REMOTE LATERAL ATTRIBUTE MONITORING DURING AN AGRICULTURAL OPERATION

Application No. 18/767,693

• Filed: Jul 09, 2024
• Examiner: MILLER, PRESTON JAY
• Art Unit: 3661
• Tech Center: 3600 — Transportation & Electronic Commerce
• Assignee: Deere & Company
• OA Round: 3 (Non-Final)

Office Action

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 05/21/2026 have been fully considered but they are not persuasive.

3. Applicant’s arguments and amendments have been addressed in the new rejection outlined below.
4. Applicant’s arguments with respect to claim(s) 1, 11, and 18 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.

5. Applicant argues the dependent claim(s) is/are patentable by the virtue of its/their dependency on one of the independent claims and the additional features recited in the dependent claim(s).
6. This argument is unpersuasive as each independent claim and dependent claim has been fully rejected and for the reasons given above.

Examiner Notes
7. The Examiner has cited particular paragraphs or columns and line numbers in the references applied to the claims below 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 § 103
8. 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.

9. Claim(s) 1-13 and 15-17
is/are rejected under 35 U.S.C. 103 as being unpatentable over Kinoshita et al. (US-20230322423-A1) in view of Kocer et al. (US-20210357664-A1).
In regard to claim 1
, Kinoshita discloses an agricultural system comprising (See at least Figs. 1-2, and [0035]: the agricultural support system [i.e., an agricultural system] includes an unmanned aerial vehicle and an agricultural machine):
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 (See at least Fig. 4, and [0116-0118 & 0135 & 0151]: the unmanned aerial vehicle 70 includes a sensor 72, a position detector 73 [i.e., a sensor system]. When the unmanned aerial vehicle 70 flies above an agricultural field [i.e., remotely positionable from an agricultural work machine at a worksite], the sensor 72 senses the agricultural field. The sensor 72 is directed toward the working implement 2 to capture an image of the surrounding area of the working implement 2, thus monitoring whether a living body M1 or an obstacle M2 is present in the surrounding area [i.e., to detect one or more attributes]. The unmanned aerial vehicle 70 includes a communication device 75 to transmit stop of travel to the agricultural machine 1 [i.e., communicably coupled to … an agricultural work machine] when the sensor 72 detects the living body while the agricultural machine 1 is traveling. Examiner notes, according to relevant paragraph [0061] of Applicant’s specification: “Environmental attributes can include field feature attributes such as field boundaries, field obstacles (e.g., type, presence, and location of obstacles at the field), field conditions (e.g., ruts, damage, etc.), field working limits (e.g., working limits due to power lines, overpasses, bridges, culverts, etc.), and other field feature attributes.” Accordingly, the presence of field obstacles, such as a living body, was interpreted as environmental attributes);
one or more processors (See at least Fig. 4, and [0116 & 0121]: the unmanned aerial vehicle 70 includes a memory 74, a communication device 75, and a controller 76 [i.e., one or more processors]. The controller 76 includes a CPU [i.e., one or more processors]); 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 (See at least Fig. 4, and [0116 & 0150]: the unmanned aerial vehicle 70 includes a memory 74 [i.e., memory], a communication device 75, and a controller 76. The controller 76 is configured or programmed to change the flight position to a surrounding area of the living body when the sensor 72 detects the living body. Examiner notes, for programming a controller, instructions are necessarily used and the instructions are stored in memory and executed by the processor of the controller):
obtain operation data indicative of a location of the agricultural work machine on the worksite and a travel path of the agricultural work machine across the worksite (See at least Figs. 1-4, 6A, and [0087-0088 & 0097 & 0125 & 0130]: the sensor 72 performs sensing in the direction of travel while the tractor 1 is automatically traveling and performing work (during work) [i.e., obtain … a travel path of the agricultural work machine across the worksite]. That is, the controller 76 of the unmanned aerial vehicle 70 changes the flight position to a position that allows an area forward of the vehicle body 3 in the direction of travel to be sensed when the working implement 2 performs the ground work. When the communication device 75 of the unmanned aerial vehicle 70 receives the work information (the travel position P1, the agricultural field information, and the operation information) [i.e., obtain operation data indicative of a location of the agricultural work machine on the worksite] transmitted from the tractor 1 (S3), the communication device 75 determines an operation such as flight based on the work information);
identify, based on the operation data indicative of the location and the travel path of the agricultural work machine, 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 (See at least Figs. 4, 11A, and [0155-0156]: the situation in the direction of travel of the tractor 1 is sensed [i.e., based on the operation data indicative of the location and the travel path of the agricultural work machine] by the sensor 72 of the unmanned aerial vehicle 70 during the automatic traveling of the tractor 1. However, the obstacle detector 45 of the tractor 1 changes a detection area [i.e., identify … one or more measurement areas] to detect an obstacle M2 based on the result sensed by the sensor 72 of the unmanned aerial vehicle 70. Examiner notes, as illustrated by Figure 1 (Fig. 11A of Kinoshita, reproduced and annotated for Applicant’s convenience), the measurement area is 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. Furthermore, an obstacle, which is an environmental attribute, is detected by the unmanned aerial vehicle 70 in the measurement area);

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Figure 1 - Annotated Fig. 11A of Kinoshita

obtain, (See at least Fig. 11A, and [0156]: when the sensor 72 detects an object M3, such as a living body M1 or an obstacle M2 [i.e., obtain … from the sensor system, sensor data indicative of the one or more attributes in the one or more measurement areas lateral of the agricultural work machine], in a situation in which the tractor 1 is traveling and the sensor 72 is capturing an image of an area located forward of the tractor 1, the communication device 75 of the unmanned aerial vehicle 70 transmits, as the detection result, information indicating the detection of the object M3, the size (height H10, width L10, depth W10) and the position of the object M3 to the tractor 1. Examiner notes, a sensor necessarily generates sensor data that is obtained by the controller);
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 (See at least Figs. 1, 4, 11A, and [0156]: when the sensor 72 [i.e., based on the sensor data] detects an object M3, such as a living body M1 or an obstacle M2 [i.e., identify the one or more attributes in the one or more measurement areas lateral of the agricultural work], in a situation in which the tractor 1 is traveling and the sensor 72 is capturing an image of an area located forward of the tractor 1, the communication device 75 of the unmanned aerial vehicle 70 transmits, as the detection result, information indicating the detection of the object M3, the size (height H10, width L10, depth W10) and the position of the object M3 to the tractor 1 [i.e., indicative of the one or more attributes in the one or more measurement areas lateral of the agricultural work machine]); 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 (See at least Fig. 8, and [0131]: the controller 76 performs control of sensing a surrounding area of the tractor 1 (a range several meters away from the tractor 1) by the unmanned aerial vehicle 70 (S7: first sensing). In the first sensing, the sensor 72 is directed toward the tractor 1 to capture an image of the range several meters away from the tractor 1, thus monitoring whether a living body M1 such as an animal or a human is present in the range [i.e., one or more attributes in the one or more measurement areas lateral of the agricultural work machine]. When the living body M1 is detected in the first sensing, the communication device 75 transmits to the communication device 51 (S8) a warning signal. When acquiring the warning signal via the communication device 51, the traveling controller 40A of the tractor 1 does not start the automatic traveling and maintains the stop (S9). The traveling controller 40A of the tractor 1 starts the automatic traveling when the warning signal is not acquired for a predetermined time or more, or when a release signal for releasing the warning is received from the unmanned aerial vehicle 70 (S10). Examiner notes, starting or stopping automatic traveling necessarily encompasses generating a control signal. As mentioned above, the automatic traveling starts or stops based on detecting an attribute, such as an obstacle, in the measurement area).
Kinoshita 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, Kocer teaches the obstacle recognition module 310 includes a prioritizing module 318. The prioritizing module 318 is configured to assign priorities to obstacles based on a catalog set of priorities, priority rules, user input priorities or user input priority rules or the like [i.e., identify a priority order of the one or more attributes]. Archived obstacles such as humans, livestock or the like have a higher priority relative to other identified obstacles including, for instance, brush, washouts, rocks, saturated or soaked areas of the field or the like. As described herein, the assigned priority of an identified object changes the operation of the agricultural system 100, for instance with the vehicle operation module 306 of the autonomous agricultural system controller 104. The identification of a human [i.e., the one or more attributes in the one or more measurement areas lateral of the agricultural work machine] proximate to a determined path of the agricultural system 100 is given a high priority while other obstacles such as livestock, brush, fence or rocks or the like proximate to the determined path are given a lower priority (and optionally scaled lower priorities with livestock higher than brush or similar inanimate obstacles). The proximity to the agricultural system 100 or the determined path of the agricultural system 100 triggers the assignment of a higher priority to an identified obstacle in comparison to the same identified obstacle that is not proximate to the determined path or is not proximate to the agricultural system 100 (See at least Figs. 1-3B, and [0075-0076]);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify the invention of Kinoshita, by incorporating the teachings of Kocer, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – agricultural machines, such that the prioritizing module of Kocer is used to assign priorities to obstacles based on a catalog set of priorities, priority rules, user input priorities or user input priority rules and the sensor system obtains the attributes of the obstacle based on their priority order.
The motivation to modify is that, as acknowledged by Kocer, to expand or dilate a boundary of the obstacle and to define an exclusion zone or mitigation region around the obstacle (See at least [0104]) which one of ordinary skill would have recognized makes the operation of the agricultural machine safer and more reliable.

In regard to claim 2
, Kinoshita, as modified by Kocer, teaches the agricultural system of claim 1, wherein the instructions, when executed by the one or more processors, cause the one or more processors to identify a measurement area, of the one or more measurement areas, based on a previous pass of the agricultural work machine at the worksite (See at least Fig. 4, and [0116 & 0150]: the unmanned aerial vehicle 70 includes a memory 74, a communication device 75, and a controller 76. The controller 76 is configured or programmed to change the flight position to a surrounding area of the living body when the sensor 72 detects the living body. Examiner notes, for programming a controller, instructions are necessarily used and the instructions are stored in memory and executed by the processor of the controller).
Further, Kocer teaches identification and indexing of obstacles includes tracking movement of the obstacles, for instance, by way of updated sensory information provided by the remote sensing device 114 continuing with additional mission controlled movement and continued or repeated observation of obstacles along the mission route [i.e., based on a previous pass of the agricultural work machine at the worksite] (See at least [0079]). Examiner notes, continued and repeated observation encompasses a previous pass of the agricultural work machine at the worksite, especially when the measurement area is identified before the current pass.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify the invention of Kinoshita, as already modified by Kocer, by further incorporating the teachings of Kocer, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – agricultural machines, such that the measurement areas that include obstacles are identified and tracked.
The motivation to do so is the same as acknowledged by Kocer in regard to claim 1.

In regard to claim 3
, Kinoshita, as modified by Kocer, teaches the agricultural system of claim 1, wherein the instructions, when executed by the one or more processors, cause the one or more processors to identify a measurement area, of the one or more measurement areas, based on an upcoming pass of the agricultural work machine at the worksite (See at least Fig. 4, and [0116 & 0150]: the unmanned aerial vehicle 70 includes a memory 74, a communication device 75, and a controller 76. The controller 76 is configured or programmed to change the flight position to a surrounding area of the living body when the sensor 72 detects the living body. Examiner notes, for programming a controller, instructions are necessarily used and the instructions are stored in memory and executed by the processor of the controller).
Further, Kocer teaches identification and indexing of obstacles includes tracking movement of the obstacles, for instance, by way of updated sensory information provided by the remote sensing device 114 continuing with additional mission controlled movement and continued or repeated observation of obstacles along the mission route [i.e., based on an upcoming pass of the agricultural work machine at the worksite] (See at least [0079]). Examiner notes, continued and repeated observation encompasses an upcoming pass of the agricultural work machine at the worksite, especially when the measurement area is identified after the current pass.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify the invention of Kinoshita, as already modified by Kocer, by further incorporating the teachings of Kocer, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – agricultural machines, such that the measurement areas that include obstacles are identified and tracked.
The motivation to do so is the same as acknowledged by Kocer in regard to claim 1.

In regard to claim 4
, Kinoshita, as modified by Kocer, teaches the agricultural system of claim 1, wherein instructions, when executed by the one or more processors, cause the one or more processors to identify a measurement area, of the one or more measurement areas, based on the current pass of the agricultural work machine, the measurement area extending laterally of a portion of the agricultural work machine and one or more dimensions of the agricultural work machine, relative to the travel direction, on the current pass (See at least Fig. 4, and [0116 & 0150]: the unmanned aerial vehicle 70 includes a memory 74, a communication device 75, and a controller 76. The controller 76 is configured or programmed to change the flight position to a surrounding area of the living body when the sensor 72 detects the living body. Examiner notes, for programming a controller, instructions are necessarily used and the instructions are stored in memory and executed by the processor of the controller. As illustrated by Figure 2 (Fig. 11A of Kinoshita, reproduced and annotated for Applicant’s convenience), the measurement area extends laterally of a portion of the agricultural work machine and one or more dimensions of the agricultural work machine, relative to the travel direction, on the current pass).

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Figure 2 - Annotated Fig. 11A of Kinoshita

In regard to claim 5
, Kinoshita, as modified by Kocer, 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 (See at least Fig. 4, and [0116 & 0151]: the unmanned aerial vehicle 70 includes a power storage 71, a sensor 72, a position detector 73 [i.e., the sensor system], a memory 74, a communication device 75, and a controller 76. The unmanned aerial vehicle 70 includes a communication device 75 to transmit stop of travel to the agricultural machine 1 [i.e., communicably coupled to the agricultural work machine] when the sensor 72 detects the living body while the agricultural machine 1 is traveling).

In regard to claim 6
, Kinoshita, as modified by Kocer, 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 (See at least Fig. 4, and [0116 & 0150]: the unmanned aerial vehicle 70 includes a memory 74, a communication device 75, and a controller 76. The controller 76 is configured or programmed to change the flight position to a surrounding area of the living body when the sensor 72 detects the living body. Examiner notes, for programming a controller, instructions are necessarily used and the instructions are stored in memory and executed by the processor of the controller):
generate, based at least in part on the priority order of the one or more attributes, 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 (See at least Fig. 6A, and [124-0133]: the controller 76 of the unmanned aerial vehicle 70 changes the flight position of the unmanned aerial vehicle 70 [i.e., generate … a travel plan for the UAV] in tandem with an operation of the tractor 1. The controller 76 of the unmanned aerial vehicle 70 changes the flight position to a position that allows an area forward of the vehicle body 3 in the direction of travel to be sensed [i.e., 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] when the working implement 2 performs the ground work. The sensor 72 is directed toward the front of the tractor 1 to capture an image of an area located forward of the tractor 1 and monitor whether a living body Ml, an obstacle, or the like, is present forward of the tractor 1 [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]. Examiner notes, changing the flight position in tandem with an operation of the tractor 1 to a position that allows an area forward of the vehicle body 3 in the direction of travel to be sensed necessarily encompasses generating a travel plan for the drone); 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 (See at least Fig. 6A, 7B, and [125-0135]: the controller 76 of the unmanned aerial vehicle 70 changes the flight position to a position that allows an area forward of the vehicle body 3 in the direction of travel to be sensed [i.e., control the drone based on the travel plan] when the working implement 2 performs the ground work. The sensor 72 is directed toward the front of the tractor 1 to capture an image of an area located forward of the tractor 1 and monitor whether a living body Ml, an obstacle, or the like, is present forward of the tractor 1. The sensor 72 is directed toward the working implement 2 to capture an image of the surrounding area of the working implement 2 [i.e., to obtain the sensor data], thus monitoring whether a living body M1 or an obstacle M2 is present in the surrounding area [i.e., indicative of the one or more attributes in the one or more measurement areas lateral of the agricultural work machine]. Examiner notes, changing the flight position necessarily encompasses generating a travel plan and performing the change is controlling the drone based on the travel plan).
Further, Kocer teaches the obstacle recognition module 310 includes a prioritizing module 318. The prioritizing module 318 is configured to assign priorities to obstacles based on a catalog set of priorities, priority rules, user input priorities or user input priority rules or the like. Archived obstacles such as humans, livestock or the like have a higher priority relative to other identified obstacles including, for instance, brush, washouts, rocks, saturated or soaked areas of the field or the like. As described herein, the assigned priority of an identified object changes the operation of the agricultural system 100, for instance with the vehicle operation module 306 of the autonomous agricultural system controller 104. The identification of a human proximate to a determined path of the agricultural system 100 is given a high priority while other obstacles such as livestock, brush, fence or rocks or the like proximate to the determined path are given a lower priority (and optionally scaled lower priorities with livestock higher than brush or similar inanimate obstacles). For instance, the prioritizing module 318 assigns a higher priority to particular types of obstacles, for instance, humans or the like. The proximity to the agricultural system 100 or the determined path of the agricultural system 100 triggers the assignment of a higher priority to an identified obstacle in comparison to the same identified obstacle that is not proximate to the determined path or is not proximate to the agricultural system 100. In operation, the obstacle recognition module 310 cooperates with and communicates with other components of the autonomous obstacle monitoring and vehicle control system 300 to identify and track obstacles and facilitate enhanced guidance of the agricultural system 100 through the field while still allowing the agricultural system 100 to accomplish one or more agricultural processes. The remote sensing device 114 is deployed by the autonomous agricultural system controller 104 by way of a mission administration module 304 providing a mission route to the remote sensing device 114 or, guiding operation of the remote sensing device 114 along a mission route. The remote sensing device 114, while conducting the mission, observes the area proximate to a determined path, proximate to the agricultural system 100 or the like, for instance, along a corresponding mission route for the remote sensing device 114 (See at least Figs. 1-3B, and [0075-0078]). Examiner notes, as mentioned above, the proximity to the agricultural system or the determined path of the agricultural system triggers the assignment of a higher priority to an identified obstacle and the autonomous agricultural system controller provides a mission route to the remote sensing device, which is also generating a travel plan for the UAV, to observe the area proximate to a determined path. That is, generating, based at least in part on the priority order of the one or more attributes, a travel plan for the UAV and controlling the drone based on the travel plan to obtain the sensor data.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify the invention of Kinoshita, as already modified by Kocer, by further incorporating the teachings of Kocer, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – agricultural machines, such that the prioritizing module of Kocer is used to assign higher priorities to obstacles along the planned route of the agricultural machine and a travel plan for the UAV is created based on the assigned priorities and the drone is controlled to collect sensor data for the higher priority obstacles.
The motivation to do so is the same as acknowledged by Kocer in regard to claim 1.

In regard to claim 7
, Kinoshita, as modified by Kocer, 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 (See at least Fig. 4, and [0116 & 0150]: the unmanned aerial vehicle 70 includes a memory 74, a communication device 75, and a controller 76. The controller 76 is configured or programmed to change the flight position to a surrounding area of the living body when the sensor 72 detects the living body. Examiner notes, for programming a controller, instructions are necessarily used and the instructions are stored in memory and executed by the processor of the controller):
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 (See at least Fig. 11A, and [0156]: when the sensor 72 detects an object M3, such as a living body M1 or an obstacle M2 [i.e., identify one or more characteristics of an obstruction at a worksite], in a situation in which the tractor 1 is traveling and the sensor 72 is capturing an image of an area located forward of the tractor 1, the communication device 75 of the unmanned aerial vehicle 70 transmits, as the detection result, information indicating the detection of the object M3, the size (height H10, width L10, depth W10) and the position of the object M3 to the tractor 1 [i.e., the one or more characteristics comprising one or more of a location of the obstruction]); 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 (See at least Fig. 6A, and [124-0133]: the controller 76 of the unmanned aerial vehicle 70 changes the flight position of the unmanned aerial vehicle 70 [i.e., generate … a travel plan for the UAV] in tandem with an operation of the tractor 1. The controller 76 of the unmanned aerial vehicle 70 changes the flight position to a position that allows an area forward of the vehicle body 3 in the direction of travel to be sensed [i.e., 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] when the working implement 2 performs the ground work. The sensor 72 is directed toward the front of the tractor 1 to capture an image of an area located forward of the tractor 1 and monitor whether a living body Ml, an obstacle, or the like, is present forward of the tractor 1 [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]. Examiner notes, changing the flight plan necessarily encompasses generating a travel plan for the drone); and
generate the travel plan based, at least in part, on the identified one or more characteristics of the obstruction and the priority order of the one or more attributes.
Further, Kocer teaches the obstacle recognition module 310 includes a prioritizing module 318. The prioritizing module 318 is configured to assign priorities to obstacles based on a catalog set of priorities, priority rules, user input priorities or user input priority rules or the like. Archived obstacles such as humans, livestock or the like have a higher priority relative to other identified obstacles including, for instance, brush, washouts, rocks, saturated or soaked areas of the field or the like. As described herein, the assigned priority of an identified object changes the operation of the agricultural system 100, for instance with the vehicle operation module 306 of the autonomous agricultural system controller 104. The identification of a human proximate to a determined path of the agricultural system 100 is given a high priority while other obstacles such as livestock, brush, fence or rocks or the like proximate to the determined path are given a lower priority (and optionally scaled lower priorities with livestock higher than brush or similar inanimate obstacles). For instance, the prioritizing module 318 assigns a higher priority to particular types of obstacles, for instance, humans or the like. The proximity to the agricultural system 100 or the determined path of the agricultural system 100 triggers the assignment of a higher priority to an identified obstacle in comparison to the same identified obstacle that is not proximate to the determined path or is not proximate to the agricultural system 100. In operation, the obstacle recognition module 310 cooperates with and communicates with other components of the autonomous obstacle monitoring and vehicle control system 300 to identify and track obstacles and facilitate enhanced guidance of the agricultural system 100 through the field while still allowing the agricultural system 100 to accomplish one or more agricultural processes. The remote sensing device 114 is deployed by the autonomous agricultural system controller 104 by way of a mission administration module 304 providing a mission route to the remote sensing device 114 or, guiding operation of the remote sensing device 114 along a mission route. The remote sensing device 114, while conducting the mission, observes the area proximate to a determined path, proximate to the agricultural system 100 or the like, for instance, along a corresponding mission route for the remote sensing device 114 (See at least Figs. 1-3B, and [0075-0078]). Examiner notes, as mentioned above, the proximity to the agricultural system or the determined path of the agricultural system triggers the assignment of a higher priority to an identified obstacle relative to other identified obstacles including, for instance, brush, washouts, rocks, saturated or soaked areas of the field or the like and the autonomous agricultural system controller provides a mission route to the remote sensing device, which is also generating a travel plan for the UAV, to observe the obstacles. The type of the obstacle, such as livestock, brush, fence or rocks, is the identified one or more characteristics of the obstruction. That is, generating the travel plan based, at least in part, on the identified one or more characteristics of the obstruction and 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 the invention of Kinoshita, as already modified by Kocer, by further incorporating the teachings of Kocer, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – agricultural machines, such that the prioritizing module of Kocer is used to assign higher priorities to obstacles along the planned route of the agricultural machine and a travel plan for the UAV is created based on the obstacle type and the assigned priorities and the drone is controlled to collect sensor data based on the obstacle type and the assigned priority to the obstacle.
The motivation to do so is the same as acknowledged by Kocer in regard to claim 1.

In regard to claim 8
, Kinoshita, as modified by Kocer, 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 (See at least Figs. 8, and [0130 & 0145-0147]: when the communication device 75 of the unmanned aerial vehicle 70 receives the work information (the travel position P1, the agricultural field information, and the operation information) transmitted from the tractor 1 (S3), the communication device 75 determines an operation such as flight based on the work information. When the controller 76 refers to the work information and determines from the work information that the travel position P1 is approaching the agricultural field H1 where the work is to be performed (S4, Yes), the controller 76 controls the rotor blades 70c to cause the unmanned aerial vehicle 70 to take off from the takeoff location 100 and then fly to the agricultural field H1 where the work of the tractor 1 is to be performed (S5). The controller 76 is operable to change the flight position to a position that allows the sensor 72 to sense an area forward of the traveling vehicle body 3 in a direction of travel when the working implement 2 performs ground work. Examiner notes, for programming a controller, instructions are necessarily used and the instructions are stored in memory and executed by the processor of the controller. As mentioned above, the drone changes its flight position to sense an area forward of the traveling vehicle body. Each position is a monitoring location and as the traveling vehicle body moves across the field, the drone moves along with the traveling vehicle body and changes its position to sense the area forward of the traveling vehicle body):
identify the monitoring sequence of the travel plan based, at least in part, on the identified one or more characteristics of the obstruction and the priority order of the one or more attributes.
Further, Kocer teaches the obstacle recognition module 310 includes a prioritizing module 318. The prioritizing module 318 is configured to assign priorities to obstacles based on a catalog set of priorities, priority rules, user input priorities or user input priority rules or the like. Archived obstacles such as humans, livestock or the like have a higher priority relative to other identified obstacles including, for instance, brush, washouts, rocks, saturated or soaked areas of the field or the like. As described herein, the assigned priority of an identified object changes the operation of the agricultural system 100, for instance with the vehicle operation module 306 of the autonomous agricultural system controller 104. The identification of a human proximate to a determined path of the agricultural system 100 is given a high priority while other obstacles such as livestock, brush, fence or rocks or the like proximate to the determined path are given a lower priority (and optionally scaled lower priorities with livestock higher than brush or similar inanimate obstacles). For instance, the prioritizing module 318 assigns a higher priority to particular types of obstacles, for instance, humans or the like. The proximity to the agricultural system 100 or the determined path of the agricultural system 100 triggers the assignment of a higher priority to an identified obstacle in comparison to the same identified obstacle that is not proximate to the determined path or is not proximate to the agricultural system 100. In operation, the obstacle recognition module 310 cooperates with and communicates with other components of the autonomous obstacle monitoring and vehicle control system 300 to identify and track obstacles and facilitate enhanced guidance of the agricultural system 100 through the field while still allowing the agricultural system 100 to accomplish one or more agricultural processes. The remote sensing device 114 is deployed by the autonomous agricultural system controller 104 by way of a mission administration module 304 providing a mission route to the remote sensing device 114 or, guiding operation of the remote sensing device 114 along a mission route. The remote sensing device 114, while conducting the mission, observes the area proximate to a determined path, proximate to the agricultural system 100 or the like, for instance, along a corresponding mission route for the remote sensing device 114. The 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, 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 (See at least Figs. 1-3B, 5, and [0075-0078 & 0102]). Examiner notes, as mentioned above, the proximity to the agricultural system or the determined path of the agricultural system triggers the assignment of a higher priority to an identified obstacle and the autonomous agricultural system controller provides a mission route to the remote sensing device, which is also generating a travel plan for the UAV, to observe the area proximate to a determined path. That is, identifying the monitoring sequence of the travel plan based, at least in part, on the identified one or more characteristics of the obstruction and the priority order of the one or more attributes. Furthermore, as illustrated by Figure 3 (Fig. 5 of Kocer, reproduced and annotated for Applicant’s convenience), the remote sensing device 114 travels along the scouting mission 500 and observes the obstacles as it moves along the path. The scouting mission 500 is a monitoring sequence defining an order in which the drone is to travel between each monitoring location of the plurality of monitoring location.

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Figure 3 - Annotated Fig. 5 of Kocer

It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify the invention of Kinoshita, as already modified by Kocer, by further incorporating the teachings of Kocer, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – agricultural machines, such that the prioritizing module of Kocer is used to assign higher priorities to obstacles along the planned route of the agricultural machine and a travel plan for the UAV is created based on the assigned priorities and the drone is controlled to collect sensor data based on the assigned priority.
The motivation to do so is the same as acknowledged by Kocer in regard to claim 1.

In regard to claim 9
, Kinoshita, as modified by Kocer, teaches the agricultural system of claim 1, wherein the control signal controls a controllable subsystem of the agricultural work machine (See at least Fig. 7A and 8, and [0133]: the sensor 72 is directed toward the front of the tractor 1 to capture an image of an area located forward of the tractor 1 and monitor whether a living body Ml, an obstacle, or the like, is present forward of the tractor 1. When the living body M1 or the obstacle is detected in the second sensing, the communication device 75 transmits a warning signal to the communication device 51 (S13). When acquiring the warning signal via the communication device 51, the traveling controller 40A of the tractor 1 stops the automatic traveling and stops the tractor 1 (S14) [i.e., wherein the control signal controls a controllable subsystem of the agricultural work machine]. The traveling controller 40A of the tractor 1 resumes the automatic traveling when the warning signal is not acquired for a predetermined time or more, or when a release signal for releasing the warning is received from the unmanned aerial vehicle 70 (S15). Examiner notes, the traveling controller 40A is a controllable subsystem of the agricultural work machine).

In regard to claim 10
, Kinoshita, as modified by Kocer, teaches the agricultural system of claim 1, wherein the control signal controls an additional agricultural work machine different than the agricultural work machine.
Further, Kocer teaches by monitoring the obstacles in the field including field obstacles 620 and optionally absent obstacles 622 (or initiating the removal of previous obstacles 620, such as now harvested crops) the remote sensing device 114 in combination with the rest of the system 300 (or 350) provides updated field information to the systems 300 for corresponding modification of the operation (e.g., driving, implement operation or the like) of one or more of the agricultural systems [i.e., an additional agricultural work machine different than the agricultural work machine] such as the fourth agricultural system 608. In the context of Fig. 6, the updated identification and indexing of obstacles facilitates modification of the determined paths from the fourth agricultural system 608 to one or more locations of interest within the field including, for instance, the dynamically changing locations of the first through third agricultural systems 602-606 (See at least Fig. 6, and [0110]). Examiner notes, changing the location of the first through third agricultural systems 602-606, based on detecting an obstacle by the remote sensing device 114, is controlling an additional agricultural work machine different than the agricultural work machine and it encompasses generating a control signal for changing the location of the additional agricultural system.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify the invention of Kinoshita, as already modified by Kocer, by further incorporating the teachings of Kocer, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – agricultural machines, such that two or more agricultural machines are controlled based on detecting an obstacle by a remote sensing system.
The motivation to modify is that, as acknowledged by Kocer, to identify obstacles from the signals of the various sensors and provide alerts regarding the identified obstacles (See at least [0006]) which one of ordinary skill would have recognized allows the obstacle detection become more accurate.

In regard to claim 11
, Kinoshita discloses a computer implemented method comprising (See at least Fig. 15, and [0121 & 0181-0182]: the controller 76 includes a CPU [i.e., a computer]. Fig. 15 is a flowchart presenting an operation in association between the unmanned aerial vehicle 70 and the tractor 1. The unmanned aerial vehicle 70 is flying forward of the tractor 1 while the sensor 72 performs sensing. Examiner notes, a flowchart is a method and a controller is a computer. As such, Kinoshita discloses a computer implemented method):
obtaining operation data indicative of a location of an agricultural work machine on a worksite and a travel path of the agricultural work machine across the worksite (See at least Figs. 1-4, 6A, and [0087-0088 & 0097 & 0125 & 0130]: the sensor 72 performs sensing in the direction of travel while the tractor 1 is automatically traveling and performing work (during work) [i.e., obtain … a travel path of the agricultural work machine across the worksite]. That is, the controller 76 of the unmanned aerial vehicle 70 changes the flight position to a position that allows an area forward of the vehicle body 3 in the direction of travel to be sensed when the working implement 2 performs the ground work. When the communication device 75 of the unmanned aerial vehicle 70 receives the work information (the travel position P1, the agricultural field information, and the operation information) [i.e., obtain operation data indicative of a location of the agricultural work machine on the worksite] transmitted from the tractor 1 (S3), the communication device 75 determines an operation such as flight based on the work information);
identifying, based on the operation data indicative of the location and the travel path of the agricultural work machine, 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 (See at least Figs. 4, 11A, and [0155-0156]: the situation in the direction of travel of the tractor 1 is sensed [i.e., based on the operation data indicative of the location and the travel path of the agricultural work machine] by the sensor 72 of the unmanned aerial vehicle 70 during the automatic traveling of the tractor 1. However, the obstacle detector 45 of the tractor 1 changes a detection area [i.e., identify … one or more measurement areas] to detect an obstacle M2 based on the result sensed by the sensor 72 of the unmanned aerial vehicle 70. Examiner notes, as illustrated by Figure 1 (Fig. 11A of Kinoshita, reproduced and annotated for Applicant’s convenience), the measurement area is 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. Furthermore, an obstacle, which is an environmental attribute, is detected by the unmanned aerial vehicle 70 in the measurement area);
generating a travel plan for a drone, the travel plan including a plurality of monitoring locations and (See at least Figs. 8, and [0130 & 0145-0147]: when the communication device 75 of the unmanned aerial vehicle 70 receives the work information (the travel position P1, the agricultural field information, and the operation information) transmitted from the tractor 1 (S3), the communication device 75 determines an operation such as flight based on the work information [i.e., generating a travel plan for a drone]. When the controller 76 refers to the work information and determines from the work information that the travel position P1 is approaching the agricultural field H1 where the work is to be performed (S4, Yes), the controller 76 controls the rotor blades 70c to cause the unmanned aerial vehicle 70 to take off from the takeoff location 100 and then fly to the agricultural field H1 where the work of the tractor 1 is to be performed (S5). The controller 76 is operable to change the flight position to a position that allows the sensor 72 to sense an area forward of the traveling vehicle body 3 in a direction of travel when the working implement 2 performs ground work. Examiner notes, as mentioned above, the drone changes its flight position to sense an area forward of the traveling vehicle body. Each position is a monitoring location and as the traveling vehicle body moves across the field, the drone moves along with the traveling vehicle body and changes its position to sense the area forward of the traveling vehicle body. That means the travel plan including a plurality of monitoring locations),
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 (See at least [0147]: the controller 76 is operable to change the flight position to a position that allows the sensor 72 to sense an area [i.e., measurement area] forward of the traveling vehicle body 3 in a direction of travel when the working implement 2 performs ground work. Examiner notes, as illustrated by Figure 1 (Fig. 11A of Kinoshita, reproduced and annotated for Applicant’s convenience), the measurement area is lateral of at least, the portion of the agricultural work machine. The position of the drone, while capturing the sensor data related to the obstacle M3, is the a monitoring location among the plurality of monitoring locations, which corresponds to a corresponding measurement area. Furthermore, an obstacle, which is an environmental attribute, is detected by the unmanned aerial vehicle 70 in the corresponding measurement area), 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 (See at least Figs. 1, 4, 11A, [0125 & 0147]: the controller 76 of the unmanned aerial vehicle 70 changes the flight position to a position that allows an area forward of the vehicle body 3 [i.e., each monitoring location, of the plurality of monitoring locations, defines a location to position the drone to have a sensor system] in the direction of travel to be sensed when the working implement 2 performs the ground work. The situation in the direction of travel of the tractor 1 is sensed by the sensor 72 [i.e., a sensor system, disposed on the drone] of the unmanned aerial vehicle 70 during the automatic traveling of the tractor 1. When the sensor 72 detects an object M3, such as a living body M1 or an obstacle M2, in a situation in which the tractor 1 is traveling and the sensor 72 is capturing an image of an area located forward of the tractor 1, the communication device 75 of the unmanned aerial vehicle 70 transmits, as the detection result, information indicating the detection of the object M3, for example, the size (height H10, width L10, depth W10) and the position of the object M3 [i.e., detect a plurality of attributes in the corresponding measurement area of the one or more measurement areas] to the tractor 1. Examiner notes, as the tractor 1 moves within the field, the drone changes its position and the measurement area for detecting the obstacles. Each location where the drone senses an area forward of the traveling vehicle body 3 surrounding the vehicle is a monitoring location):
controlling positioning of the drone relative to an agricultural work machine based on the travel plan (See at least Figs. 1, 4, 6B, 8, and [0130 & 0145]: when the communication device 75 of the unmanned aerial vehicle 70 receives the work information (the travel position P1, the agricultural field information, and the operation information) transmitted from the tractor 1 (S3), the communication device 75 determines an operation such as flight based on the work information. When the controller 76 refers to the work information and determines from the work information that the travel position P1 is approaching the agricultural field H1 where the work is to be performed (S4, Yes), the controller 76 controls the rotor blades 70c to cause the unmanned aerial vehicle 70 to take off from the takeoff location 100 and then fly to the agricultural field H1 where the work of the tractor 1 is to be performed (S5). When the working implement 2 is raised or lowered, the controller 76 of the unmanned aerial vehicle 70 senses the entire working implement 2 by causing the unmanned aerial vehicle 70 to fly in the surrounding area of the working implement 2 [i.e., controlling positioning of the drone relative to an agricultural work machine based on the travel plan], and when the working implement 2 is lowered from the raised position, the controller 76 senses mainly the blind spot of the working implement 2 by setting the flight position of the unmanned aerial vehicle 70 below the working implement 2. Examiner notes, the drone following the agricultural machine to monitor the area surrounding the agricultural machine is the travel plan for the drone. As such, Kinoshita teaches controlling positioning of the drone relative to an agricultural work machine based on the travel plan);
detecting, with the sensor system disposed on the drone, the plurality of attributes (See at least Fig. 11A, and [0156]: when the sensor 72 [i.e., the sensor system disposed on the drone] detects an object M3, such as a living body M1 or an obstacle M2 [i.e., detecting, with the sensor system disposed on the drone, the plurality of attributes], in a situation in which the tractor 1 is traveling and the sensor 72 is capturing an image of an area located forward of the tractor 1, the communication device 75 of the unmanned aerial vehicle 70 transmits, as the detection result, information indicating the detection of the object M3, the size (height H10, width L10, depth W10) and the position of the object M3 [i.e., the plurality of attributes] to the tractor 1);
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 (See at least Fig. 11A, and [0156]: when the sensor 72 [i.e., the sensor system] detects an object M3, such as a living body M1 or an obstacle M2 [i.e., generating … 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], in a situation in which the tractor 1 is traveling and the sensor 72 is capturing an image of an area located forward of the tractor 1, the communication device 75 of the unmanned aerial vehicle 70 transmits, as the detection result, information indicating the detection of the object M3, the size (height H10, width L10, depth W10) and the position of the object M3 to the tractor 1. Examiner notes, when a sensor detects an obstacle, it necessarily generates sensor data);
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 (See at least Figs. 1, 4, 11A, and [0156]: when the sensor 72 [i.e., based on the sensor data] detects an object M3, such as a living body M1 or an obstacle M2 [i.e., identify the one or more attributes in the one or more measurement areas lateral of the agricultural work], in a situation in which the tractor 1 is traveling and the sensor 72 is capturing an image of an area located forward of the tractor 1, the communication device 75 of the unmanned aerial vehicle 70 transmits, as the detection result, information indicating the detection of the object M3, the size (height H10, width L10, depth W10) and the position of the object M3 to the tractor 1 [i.e., indicative of the one or more attributes in the one or more measurement areas lateral of the agricultural work machine]. Examiner notes, a sensor necessarily generates sensor data); 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 (See at least Figs. 1, 4, 8, and [0131]: the controller 76 performs control of sensing a surrounding area of the tractor 1 (a range several meters away from the tractor 1) by the unmanned aerial vehicle 70 (S7: first sensing). In the first sensing, the sensor 72 is directed toward the tractor 1 to capture an image of the range several meters away from the tractor 1, thus monitoring whether a living body M1 such as an animal or a human is present in the range [i.e., one or more attributes in the one or more measurement areas lateral of the agricultural work machine]. When the living body M1 is detected in the first sensing, the communication device 75 transmits to the communication device 51 (S8) a warning signal. When acquiring the warning signal via the communication device 51, the traveling controller 40A of the tractor 1 does not start the automatic traveling and maintains the stop (S9). The traveling controller 40A of the tractor 1 starts the automatic traveling when the warning signal is not acquired for a predetermined time or more, or when a release signal for releasing the warning is received from the unmanned aerial vehicle 70 (S10). Examiner notes, starting or stopping automatic traveling necessarily encompasses generating a control signal. As mentioned above, the automatic traveling starts or stops based on detecting an attribute, such as an obstacle, in the measurement area).
Kinoshita is silent on a monitoring sequence defining an order in which the drone is to travel between each monitoring location of the plurality of monitoring location.
However, Kocer teaches the remote sensing device 114 is deployed by the autonomous agricultural system controller 104 by way of a mission administration module 304 providing a mission route to the remote sensing device 114 or, guiding operation of the remote sensing device 114 along a mission route. The remote sensing device 114, while conducting the mission, observes the area proximate to a determined path, proximate to the agricultural system 100 or the like, for instance, along a corresponding mission route for the remote sensing device 114. The 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, 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 (See at least Figs. 1-3B, 5, and [0078 & 0102]). Examiner notes, as illustrated by Figure 3 (Fig. 5 of Kocer, reproduced and annotated for Applicant’s convenience), the remote sensing device 114 travels along the scouting mission 500 and observes the obstacles as it moves along the path. The scouting mission 500 is a monitoring sequence defining an order in which the drone is to travel between each monitoring location of the plurality of monitoring location.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify the invention of Kinoshita, by incorporating the teachings of Kocer, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – agricultural machines, such that a scouting mission is generated for the drone, which is a monitoring sequence for monitoring obstacles along the created travel plan for the drone.
The motivation to do so is the same as acknowledged by Kocer in regard to claim 1.

In regard to claim 12
, Kinoshita, as modified by Kocer, teaches the computer implemented method of claim 11, wherein the plurality of monitoring locations are remote from the agricultural work machine.
Further, Kocer teaches one or more different missions are conducted by the remote sensing device 114. For instance, relative to the second agricultural system 702, one or more of an inspection mission 720A and a scouting mission 732A [i.e., the plurality of monitoring locations] are conducted proximate to the second agricultural system 702 or along a determined path 730 (proposed, initial or undefined path) of the second agricultural system 702 [i.e., remote from the agricultural work machine] (Fig. 7, and [0118]). Examiner notes, when the inspection is along the determined path 730, the monitoring locations 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 the invention of Kinoshita, as already modified by Kocer, by further incorporating the teachings of Kocer, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – agricultural machines, such that a remote sensing device, such as a drone or a UAV, is used for monitoring locations that are remote from the agricultural work machine.
The motivation to do so is the same as acknowledged by Kocer in regard to claim 1.

In regard to claim 13
, Kinoshita, as modified by Kocer, teaches 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 (See at least Fig. 10, and [0156]: when the sensor 72 detects an object M3, such as a living body M1 or an obstacle M2, in a situation in which the tractor 1 is traveling and the sensor 72 is capturing an image of an area located forward of the tractor 1, the communication device 75 of the unmanned aerial vehicle 70 transmits, as the detection result, information indicating the detection of the object M3, for example, the size (height H10, width L10, depth W10) and the position of the object M3 [i.e., 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] to the tractor 1); and
generating the travel plan based, at least in part, on the identified one or more characteristics of the obstruction.
Further, Kocer teaches the obstacle recognition module 310 includes a prioritizing module 318. The prioritizing module 318 is configured to assign priorities to obstacles based on a catalog set of priorities, priority rules, user input priorities or user input priority rules or the like. Archived obstacles such as humans, livestock or the like have a higher priority relative to other identified obstacles including, for instance, brush, washouts, rocks, saturated or soaked areas of the field or the like. As described herein, the assigned priority of an identified object changes the operation of the agricultural system 100, for instance with the vehicle operation module 306 of the autonomous agricultural system controller 104. The identification of a human proximate to a determined path of the agricultural system 100 is given a high priority while other obstacles such as livestock, brush, fence or rocks or the like proximate to the determined path are given a lower priority (and optionally scaled lower priorities with livestock higher than brush or similar inanimate obstacles). For instance, the prioritizing module 318 assigns a higher priority to particular types of obstacles, for instance, humans or the like. The proximity to the agricultural system 100 or the determined path of the agricultural system 100 triggers the assignment of a higher priority to an identified obstacle in comparison to the same identified obstacle that is not proximate to the determined path or is not proximate to the agricultural system 100. In operation, the obstacle recognition module 310 cooperates with and communicates with other components of the autonomous obstacle monitoring and vehicle control system 300 to identify and track obstacles and facilitate enhanced guidance of the agricultural system 100 through the field while still allowing the agricultural system 100 to accomplish one or more agricultural processes. The remote sensing device 114 is deployed by the autonomous agricultural system controller 104 by way of a mission administration module 304 providing a mission route to the remote sensing device 114 or, guiding operation of the remote sensing device 114 along a mission route. The remote sensing device 114, while conducting the mission, observes the area proximate to a determined path, proximate to the agricultural system 100 or the like, for instance, along a corresponding mission route for the remote sensing device 114 (See at least Figs. 1-3B, and [0075-0078]); Examiner notes, as mentioned above, the proximity to the agricultural system or the determined path of the agricultural system triggers the assignment of a higher priority to an identified obstacle relative to other identified obstacles including, for instance, brush, washouts, rocks, saturated or soaked areas of the field or the like and the autonomous agricultural system controller provides a mission route to the remote sensing device, which is also generating a travel plan for the UAV, to observe the obstacles. The type of the obstacle, such as livestock, brush, fence or rocks, is the identified one or more characteristics of the obstruction. That is, generating the travel plan based, at least in part, on the identified one or more characteristics of the obstruction.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify the invention of Kinoshita, as already modified by Kocer, by further incorporating the teachings of Kocer, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – agricultural machines, such that the prioritizing module of Kocer is used to assign higher priorities to obstacles along the planned route of the agricultural machine and a travel plan for the UAV is created based on the obstacle type and the drone is controlled to collect sensor data based on the obstacle type and the assigned priority to the obstacle.
The motivation to do so is the same as acknowledged by Kocer in regard to claim 1.

In regard to claim 15
, Kinoshita, as modified by Kocer, teaches 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.
Further, Kocer teaches the obstacle recognition module 310 includes a prioritizing module 318. The prioritizing module 318 is configured to assign priorities to obstacles based on a catalog set of priorities, priority rules, user input priorities or user input priority rules or the like. Archived obstacles such as humans, livestock or the like have a higher priority relative to other identified obstacles including, for instance, brush, washouts, rocks, saturated or soaked areas of the field or the like. As described herein, the assigned priority of an identified object changes the operation of the agricultural system 100, for instance with the vehicle operation module 306 of the autonomous agricultural system controller 104. The identification of a human proximate to a determined path of the agricultural system 100 is given a high priority while other obstacles such as livestock, brush, fence or rocks or the like proximate to the determined path are given a lower priority (and optionally scaled lower priorities with livestock higher than brush or similar inanimate obstacles). For instance, the prioritizing module 318 assigns a higher priority to particular types of obstacles, for instance, humans or the like. The proximity to the agricultural system 100 or the determined path of the agricultural system 100 triggers the assignment of a higher priority to an identified obstacle in comparison to the same identified obstacle that is not proximate to the determined path or is not proximate to the agricultural system 100. In operation, the obstacle recognition module 310 cooperates with and communicates with other components of the autonomous obstacle monitoring and vehicle control system 300 to identify and track obstacles and facilitate enhanced guidance of the agricultural system 100 through the field while still allowing the agricultural system 100 to accomplish one or more agricultural processes. The remote sensing device 114 is deployed by the autonomous agricultural system controller 104 by way of a mission administration module 304 providing a mission route to the remote sensing device 114 or, guiding operation of the remote sensing device 114 along a mission route. The remote sensing device 114, while conducting the mission, observes the area proximate to a determined path, proximate to the agricultural system 100 or the like, for instance, along a corresponding mission route for the remote sensing device 114 (See at least Figs. 1-3B, and [0075-0078]). Examiner notes, as mentioned above, the proximity to the agricultural system or the determined path of the agricultural system triggers the assignment of a higher priority to an identified obstacle relative to other identified obstacles including, for instance, brush, washouts, rocks, saturated or soaked areas of the field or the like and the autonomous agricultural system controller provides a mission route to the remote sensing device, which is also generating a travel plan for the UAV, to observe the obstacles. The type of the obstacle, such as livestock, brush, fence or rocks, is the identified one or more characteristics of the obstruction. That is, generating the travel plan based, at least in part, on the identified one or more characteristics of the obstruction and the priority order of the one or more attributes. Furthermore, as illustrated by Figure 3 (Fig. 5 of Kocer, reproduced and annotated for Applicant’s convenience), the remote sensing device 114 travels along the scouting mission 500 and observes the obstacles as it moves along the path. The scouting mission 500 is a monitoring sequence defining an order in which the drone is to travel between each monitoring location of the plurality of monitoring location.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify the invention of Kinoshita, as already modified by Kocer, by further incorporating the teachings of Kocer, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – agricultural machines, such that the prioritizing module of Kocer is used to assign higher priorities to obstacles along the planned route of the agricultural machine and a travel plan for the UAV is created based on the obstacle type and the assigned priorities and the drone is controlled to collect sensor data based on the obstacle type and the assigned priority to the obstacle.
The motivation to do so is the same as acknowledged by Kocer in regard to claim 1.

In regard to claim 16
, Kinoshita, as modified by Kocer, teaches the computer implemented method of claim 11, 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.
Further, Kocer teaches the obstacle recognition module 310 includes a prioritizing module 318. The prioritizing module 318 is configured to assign priorities to obstacles based on a catalog set of priorities, priority rules, user input priorities or user input priority rules or the like [i.e., identifying a priority of each monitoring location of the plurality of monitoring locations]. The identification of a human proximate to a determined path of the agricultural system 100 is given a high priority while other obstacles such as livestock, brush, fence or rocks or the like proximate to the determined path are given a lower priority (and optionally scaled lower priorities with livestock higher than brush or similar inanimate obstacles). For instance, the prioritizing module 318 assigns a higher priority to particular types of obstacles, for instance, humans or the like. The proximity to the agricultural system 100 or the determined path of the agricultural system 100 triggers the assignment of a higher priority to an identified obstacle in comparison to the same identified obstacle that is not proximate to the determined path or is not proximate to the agricultural system 100. In operation, the obstacle recognition module 310 cooperates with and communicates with other components of the autonomous obstacle monitoring and vehicle control system 300 to identify and track obstacles and facilitate enhanced guidance of the agricultural system 100 through the field while still allowing the agricultural system 100 to accomplish one or more agricultural processes. The remote sensing device 114 is deployed by the autonomous agricultural system controller 104 by way of a mission administration module 304 providing a mission route to the remote sensing device 114 or, guiding operation of the remote sensing device 114 along a mission route [i.e., generating the travel plan]. The remote sensing device 114, while conducting the mission, observes the area proximate to a determined path, proximate to the agricultural system 100 or the like [i.e., based, at least in part, on the identified priority of each of the one or more monitoring locations], for instance, along a corresponding mission route for the remote sensing device 114 (See at least Figs. 1-3B, and [0075-0078]). Examiner notes, as mentioned above, the proximity to the agricultural system or the determined path of the agricultural system triggers the assignment of a higher priority to an identified obstacle relative to other identified obstacles including, for instance, brush, washouts, rocks, saturated or soaked areas of the field or the like and the autonomous agricultural system controller provides a mission route to the remote sensing device, which is also generating a travel plan for the UAV, to observe the obstacles. The type of the obstacle, such as livestock, brush, fence or rocks, is the identified one or more characteristics of the obstruction. That is, generating the travel plan based, at least in part, on the identified priority of each of the one or more monitoring locations.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify the invention of Kinoshita, as already modified by Kocer, by further incorporating the teachings of Kocer, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – agricultural machines, such that the prioritizing module of Kocer is used to assign higher priorities to obstacles along the planned route of the agricultural machine and a travel plan for the UAV is created based on the assigned priorities.
The motivation to do so is the same as acknowledged by Kocer in regard to claim 1.

In regard to claim 17
, Kinoshita, as modified by Kocer, teaches 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 (See at least Fig. 8, and [0131]: the controller 76 performs control of sensing a surrounding area of the tractor 1 (a range several meters away from the tractor 1) by the unmanned aerial vehicle 70 (S7: first sensing). In the first sensing, the sensor 72 is directed toward the tractor 1 to capture an image of the range several meters away from the tractor 1, thus monitoring whether a living body M1 such as an animal or a human is present in the range. When the living body M1 is detected in the first sensing, the communication device 75 transmits to the communication device 51 (S8) a warning signal. When acquiring the warning signal via the communication device 51, the traveling controller 40A of the tractor 1 does not start the automatic traveling and maintains the stop (S9). The traveling controller 40A of the tractor 1 starts the automatic traveling when the warning signal is not acquired for a predetermined time or more, or when a release signal for releasing the warning is received from the unmanned aerial vehicle 70 (S10). Examiner notes, starting or stopping automatic traveling based on a warning or a release signal necessarily encompasses generating a control signal to control the agricultural work machine. As mentioned above, the automatic traveling starts or stops based on detecting an attribute, such as an obstacle, in the measurement area); or
generating a control signal to control an additional agricultural work machine different than the agricultural work machine.
Further, Kocer teaches by monitoring the obstacles in the field including field obstacles 620 and optionally absent obstacles 622 (or initiating the removal of previous obstacles 620, such as now harvested crops) the remote sensing device 114 in combination with the rest of the system 300 (or 350) provides updated field information to the systems 300 for corresponding modification of the operation (e.g., driving, implement operation or the like) of one or more of the agricultural systems [i.e., an additional agricultural work machine different than the agricultural work machine] such as the fourth agricultural system 608. In the context of Fig. 6, the updated identification and indexing of obstacles facilitates modification of the determined paths from the fourth agricultural system 608 to one or more locations of interest within the field including, for instance, the dynamically changing locations of the first through third agricultural systems 602-606 (See at least Fig. 6, and [0110]). Examiner notes, changing the location of the first through third agricultural systems 602-606, based on detecting an obstacle by the remote sensing device 114, is controlling an additional agricultural work machine different than the agricultural work machine and it encompasses generating a control signal for changing the location of the additional agricultural system.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify the invention of Kinoshita, as already modified by Kocer, by further incorporating the teachings of Kocer, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – agricultural machines, such that two or more agricultural machines are controlled based on detecting an obstacle by a remote sensing system.
The motivation to do so is the same as acknowledged by Kocer in regard to claim 1.

10. Claim(s) 14
is/are rejected under 35 U.S.C. 103 as being unpatentable over Kinoshita et al. (US-20230322423-A1) in view of Kocer (US-20210357664-A1) and further in view of Skowronek et al. (US-20180143321-A1).
In regard to claim 14
, Kinoshita, as modified by Kocer, teaches 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 (See at least Fig. 10, and [0156]: when the sensor 72 detects an object M3, such as a living body M1 or an obstacle M2, in a situation in which the tractor 1 is traveling and the sensor 72 is capturing an image of an area located forward of the tractor 1, the communication device 75 of the unmanned aerial vehicle 70 transmits, as the detection result, information indicating the detection of the object M3, for example, the size (height H10, width L10, depth W10) and the position of the object M3 [i.e., 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] to the tractor 1).
Kinoshita, as modified by Kocer, 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 (See at least Fig. 1, [0046 & 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 the invention of Kinoshita, as already modified by Kocer, by incorporating the teachings of Skowronek, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – tracking systems, such that the drone is positioned in an open location to ensure that the drone is not obstructed.
The motivation to modify is that, as acknowledged by Kocer, to improve passive tracking (See at least [0086]) which one of ordinary skill would have recognized makes the operation of the agricultural machine safer and more reliable.

11. Claim(s) 18
is/are rejected under 35 U.S.C. 103 as being unpatentable over Kinoshita et al. (US-20230322423-A1) in view of Menzel et al. (US-20190094861-A1).
In regard to claim 18
, Kinoshita discloses an agricultural system comprising (See at least Figs. 1-2, and [0035]: the agricultural support system [i.e., an agricultural system] includes an unmanned aerial vehicle and an agricultural machine):
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 (See at least Fig. 4, and [0116-0118 & 0135 & 0151]: the unmanned aerial vehicle 70 includes a sensor 72, a position detector 73 [i.e., a sensor system]. When the unmanned aerial vehicle 70 flies above an agricultural field [i.e., remotely positionable from an agricultural work machine at a worksite], the sensor 72 senses the agricultural field. The sensor 72 is directed toward the working implement 2 to capture an image of the surrounding area of the working implement 2, thus monitoring whether a living body M1 or an obstacle M2 is present in the surrounding area [i.e., to detect one or more attributes]. The unmanned aerial vehicle 70 includes a communication device 75 to transmit stop of travel to the agricultural machine 1 [i.e., communicably coupled to … an agricultural work machine] when the sensor 72 detects the living body while the agricultural machine 1 is traveling. Examiner notes, according to relevant paragraph [0061] of Applicant’s specification: “Environmental attributes can include field feature attributes such as field boundaries, field obstacles (e.g., type, presence, and location of obstacles at the field), field conditions (e.g., ruts, damage, etc.), field working limits (e.g., working limits due to power lines, overpasses, bridges, culverts, etc.), and other field feature attributes.” Accordingly, the presence of field obstacles, such as a living body, was interpreted as environmental attributes);
one or more processors (See at least Fig. 4, and [0116 & 0121]: the unmanned aerial vehicle 70 includes a memory 74, a communication device 75, and a controller 76 [i.e., one or more processors]. The controller 76 includes a CPU [i.e., one or more processors]); 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 (See at least Fig. 4, and [0116 & 0150]: the unmanned aerial vehicle 70 includes a memory 74 [i.e., memory], a communication device 75, and a controller 76. The controller 76 is configured or programmed to change the flight position to a surrounding area of the living body when the sensor 72 detects the living body. Examiner notes, for programming a controller, instructions are necessarily used and the instructions are stored in memory and executed by the processor of the controller):
obtain operation data indicative of a location of the agricultural work machine on the worksite and a travel path of the agricultural work machine across the worksite (See at least Figs. 1-4, 6A, and [0087-0088 & 0097 & 0125 & 0130]: the sensor 72 performs sensing in the direction of travel while the tractor 1 is automatically traveling and performing work (during work) [i.e., obtain … a travel path of the agricultural work machine across the worksite]. That is, the controller 76 of the unmanned aerial vehicle 70 changes the flight position to a position that allows an area forward of the vehicle body 3 in the direction of travel to be sensed when the working implement 2 performs the ground work. When the communication device 75 of the unmanned aerial vehicle 70 receives the work information (the travel position P1, the agricultural field information, and the operation information) [i.e., obtain operation data indicative of a location of the agricultural work machine on the worksite] transmitted from the tractor 1 (S3), the communication device 75 determines an operation such as flight based on the work information);
identify, based on the operation data indicative of the location and the travel path of the agricultural work machine, 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 (See at least Figs. 4, 11A, and [0155-0156]: the situation in the direction of travel of the tractor 1 is sensed [i.e., based on the operation data indicative of the location and the travel path of the agricultural work machine] by the sensor 72 of the unmanned aerial vehicle 70 during the automatic traveling of the tractor 1. However, the obstacle detector 45 of the tractor 1 changes a detection area [i.e., identify … one or more measurement areas] to detect an obstacle M2 based on the result sensed by the sensor 72 of the unmanned aerial vehicle 70. Examiner notes, as illustrated by Figure 1 (Fig. 11A of Kinoshita, reproduced and annotated for Applicant’s convenience), the measurement area is 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. Furthermore, an obstacle, which is an environmental attribute, is detected by the unmanned aerial vehicle 70 in the measurement area);
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 (See at least Fig. 11A, and [0156]: when the sensor 72 detects an object M3, such as a living body M1 or an obstacle M2 [i.e., identify one or more characteristics of an obstruction at the worksite], in a situation in which the tractor 1 is traveling and the sensor 72 is capturing an image of an area located forward of the tractor 1, the communication device 75 of the unmanned aerial vehicle 70 transmits, as the detection result, information indicating the detection of the object M3, the size (height H10, width L10, depth W10) and the position of the object M3 to the tractor 1 [i.e., the one or more characteristics comprising one or more of a location of the obstruction]):
generate a travel plan for the drone (See at least Fig. 6A, and [124-0133]: the controller 76 of the unmanned aerial vehicle 70 changes the flight position of the unmanned aerial vehicle 70 [i.e., generate a travel plan for the drone] in tandem with an operation of the tractor 1. The controller 76 of the unmanned aerial vehicle 70 changes the flight position to a position that allows an area forward of the vehicle body 3 in the direction of travel to be sensed [i.e., 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 drone to have the sensor system] when the working implement 2 performs the ground work. The sensor 72 is directed toward the front of the tractor 1 to capture an image of an area located forward of the tractor 1 and monitor whether a living body Ml, an obstacle, or the like, is present forward of the tractor 1 [i.e., detect the one or more attributes in a corresponding measurement area of the one or more measurement areas lateral of, at least, the portion of the agricultural work machine]. Examiner notes, changing the flight plan necessarily encompasses generating a travel plan for the drone);
control the drone based on the travel plan (See at least Fig. 6A, and [125-0133]: the controller 76 of the unmanned aerial vehicle 70 changes the flight position to a position that allows an area forward of the vehicle body 3 in the direction of travel to be sensed [i.e., control the drone based on the travel plan] when the working implement 2 performs the ground work. The sensor 72 is directed toward the front of the tractor 1 to capture an image of an area located forward of the tractor 1 and monitor whether a living body Ml, an obstacle, or the like, is present forward of the tractor 1. Examiner notes, changing the flight position necessarily encompasses generating a travel plan and performing the change 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 (See at least Fig. 11A, and [0156]: when the sensor 72 detects an object M3, such as a living body M1 or an obstacle M2 [i.e., 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], in a situation in which the tractor 1 is traveling and the sensor 72 is capturing an image of an area located forward of the tractor 1, the communication device 75 of the unmanned aerial vehicle 70 transmits, as the detection result, information indicating the detection of the object M3, the size (height H10, width L10, depth W10) and the position of the object M3 to the tractor 1. Examiner notes, a sensor necessarily generates sensor data that is obtained by the controller);
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 (See at least Figs. 1, 4, 11A, and [0156]: when the sensor 72 [i.e., based on the sensor data] detects an object M3, such as a living body M1 or an obstacle M2 [i.e., identify the one or more attributes in the one or more measurement areas lateral of, at least, the portion of the agricultural work machine], in a situation in which the tractor 1 is traveling and the sensor 72 is capturing an image of an area located forward of the tractor 1, the communication device 75 of the unmanned aerial vehicle 70 transmits, as the detection result, information indicating the detection of the object M3, the size (height H10, width L10, depth W10) and the position of the object M3 to the tractor 1 [i.e., 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]. Examiner notes, a sensor necessarily generates sensor data); 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 (See at least Fig. 8, and [0131]: the controller 76 performs control of sensing a surrounding area of the tractor 1 (a range several meters away from the tractor 1) by the unmanned aerial vehicle 70 (S7: first sensing). In the first sensing, the sensor 72 is directed toward the tractor 1 to capture an image of the range several meters away from the tractor 1, thus monitoring whether a living body M1 such as an animal or a human is present in the range [i.e., the identified one or more attributes in the one or more measurement areas lateral of, at least, the portion of the agricultural work machine]. When the living body M1 is detected in the first sensing, the communication device 75 transmits to the communication device 51 (S8) a warning signal. When acquiring the warning signal via the communication device 51, the traveling controller 40A of the tractor 1 does not start the automatic traveling and maintains the stop (S9). The traveling controller 40A of the tractor 1 starts the automatic traveling when the warning signal is not acquired for a predetermined time or more, or when a release signal for releasing the warning is received from the unmanned aerial vehicle 70 (S10). Examiner notes, starting or stopping automatic traveling necessarily encompasses generating a control signal. As mentioned above, the automatic traveling starts or stops based on detecting an attribute, such as an obstacle, in the measurement area).
Kinoshita 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 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 (See 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. According to relevant paragraph [0193] of Applicant’s specification: “At block 728, system 235 (e.g., obstruction identification system 336) identifies one or more obstructions, and characteristics thereof, based, at least, on one or more of the data obtained at block 702. For example, system 235 can, at block 728, identify presence, location, and type of each obstruction.” Accordingly, the location of the obstacle was interpreted as one or more characteristics of the obstruction at the worksite. To generate a collision free flight path, the drone must necessarily avoid the location of the obstacle on its path. That is, by avoiding the obstacle, is generating a travel plan for the drone based on the one or more characteristics of the obstruction at the worksite.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify the invention of Kinoshita, by incorporating the teachings of Menzel, with a reasonable expectation of success, as both inventions are directed to the same field of endeavor – unmanned vehicles, such that a collision free flight path to the desired target position is generated for the drone to avoid the obstacles.
The motivation to modify is that, as acknowledged by Menzel, avoiding collision of the unmanned aerial vehicle with an obstacle located in the flight path of the unmanned aerial vehicle (See at least [0002]) which one of ordinary skill would have recognized allows the drone to operate without being damages.

12. Claim(s) 19
is/are rejected under 35 U.S.C. 103 as being unpatentable over Kinoshita et al. (US-20230322423-A1) in view of Menzel et al. (US-20190094861-A1) and further in view of Tamatani (US-20250068172-A1).
In regard to claim 19
, Kinoshita, 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 (See at least Fig. 4, and [0116 & 0150]: the unmanned aerial vehicle 70 includes a memory 74, a communication device 75, and a controller 76. The controller 76 is configured or programmed to change the flight position to a surrounding area of the living body when the sensor 72 detects the living body. Examiner notes, for programming a controller, instructions are necessarily used and the instructions are stored in memory and executed by the processor of the controller):

Kinoshita, 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 the GNSS unit 110 includes an inertial measurement unit (IMU). Signals from the IMU [i.e., a sensor on-board the agricultural work machine] 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 [i.e., identify a performance of a sensor]. 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 (See at least Fig. 1, and [0067 & 0184]). Examiner notes, as mentioned above a GNSS is used to determine the position of the agricultural machine. Generating a path by using the more accurate position from the IMU sensor is 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 the invention of Kinoshita, as already modified by Menzel, by incorporating the teachings of Menzel, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – vehicles, such that the data acquired by the IMU is used to complement the position data based on the satellite signals, to improve performance of positioning.
The motivation to modify is that, as acknowledged by Menzel, improved path planning (See at least [0004]) which one of ordinary skill would have recognized improves the operation cost of the agricultural machine.

13. Claim(s) 20
is/are rejected under 35 U.S.C. 103 as being unpatentable over Kinoshita et al. (US-20230322423-A1) in view of Menzel et al. (US-20190094861-A1) and further in view of Kocer et al. (US-20210357664-A1).
In regard to claim 20
, Kinoshita, as modified by Menzel, teaches the agricultural system of claim 18, (See at least Fig. 4, and [0116 & 0150]: the unmanned aerial vehicle 70 includes a memory 74, a communication device 75, and a controller 76. The controller 76 is configured or programmed to change the flight position to a surrounding area of the living body when the sensor 72 detects the living body. Examiner notes, for programming a controller, instructions are necessarily used and the instructions are stored in memory and executed by the processor of the controller):

Kinoshita, as modified by Menzel, is silent on 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,
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, Kocer teaches the obstacle recognition module 310 includes a prioritizing module 318. The prioritizing module 318 is configured to assign priorities to obstacles based on a catalog set of priorities, priority rules, user input priorities or user input priority rules or the like [i.e., identify one or more of: (ii) a priority of each attribute of the one or more attributes]. Archived obstacles such as humans, livestock or the like have a higher priority relative to other identified obstacles including, for instance, brush, washouts, rocks, saturated or soaked areas of the field or the like. As described herein, the assigned priority of an identified object changes the operation of the agricultural system 100, for instance with the vehicle operation module 306 of the autonomous agricultural system controller 104. The identification of a human proximate to a determined path of the agricultural system 100 is given a high priority while other obstacles such as livestock, brush, fence or rocks or the like proximate to the determined path are given a lower priority (and optionally scaled lower priorities with livestock higher than brush or similar inanimate obstacles). For instance, the prioritizing module 318 assigns a higher priority to particular types of obstacles, for instance, humans or the like. The proximity to the agricultural system 100 or the determined path of the agricultural system 100 triggers the assignment of a higher priority to an identified obstacle in comparison to the same identified obstacle that is not proximate to the determined path or is not proximate to the agricultural system 100. In operation, the obstacle recognition module 310 cooperates with and communicates with other components of the autonomous obstacle monitoring and vehicle control system 300 to identify and track obstacles and facilitate enhanced guidance of the agricultural system 100 through the field while still allowing the agricultural system 100 to accomplish one or more agricultural processes. The remote sensing device 114 is deployed by the autonomous agricultural system controller 104 by way of a mission administration module 304 providing a mission route to the remote sensing device 114 [i.e., generate the travel plan] or, guiding operation of the remote sensing device 114 along a mission route. The remote sensing device 114, while conducting the mission, observes the area proximate to a determined path, proximate to the agricultural system 100 or the like, for instance, along a corresponding mission route for the remote sensing device 114. The 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, 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 (See at least Figs. 1-3B, 5, and [0075-0078 & 0102]); Examiner notes, as mentioned above, the proximity to the agricultural system or the determined path of the agricultural system triggers the assignment of a higher priority to an identified obstacle relative to other identified obstacles including, for instance, brush, washouts, rocks, saturated or soaked areas of the field or the like and the autonomous agricultural system controller provides a mission route to the remote sensing device, which is also generating a travel plan for the UAV, to observe the obstacles. The type of the obstacle, such as livestock, brush, fence or rocks, is the identified one or more characteristics of the obstruction. That is, generating 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 and the monitoring sequence defining an order in which the drone is to travel to each monitoring location in the one or more monitoring locations. Furthermore, as illustrated by Figure 3 (Fig. 5 of Kocer, reproduced and annotated for Applicant’s convenience), the remote sensing device 114 travels along the scouting mission 500 and observes the obstacles as it moves along the path. The scouting mission 500 is a monitoring sequence defining an order in which the drone is to travel between each monitoring location of the plurality of monitoring location.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify the invention of Kinoshita, as already modified by Kocer, by further incorporating the teachings of Kocer, with a reasonable expectation of success, as all inventions are directed to the same field of endeavor – agricultural machines, such that the prioritizing module of Kocer is used to assign higher priorities to obstacles along the planned route of the agricultural machine and a travel plan for the UAV is created based on the obstacle type and the assigned priorities and the drone is controlled to collect sensor data based on the obstacle type and the assigned priority to the obstacle.
The motivation to do so is the same as acknowledged by Kocer in regard to claim 1.

Conclusion
14. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Stanhope et al. (US-20210300547-A1) teaches a system for anchoring unmanned aerial vehicles to surfaces.
Machida (US-20210012399-A1) teaches a path determination system that includes a priority determination system.
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.

15. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Preston J Miller whose telephone number is [phone]. The examiner can normally be reached Monday through Friday 7:30 AM - 4:30 PM EST.
16. 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.
17. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ramya P Burgess can be reached at [phone]. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
18. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.

/P.J.M./Examiner, Art Unit 3661
/MATTHIAS S WEISFELD/Examiner, Art Unit 3661

Prosecution Timeline

• Jul 09, 2024: Application Filed
• Oct 29, 2025: Non-Final Rejection mailed — §103
• Jan 29, 2026: Response Filed
• Apr 09, 2026: Final Rejection mailed — §103
• May 07, 2026: Interview Requested
• May 20, 2026: Examiner Interview Summary
• May 21, 2026: Response after Non-Final Action
• Jun 04, 2026: Request for Continued Examination
• Jun 10, 2026: Response after Non-Final Action
• Jul 23, 2026: Non-Final Rejection mailed — §103
• Sep 16, 2026: Interview Requested
• Sep 28, 2026: Applicant Interview (Telephonic)
• Sep 28, 2026: Examiner Interview Summary