DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The Amendment filed September 8th, 2025 has been entered. Claims 1-9, 16, 18-19, 21, and 23-24 remain pending in the application.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-9 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Sullivan et al. (US 20160175869 A1) in view of Redden et al. (US 20190357520 A1) and Kremmer et al. (US 20180281798 A1).
Regarding claim 1, Sullivan discloses a system (20, Fig. 1) for an agricultural vehicle (system is mounted on a traveling vehicle, shown in Fig. 1, Paragraph 0014), the system (20, Fig. 1) comprising:
a boom assembly (32, 50, Fig. 1);
a nozzle assembly (60, Fig. 2) positioned along the boom assembly (32, 50, shown in Figs. 1-2);
a position sensor (36, Figs. 1, 3) associated with the boom assembly (32, 50, GPS 36 detects various parameters for boom assembly 32, shown in Fig. 1, Paragraphs 0021-0022);
a field sensor (76a, 76b, Fig. 3) associated with the nozzle assembly (60, sensors 76a and 76b are located within or near nozzles 60 to detect flow characteristics, Fig, 2, Paragraph 0034); and
a computing system (34, Figs. 1, 3) operably coupled with the nozzle assembly (60, Fig. 2), the position sensor (36, Figs. 1, 3), and the field sensor (76a, 76b, controller 34 is in communication with various other systems and devices on the sprayer 20, shown in Fig. 3, Paragraph 0019), the computing system (34, Figs. 1, 3) configured to:
detect a target within a field based on data from the field sensor (sensors of sprayer 20 communicate with controller 34 regarding various parameters, including a specific location within a field, Paragraph 0020);
activate the nozzle assembly to apply an agricultural product to the target when the target is within the application region (GPS detected location can be mapped to or correlated with an amount of fluid released, an amount of flow rate, and given flow pressure to activate the nozzles when sprayer is at specific location, Paragraph 0020); and
deactivate the nozzle assembly when the target is offset from the application region (valves 74, which permit nozzles 60 to spray, are in communication with controller 34 so signals from controller 34 control the operation of the valves 74, and these signals may include a detected location with a correlated amount of fluid released, which can be deactivated or 0 for a particular location, Paragraphs 0020, 0027, 0036, 0038).
However, Sullivan does not disclose the computing system is configured to determine a boom deflection model based on data from the position sensor, determine an acceleration of the nozzle assembly relative to a frame of the boom assembly, determine a direction of movement of the nozzle assembly relative to the frame of the boom assembly, and activate the nozzle assembly to apply an agricultural product to the target when the target is within the application region based on the acceleration of the nozzle assembly and the direction of movement of the nozzle assembly relative to the frame as claimed. Redden teaches a system (100, 200, Figs. 1-2) for an agricultural vehicle (shown in Figs. 1-2, Paragraph 0035), the system (100, 200, Figs. 1-2) comprising:
a computing system (800, Fig. 8) operably coupled with the nozzle assembly, the position sensor, and the field sensor (Paragraph 0134), the computing system (800, Fig. 8) configured to:
determine a boom model based on data from the position sensor (the machine generates a machine learned model that automatically determines actions to affect components of the machine based on measurements collected from sensors, such as tilt sensors, which help the spray boom assembly to determine the angle of each segment relative to the ground, Paragraphs 0018, 0046, 0057, 0073, 0075); and
determine, based on the boom model, a boundary of the application region as the target approaches the boom assembly (using reinforcement training, the agent of the boom sprayer 200 interacts with an environment to select actions of the system based on specifications of an environment and an input state vector is determined for a model based on measurements received from sensors 330, Paragraphs 0080-0086, 0125-0130);
determine an acceleration of the nozzle assembly relative to a frame of the boom assembly (IMU sensor 372 can report acceleration data, such as lateral acceleration, longitudinal acceleration, and a vertical acceleration of the boom sprayer 200 and boom sprayer assembly 212 with respect to boom sprayer 200, Paragraph 0061);
determine a direction of movement of the nozzle assembly relative to the frame of the boom assembly (IMU sensor 372 can provide motion sensing, angular velocity, and orientation data, such as pitch angle, roll angle, yaw rate, pitch rate, and roll rate of the boom sprayer 200 and boom sprayer assembly 212 with respect to boom sprayer 200, Paragraph 0061);
activate the nozzle assembly to apply an agricultural product to the target when the target is within the application region based on the acceleration of the nozzle assembly and the direction of movement of the nozzle assembly relative to the frame (sensors can determine a position and movement of the sprayer, a position and a movement of one or more spray sections, and an amount of the spray being sprayed based on information collected through the sensors, and boom sprayer 200 may use a memory of an action at a particular location to influence a current action taken at that location, Paragraphs 0043, 0063, 0066).
Sullivan and Redden are considered to be analogous art to the claimed invention because they are in the same field of systems for agricultural vehicles. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of the computing system taught in Redden’s system to Sullivan’s system, to have the computing system is configured to determine a boom model based on data from the position sensor, determine based on the boom model a boundary of the application region as the target approaches the boom assembly, determine an acceleration of the nozzle assembly relative to a frame of the boom assembly, determine a direction of movement of the nozzle assembly relative to the frame of the boom assembly, and activate the nozzle assembly to apply an agricultural product to the target when the target is within the application region based on the acceleration of the nozzle assembly and the direction of movement of the nozzle assembly relative to the frame. Doing so helps to improve the performance of the machine by using data recognition and reinforcement learning (Redden, Paragraph 0018).
However, Sullivan and Redden do not explicitly teach a boom deflection model and the boom is deflected in a fore-aft direction as claimed. Kremmer teaches a system (12, Fig. 1) for an agricultural vehicle (10, Fig. 1) comprising a computing system (32, 34, 36, 62, Figs. 1-2) operably coupled with the nozzle assembly (42, Fig. 1), the position sensor (40, Fig. 1), and the field sensor (58, Fig. 1, Paragraph 0028), the computing system (32, 34, 36, 62, Figs. 1-2) configured to:
determine a boom deflection model based on data from the position sensor (sensors 70, 72, can be used to determine current deflection of the sprayer boom in any manner and data from the sensors 70, 72 can be used to determine how the controller controls the tractor 10 and spraying machine 12, shown in Figs. 2, 4, Paragraphs 0033-0034);
activate the nozzle assembly to apply an agricultural product to the target when the target is within the application region with the boom deflected in a fore-aft direction (output device 42, which are nozzles of the spraying machine 12, is controlled to have a discharge rate that a sprayed agent is discharged and the discharge rate can be position specific, and sensors 70, 72, can be used to determine current deflection of the sprayer boom in any manner, such as a deflection of the sprayer boom in the forward direction and aft of the sprayer boom, which would be the opposite direction of the forward direction, Paragraphs 0028, 0033-0034); and
deactivate the nozzle assembly when the target is offset from the application region and the boom is deflected in a fore-aft direction (sensors 70, 72, can be used to determine current deflection of the sprayer boom in any manner, such as a deflection of the sprayer boom in the forward direction and aft of the sprayer boom, which would be the opposite direction of the forward direction, which the controller 36 can then derive control parameters based on the response of the sprayer boom to adjust the speed change, and output device 42, which are nozzles of the spraying machine 12, is controlled to have a discharge rate that a sprayed agent is discharged and the discharge rate can be position specific, such as a rate of 0 for a given deflection of the sprayer boom, Paragraphs 0028, 0033-0034).
Sullivan, Redden, and Kremmer are considered to be analogous art to the claimed invention because they are in the same field of systems for agricultural vehicles. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of the computing system taught in Kremmer’s system to Sullivan’s system, as modified by Redden, to have the computing system is configured to determine a boom deflection model based on data from the position sensor, determine based on the boom deflection model a boundary of the application region as the target approaches the boom assembly, activate the nozzle assembly to apply an agricultural product to the target when the target is within the application region and the boom is deflected in a fore-aft direction, deactivate the nozzle assembly when the target is offset from the application region and the boom is deflected in a fore-aft direction, and activate the nozzle assembly to apply an agricultural product to the target when the target is within the application region based on the acceleration of the nozzle assembly and the direction of movement of the nozzle assembly relative to the frame with the boom deflected in a fore-aft direction. Doing so helps to reduce undesired consequences caused by oscillating movements of the boom (Kremmer, Paragraph 0010).
Regarding claim 2, Sullivan, as modified by Redden and Kremmer, teaches the system of claim 1 above. Redden further teaches the boom model predicts a boom curvature and a speed of movement of the nozzle assembly relative to a chassis of the vehicle (model can take measurements from any aspect of the machine 100, Paragraphs 0018, 0045-0046), and as modified by Kremmer above, would result in the boom deflection model predicts a boom curvature and a speed of movement of the nozzle assembly relative to a chassis of the vehicle.
With respect to claim 3, Sullivan, as modified by Redden and Kremmer, teaches the system of claim 1 above. Sullivan further discloses the position sensor (36, Figs. 1, 3) comprises an accelerometer (Paragraph 0021).
With respect to claim 4, Sullivan, as modified by Redden and Kremmer, teaches the system of claim 1 above. Sullivan further discloses the position sensor (36, Figs. 1, 3) is configured as a pressure sensor integrated into at least one actuator of the boom assembly (sensor can be any sensing device, Paragraphs, 0021 0025).
Regarding claim 5, Sullivan, as modified by Redden and Kremmer, teaches the system of claim 1 above. Sullivan further discloses the nozzle assembly (60, Fig. 2) includes a valve (72a, 72b, Fig. 3) operably coupled with a nozzle (60b-60h, shown in Fig. 3) and configured to control a flow of agricultural product through the nozzle (Paragraph 0032).
In regards to claim 6, Sullivan, as modified by Redden and Kremmer, teaches the system of claim 2 above. Sullivan further discloses the agricultural product is exhausted from the nozzle (60b-60h, shown in Figs. 3, 5) towards the target that is a first distance (164, Fig. 5) from a default axis when the boom assembly is generally aligned with the default axis (shown in Fig. 5, Paragraph 0070), and the agricultural product is exhausted from the nozzle (60b-60h, shown in Figs. 3, 5) towards the target that is a second distance (162, Fig. 5) from the default axis when the boom assembly is deflected (shown in Fig. 5, Paragraph 0070).
In regards to claim 7, Sullivan, as modified by Redden and Kremmer, teaches the system of claim 5 above. Sullivan further discloses the computing system (34, Figs. 1, 3) is further configured to:
activate the valve (72a, 72b, Fig. 3) when the target is projected to pass through an application region a second time due to oscillation of the boom assembly (Paragraphs 0027, 0032, 0036, 0039, 0053, 0060), which as modified in view of Redden as set forth above regarding claim 1 would result in based on the boom deflection model.
With respect to claim 8, Sullivan, as modified by Redden and Kremmer, teaches the system of claim 1 above. Sullivan further discloses an application region defines an area of an underlying field from that is contacted by agricultural product when the nozzle is actuated from an off position to a spray position (shown in Fig. 5, Paragraphs 0020, 0050).
Regarding claim 9, Sullivan, as modified by Redden and Kremmer, teaches the system of claim 1 above. Redden further teaches the boom model is configured to determine a geometric boundary of an application region of the nozzle assembly (Paragraphs 0020, 0025, 0085-0086), and the nozzle assembly is activated when the target is within the application region of the nozzle assembly based on the boom model (Paragraphs 0020, 0025, 0125-0129), and as modified by Kremmer above, would result in the boom deflection model is configured to determine a geometric boundary of an application region of the nozzle, and the nozzle assembly is activated when the target is within the application region of the nozzle assembly based on the boom deflection model.
With respect to claim 21, Sullivan discloses a system (20, Fig. 1) for an agricultural vehicle (shown in Fig. 1, Paragraph 0014), the system (20, Fig. 1) comprising:
a boom assembly (32, 50, Fig. 1);
a nozzle assembly (60, Fig. 2) positioned along the boom assembly (32, 50, shown in Figs. 1-2);
a position sensor (36, Figs. 1, 3) associated with the boom assembly (32, 50, shown in Fig. 1, Paragraphs 0021-0022); and
a computing system (34, Figs. 1, 3) operably coupled with the nozzle assembly (60, Fig. 2) and the position sensor (36, Figs. 1, 3, Paragraph 0019), the computing system (34, Figs. 1, 3) configured to:
receive data from the position sensor (Paragraph 0021); and
detect a target within a field (sensors of sprayer 20 communicate with controller 34 regarding various parameters, including detecting locations for spraying corresponding to a particular field location, Paragraph 0020);
However, Sullivan does not disclose the computing system is configured to determine a boom deflection model based on the data from the position sensor and determine a geometric boundary of an application region as claimed. Redden teaches a system (100, 200, Figs. 1-2) for an agricultural vehicle (shown in Figs. 1-2, Paragraph 0035), the system (200, Fig. 2) comprising:
a computing system (800, Fig. 8) operably coupled with the nozzle assembly and the position sensor (Paragraph 0134), the computing system (800, Fig. 8) configured to:
determine a boom model based on data from the position sensor (the machine generates a machine learned model that automatically determines actions to affect components of the machine based on measurements collected from sensors, such as tilt sensors, which help the spray boom assembly to determine the angle of each segment relative to the ground, Paragraphs 0018, 0046, 0057, 0073, 0075); and
determine a geometric boundary of an application region based on the boom model (there is an active area within a geographic area to manipulate plants with various tasks, and using reinforcement training, the agent of the boom sprayer 200 interacts with an environment to select actions of the system based on specifications of an environment and an input state vector is determined for a model based on measurements received from sensors 330, Paragraphs 0020, 0025, 0080-0086, 0125-0130); and
activate the nozzle assembly to apply an agricultural product to the target (model enables machine commands to actuate components of the boom sprayer to a certain area based on tilt sensor data and the frame angle, Paragraphs 0125-0130).
Sullivan and Redden are considered to be analogous art to the claimed invention because they are in the same field of systems for agricultural vehicles. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of the computing system taught in Redden’s system to Sullivan’s system, to determine a boom model based on the data from the position sensor, determine a geometric boundary of an application region based on the boom model, and activate the nozzle assembly to apply an agricultural product to the target. Doing so helps to improve the performance of the machine by using data recognition and reinforcement learning (Redden, Paragraph 0018).
However, Sullivan and Redden do not explicitly teach a boom deflection model, determine a geometric boundary of an application region and a position of the geometric boundary relative to a default axis of the boom assembly based on the boom deflection model, wherein the geometric boundary is non-symmetrical to the default axis when the boom assembly is deflected from the default axis, and activate the nozzle assembly to apply an agricultural product to the target based on the geometric boundary of the application region with the geometric boundary being non-symmetrical to the default axis as claimed. Kremmer teaches a system (12, Fig. 1) for an agricultural vehicle (10, Fig. 1) comprising a computing system (32, 34, 36, 62, Figs. 1-2) operably coupled with the nozzle assembly (42, Fig. 1) and the position sensor (40, Fig. 1), the computing system (32, 34, 36, 62, Figs. 1-2) configured to:
determine a boom deflection model indicative of a magnitude of fore-aft deflection of the boom assembly based on data from the position sensor (sensors 70, 72, can be used to determine current deflection of the sprayer boom in any manner, such as a deflection of the sprayer boom in the forward direction and aft of the sprayer boom, which would be the opposite direction of the forward direction, and data from the sensors 70, 72 can be used to determine how the controller controls the tractor 10 and spraying machine 12, shown in Figs. 2, 4, Paragraphs 0033-0034);
determine a geometric boundary of an application region (controller determines a position within a map of the field, which has a given geometric boundary, and controls the output device 42, which are nozzles of the nozzles of the spraying machine 12, to spray at a discharge rate corresponding to the position, Paragraph 0028), and a position of the geometric boundary relative to a default axis of the boom assembly based on the boom deflection model (sensors can determine a position within a map of the field, which has a given geometric boundary, relative to the current position of the spraying machine in at least two horizontal dimensions, such as a longitudinal axis of the spraying machine and a lateral axis of the spraying machine, and data from the sensors 70, 72 can be used to determine how the controller controls the tractor 10 and spraying machine 12, Paragraphs 0025, 0028, 0033-0034), the geometric boundary is non-symmetrical to the default axis when the boom assembly is deflected from the default axis (sensors 70, 72, can be used to determine current deflection of the sprayer boom in any manner, such as a deflection of the sprayer boom in the forward direction and aft of the sprayer boom, which would be the opposite direction of the forward direction, indicating a deflection in the default axis, the lateral axis, of the spraying machine, and causing the determined position with a given geometric boundary to deflect with respect to the lateral axis of the spraying machine, making its axis non-symmetrical to the lateral axis, Paragraphs 0033-0034); and
activate the nozzle assembly to apply an agricultural product to the target based on the geometric boundary of the application region with the geometric boundary being non-symmetrical to the default axis (output device 42, which are nozzles of the spraying machine 12, is controlled to have a discharge rate that a sprayed agent is discharged and the discharge rate can be position specific, and sensors 70, 72, can be used to determine current deflection of the sprayer boom in any manner, such as a deflection of the sprayer boom in the forward direction and aft of the sprayer boom, which would be the opposite direction of the forward direction, which the controller 36 can then derive control parameters based on the response of the sprayer boom to adjust the speed change, Paragraphs 0028, 0033-0034).
Sullivan, Redden, and Kremmer are considered to be analogous art to the claimed invention because they are in the same field of systems for agricultural vehicles. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of the computing system taught in Kremmer’s system to Sullivan’s system, as modified by Redden, to have the computing system is configured to determine a boom deflection model indicative of a magnitude of fore-aft deflection of the boom assembly based on data from the position sensor, determine a geometric boundary of an application region and a position of the geometric boundary relative to a default axis of the boom assembly based on the boom deflection model, and activate the nozzle assembly to apply an agricultural product to the target based on the geometric boundary of the application region with the geometric boundary being non-symmetrical to the default axis. Doing so helps to reduce undesired consequences caused by oscillating movements of the boom (Kremmer, Paragraph 0010).
Claims 16-17, 19, 22, and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Sullivan et al. (US 20160175869 A1) in view of Redden et al. (US 20190357520 A1) and Pickett et al. (US 20190124826 A1).
With respect to claim 16, Sullivan discloses a system (20, Fig. 1) for an agricultural vehicle (shown in Fig. 1, Paragraph 0014), the system (20, Fig. 1) comprising:
a boom assembly (32, 50, Fig. 1);
a nozzle assembly (60, Fig. 2) positioned along the boom assembly (32, 50, shown in Figs. 1-2);
a position sensor (36, Figs. 1, 3) associated with the boom assembly (32, 50, shown in Fig. 1, Paragraphs 0021-0022);
a field sensor associated with the nozzle assembly (not explicitly shown, but the sprayer 200 can have any number of sensors to determine an amount of spray being sprayed, Paragraph 0043); and
a computing system (34, Figs. 1, 3) operably coupled with the nozzle assembly (60, Fig. 2) and the position sensor (36, shown in Figs. 1, 3, Paragraph 0019), the computing system (34, Figs. 1, 3) configured to:
receive data from the position sensor (Paragraph 0021); and
detect a target within a field based on data from the field sensor (Paragraph 0020); and
activate the nozzle assembly to apply an agricultural product to the target (GPS detected location can be mapped to or correlated with an amount of fluid released, an amount of flow rate, and given flow pressure to activate the nozzles when sprayer is at specific location, Paragraph 0020).
However, Sullivan does not disclose the computing system is configured to determine a boom deflection model based on the data from the position sensor and determine a boundary of an application region based on the boom deflection model as claimed. Redden teaches a system (100, 200, Figs. 1-2) for an agricultural vehicle (shown in Figs. 1-2, Paragraph 0035), the system (200, Fig. 2) comprising:
a computing system (800, Fig. 8) operably coupled with the nozzle assembly and the position sensor (Paragraph 0134), the computing system (800, Fig. 8) configured to:
determine a boom model based on data from the position sensor (the machine generates a machine learned model that automatically determines actions to affect components of the machine based on measurements collected from sensors, such as tilt sensors, which help the spray boom assembly to determine the angle of each segment relative to the ground, Paragraphs 0018, 0046, 0057, 0073, 0075); and
determine a boundary of an application region based on the boom model (there is an active area within a geographic area to manipulate plants with various tasks, and using reinforcement training, the agent of the boom sprayer 200 interacts with an environment to select actions of the system based on specifications of an environment and an input state vector is determined for a model based on measurements received from sensors 330, Paragraphs 0020, 0025, 0080-0086, 0125-0130),
the boundary of the application region defines a longitudinal axis (farming machine has a mounting mechanism 140 that statically retains and mechanically supports positions of the detection mechanisms 110, components 120, and verification systems 150 relative to its longitudinal axis to improve the performance of the farming machine, Paragraph 0028).
Sullivan and Redden are considered to be analogous art to the claimed invention because they are in the same field of systems for agricultural vehicles. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of the computing system taught in Redden’s system to Sullivan’s system, to have the computing system is configured to determine a boom model based on the data from the position sensor, determine a boundary of an application region based on the boom model, and the boundary of the application region defines a longitudinal axis. Doing so helps to improve the performance of the machine by using data recognition and reinforcement learning (Redden, Paragraph 0018).
However, Sullivan and Redden do not teach a boom deflection model, the boom deflection model determines an offset of the longitudinal axis relative to a default axis, and activate the nozzle assembly to apply an agricultural product to the target based on the offset of the longitudinal axis relative to a default axis as claimed. Pickett teaches a system (11, Fig. 1) for an agricultural vehicle (61, Fig. 2, Paragraph 0024) comprising a boundary of the application region (466, Fig. 7A) defines a longitudinal axis (lines shown in Fig. 7A-7C, Paragraphs 0087-0089), and a boom deflection model (22, Fig. 1) determines an offset of the longitudinal axis relative to a default axis (module determines an offset between a nozzle assembly and one or more plant rows using a reference center point or row position, Paragraphs 0036, 0046, 0107-0108, 0130); and
activate the nozzle assembly to apply an agricultural product to the target based on the offset of the longitudinal axis relative to a default axis (module determines an offset between a nozzle assembly and one or more plant rows using a reference center point or row position, and later offset of spray pattern is adjusted based on lateral offset of the nozzle assembly, Paragraphs 0036, 0046, 0107-0108, 0130).
Sullivan, Redden, and Pickett are considered to be analogous art to the claimed invention because they are in the same field of systems for agricultural vehicles. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching the application region and the boom deflection model taught in Pickett’s system to Sullivan’s system, as modified by Redden above, to determine a boom deflection model based on the data from the position sensor, determine a boundary of an application region based on the boom deflection model, the boundary of the application region defines a longitudinal axis, the boom deflection model determines an offset of the longitudinal axis relative to a default axis, and activate the nozzle assembly to apply an agricultural product to the target based on the offset of the longitudinal axis relative to a default axis. Doing so provides more precise spraying within a region (Pickett, Paragraph 0046).
In regards to claim 19, Sullivan, as modified by Redden and Pickett, teaches the system of claim 17 above. Redden further teaches the boundary of the application region defines a first geometric shape having a first area at a defined distance from the nozzle when the nozzle is traveling at a first speed (Paragraphs 0085-0086) and a second geometric shape having a second area at the defined distance from the nozzle when the nozzle is traveling at a second speed (boundary can be located at different places for different purposes operating at once, Paragraphs 0085-0086), and wherein the first area is different than the second area (size of the boundary can be adjusted and boundary can be located at different places for different purposes operating at once, Paragraphs 0085-0086).
Regarding claim 22, Sullivan, as modified by Redden and Pickett, teaches the system of claim 16 above. Sullivan further discloses a field sensor associated with the nozzle assembly (not explicitly shown, but the sprayer 200 can have any number of sensors to determine an amount of spray being sprayed, Paragraph 0043), the computing system (34, Figs. 1, 3) is further operably coupled with the field sensor (76a, 76b, shown in Fig. 3, Paragraph 0019), the computing system (34, Figs. 1, 3) is further configured to:
detect a target within a field based on data from the field sensor (Paragraph 0020).
Redden further teaches the computing system (800, Fig. 8) is further configured to activate the nozzle assembly to apply an agricultural product to the target based on the boom deflection model (Paragraphs 0125-0129).
In regards to claim 24, Sullivan, as modified by Redden and Pickett, teaches the system of claim 17 above. Redden further teaches the boundary of the application region defines a first geometric shape having a first area at a defined distance from the nozzle when the nozzle is traveling at a first speed (Paragraphs 0085-0086) and a second geometric shape having a second area at the defined distance from the nozzle when the nozzle is traveling at a second speed (boundary can be located at different places for different purposes operating at once, Paragraphs 0085-0086), and the first area is different than the second area (size of the boundary can be adjusted and boundary can be located at different places for different purposes operating at once, Paragraphs 0085-0086).
Claims 18 and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Sullivan et al. (US 20160175869 A1) in view of Redden et al. (US 20190357520 A1) and Pickett et al. (US 20190124826 A1) as applied to claim 17 above, and further in view of Crinklaw et al. (US 20190090472 A1).
Regarding claim 18, Sullivan, as modified by Redden and Pickett, teaches the system of claim 17 above. Redden further teaches the boom deflection model determines a speed of movement of the nozzle assembly relative to the vehicle (current speed of a component, such as the boom sprayer, as the machine takes actions can be measured, Paragraphs 0045, 0059, 0062).
However, Sullivan, Redden, and Pickett do not teach the boom deflection model determines a magnitude of fore-aft deflection of the boom assembly relative to the vehicle as claimed. Crinklaw teaches a system (100, Fig. 1) for an agricultural vehicle (110, Fig. 1) comprising determining a magnitude of fore-aft deflection relative to a vehicle (Paragraph 0040).
Sullivan, Redden, Pickett, and Crinklaw are considered to be analogous art to the claimed invention because they are in the same field of systems for agricultural vehicles. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of determining a magnitude of fore-aft deflection relative to the vehicle taught in Crinklaw’s system to Sullivan’s system, as modified by Redden and Pickett above, to have the boom deflection model determines a magnitude of fore-aft deflection of the boom assembly relative to the vehicle. Doing so provides more precise positioning of the components of the system (Crinklaw, Paragraph 0040).
Regarding claim 23, Sullivan, as modified by Redden and Pickett, teaches the system of claim 17 above. Redden further teaches the boom deflection model determines a speed of movement of the nozzle assembly relative to the vehicle (current speed of a component, such as the boom sprayer, as the machine takes actions can be measured, Paragraphs 0045, 0059, 0062).
However, Sullivan, Redden, and Pickett do not teach the boom deflection model determines a magnitude of fore-aft deflection of the boom assembly relative to the vehicle. Crinklaw teaches a system (100, Fig. 1) for an agricultural vehicle (110, Fig. 1) comprising determining a magnitude of fore-aft deflection relative to a vehicle (Paragraph 0040).
Sullivan, Redden, Pickett, and Crinklaw are considered to be analogous art to the claimed invention because they are in the same field of systems for agricultural vehicles. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of determining a magnitude of fore-aft deflection relative to the vehicle taught in Crinklaw’s system to Sullivan’s system, as modified by Redden and Pickett above, to have the boom deflection model determines a magnitude of fore-aft deflection of the boom assembly relative to the vehicle. Doing so provides more precise positioning of the components of the system (Crinklaw, Paragraph 0040).
Response to Arguments
Applicant's arguments filed September 8th, 2025 have been fully considered but they are not persuasive.
In response to applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, specifically Sullivan, Redden, and Kremmer, see Remarks, pg. 6-16, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). Redden teaches a farming machine that applies a machine learned model that automatically determines in real-time actions to affect components of the machine (Paragraph 0018). Redden states that a component may include fertilizing the plant or watering the plant (Paragraph 0025). Redden provides a motivation to combine or modify the structure taught in Sullivan to one of ordinary skill in the art because the structure applies a model that uses real-time data, data recognition, and reinforcement training to generate actions of the machine to improve its performance, such as fertilizing or watering a plant in a specific location (Paragraphs 0018, 0025). This allows the farming machine to operate more efficiently and precisely with less input from the operator (Paragraph 0018).
Kremmer teaches an agricultural spraying machine including an electronic controller that is configured to control components of the machine based on a detected or expected oscillation of the sprayer boom. Kremmer states that the control unit of the spraying machine can control a discharge rate that is position-specific, based on signals of the position-determination device, a map of the field, and local sensors which can be used to detect a deflection of the sprayer boom (Paragraphs 0028, 0033-0034). Kremmer provides a motivation to combine or modify the structure taught in Sullivan, as modified by Redden, to one of ordinary skill in the art because the structure enables a controller to control various components of the machine based on detected or expected deflection of the sprayer boom using a position-determination device, a map of the field, local sensors, and calculations, which would mitigate the effects of oscillation of the sprayer boom to improve machine performance (Paragraph 0010).
In response to applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, specifically Sullivan, Redden, and Pickett, see Remarks, pg. 16-19, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). Pickett teaches a method for treating plants in a root zone which includes estimating a distance between a plant row and a nozzle assembly and an offset between a nozzle assembly and one or more plant rows in a target zone (Paragraphs 0036, 0046). Pickett provides a motivation to combine or modify the structure taught in Sullivan, as modified by Redden, to one of ordinary skill in the art because the distance and offset estimations are correlated to a particular crop and target zone, which provides more precise spraying within a region (Paragraph 0046).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Anna T Ho whose telephone number is (571)272-2587. The examiner can normally be reached M-F 8:00 AM-5:00 PM, First Friday of Pay Period off.
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/ANNA THI HO/Examiner, Art Unit 3752
/CODY J LIEUWEN/Primary Examiner, Art Unit 3752