00184]). Examiner notes, generating a path that gives priority to roads on which satellite signals are properly received, encompasses identifying a priority order of the one or more attributes, such as the location. Receiving satellite signals properly, is obtaining the sensor data (e.g., GNSS sensor that receives signal from satellites and determines the location) indicative of the one or more attributes in the one or more measurement areas lateral of the agricultural work machine, based at least in part on the priority order of the one or more attributes.
5. As such, Stanhope, in view of Tamatani, teaches each and every limitation of these claims and this argument is moot.
6. Applicant argues the amended claim(s) 11 is/are allowable over Stanhope et al. (US-20210300547-A1). Applicant continues, Stanhope has not been shown to disclose, “generating a travel plan for a drone, the travel plan including a plurality of monitoring locations and a monitoring sequence defining an order in which the drone is to travel between each monitoring location of the plurality of monitoring locations, wherein: the plurality of locations corresponds to a corresponding measurement area ... each monitoring location of the plurality of monitoring locations, defines a location to position the drone to have a sensor system, disposed on the drone, detect a plurality of attributes in the corresponding measurement area,” as recited in amended independent claim 11. (Emphasis added).
7. However, in regard to the limitation of “a monitoring sequence defining an order in which the drone is to travel between each monitoring location of the plurality of monitoring locations,” Stanhope discloses at (304), the method 300 includes controlling, with the computing system, the operation of a propulsion system of the UAV such that the UAV is flown relative to a field and landed at a data collection point within the field (Stanhope, in at least Figs. 2, 7, and [0043]). The data collection point is the monitoring location. While one data collection point is a monitoring sequence of one monitoring location, further Stanhope discloses the UAV 100 is configured to take off from the landing pad 202, fly over a field (e.g., an agricultural field), and land at one or more data collection points within the field (Stanhope, in at least Figs. 2, 7, and [0026]). That is, stanhope discloses flying and navigating to one or more data collection points which necessarily encompasses defining an order in which the drone is to travel between the collection points or the monitoring locations. As such, Stanhope discloses generating a travel plan for a drone, the travel plan including a plurality of monitoring locations and a monitoring sequence defining an order in which the drone is to travel between each monitoring location of the plurality of monitoring locations.
8. In regard to the limitation of “the plurality of locations corresponds to a corresponding measurement area,” Stanhope discloses one or more sensors 118 are supported on the UAV 100. When the UAV 100 has landed at a data collection point within the field, the sensor(s) 118 are configured to capture data indicative of one or more field characteristics of the field at such data collection point (Stanhope, in at least Figs. 2, 7, and [0029 & 0043]). As mentioned above, the UAV captures/measures one or more field characteristics of the field, by using its sensors, at the collection point. That means, each collection point corresponds to an area that data is captured or measured. Accordingly, Stanhope discloses the plurality of locations corresponds to a corresponding measurement area.
9. In regard to the limitation of “defines a location to position the drone,” and “detect a plurality of attributes in the corresponding measurement area,” Stanhope discloses one or more sensors 118 are supported on the UAV 100. When the UAV 100 has landed at a data collection point within the field, the sensor(s) 118 are configured to capture data indicative of one or more field characteristics of the field at such data collection point. Moreover, the sensor(s) 118 are configured to capture any other type(s) of field characteristic data, such as the top field surface profile, seedbed depth, soil moisture content, and/or the like. At (304), the method 300 includes controlling, with the computing system, the operation of a propulsion system of the UAV such that the UAV is flown relative to a field and landed at a data collection point within the field (Stanhope, in at least Figs. 2, 7, and [0029 & 0043]). As mentioned above, when the UAV 100 has landed at a data collection point within the field, the sensor(s) 118 are configured to capture data indicative of one or more field characteristics of the field at such data collection point. The landing location of the UAV defines a location to position the drone. That means, the landing location is the defined location to have a sensor system, disposed on the drone, to detect a plurality of attributes in the corresponding measurement area. Furthermore, capturing data indicative of one or more field characteristics of the field is detecting a plurality of attributes in the corresponding measurement area.
10. As such, teaches each and every limitation of these claims and this argument is unpersuasive.
11. Applicant argues the amended claim(s) 18 is/are allowable over Stanhope et al. (US-20210300547-A1). Applicant continues, “generate a travel plan for the drone based on the one or more characteristics of the obstruction at the worksite,” as recited in amended independent claim 18.
12. Indeed, Stanhope does not teach the newly amended feature(s) mentioned above. As such, this amendment has necessitated additional reference Menzel et al. (US-20190094861-A1) which teaches, in brief, the one or more processors are further configured to modify the flight path of the unmanned aerial vehicle 600 based on detected obstacles to generate a collision free flight path to the desired target position avoiding obstacles in the vicinity of the unmanned aerial vehicle (Menzel, in at least Fig. 1, and [0085]). Examiner notes, generating a collision free flight path to the desired target position avoiding obstacles in the vicinity of the unmanned aerial vehicle is generating a travel plan for the drone based on the one or more characteristics of the obstruction at the worksite, especially when the drone is used in a worksite.
13. As such, Stanhope, in view of Menzel, teaches each and every limitation of these claims and this argument is moot.
14. Applicant argues dependent claim(s) is/are patentable by the virtue of their dependency on independent one of the independent claims and the additional features recited in the dependent claims.
15. This argument is unpersuasive as each independent claim and dependent claim has been fully rejected and for the reasons given above.
Prior Art of Record
16. The Examiner has cited particular paragraphs or columns and line numbers in the references applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested of the applicant in preparing responses, to fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner. The prompt development of a clear issue requires that the replies of the Applicant meet the objections to and rejections of the claims. Applicant should also specifically point out the support for any amendments made to the disclosure (see MPEP §2163.06). Applicant is reminded that the Examiner is entitled to give the Broadest Reasonable Interpretation (BRI) of the language of the claims. Furthermore, the Examiner is not limited to Applicant’s definition which is not specifically set forth in the claims. SEE MPEP 2141.02 [R-07.2015] VI. PRIOR ART MUST BE CONSIDERED IN ITS ENTIRETY, INCLUDING DISCLOSURES THAT TEACH AWAY FROM THE CLAIMS: A prior art reference must be considered in its entirety, i.e., as a whole, including portions that would lead away from the claimed invention. W.L. Gore & Associates, Inc. v. Garlock, Inc., 721 F.2d 1540, 220 USPQ 303 (Fed. Cir. 1983), cert, denied, 469 U.S. 851 (1984). See also MPEP §2123.
Claim Rejections - 35 USC § 102
17. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
18. Claim(s) 11, 13, and 15
is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Stanhope et al. (US-20210300547-A1).
In regard to claim 11
, Stanhope discloses a computer implemented method comprising (Stanhope, in at least [0018], discloses systems and methods for anchoring unmanned aerial vehicles to surfaces):
identifying one or more measurement areas lateral of, at least, a portion of an agricultural work machine (Stanhope, in at least [0045], discloses the sensor(s) 118 captures data indicative of one or more characteristics of the field, such as the soil hardness, soil moisture, seedbed surface profile, seedbed depth, and/or the like. Thereafter, the computing system 206 is configured to receive the captured data from the sensor(s) 118 (e.g., via the communicative link 208). Examiner notes, capturing data of the field encompasses identifying one or more measurement areas lateral of, at least, a portion of an agricultural work machine, especially when the identified measurement areas are lateral of the agricultural work machine):
generating a travel plan for a drone, the travel plan including a plurality of monitoring locations and a monitoring sequence defining an order in which the drone is to travel between each monitoring location of the plurality of monitoring locations (Stanhope, in at least Figs. 2, 7, and [0026 & 0029 & 0043], discloses the UAV 100 is configured to take off from the landing pad 202, fly over a field (e.g., an agricultural field), and land at one or more data collection points [i.e., a monitoring sequence defining an order in which the drone is to travel between each monitoring location of the plurality of monitoring locations] within the field. After capturing data and/or soil samples at the data collection point(s), the UAV 100 may return to and land on the landing pad 202. One or more sensors 118 are supported on the UAV 100. When the UAV 100 has landed at a data collection point within the field, the sensor(s) 118 are configured to capture data indicative of one or more field characteristics of the field at such data collection point. At (304), the method 300 includes controlling, with the computing system, the operation of a propulsion system of the UAV such that the UAV is flown relative to a field and landed at a data collection point within the field. Flying a UAV to a data collection point encompasses generating a travel plan for the drone),
wherein:
the plurality of monitoring locations corresponds to a corresponding measurement area of the one or more measurement areas lateral of at least, the portion of the agricultural work machine (Stanhope, in at least Figs. 2, 7, and [0029 & 0043], discloses one or more sensors 118 are supported on the UAV 100. When the UAV 100 has landed at a data collection point within the field, the sensor(s) 118 are configured to capture data indicative of one or more field characteristics of the field at such data collection point. At (304), the method 300 includes controlling, with the computing system, the operation of a propulsion system of the UAV such that the UAV is flown relative to a field and landed at a data collection point within the field. Examiner notes, the collection points are the plurality of monitoring locations corresponds to a corresponding measurement area of the one or more measurement areas lateral of at least, the portion of the agricultural work machine, especially when the collection point is lateral of the agricultural work machine), and
each monitoring location, of the plurality of monitoring locations, defines a location to position the drone to have a sensor system, disposed on the drone, detect a plurality of attributes in the corresponding measurement area of the one or more measurement areas lateral of, at least, the portion of the agricultural work machine relative to a travel direction of the agricultural work machine on a current pass (Stanhope, in at least Figs. 2, 7, and [0029 & 0043], discloses one or more sensors 118 are supported on the UAV 100. When the UAV 100 has landed at a data collection point within the field, the sensor(s) 118 are configured to capture data indicative of one or more field characteristics of the field at such data collection point. Moreover, the sensor(s) 118 are configured to capture any other type(s) of field characteristic data, such as the top field surface profile, seedbed depth, soil moisture content, and/or the like. At (304), the method 300 includes controlling, with the computing system, the operation of a propulsion system of the UAV such that the UAV is flown relative to a field and landed at a data collection point [i.e., one or more monitoring locations] within the field. Flying a UAV to a data collection point encompasses generating a travel plan for the UAV. Accordingly, Stanhope discloses one or more measurement areas lateral of, at least, the portion of the agricultural work machine relative to a travel direction of the agricultural work machine on a current pass, especially when the collection points of the UAV are performed in areas lateral to the travel direction of the agricultural machine on the current pass):
controlling positioning of the drone relative to an agricultural work machine based on the travel plan (Stanhope, in at least Figs. 1 and 7, and [0043], discloses at (304), the method 300 includes controlling, with the computing system, the operation of a propulsion system of the UAV such that the UAV is flown relative to a field and landed at a data collection point within the field. Examiner notes, as mentioned above, the UAV such that the UAV is flown relative to the field which could easily be converted to a relative position with respect to the agricultural work machine. Furthermore, flying a drone to a data collection point is controlling positioning of the drone based on the travel plan);
detecting, with the sensor system disposed on the drone, the plurality of attributes (Stanhope, in at least Fig. 2, and [0029], discloses one or more sensors 118 are supported on the UAV 100 [i.e., a sensor system disposed on the drone]. When the UAV 100 has landed at a data collection point within the field, the sensor(s) 118 are configured to capture data indicative of one or more field characteristics [i.e., detecting … the plurality of attributes ] of the field at such data collection point. Moreover, the sensor(s) 118 are configured to capture any other type(s) of field characteristic data, such as the top field surface profile, seedbed depth, soil moisture content, and/or the like) ;
generating, with the sensor system, sensor data indicative of the plurality of attributes in the one or more measurement areas lateral of, at least, the portion of the agricultural work machine (Stanhope, in at least Fig. 7, and [0045], discloses after the UAV is anchored to the field, at (308), the method 300 includes receiving, with the computing system, sensor data indicative of a field characteristic of the field [i.e., generating, with the sensor system, sensor data indicative of the plurality of attributes]);
identifying the plurality of attributes in the one or more measurement areas lateral of, at least, the portion of the agricultural work machine based on the sensor data indicative of the plurality of attributes in the one or more measurement areas lateral of, at least, the portion of the agricultural work machine (Stanhope, in at least [0045], discloses the sensor(s) 118 captures data indicative of one or more characteristics of the field, such as the soil hardness, soil moisture, seedbed surface profile, seedbed depth, and/or the like. Thereafter, the computing system 206 is configured to receive the captured data from the sensor(s) 118 (e.g., via the communicative link 208)); and
generating a control signal based on the identified plurality of attributes in the one or more measurement areas lateral of, at least, the portion of the agricultural work machine (Stanhope, in at least Fig. 7, and [0049], discloses at (316), the method 300 includes controlling, with the computing system, the operation of the anchoring device such that the anchoring device engages landing pad to anchor the UAV to the landing surface after the UAV has landed on the landing pad).
In regard to claim 13
, Stanhope discloses the computer implemented method of claim 11 and further comprising:
identifying one or more characteristics of an obstruction at a worksite, the one or more characteristics comprising one or more of a location of the obstruction or a future location of the obstruction (Stanhope, in at least [0050], discloses the UAV 100 identifies obstacles (e.g., rocks, standing water, excessively wet spots, and/or the like) [i.e., a location of the obstruction] within the field at the data collection point(s). ); and
generating the travel plan based, at least in part, on the identified one or more characteristics of the obstruction (Stanhope, in at least [0050], discloses the operation of the agricultural machine 10 is controlled such that the machine 10 avoids the identified obstacles which encompasses generating the travel plan based on the one or more characteristics of the obstruction).
In regard to claim 15
, Stanhope discloses the computer implemented method of claim 13 and further comprising:
identifying the monitoring sequence of the travel plan based, at least in part, on the identified one or more characteristics of the obstruction (Stanhope, in at least [0050], discloses the UAV 100 identifies obstacles (e.g., rocks, standing water, excessively wet spots, and/or the like) within the field at the data collection point(s)).
Claim Rejections - 35 USC § 103
19. 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.
20. Claim(s) 1-9
is/are rejected under 35 U.S.C. 103 as being unpatentable over Stanhope et al. (US-20210300547-A1) in view of Tamatani (US-20250068172-A1).
In regard to claim 1
, Stanhope discloses an agricultural system comprising (Stanhope, in at least Fig. 1, and [0021], discloses an agricultural machine 10):
a sensor system communicably coupled to and remotely positionable from an agricultural work machine at a worksite, the sensor system configured to detect one or more attributes in one or more measurement areas lateral of the agricultural work machine relative to a travel direction of the agricultural work machine on a current pass (Stanhope, in at least Fig. 2, and [0029], discloses one or more sensors 118 are supported on the UAV 100 [i.e., a sensor system communicably coupled to and remotely positionable from an agricultural work machine at a worksite]. When the UAV 100 has landed at a data collection point within the field, the sensor(s) 118 are configured to capture data indicative of one or more field characteristics [i.e., one or more attributes in one or more measurement areas lateral of the agricultural work machine] of the field at such data collection point. Moreover, the sensor(s) 118 are configured to capture any other type(s) of field characteristic data, such as the top field surface profile, seedbed depth, soil moisture content, and/or the like. Accordingly, Stanhope discloses one or more measurement areas lateral of the agricultural work machine relative to a travel direction of the agricultural work machine on a current pass, especially when the collection points of the UAV are performed in areas lateral to the travel direction of the agricultural machine on the current pass);
one or more processors (Stanhope, in at least Fig. 6, and [0039], discloses the computing system 206 includes one or more processor(s) 210 [i.e., one or more processors] and associated memory device(s) 212 configured to perform a variety of computer-implemented functions); and
memory storing instructions, executable by the one or more processors, that, when executed by the one or more processors, cause the one or more processors to (Stanhope, in at least Fig. 6, and [0039], discloses memory device(s) 212 [i.e., memory] is generally configured to store suitable computer-readable instructions [i.e., instructions, executable by the one or more processors] that, when implemented by the processor(s) 210, configure the computing system 206 to perform various computer-implemented functions):
obtain, (Stanhope, in at least Fig. 7, and [0045], discloses after the UAV is anchored to the field, at (308), the method 300 includes receiving, with the computing system, sensor data indicative of a field characteristic of the field);
identify the one or more attributes in the one or more measurement areas lateral of the agricultural work machine based on the sensor data indicative of the one or more attributes in the one or more measurement areas lateral of the agricultural work machine (Stanhope, in at least [0045], discloses the sensor(s) 118 captures data indicative of one or more characteristics of the field, such as the soil hardness, soil moisture, seedbed surface profile, seedbed depth, and/or the like. Thereafter, the computing system 206 is configured to receive the captured data from the sensor(s) 118 (e.g., via the communicative link 208)); and
generate a control signal based on the identified one or more attributes in the one or more measurement areas lateral of the agricultural work machine (Stanhope, in at least Fig. 7, and [0049], discloses at (316), the method 300 includes controlling, with the computing system, the operation of the anchoring device such that the anchoring device engages landing pad to anchor the UAV to the landing surface after the UAV has landed on the landing pad which encompasses generating a control signal).
Stanhope is silent on identify a priority order of the one or more attributes in the one or more measurement areas lateral of the agricultural work machine;
based at least in part on the priority order of the one or more attributes.
However, Tamatani teaches identify a priority order of the one or more attributes in the one or more measurement areas lateral of the agricultural work machine (Tamatani, in at least Fig. 1, and [00184], teaches when generating a path to a field, or a path from a field to another place, based on the attribute information of each road on the map [i.e., one or more attributes in the one or more measurement areas lateral of the agricultural work machine, especially when the roads are in the one or more measurement areas lateral of the agricultural work machine], the management device 600 generates as a path for the work vehicle 100 at least one of a path that gives priority to agricultural roads, a path that gives priority to roads following along a particular geographic feature, or a path that gives priority to roads on which satellite signals are properly received. Examiner notes, giving priority to agricultural roads encompasses identifying a priority order of the one or more attributes);
based at least in part on the priority order of the one or more attributes (Tamatani, in at least Fig. 1, and [00184], teaches when generating a path to a field, or a path from a field to another place, based on the attribute information of each road on the map [i.e., based at least in part on the priority order of the one or more attributes], the management device 600 generates as a path for the work vehicle 100 at least one of a path that gives priority to agricultural roads, a path that gives priority to roads following along a particular geographic feature, or a path that gives priority to roads on which satellite signals are properly received. Examiner notes, giving priority to agricultural roads encompasses identifying a priority order of the one or more attributes).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify Stanhope in view of Tamatani with a reasonable expectation of success, as both inventions are directed to the same field of endeavor -- agricultural machine -- and give priority to agricultural roads and the combination would provide for efficiently generating a map for an agricultural machine that performs self-driving (Tamatani, see at least [0004]).
In regard to claim 2
, Stanhope, as modified by Tamatani, teaches the agricultural system of claim 1, wherein the one or more measurement areas include a measurement area associated with a previous pass of the agricultural work machine at the worksite (Stanhope, in at least Fig. 7, and [0045], discloses after the UAV is anchored to the field, at (308), the method 300 includes receiving, with the computing system, sensor data indicative of a field characteristic of the field which encompasses a measurement area associated with previous pass, especially when the sensor data is obtained in an area that the work machine has already passed through).
In regard to claim 3
, Stanhope, as modified by Tamatani, teaches the agricultural system of claim 1, wherein the one or more measurement areas include a measurement area associated with an upcoming pass of the agricultural work machine at the worksite (Stanhope, in at least Fig. 7, and [0045], discloses after the UAV is anchored to the field, at (308), the method 300 includes receiving, with the computing system, sensor data indicative of a field characteristic of the field which encompasses a measurement area associated with an upcoming pass of the agricultural work machine at the worksite, especially when the sensor data is obtained in an area that the work machine is about to pass through).
In regard to claim 4
, Stanhope, as modified by Tamatani, teaches the agricultural system of claim 1, wherein the one or more measurement areas include a measurement area associated with the current pass of the agricultural work machine, the measurement area extending laterally of a portion of the agricultural work machine, relative to the travel direction, on the current pass (Stanhope, in at least Fig. 7, and [0045], discloses after the UAV is anchored to the field, at (308), the method 300 includes receiving, with the computing system, sensor data indicative of a field characteristic of the field which encompasses a measurement area associated with the current pass of the agricultural work machine, the measurement area extending laterally of a portion of the agricultural work machine, relative to the travel direction, on the current pass, especially when the sensor data is obtained in an area on the right or the left side of the direction that the work machine is travelling).
In regard to claim 5
, Stanhope, as modified by Tamatani, teaches the agricultural system of claim 1, wherein the sensor system is disposed on an unmanned aerial vehicle (UAV), communicably coupled to the agricultural work machine (Stanhope, in at least Fig. 2, and [0029], discloses one or more sensors 118 are supported on the UAV 100).
In regard to claim 6
, Stanhope, as modified by Tamatani, teaches the agricultural system of claim 5, wherein the instructions, when executed by the one or more processors, further cause the one or more processors to (Stanhope, in at least Fig. 6, and [0039], discloses memory device(s) 212 is generally configured to store suitable computer-readable instructions that, when implemented by the processor(s) 210, configure the computing system 206 to perform various computer-implemented functions):
generate, (Stanhope, in at least Figs. 2, 7, and [0029 & 0043], discloses one or more sensors 118 are supported on the UAV 100. When the UAV 100 has landed at a data collection point within the field, the sensor(s) 118 are configured to capture data indicative of one or more field characteristics of the field at such data collection point. At (304), the method 300 includes controlling, with the computing system, the operation of a propulsion system of the UAV such that the UAV is flown relative to a field and landed at a data collection point [i.e., one or more monitoring locations] within the field. Flying a UAV to a data collection point encompasses generating a travel plan for the UAV); and
control the drone based on the travel plan to obtain the sensor data indicative of the one or more attributes in the one or more measurement areas lateral of the agricultural work machine (Stanhope, in at least Fig. 7, and [0043-0045], discloses the computing system 206 is configured to control the operation of the propulsion system motor(s) 106 of the UAV 100 such that the UAV 100 takes off from the landing pad 202, flies relative to the field across which the agricultural machine 10 is traveling, and lands at a data collection point within the field [i.e., control the drone based on the travel plan]. After the UAV is anchored to the field, at (308), the method 300 includes receiving, with the computing system, sensor data indicative of a field characteristic of the field [i.e., to obtain the sensor data indicative of the one or more attributes in the one or more measurement areas lateral of the agricultural work machine, especially when the measurement areas are lateral of the agricultural work machine]).
Further Tamatani teaches based at least in part on the priority order of the one or more attributes (Tamatani, in at least Fig. 1, and [00184], teaches when generating a path to a field, or a path from a field to another place, based on the attribute information of each road on the map, the management device 600 generates as a path for the work vehicle 100 at least one of a path that gives priority to agricultural roads, a path that gives priority to roads following along a particular geographic feature, or a path that gives priority to roads on which satellite signals are properly received. Examiner notes, giving priority to agricultural roads encompasses identifying a priority order of the one or more attributes).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify Stanhope in view of Tamatani with a reasonable expectation of success, as both inventions are directed to the same field of endeavor -- agricultural machine -- and generate a path based on the attribute information of each road and give priority to a path based on the attribute information of each road and the combination would provide for efficiently generating a map for an agricultural machine that performs self-driving (Tamatani, see at least [0004]).
In regard to claim 7
, Stanhope, as modified by Tamatani, teaches the agricultural system of claim 5, wherein the instructions, when executed by the one or more processors, further cause the one or more processors to (Stanhope, in at least Fig. 6, and [0039], discloses memory device(s) 212 is generally configured to store suitable computer-readable instructions that, when implemented by the processor(s) 210, configure the computing system 206 to perform various computer-implemented functions):
identify one or more characteristics of an obstruction at a worksite, the one or more characteristics comprising one or more of a location of the obstruction or a future location of the obstruction (Stanhope, in at least [0050], discloses the UAV 100 identifies obstacles (e.g., rocks, standing water, excessively wet spots, and/or the like) [i.e., one or more characteristics of an obstruction and a location of the obstruction] within the field at the data collection point(s)); and
generate a travel plan for the UAV, the travel plan including one or more monitoring locations, each monitoring location of the one or more monitoring locations defining a location to position the UAV to have the sensor system, disposed on the UAV, detect the one or more attributes in a corresponding one measurement area of the one or more measurement areas lateral of the agricultural work machine (Stanhope, in at least Fig. 2, and [0029 & 0043], discloses one or more sensors 118 are supported on the UAV 100. When the UAV 100 has landed at a data collection point within the field, the sensor(s) 118 are configured to capture data indicative of one or more field characteristics [i.e., detect the one or more attributes in a corresponding one measurement area of the one or more measurement areas lateral of the agricultural work machine, especially when the data is captured in an area lateral of the agricultural work machine] of the field at such data collection point. Moreover, the sensor(s) 118 are configured to capture any other type(s) of field characteristic data, such as the top field surface profile, seedbed depth, soil moisture content, and/or the like. At (304), the method 300 includes controlling, with the computing system, the operation of a propulsion system of the UAV such that the UAV is flown relative to a field and landed at a data collection point within the field. Flying a UAV to a data collection point encompasses generating a travel plan for the UAV. Furthermore, flying the UAV to data collection point is positioning the UAV to have the sensor system, disposed on the UAV, detect the one or more attributes in a corresponding one measurement area of the one or more measurement areas lateral of the agricultural work machine); and
generate the travel plan based, at least in part, on the identified one or more characteristics of the obstruction (Stanhope, in at least Fig. 7, and [0043], discloses the computing system 206 is configured to control the operation of the propulsion system motor(s) 106 of the UAV 100 such that the UAV 100 takes off from the landing pad 202, flies relative to the field across which the agricultural machine 10 is traveling, and lands at a data collection point within the field which encompasses generating the travel plan based on the identified one or more characteristics of the obstruction).
Further, Tamatani teaches the priority order of the one or more attribute (Tamatani, in at least Fig. 1, and [00184], teaches when generating a path to a field, or a path from a field to another place, based on the attribute information of each road on the map, the management device 600 generates as a path for the work vehicle 100 at least one of a path that gives priority to agricultural roads, a path that gives priority to roads following along a particular geographic feature, or a path that gives priority to roads on which satellite signals are properly received. Examiner notes, giving priority to agricultural roads encompasses generating the travel plan based on the priority order of the one or more attributes);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify Stanhope, as already modified by Tamatani, in view of Tamatani with a reasonable expectation of success, as all inventions are directed to the same field of endeavor -- agricultural machine -- and generate the path based by giving priority to agricultural roads, a path that gives priority to roads following along a particular geographic feature, or a path that gives priority to roads on which satellite signals are properly received and the combination would provide for efficiently generating a map for an agricultural machine that performs self-driving (Tamatani, see at least [0004]).
In regard to claim 8
, Stanhope, as modified by Tamatani, teaches the agricultural work machine of claim 7, wherein the sensor system is configured to detect the one or more attributes at each monitoring location, of the more or more monitoring locations, wherein the travel plan further includes a monitoring sequence, the monitoring sequence defining an order in which the UAV is to travel to the one or more monitoring locations, and wherein the instructions, when executed by the one or more processors, further cause the one or more processors to (Stanhope, in at least Fig. 6, [0026 & 0039], discloses the UAV 100 is configured to take off from the landing pad 202, fly over a field (e.g., an agricultural field), and land at one or more data collection points within the field [i.e., wherein the travel plan further includes a monitoring sequence, the monitoring sequence defining an order in which the UAV is to travel to the one or more monitoring locations]. After capturing data and/or soil samples at the data collection point(s) [i.e., wherein the sensor system is configured to detect the one or more attributes at each monitoring location, of the more or more monitoring locations], the UAV 100 returns to and land on the landing pad 202. Memory device(s) 212 is generally configured to store suitable computer-readable instructions that, when implemented by the processor(s) 210, configure the computing system 206 to perform various computer-implemented functions):
identify the monitoring sequence of the travel plan based, at least in part, on the identified one or more characteristics of the obstruction and (Stanhope, in at least [0050], discloses the UAV 100 identifies obstacles (e.g., rocks, standing water, excessively wet spots, and/or the like) [i.e., a location of the obstruction] within the field at the data collection point(s) which is identifying the monitoring sequence of the travel plan based on the identified one or more characteristics of the obstruction).
Further, Tamatani teaches the priority order of the one or more attribute (Tamatani, in at least Fig. 1, and [00184], teaches when generating a path to a field, or a path from a field to another place, based on the attribute information of each road on the map, the management device 600 generates as a path for the work vehicle 100 at least one of a path that gives priority to agricultural roads, a path that gives priority to roads following along a particular geographic feature, or a path that gives priority to roads on which satellite signals are properly received. Examiner notes, giving priority to agricultural roads encompasses generating the travel plan based on the priority order of the one or more attributes);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify Stanhope, as already modified by Tamatani, in view of Tamatani with a reasonable expectation of success, as all inventions are directed to the same field of endeavor -- agricultural machine -- and identify the path based by giving priority to agricultural roads, a path that gives priority to roads following along a particular geographic feature, or a path that gives priority to roads on which satellite signals are properly received and the combination would provide for efficiently generating a map for an agricultural machine that performs self-driving (Tamatani, see at least [0004]).
In regard to claim 9
, Stanhope, as modified by Tamatani, teaches the agricultural system of claim 1, wherein the control signal controls a controllable subsystem of the agricultural work machine (Stanhope, in at least [0050], discloses the UAV 100 identifies obstacles (e.g., rocks, standing water, excessively wet spots, and/or the like) within the field at the data collection point(s). The operation of the agricultural machine 10 is controlled such that the machine 10 avoids the identified obstacles which encompasses controlling a controllable subsystem of the agricultural work machine).
21. Claim(s) 10
is/are rejected under 35 U.S.C. 103 as being unpatentable over Stanhope et al. (US-20210300547-A1) in view of Tamatani (US-20250068172-A1) and further in view of Kocer et al. (US-20210357664-A1).
In regard to claim 10
, Stanhope, as modified by Tamatani, teaches the agricultural system of claim 1, accordingly the rejection of claim 1 is incorporated.
Stanhope, as modified by Tamatani, is silent on wherein the control signal controls an additional agricultural work machine different than the agricultural work machine.
However, Kocer teaches wherein the control signal controls an additional agricultural work machine different than the agricultural work machine (Kocer, in at least Fig. 5, and [0100-0102], teaches Fig. 5 is a schematic view of one example of a scouting mission 500 conducted proximate a path extending between one or more agricultural systems, such as a first agricultural system 501 [i.e., the agricultural work machine] and a second agricultural system 502 [i.e., an additional agricultural work machine]. In operation, a remote sensing device 114 is deployed from one or more of the first or second agricultural systems 501, 502 and conducts the scouting mission 500, for instance, along the scouting route 510 (e.g., proximate to the initial path 504). As shown in FIG. 5, the remote sensing device 114 travels along the scouting route 510 and observes the area proximate to the initial path 504 of the second agricultural system 502 as it approaches the first agricultural system 501. Accordingly, the one or more sensors of the remote sensing device observe the field obstacles 506 along the initial path 504).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify Stanhope, as already modified by Tamatani, in view of Kocer with a reasonable expectation of success, as both inventions are directed to the same field of endeavor -- vehicle control system -- and control two or more agricultural systems and the combination would provide for identifying obstacles from the signals of the various sensors and providing alerts regarding the identified obstacles (Kocer, see at least [0006]).
22. Claim(s) 12 and 17
is/are rejected under 35 U.S.C. 103 as being unpatentable over Stanhope et al. (US-20210300547-A1) in view of Kocer et al. (US-20210357664-A1).
In regard to claim 12
, Stanhope discloses the computer implemented method of claim 11, accordingly the rejection of claim 11 is incorporated.
Stanhope is silent on wherein the plurality of monitoring locations are remote from the agricultural work machine.
However, Kocer teaches wherein the plurality of monitoring locations are remote from the agricultural work machine (Kocer, in at least Fig. 2A-2B, 11-12, and [0038], teaches the system 110 includes a remote sensing system configured to observe the area proximate to the agricultural system 100, proximate to a determined path (e.g., along, adjacent to, within a scanning range of onboard instruments for a planned path, automated route or the like) and observe obstacles for identification and indexing. The system 110 in includes one or more remote sensing devices 114, 118. Examiner notes, as illustrated by Fig. 2A, 11 and 12, the remote sensing system 114 monitors locations that are remote from the agricultural work machine).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify Stanhope in view of Kocer with a reasonable expectation of success, as all inventions are directed to the same field of endeavor -- vehicle control system -- and a remote sensing device, such as a drone or a UAV, is used for monitoring locations that are remote from the agricultural work machine and the combination would provide for identifying obstacles from the signals of the various sensors and providing alerts regarding the identified obstacles (Kocer, see at least [0006]).
In regard to claim 17
, Stanhope discloses the computer implemented method of claim 11, wherein generating the control signal comprises at least one of:
generating a control signal to control the agricultural work machine (Stanhope, in at least [0050], discloses the operation of the agricultural machine 10 is controlled such that the machine 10 avoids the identified obstacles which encompasses generating the travel plan based on the one or more characteristics of the obstruction); or
Stanhope is silent on generating a control signal to control an additional agricultural work machine different than the agricultural work machine.
However, Kocer teaches generating a control signal to control an additional agricultural work machine different than the agricultural work machine (Kocer, in at least Fig. 5, and [0100-0102], teaches Fig. 5 is a schematic view of one example of a scouting mission 500 conducted proximate a path extending between one or more agricultural systems, such as a first agricultural system 501 [i.e., the agricultural work machine] and a second agricultural system 502 [i.e., an additional agricultural work machine]. The second agricultural system 502 is configured to approach the first agricultural system and receive harvested crops from the first agricultural system 501 which encompasses generating a control signal to control an additional agricultural work machine).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify Stanhope in view of Kocer with a reasonable expectation of success, as both inventions are directed to the same field of endeavor -- vehicle control system -- and control two or more agricultural systems and the combination would provide for identifying obstacles from the signals of the various sensors and providing alerts regarding the identified obstacles (Kocer, see at least [0006]).
23. Claim(s) 14
is/are rejected under 35 U.S.C. 103 as being unpatentable over Stanhope et al. (US-20210300547-A1) in view of Skowronek et al. (US-20180143321-A1).
In regard to claim 14
, Stanhope discloses the computer implemented method of claim 13 and further comprising:
identifying a monitoring location of the plurality of monitoring locations, based, at least in part, on the identified one or more characteristics of the obstruction (Stanhope, in at least [0050], discloses the UAV 100 identifies obstacles (e.g., rocks, standing water, excessively wet spots, and/or the like) [i.e., a location of the obstruction] within the field at the data collection point(s) which is identifying the monitoring sequence of the travel plan based on the identified one or more characteristics of the obstruction).
Stanhope is silent on the identified monitoring location defining a location to position the drone such that the obstruction does not obstruct the sensor system from detecting the plurality of attributes in the corresponding measurement area.
However, Skowronek teaches the identified monitoring location defining a location to position the drone such that the obstruction does not obstruct the sensor system from detecting the plurality of attributes in the corresponding measurement area (Skowronek, in at least Fig. 1, [0046], and [0257] teaches one or more passive-tracking systems 115 are configured to move along a track or some other structure that supports movement or are attached to or integrated with a machine capable of motion, like a drone, vehicle, or robot. Passive-tracking systems 115 is capable of being positioned in monitoring areas 110 that are not enclosed or sheltered. The expanded range is necessary in view of the monitoring area 110 being an open location [i.e., positioning the drone such that the obstruction does not obstruct the sensor system]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify Stanhope in view of Skowronek with a reasonable expectation of success, as both inventions are directed to the same field of endeavor -- tracking systems -- and position the drone in an open location to and the combination would provide for detect the presence of an object and in response, take some sort of action (Skowronek, see at least [0002]).
24. Claim(s) 16
is/are rejected under 35 U.S.C. 103 as being unpatentable over Stanhope et al. (US-20210300547-A1) in view of Machida (US-20210012399-A1).
In regard to claim 16
, Stanhope discloses the computer implemented method of claim 11, accordingly the rejection of claim 11 is incorporated.
Stanhope is silent on and further comprising:
identifying a priority of each monitoring location of the plurality of monitoring locations; and
generating the travel plan based, at least in part, on the identified priority of each of the one or more monitoring locations.
However, Machida teaches and further comprising:
identifying a priority of each monitoring location of the one or more monitoring locations (Machida, in at least Fig. 1, and [0025-0026], teaches a path determination system 1 a includes a priority determination system 100, a path calculation system 150, and mobile bodies 5a to 5c. The priority determination system 100 includes a priority receiving unit 10. The priority receiving unit 10 receives, for example, priority information indicating a priority from each of the mobile bodies 5a to 5c, and stores the received priority information in the priority storage unit 11 which encompasses identifying a priority of each monitoring location of the one or more monitoring locations); and
generating the travel plan based, at least in part, on the identified priority of each monitoring location of the plurality of monitoring locations (Machida, in at least [0038], teaches the path calculation system 150 transmits, to the priority determination system 100, the path information received from each mobile body 5 and the path determined on the basis of priority. In the priority determination system 100, the path acquisition unit 13 compares these two paths and calculates, for each mobile body 5, a time loss in a case where the path determined based on priority is selected).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify Stanhope in view of Machida with a reasonable expectation of success, as both inventions are directed to the same field of endeavor -- vehicle control system -- and include a priority determination system to generate the path on the basis of priority of the monitoring locations and the combination would provide for calculating an appropriate cost for a mobile body to travel (Machida, see at least [0012]).
25. Claim(s) 18
is/are rejected under 35 U.S.C. 103 as being unpatentable over Stanhope et al. (US-20210300547-A1) in view of Menzel et al. (US-20190094861-A1).
In regard to claim 18
, Stanhope discloses an agricultural system comprising (Stanhope, in at least Fig. 1, and [0021], discloses an agricultural machine 10):
a sensor system disposed on a drone communicably coupled to and remotely positionable from an agricultural work machine at a worksite, the sensor system configured to detect one or more attributes in one or more measurement areas lateral of, at least, a portion of the agricultural work machine relative to a travel direction of the agricultural work machine on a current pass (Stanhope, in at least Fig. 2, and [0029], discloses one or more sensors 118 are supported on the UAV 100 [i.e., a sensor system disposed on a drone communicably coupled to and remotely positionable from an agricultural work machine at a worksite]. When the UAV 100 has landed at a data collection point within the field, the sensor(s) 118 are configured to capture data indicative of one or more field characteristics [i.e., one or more attributes in one or more measurement areas lateral of, at least, a portion of the agricultural work machine relative to a travel direction of the agricultural work machine on a current pass] of the field at such data collection point. Moreover, the sensor(s) 118 are configured to capture any other type(s) of field characteristic data, such as the top field surface profile, seedbed depth, soil moisture content, and/or the like. Accordingly, Stanhope discloses one or more measurement areas lateral of the agricultural work machine relative to a travel direction of the agricultural work machine on a current pass, especially when the collection points of the UAV are performed in areas lateral to the travel direction of the agricultural machine on the current pass);
one or more processors(Stanhope, in at least Fig. 6, and [0039], discloses the computing system 206 includes one or more processor(s) 210 and associated memory device(s) 212 configured to perform a variety of computer-implemented functions); and
memory storing instructions, executable by the one or more processors, that, when executed by the one or more processors, cause the one or more processors to (Stanhope, in at least Fig. 6, and [0039], discloses memory device(s) 212 is generally configured to store suitable computer-readable instructions that, when implemented by the processor(s) 210, configure the computing system 206 to perform various computer-implemented functions):
identify one or more characteristics of an obstruction at the worksite, the one or more characteristics comprising one or more of a location of the obstruction or a future location of the obstruction (Stanhope, in at least [0050], discloses the UAV 100 identifies obstacles (e.g., rocks, standing water, excessively wet spots, and/or the like) [i.e., a location of the obstruction] within the field at the data collection point(s). The operation of the agricultural machine 10 is controlled such that the machine 10 avoids the identified obstacles. Examiner notes, for the agricultural work machine to avoid an obstruction, the location of the obstruction must be necessarily identified. Accordingly, identifying the obstacle within the field, by the UAV, is identifying the location of the obstacle):
generate a travel plan for the drone (Stanhope, in at least Fig. 7, and [0026 & 0043], discloses the UAV 100 is configured to take off from the landing pad 202, fly over a field (e.g., an agricultural field), and land at one or more data collection points within the field. At (304), the method 300 includes controlling, with the computing system, the operation of a propulsion system of the UAV such that the UAV is flown relative to a field and landed at a data collection point [i.e., one or more monitoring locations] within the field. Flying a drone to a data collection point encompasses generating a travel plan for the drone);
control the drone based on the travel plan (Stanhope, in at least Fig. 7, and [0043], discloses the computing system 206 is configured to control the operation of the propulsion system motor(s) 106 of the UAV 100 such that the UAV 100 takes off from the landing pad 202, flies relative to the field across which the agricultural machine 10 is traveling, and lands at a data collection point within the field which is controlling the drone based on the travel plan);
obtain, from the sensor system, the sensor data indicative of the detected one or more attributes in the one or more measurement areas lateral of, at least, the portion of the agricultural work machine (Stanhope, in at least Fig. 7, and [0045], discloses after the UAV is anchored to the field, at (308), the method 300 includes receiving, with the computing system, sensor data indicative of a field characteristic of the field);
identify the one or more attributes in the one or more measurement areas lateral of, at least, the portion of the agricultural work machine based on the sensor data indicative of the one or more attributes in the one or more measurement areas lateral of, at least, the portion of the agricultural work machine (Stanhope, in at least [0045], discloses the sensor(s) 118 captures data indicative of one or more characteristics of the field, such as the soil hardness, soil moisture, seedbed surface profile, seedbed depth, and/or the like. Thereafter, the computing system 206 is configured to receive the captured data from the sensor(s) 118 (e.g., via the communicative link 208)); and
generate a control signal based on the identified one or more attributes in the one or more measurement areas lateral of, at least, the portion of the agricultural work machine (Stanhope, in at least Fig. 7, and [0049], discloses at (316), the method 300 includes controlling, with the computing system, the operation of the anchoring device such that the anchoring device engages landing pad to anchor the UAV to the landing surface after the UAV has landed on the landing pad).
Stanhope is silent on generate a travel plan for the drone based on the one or more characteristics of the obstruction at the worksite.
However, Menzel teaches generate a travel plan for the drone based on the one or more characteristics of the obstruction at the worksite (Menzel, in at least Fig. 1, and [0085], teaches the one or more processors are further configured to modify the flight path of the unmanned aerial vehicle 600 based on detected obstacles to generate a collision free flight path to the desired target position avoiding obstacles in the vicinity of the unmanned aerial vehicle. Examiner notes, generating a collision free flight path to the desired target position avoiding obstacles in the vicinity of the unmanned aerial vehicle is generating a travel plan for the drone based on the one or more characteristics of the obstruction at the worksite, especially when the drone is used in a worksite).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify Stanhope in view of Menzel with a reasonable expectation of success, as both inventions are directed to the same field of endeavor -- unmanned aerial vehicle -- and generate a collision free flight path to the desired target position avoiding obstacles and the combination would provide for avoiding collision of the unmanned aerial vehicle with an obstacle located in the flight path of the unmanned aerial vehicle (Menzel, see at least [0002]).
26. Claim(s) 19-20
is/are rejected under 35 U.S.C. 103 as being unpatentable over Stanhope et al. (US-20210300547-A1) in view of Menzel et al. (US-20190094861-A1) and further in view of Tamatani (US-20250068172-A1).
In regard to claim 19
, Stanhope, as modified by Menzel, teaches the agricultural system of claim 18, wherein the instructions, when executed by the one or more processors, further cause the one or more processors to (Stanhope, in at least Fig. 6, and [0039], discloses memory device(s) 212 is generally configured to store suitable computer-readable instructions that, when implemented by the processor(s) 210, configure the computing system 206 to perform various computer-implemented functions):
.
Stanhope, as modified by Menzel, is silent on identify a performance of a sensor on-board the agricultural work machine; and
generate the travel plan based the performance of sensor on-board the agricultural work machine.
However, Tamatani teaches identify a performance of a sensor on-board the agricultural work machine; and generate the travel plan based the performance of sensor on-board the agricultural work machine (Tamatani, in at least Fig. 1, and [0067 & 00184], teaches the GNSS unit 110 includes an inertial measurement unit (IMU). Signals from the IMU issued to complement position data. The IMU measures a tilt or a small motion of the work vehicle 100. The data acquired by the IMU is used to complement the position data based on the satellite signals, so as to improve the performance of positioning. When generating a path to a field, or a path from a field to another place, based on the attribute information of each road on the map, the management device 600 generates as a path for the work vehicle 100 at least one of a path that gives priority to agricultural roads, a path that gives priority to roads following along a particular geographic feature, or a path that gives priority to roads on which satellite signals are properly received. Examiner notes, as mentioned above a GNSS is used to determine the position of the agricultural machine. Generating a path by giving priority to roads on which satellite signals are properly received encompasses identifying the performance of the GNSS, which is a sensor on-board the agricultural work machine. That is, identifying a performance of a sensor on-board the agricultural work machine and generating the travel plan based the performance of sensor on-board the agricultural work machine).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify Stanhope, as already modified by Menzel, in view of Tamatani with a reasonable expectation of success, as all inventions are directed to the same field of endeavor -- agricultural machine -- and the path is generated by giving priority to roads on which satellite signals are properly received and the combination would provide for efficiently generating a map for an agricultural machine that performs self-driving (Tamatani, see at least [0004]).
In regard to claim 20
, Stanhope, as modified by Menzel, teaches the agricultural system of claim 18, wherein the travel plan further includes a monitoring sequence, the monitoring sequence defining an order in which the drone is to travel to each monitoring location in the one or more monitoring locations, and wherein the instructions, when executed by the one or more processors, further cause the one or more processors to (Stanhope, in at least Fig. 6, [0026 & 0039], discloses the UAV 100 is configured to take off from the landing pad 202, fly over a field (e.g., an agricultural field), and land at one or more data collection points within the field [i.e., the travel plan further includes a monitoring sequence, the monitoring sequence defining an order in which the drone is to travel to each monitoring location in the one or more monitoring locations]. After capturing data and/or soil samples at the data collection point(s), the UAV 100 returns to and land on the landing pad 202. Memory device(s) 212 is generally configured to store suitable computer-readable instructions that, when implemented by the processor(s) 210, configure the computing system 206 to perform various computer-implemented functions):
Stanhope, as modified by Menzel, is silent on identify one or more of:
(i) a priority of each monitoring location of the one or more monitoring locations;
(ii) a priority of each attribute of the one or more attributes; and
(iii) performance of a sensor on-board the agricultural work machine; and
generate the travel plan based, at least, in part, on one or more of: (i) the priority of each of the one or more monitoring locations; (ii) the priority of each of the one or more attributes; or (iii) the performance of the sensor on-board the agricultural work machine.
However, Tamatani teaches a priority of each attribute of the one or more attribute and generate the travel plan based, at least, in part, on one or more of: (ii) the priority of each of the one or more attributes; (Tamatani, in at least Fig. 1, and [00184], teaches when generating a path to a field, or a path from a field to another place, based on the attribute information of each road on the map, the management device 600 generates as a path for the work vehicle 100 at least one of a path that gives priority to agricultural roads, a path that gives priority to roads following along a particular geographic feature, or a path that gives priority to roads on which satellite signals are properly received. Examiner notes, As mentioned above, the path is generated and given priority based on the attribute information of each road on the map. That is, identifying a priority of each attribute of the one or more attributes and generating the path based on the priority of each of the one or more attributes).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify Stanhope, as already modified by Menzel, in view of Tamatani with a reasonable expectation of success, as both inventions are directed to the same field of endeavor -- agricultural machine -- and the priority of each attribute is identified and the path is generated based on the priority of the attribute and the combination would provide for efficiently generating a map for an agricultural machine that performs self-driving (Tamatani, see at least [0004]).
Conclusion
27. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Wake et al. (US-20220091619-A1) teaches a drone system, in which the drone and a movable body operate in coordination with each other, and the drone performs a predetermined operation in an agricultural field.
Kinoshita et al. (US-20230312146-A1) teaches an agricultural machine which is accompanied by an unmanned aerial vehicle that captures an image of the working state (working trace) after the work with the working implement, or detects an obstacle in the surrounding area of the working implement.
28. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
29. 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.
30. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Preston J Miller whose telephone number is (703)756-1582. The examiner can normally be reached Monday through Friday 7:30 AM - 4:30 PM EST.
31. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
32. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ramya P Burgess can be reached at (571) 272-6011. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/P.J.M./Examiner, Art Unit 3661
/RAMYA P BURGESS/Supervisory Patent Examiner, Art Unit 3661