CTFR 18/977,285 CTFR 96238 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia 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 Applicant’s arguments, see the subsection titled “Claim 17”on page 7 of the reply filed 05/28/2026, with respect to the rejection of claim 17 under 35 U.S.C. 103 have been fully considered and are persuasive. In light of the amendments, the rejection of claim 17 under 35 U.S.C. 103 has been withdrawn. Examiner additionally notes that the rejection of claim 11 under 35 U.S.C. 102(a) has been withdrawn in light of the amendments. See the section on Allowable Subject Matter below. Applicant's arguments, see the subsections titled “Claim 1”, “Claim 12”, and “Dependent claims” starting on page 7 of the reply filed 05/28/2026, have been fully considered but they are not persuasive. Regarding claim 1, Applicant argues that “the cited references have not been shown to teach or suggest ‘wherein the weight prioritizes use of the data received from the first sensor, relative to the data received from the second sensor, in determining a magnitude of shift’” for example. However, the Examiner disagrees. It is the Examiner’s opinion that Weidenbach teaches assigning a weight to the data received from the first sensor, wherein the weight prioritizes use of the data received from the first sensor, relative to the data received from the second sensor, in determining a magnitude of shift; and identifying, based on the weight, a correction operation (In paragraph [0057], Weidenbach teaches multi-sensor fusion, e.g., using weighted sensor solutions from two or more sensors based on confidence; see also paragraph [0050] where Weidenbach teaches that a machine controller can use determined or obtained confidence in each sensor to select a measurement generated by the less obstruction (higher confidence) sensor for calculating cross track error or cross heading error, in various embodiments of the present subject matter in cases with the same types of sensors and different types of sensors). Weidenbach is considered to be analogous to the claimed invention in that they both pertain to weighing sensor data differently between multiple sensors for use with an agricultural vehicle. It would be obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Weidenbach with the method as disclosed by Vorobiev, where doing so advantageously improves the accuracy of detections made using the sensor data, as for example sensor data with a higher expected confidence will produce more reliable results. Therefore, claim 1 is rejected under 35 U.S.C. 103 as being unpatentable over Vorobiev (US 2024/0389494 A1), in view of Weidenbach (US 2022/0187832 A1). See the rejections below. Regarding claim 12, Applicant argues that Vorobiev does not disclose “a comparison, let alone teach ‘a comparison of how a shift in the plurality of crop rows affects data gathered by the two sensors’” for example. However, the Examiner disagrees. It is the Examiner’s opinion that Vorobiev discloses wherein the row alignment control system identifies the correction operation based at least in part on a comparison of how a shift in the plurality of crop rows affects data gathered by the two sensors (In paragraph [0044], Vorobiev discloses that in one embodiment, a Hough transform detection algorithm is used to detect a centerline of rows of plants, for example, a Tractor mode in which a camera is located between rows and it is necessary to detect both rows from the left and right sides of the sensor; in paragraph [0047], Vorobiev discloses horizontal projection 1202 for detecting the location of rows in order to control operation of a tractor with respect to the location of the rows; in paragraph [0052], Vorobiev discloses a graph 1602 for use with a tractor, where two rows are selected, and based on the two rows, a lateral bias for the tractor can be determined relative to the centerline between the two rows, and the information concerning the centerline of the alley, along with vehicle orientation information, can be used to determine how a vehicle should be steered to traverse a desired path (i.e., along a centerline of an alley for a tractor); in paragraphs [0067-0068], Vorobiev that at step 1704, a location of a row is determined based on the point cloud, and at step 1706, a steering angle is generated based on the location of the row with respect to the location of the vehicle). It is the Examiner’s opinion that use of a Hough transform detection algorithm and/or determination of lateral bias are both examples of “comparison” utilizing the sensor data under its broadest reasonable interpretation. For example, a Hough transform detection algorithm must reflect at least “a comparison of how a shift in the plurality of crop rows affects data gathered by the two sensors” under its broadest reasonable interpretation in that the sensor data utilized from multiple sensors must reflect the changing relative positioning of the crop rows as reflected in the corresponding sensor data. See also where Vorobiev further discloses in paragraph [0052] that: “Line 1604 is generated using median averaging (as shown in FIG. 14). Line 1606 is generated using sliding window averaging. … As such, lines 1604 and 1606 are used to determine lines 1608A and 1608B which are used to determine line 1610 (i.e., the centerline of an alley)”; the Examiner understands median averaging and sliding window averaging to also be examples of “a comparison of how a shift in the plurality of crop rows affects data gathered by the two sensors” in that the sensor data is averaged (e.g. comparing) in order to determine an observed centerline (e.g. how a shift in the plurality of crop rows affects data gathered by the two sensors). Applicant does not further ague why the detection of the centerline based on a Hough transform detection algorithm and/or determination of lateral bias does not comprise a “comparison” under its broadest reasonable interpretation. Therefore, the rejection of claim 12 is maintained. See the rejections below. Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 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. 07-07-aia AIA 07-07 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – 07-08-aia AIA (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. 07-12-aia AIA (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. 07-15 AIA Claim s 12 and 16 are rejected under 35 U.S.C. 102( a)(1) and (a)(2 ) as being anticipated by Vorobiev (US 2024/0389494 A1) . Regarding claim 12, Vorobiev discloses a mobile work machine (In paragraphs [0027-0028], Vorobiev discloses agricultural machines such as tractor 202 configured to travel along alley 102 without damaging plants of rows 104A, 104B located on either side of alley 102), comprising: two sensors that capture data indicative of an area of crops (In paragraph [0030], Vorobiev discloses tractor 402 having camera 404A mounted on an upper body member (e.g., roof 410) and camera 404B mounted near the front of tractor 402 (e.g., hood 412), where in one embodiment, cameras 404A, 404B are stereo cameras with each camera comprising two lenses, and cameras 404A, 404B can be any type of three-dimensional (3D) sensor such as a Time of Flight (ToF) camera or 3D LIDAR sensor; see also paragraph [0041] where Vorobiev discloses that the point cloud is defined based on a local coordinate system with respect to image sensors 1006A and 1006B having a left lens 1004A and right lens 1004B; in paragraph [0066], Vorobiev discloses that at step 1702, a point cloud of data is received by the machine controller, where in one embodiment, the point cloud is generated using a stereo camera mounted on the vehicle); a row alignment control system that identifies a correction operation to bring the mobile work machine into alignment with a plurality of crop rows in the area of crops, wherein the row alignment control system identifies the correction operation based at least in part on a comparison of how a shift in the plurality of crop rows affects data gathered by the two sensors (In paragraph [0044], Vorobiev discloses that in one embodiment, a Hough transform detection algorithm is used to detect a centerline of rows of plants, for example, a Tractor mode in which a camera is located between rows and it is necessary to detect both rows from the left and right sides of the sensor; in paragraph [0047], Vorobiev discloses horizontal projection 1202 for detecting the location of rows in order to control operation of a tractor with respect to the location of the rows; in paragraph [0052], Vorobiev discloses a graph 1602 for use with a tractor, where two rows are selected, and based on the two rows, a lateral bias for the tractor can be determined relative to the centerline between the two rows, and the information concerning the centerline of the alley, along with vehicle orientation information, can be used to determine how a vehicle should be steered to traverse a desired path (i.e., along a centerline of an alley for a tractor); in paragraphs [0067-0068], Vorobiev that at step 1704, a location of a row is determined based on the point cloud, and at step 1706, a steering angle is generated based on the location of the row with respect to the location of the vehicle); and a control system that controls the mobile work machine using a control signal generated by the row alignment control system based on the identified correction operation (In paragraph [0052], Vorobiev discloses a graph 1602 for use with a tractor, where two rows are selected, and based on the two rows, a lateral bias for the tractor can be determined relative to the centerline between the two rows, and the information concerning the centerline of the alley, along with vehicle orientation information, can be used to determine how a vehicle should be steered to traverse a desired path (i.e., along a centerline of an alley for a tractor); in paragraph [0068], Vorobiev that at step 1706, a steering angle is generated based on the location of the row with respect to the location of the vehicle; in paragraph [0069], Vorobiev discloses that in one embodiment, camera 1804 generates a point cloud of data that is transmitted to machine controller 1802, where machine controller 1802 is in communication with steering controller 1806 which receives steering commands transmitted from machine controller 1802, and steering controller 1806 is in communication with steering actuator 1808 which steers agricultural vehicle when machine controller 1802 is operating to automatically steer the agricultural vehicle). Regarding claim 16, Vorobiev further discloses wherein the comparison is a comparison of distance measurements (In paragraph [0052], Vorobiev discloses a graph 1602 for use with a tractor, where two rows are selected, and based on the two rows, a lateral bias for the tractor can be determined relative to the centerline between the two rows, and the information concerning the centerline of the alley, along with vehicle orientation information, can be used to determine how a vehicle should be steered to traverse a desired path (i.e., along a centerline of an alley for a tractor); in paragraph [0068], Vorobiev that at step 1706, a steering angle is generated based on the location of the row with respect to the location of the vehicle; see also paragraph [0030] where Vorobiev discloses that cameras 404A, 404B can be any type of three-dimensional (3D) sensor such as a Time of Flight (ToF) camera or 3D LIDAR sensor) . Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA 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. 07-23-aia AIA 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. 07-21-aia AIA Claim s 1-5, 8-10, 13, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Vorobiev (US 2024/0389494 A1), in view of Weidenbach (US 2022/0187832 A1) . Regarding claim 1, Vorobiev discloses a method of controlling a mobile work machine (In paragraphs [0027-0028], Vorobiev discloses agricultural machines such as tractor 202 configured to travel along alley 102 without damaging plants of rows 104A, 104B located on either side of alley 102), the method comprising: receiving data indicative of an area of crops from a first sensor (In paragraph [0030], Vorobiev discloses tractor 402 having camera 404A mounted on an upper body member (e.g., roof 410) and camera 404B mounted near the front of tractor 402 (e.g., hood 412), where in one embodiment, cameras 404A, 404B are stereo cameras with each camera comprising two lenses, and cameras 404A, 404B can be any type of three-dimensional (3D) sensor such as a Time of Flight (ToF) camera or 3D LIDAR sensor; see also paragraph [0041] where Vorobiev discloses that the point cloud is defined based on a local coordinate system with respect to image sensors 1006A and 1006B having a left lens 1004A and right lens 1004B; in paragraph [0066], Vorobiev discloses that at step 1702, a point cloud of data is received by the machine controller, where in one embodiment, the point cloud is generated using a stereo camera mounted on the vehicle); receiving data indicative of the area of crops from a second sensor (In paragraph [0030], Vorobiev discloses tractor 402 having camera 404A mounted on an upper body member (e.g., roof 410) and camera 404B mounted near the front of tractor 402 (e.g., hood 412), where in one embodiment, cameras 404A, 404B are stereo cameras with each camera comprising two lenses, and cameras 404A, 404B can be any type of three-dimensional (3D) sensor such as a Time of Flight (ToF) camera or 3D LIDAR sensor; see also paragraph [0041] where Vorobiev discloses that the point cloud is defined based on a local coordinate system with respect to image sensors 1006A and 1006B having a left lens 1004A and right lens 1004B; in paragraph [0066], Vorobiev discloses that at step 1702, a point cloud of data is received by the machine controller, where in one embodiment, the point cloud is generated using a stereo camera mounted on the vehicle); identifying, based on the data received from the first and second sensors, a correction operation to bring the mobile work machine into alignment with a plurality of crop rows in the area of crops (In paragraph [0044], Vorobiev discloses that in one embodiment, a Hough transform detection algorithm is used to detect a centerline of rows of plants, for example, a Tractor mode in which a camera is located between rows and it is necessary to detect both rows from the left and right sides of the sensor; in paragraph [0047], Vorobiev discloses horizontal projection 1202 for detecting the location of rows in order to control operation of a tractor with respect to the location of the rows; in paragraph [0052], Vorobiev discloses a graph 1602 for use with a tractor, where two rows are selected, and based on the two rows, a lateral bias for the tractor can be determined relative to the centerline between the two rows, and the information concerning the centerline of the alley, along with vehicle orientation information, can be used to determine how a vehicle should be steered to traverse a desired path (i.e., along a centerline of an alley for a tractor); in paragraphs [0067-0068], Vorobiev that at step 1704, a location of a row is determined based on the point cloud, and at step 1706, a steering angle is generated based on the location of the row with respect to the location of the vehicle); generating a control signal based on the correction operation (In paragraph [0052], Vorobiev discloses a graph 1602 for use with a tractor, where two rows are selected, and based on the two rows, a lateral bias for the tractor can be determined relative to the centerline between the two rows, and the information concerning the centerline of the alley, along with vehicle orientation information, can be used to determine how a vehicle should be steered to traverse a desired path (i.e., along a centerline of an alley for a tractor); in paragraph [0068], Vorobiev that at step 1706, a steering angle is generated based on the location of the row with respect to the location of the vehicle; in paragraph [0069], Vorobiev discloses that in one embodiment, camera 1804 generates a point cloud of data that is transmitted to machine controller 1802, where machine controller 1802 is in communication with steering controller 1806 which receives steering commands transmitted from machine controller 1802, and steering controller 1806 is in communication with steering actuator 1808 which steers agricultural vehicle when machine controller 1802 is operating to automatically steer the agricultural vehicle); and using the control signal to control the mobile work machine (In paragraph [0068], Vorobiev that at step 1706, a steering angle is generated based on the location of the row with respect to the location of the vehicle; in paragraph [0069], Vorobiev discloses that in one embodiment, camera 1804 generates a point cloud of data that is transmitted to machine controller 1802, where machine controller 1802 is in communication with steering controller 1806 which receives steering commands transmitted from machine controller 1802, and steering controller 1806 is in communication with steering actuator 1808 which steers agricultural vehicle when machine controller 1802 is operating to automatically steer the agricultural vehicle). Vorobiev does not explicitly disclose assigning a weight to the data received from the first sensor, wherein the weight prioritizes use of the data received from the first sensor, relative to the data received from the second sensor, in determining a magnitude of shift; and identifying, based on the weight, a correction operation. However, Weidenbach teaches assigning a weight to the data received from the first sensor, wherein the weight prioritizes use of the data received from the first sensor, relative to the data received from the second sensor, in determining a magnitude of shift (In paragraph [0057], Weidenbach teaches multi-sensor fusion, e.g., using weighted sensor solutions from two or more sensors based on confidence; see also paragraph [0050] where Weidenbach teaches that a machine controller can use determined or obtained confidence in each sensor to select a measurement generated by the less obstruction (higher confidence) sensor for calculating cross track error or cross heading error, in various embodiments of the present subject matter in cases with the same types of sensors and different types of sensors); and identifying, based on the weight, a correction operation (In paragraph [0057], Weidenbach teaches multi-sensor fusion, e.g., using weighted sensor solutions from two or more sensors based on confidence; see also paragraph [0050] where Weidenbach teaches that a machine controller can use determined or obtained confidence in each sensor to select a measurement generated by the less obstruction (higher confidence) sensor for calculating cross track error or cross heading error, in various embodiments of the present subject matter in cases with the same types of sensors and different types of sensors). Weidenbach is considered to be analogous to the claimed invention in that they both pertain to weighing sensor data differently between multiple sensors for use with an agricultural vehicle. It would be obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Weidenbach with the method as disclosed by Vorobiev, where doing so advantageously improves the accuracy of detections made using the sensor data, as for example sensor data with a higher expected confidence will produce more reliable results. Regarding claim 2, Vorobiev further discloses wherein the second sensor is an image sensing device (In paragraph [0030], Vorobiev discloses tractor 402 having camera 404A mounted on an upper body member (e.g., roof 410) and camera 404B mounted near the front of tractor 402 (e.g., hood 412), where in one embodiment, cameras 404A, 404B are stereo cameras with each camera comprising two lenses, and cameras 404A, 404B can be any type of three-dimensional (3D) sensor such as a Time of Flight (ToF) camera or 3D LIDAR sensor). Weidenbach further teaches wherein the first sensor is a radar sensor and the second sensor is an image sensing device (In paragraph [0036], Weidenbach teaches a row steering system which uses multiple sensors (radar, camera based, LIDAR, ultrasound, mechanical elements or the like) and either chooses a sensor that is trusted (e.g., with a sufficient confidence) or blends the values together into a combined sensor reading to pass along to a navigation controller; in paragraph [0050], Weidencbach teaches an example of an agricultural machine 800 having sensors 802, 804, 812, 814, 816 that are alternatively or cooperatively usable to obtain guidance parameters for automated control of the machine, where in one example sensors A and B are different types of sensors (e.g., sensor A is a vision sensor and sensor B is a radar sensor, or other different types of sensors)). It would be obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to further implement the use of radar as taught by Weidenbach, where the use of radar in vehicle sensing contexts is well understood in the art, and may be implemented without undue experimentation, and with a reasonable expectation of success and predictable results, and where using a wider variety of obtained sensor data can advantageously improve the accuracy of detections in a wider variety of circumstances. For example, the operation of the machine may be improved such as the processing of crop rows in a scenario including field or environmental conditions that limit operation (e.g., fog that decreases confidence in vision sensors or gaps along rows that decrease confidence in radar sensors) of one or more of the sensors, as suggested by Weidenbach in paragraph [0016]. Regarding claim 3, Weidenbach further teaches wherein the first and second sensors are both radar sensors (In paragraph [0036], Weidenbach teaches a row steering system which uses multiple sensors (radar, camera based, LIDAR, ultrasound, mechanical elements or the like) and either chooses a sensor that is trusted (e.g., with a sufficient confidence) or blends the values together into a combined sensor reading to pass along to a navigation controller; in paragraph [0050], Weidencbach teaches an example of an agricultural machine 800 having sensors 802, 804, 812, 814, 816 that are alternatively or cooperatively usable to obtain guidance parameters for automated control of the machine, where in one example sensors A and B are in one example the same types of sensors (e.g., both vision sensors, both radar sensors, or the same type of other sensor, such as ultrasound, LIDAR or the like)). It would be obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to further implement the use of radar as taught by Weidenbach, where the use of radar in vehicle sensing contexts is well understood in the art, and may be implemented without undue experimentation, and with a reasonable expectation of success and predictable results, and where using radar sensor data can advantageously improve the accuracy of detections in specific circumstances. For example, the operation of the machine may be improved such as the processing of crop rows in a scenario including field or environmental conditions that limit operation (e.g., fog that decreases confidence in vision sensors or gaps along rows that decrease confidence in radar sensors) of one or more of the sensors, as suggested by Weidenbach in paragraph [0016]. Regarding claim 4, Vorobiev further discloses wherein receiving data indicative of the area of crops from the first sensor comprises receiving a distance from a reference point on the mobile work machine to the plurality of crop rows (In paragraph [0052], Vorobiev discloses a graph 1602 for use with a tractor, where two rows are selected, and based on the two rows, a lateral bias for the tractor can be determined relative to the centerline between the two rows, and the information concerning the centerline of the alley, along with vehicle orientation information, can be used to determine how a vehicle should be steered to traverse a desired path (i.e., along a centerline of an alley for a tractor); see also paragraphs [0033-0034], where Vorobiev discloses that camera 504 is located a height H 506 above ground 414 on which harvester 502 operates, and offset D is based on the distance between a centerline of a vehicle and a projection to the ground of the origin of the local coordinate system of the stereo camera, where offset D, height H and one or more of the angles described are used to link the vehicle's coordinate system to the camera's coordinate system). Regarding claim 5, Vorobiev further discloses wherein using the control signal to control the mobile work machine further comprises using the control signal to cause a steering subsystem to steer the mobile work machine (In paragraph [0069], Vorobiev discloses that in one embodiment, camera 1804 generates a point cloud of data that is transmitted to machine controller 1802, where machine controller 1802 is in communication with steering controller 1806 which receives steering commands transmitted from machine controller 1802, and steering controller 1806 is in communication with steering actuator 1808 which steers agricultural vehicle when machine controller 1802 is operating to automatically steer the agricultural vehicle). Regarding claim 8, Vorobiev further discloses wherein the data received from the first sensor and the second sensor comprises image data (In paragraph [0030], Vorobiev discloses tractor 402 having camera 404A mounted on an upper body member (e.g., roof 410) and camera 404B mounted near the front of tractor 402 (e.g., hood 412), where in one embodiment, cameras 404A, 404B are stereo cameras with each camera comprising two lenses, and cameras 404A, 404B can be any type of three-dimensional (3D) sensor such as a Time of Flight (ToF) camera or 3D LIDAR sensor). Weidenbach further teaches wherein the data received from the first sensor and the second sensor comprises a combination of radar and image data (In paragraph [0036], Weidenbach teaches a row steering system which uses multiple sensors (radar, camera based, LIDAR, ultrasound, mechanical elements or the like) and either chooses a sensor that is trusted (e.g., with a sufficient confidence) or blends the values together into a combined sensor reading to pass along to a navigation controller; in paragraph [0050], Weidencbach teaches an example of an agricultural machine 800 having sensors 802, 804, 812, 814, 816 that are alternatively or cooperatively usable to obtain guidance parameters for automated control of the machine, where in one example sensors A and B are different types of sensors (e.g., sensor A is a vision sensor and sensor B is a radar sensor, or other different types of sensors)). It would be obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to further implement the use of radar as taught by Weidenbach, where the use of radar in vehicle sensing contexts is well understood in the art, and may be implemented without undue experimentation, and with a reasonable expectation of success and predictable results, and where using a wider variety of obtained sensor data can advantageously improve the accuracy of detections in a wider variety of circumstances. For example, the operation of the machine may be improved such as the processing of crop rows in a scenario including field or environmental conditions that limit operation (e.g., fog that decreases confidence in vision sensors or gaps along rows that decrease confidence in radar sensors) of one or more of the sensors, as suggested by Weidenbach in paragraph [0016]. Regarding claim 9, Weidenbach further teaches wherein identifying the correction operation further comprises identifying the data received from the first sensor as being more reliable than the data received from the second sensor (In paragraph [0057], Weidenbach teaches multi-sensor fusion, e.g., using weighted sensor solutions from two or more sensors based on confidence; see also paragraph [0050] where Weidenbach teaches that a machine controller can use determined or obtained confidence in each sensor to select a measurement generated by the less obstruction (higher confidence) sensor for calculating cross track error or cross heading error, in various embodiments of the present subject matter in cases with the same types of sensors and different types of sensors). It would be obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to further implement the teachings of Weidenbach, where doing so advantageously improves the accuracy of detections made using the sensor data, as for example sensor data with a higher expected confidence will produce more reliable results. Regarding claim 10, Weidenbach further teaches wherein the weight comprises a first weight, and further comprising assigning a second weight to the data received from the second sensor, wherein the second weight prioritizes use of the data received from the second sensor, relative to the data received from the first sensor, in determining a direction of shift, and wherein identifying the correction operation comprises identifying the correction operation based on the second weight (In paragraph [0057], Weidenbach teaches multi-sensor fusion, e.g., using weighted sensor solutions from two or more sensors based on confidence; see also paragraph [0050] where Weidenbach teaches that a machine controller can use determined or obtained confidence in each sensor to select a measurement generated by the less obstruction (higher confidence) sensor for calculating cross track error or cross heading error, in various embodiments of the present subject matter in cases with the same types of sensors and different types of sensors). Regarding claim 13, although in paragraph [0030] Vorobiev discloses that cameras 404A, 404B can be any type of three-dimensional (3D) sensor such as a Time of Flight (ToF) camera or 3D LIDAR sensor, Vorobiev does not explicitly disclose wherein the two sensors are two radar sensors. However, Weidenbach teaches wherein the two sensors are two radar sensors (In paragraph [0036], Weidenbach teaches a row steering system which uses multiple sensors (radar, camera based, LIDAR, ultrasound, mechanical elements or the like) and either chooses a sensor that is trusted (e.g., with a sufficient confidence) or blends the values together into a combined sensor reading to pass along to a navigation controller; in paragraph [0050], Weidencbach teaches an example of an agricultural machine 800 having sensors 802, 804, 812, 814, 816 that are alternatively or cooperatively usable to obtain guidance parameters for automated control of the machine, where in one example sensors A and B are in one example the same types of sensors (e.g., both vision sensors, both radar sensors, or the same type of other sensor, such as ultrasound, LIDAR or the like)). Weidenbach is considered to be analogous to the claimed invention in that they both pertain to utilizing both radar and image sensing for row-steering of an agricultural vehicle. It would be obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to implement the use of radar as taught by Weidenbach with the machine as disclosed by Vorobiev, where the use of radar in vehicle sensing contexts is well understood in the art, and may be implemented without undue experimentation, and with a reasonable expectation of success and predictable results, and where using radar sensor data can advantageously improve the accuracy of detections in specific circumstances. For example, the operation of the machine may be improved such as the processing of crop rows in a scenario including field or environmental conditions that limit operation (e.g., fog that decreases confidence in vision sensors or gaps along rows that decrease confidence in radar sensors) of one or more of the sensors, as suggested by Weidenbach in paragraph [0016]. Regarding claim 15, Vorobiev further discloses wherein the one sensor is an image sensing device (In paragraph [0030], Vorobiev discloses tractor 402 having camera 404A mounted on an upper body member (e.g., roof 410) and camera 404B mounted near the front of tractor 402 (e.g., hood 412), where in one embodiment, cameras 404A, 404B are stereo cameras with each camera comprising two lenses, and cameras 404A, 404B can be any type of three-dimensional (3D) sensor such as a Time of Flight (ToF) camera or 3D LIDAR sensor). Although in paragraph [0030] Vorobiev discloses that cameras 404A, 404B can be any type of three-dimensional (3D) sensor such as a Time of Flight (ToF) camera or 3D LIDAR sensor, Vorobiev does not explicitly disclose wherein the two sensors are a radar sensor and an image sensing device. However, Weidenbach teaches wherein the two sensors are a radar sensor and an image sensing device (In paragraph [0036], Weidenbach teaches a row steering system which uses multiple sensors (radar, camera based, LIDAR, ultrasound, mechanical elements or the like) and either chooses a sensor that is trusted (e.g., with a sufficient confidence) or blends the values together into a combined sensor reading to pass along to a navigation controller; in paragraph [0050], Weidencbach teaches an example of an agricultural machine 800 having sensors 802, 804, 812, 814, 816 that are alternatively or cooperatively usable to obtain guidance parameters for automated control of the machine, where in one example sensors A and B are different types of sensors (e.g., sensor A is a vision sensor and sensor B is a radar sensor, or other different types of sensors)). Weidenbach is considered to be analogous to the claimed invention in that they both pertain to utilizing both radar and image sensing for row-steering of an agricultural vehicle. It would be obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to implement the use of radar as taught by Weidenbach with the machine as disclosed by Vorobiev, where the use of radar in vehicle sensing contexts is well understood in the art, and may be implemented without undue experimentation, and with a reasonable expectation of success and predictable results, and where using a wider variety of obtained sensor data can advantageously improve the accuracy of detections in a wider variety of circumstances. For example, the operation of the machine may be improved such as the processing of crop rows in a scenario including field or environmental conditions that limit operation (e.g., fog that decreases confidence in vision sensors or gaps along rows that decrease confidence in radar sensors) of one or more of the sensors, as suggested by Weidenbach in paragraph [0016] . 07-21-aia AIA Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Vorobiev (US 2024/0389494 A1) and Weidenbach (US 2022/0187832 A1), in view of Hayashida (US 2025/0380625 A1) . Regarding claim 6, the combination of Vorobiev and Weidenbach does not explicitly disclose wherein using the control signal to control the mobile work machine further comprises using the control signal to cause a propulsion subsystem to propel the mobile work machine. However, Hayashida teaches wherein using the control signal to control the mobile work machine further comprises using the control signal to cause a propulsion subsystem to propel the mobile work machine (In paragraph [0042], Hayashida teaches an agricultural machine 100 which performs self-driving in an environment where a plurality of crop rows (e.g., rows of trees) are planted, e.g., an orchard such as a vineyard or an agricultural field; in paragraphs [0070-0071], Hayashida teaches that an ECU 181 controls the prime mover 102, the transmission 103, and brakes included in the driver 240, thus controlling the speed of the agricultural machine 100, as well as controlling the hydraulic device or the electric motor included in the steering device 106 based on a measurement value of the steering wheel sensor 152, thus controlling the steering of the agricultural machine 100). Hayashida is considered to be analogous to the claimed invention in that they both pertain to controlling propulsion of a vehicle in an agricultural setting. It would be obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Hayashida with the method as disclosed by the combination of Vorobiev and Weidenbach, where doing so allows control of speed of the vehicle, advantageously improving safety of control of the vehicle by, for example, preventing collisions or other dangerous operations which cannot be avoided by control of steering alone . 07-21-aia AIA Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Vorobiev (US 2024/0389494 A1) and Weidenbach (US 2022/0187832 A1), in view of Aberle (US 2018/0373259 A1) . Regarding claim 7, although in paragraph [0028] Vorobiev discloses that the agricultural machines that are controlled by an operator, and in paragraph [0072] that the computer 1902 also includes input/output devices 1908 that enable user interaction with the computer 1902 (e.g., display, keyboard, mouse, speakers, buttons, etc.), the combination of Vorobiev and Weidenbach does not explicitly disclose wherein the using the control signal to control the mobile work machine further comprises using the control signal to generate a user interface. However, Aberle teaches wherein the using the control signal to control the mobile work machine further comprises using the control signal to generate a user interface (In paragraphs [0038-0039], Aberle teaches that in order to provide appropriate feedback and notifications to an operator, an enhanced steering system 700 will include a display panel 900 capable of communicating valuable information, for example, a portion of display 900 may indicate the offset distance measured by the alignment sensor 400 in relation to the actual center line (CL) between crop rows). Aberle is considered to be analogous to the claimed invention in that they both pertain to generating a user interface for an agricultural vehicle travelling between crop rows. It would be obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Aberle with the method as disclosed by the combination of Vorobiev and Weidenbach, where doing so provides appropriate feedback and notifications to an operator as suggested by Aberle in paragraph [0038], thereby advantageously increasing the operator’s contextual understanding of operation of the vehicle, for example . 07-21-aia AIA Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Vorobiev (US 2024/0389494 A1), in view of Mitsuta (US 9,597,997 B2) . Regarding claim 14, although in paragraph [0030] Vorobiev discloses that cameras 404A, 404B can be any type of three-dimensional (3D) sensor such as a Time of Flight (ToF) camera or 3D LIDAR sensor, Vorobiev does not explicitly disclose wherein the two sensors are a first radar sensor located on one side of the mobile work machine and a second radar sensor located on an opposite side of the mobile work machine. However, Mitsuta teaches wherein the two sensors are a first radar sensor located on one side of the mobile work machine and a second radar sensor located on an opposite side of the mobile work machine (In column 5 lines 7-49, Mitsuta teaches that eight radar apparatuses 21 to 28 detect the relative position of an obstacle which is present in the surroundings of the work vehicle, for example radar apparatuses disposed on the left of the vehicle with symmetrically placed radar apparatuses on the right; see also fig. 4 below which depicts the radar apparatuses placed on both the left and right of the work vehicle). PNG media_image1.png 700 409 media_image1.png Greyscale Figure 4 of Mitsuta (US 9,597,997 B2) Mitsuta is considered to be analogous to the claimed invention in that they both pertain to placing a plurality of radar sensors on a work vehicle, at least on opposite sides of the vehicle. It would be obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Mitsuta with the machine as disclosed by Vorobiev, where it is possible to detect the relative position of an obstacle with regard to the work vehicle across substantially the entire surroundings of the work vehicle, as suggested by Mitsuta in column 5 lines 42-39 for example, thereby improving the detection of the vehicle’s surroundings . Allowable Subject Matter 12-151-08 AIA 07-43 12-51-08 Claim 11 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. 12-151-07 AIA 07-97 12-51-07 Claim s 17-18 and 20 are allowed. 13-03-01 AIA The following is a statement of reasons for the indication of allowable subject matter: Regarding claim 17, the closest prior art of record Vorobiev (US 2024/0389494 A1) discloses a mobile work machine (In paragraphs [0027-0028], Vorobiev discloses agricultural machines such as tractor 202 configured to travel along alley 102 without damaging plants of rows 104A, 104B located on either side of alley 102), comprising: a first sensor that provides a distance for each of a plurality of crop rows in an area of crops in front of the mobile work machine (In paragraph [0030], Vorobiev discloses tractor 402 having camera 404A mounted on an upper body member (e.g., roof 410) and camera 404B mounted near the front of tractor 402 (e.g., hood 412), where in one embodiment, cameras 404A, 404B are stereo cameras with each camera comprising two lenses, and cameras 404A, 404B can be any type of three-dimensional (3D) sensor such as a Time of Flight (ToF) camera or 3D LIDAR sensor; see also paragraph [0041] where Vorobiev discloses that the point cloud is defined based on a local coordinate system with respect to image sensors 1006A and 1006B having a left lens 1004A and right lens 1004B; in paragraph [0066], Vorobiev discloses that at step 1702, a point cloud of data is received by the machine controller, where in one embodiment, the point cloud is generated using a stereo camera mounted on the vehicle); a second sensor that provides a distance for each of a plurality of crop rows in an area of crops in front of the mobile work machine (In paragraph [0030], Vorobiev discloses tractor 402 having camera 404A mounted on an upper body member (e.g., roof 410) and camera 404B mounted near the front of tractor 402 (e.g., hood 412), where in one embodiment, cameras 404A, 404B are stereo cameras with each camera comprising two lenses, and cameras 404A, 404B can be any type of three-dimensional (3D) sensor such as a Time of Flight (ToF) camera or 3D LIDAR sensor; see also paragraph [0041] where Vorobiev discloses that the point cloud is defined based on a local coordinate system with respect to image sensors 1006A and 1006B having a left lens 1004A and right lens 1004B; in paragraph [0066], Vorobiev discloses that at step 1702, a point cloud of data is received by the machine controller, where in one embodiment, the point cloud is generated using a stereo camera mounted on the vehicle); a row alignment control system that identifies a correction operation based on a combination of the distances provided by the first and second sensors, wherein the row alignment control system generates a control signal based on the identified correction operation (In paragraph [0044], Vorobiev discloses that in one embodiment, a Hough transform detection algorithm is used to detect a centerline of rows of plants, for example, a Tractor mode in which a camera is located between rows and it is necessary to detect both rows from the left and right sides of the sensor; in paragraph [0047], Vorobiev discloses horizontal projection 1202 for detecting the location of rows in order to control operation of a tractor with respect to the location of the rows; in paragraph [0052], Vorobiev discloses a graph 1602 for use with a tractor, where two rows are selected, and based on the two rows, a lateral bias for the tractor can be determined relative to the centerline between the two rows, and the information concerning the centerline of the alley, along with vehicle orientation information, can be used to determine how a vehicle should be steered to traverse a desired path (i.e., along a centerline of an alley for a tractor); in paragraphs [0067-0068], Vorobiev that at step 1704, a location of a row is determined based on the point cloud, and at step 1706, a steering angle is generated based on the location of the row with respect to the location of the vehicle); and a control system that controls the mobile work machine using the control signal (In paragraph [0052], Vorobiev discloses a graph 1602 for use with a tractor, where two rows are selected, and based on the two rows, a lateral bias for the tractor can be determined relative to the centerline between the two rows, and the information concerning the centerline of the alley, along with vehicle orientation information, can be used to determine how a vehicle should be steered to traverse a desired path (i.e., along a centerline of an alley for a tractor); in paragraph [0068], Vorobiev that at step 1706, a steering angle is generated based on the location of the row with respect to the location of the vehicle; in paragraph [0069], Vorobiev discloses that in one embodiment, camera 1804 generates a point cloud of data that is transmitted to machine controller 1802, where machine controller 1802 is in communication with steering controller 1806 which receives steering commands transmitted from machine controller 1802, and steering controller 1806 is in communication with steering actuator 1808 which steers agricultural vehicle when machine controller 1802 is operating to automatically steer the agricultural vehicle). Weidenbach (US 2022/0187832 A1) teaches a first radar sensor that provides a distance for each of a plurality of crop rows in an area of crops in front of the mobile work machine; and a second radar sensor that provides a distance for each of a plurality of crop rows in an area of crops in front of the mobile work machine (In paragraph [0036], Weidenbach teaches a row steering system which uses multiple sensors (radar, camera based, LIDAR, ultrasound, mechanical elements or the like) and either chooses a sensor that is trusted (e.g., with a sufficient confidence) or blends the values together into a combined sensor reading to pass along to a navigation controller; in paragraph [0050], Weidencbach teaches an example of an agricultural machine 800 having sensors 802, 804, 812, 814, 816 that are alternatively or cooperatively usable to obtain guidance parameters for automated control of the machine, where in one example sensors A and B are in one example the same types of sensors (e.g., both vision sensors, both radar sensors, or the same type of other sensor, such as ultrasound, LIDAR or the like)). However, the prior art of record, alone or in combination, does not explicitly disclose wherein the plurality of crop rows for which the first radar sensor provides the distance is different than the plurality of crop rows for which the second radar sensor provides the distance. Therefore, independent claim 17 and corresponding dependent claims 18 and 20 are allowed . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Schleicher (US 2019/0000007 A1) teaches crop row sensing on a vehicle with multiple, independently steerable axles/wheels. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL . See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). 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 Harrison Heflin whose telephone number is (571)272-5629. The examiner can normally be reached Monday - Friday, 1:00PM - 10:00PM EST. 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. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hunter Lonsberry can be reached at 571-272-7298. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. 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. /HARRISON HEFLIN/Examiner, Art Unit 3665 /HUNTER B LONSBERRY/Supervisory Patent Examiner, Art Unit 3665 Application/Control Number: 18/977,285 Page 2 Art Unit: 3665 Application/Control Number: 18/977,285 Page 3 Art Unit: 3665 Application/Control Number: 18/977,285 Page 4 Art Unit: 3665 Application/Control Number: 18/977,285 Page 5 Art Unit: 3665 Application/Control Number: 18/977,285 Page 6 Art Unit: 3665 Application/Control Number: 18/977,285 Page 7 Art Unit: 3665 Application/Control Number: 18/977,285 Page 8 Art Unit: 3665 Application/Control Number: 18/977,285 Page 9 Art Unit: 3665 Application/Control Number: 18/977,285 Page 10 Art Unit: 3665 Application/Control Number: 18/977,285 Page 11 Art Unit: 3665 Application/Control Number: 18/977,285 Page 12 Art Unit: 3665 Application/Control Number: 18/977,285 Page 13 Art Unit: 3665 Application/Control Number: 18/977,285 Page 14 Art Unit: 3665 Application/Control Number: 18/977,285 Page 15 Art Unit: 3665 Application/Control Number: 18/977,285 Page 16 Art Unit: 3665 Application/Control Number: 18/977,285 Page 17 Art Unit: 3665 Application/Control Number: 18/977,285 Page 18 Art Unit: 3665 Application/Control Number: 18/977,285 Page 19 Art Unit: 3665 Application/Control Number: 18/977,285 Page 20 Art Unit: 3665 Application/Control Number: 18/977,285 Page 21 Art Unit: 3665 Application/Control Number: 18/977,285 Page 22 Art Unit: 3665 Application/Control Number: 18/977,285 Page 23 Art Unit: 3665
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