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 Arguments
The reply filed on 3/30/2026 has been entered. Some of the applicant’s arguments with respect to claims 16 and 29 have been considered but are moot in view of new ground(s) of rejection caused by the amendments. The 112(b) claim rejections have been withdrawn because of the current amendment. Claims 16-29 are pending in this application and have been considered below.
Argument pg. 9 par. 1-2:
The applicant argues that Seitz does not cure the deficiencies of Wu and the Seitz does not disclose or suggest selecting a variable depth of the image evaluation region using the control unit.
Response:
Seitz teaches selecting a variable depth of the image evaluation region by utilizing a control unit to dynamically define a specific, smaller evaluation portion within a larger monitored field section based on the direction of travel of the spraying device. The control unit selects the position and size of this specified evaluation portion such that its length of the evaluation region is less than the length of the monitored field section. This selection allows the system to reduce the number of pixels processed for image analysis, decreasing processing time and, consequently, increasing the maximum possible reaction time for the nozzle. The arguments of counsel cannot take the place of evidence in the record. In re Schulze, 346 F.2d 600, 602, 145 USPQ 716, 718 (CCPA 1965); In re Geisler, 116 F.3d 1465, 43 USPQ2d 1362 (Fed. Cir. 1997) ("An assertion of what seems to follow from common experience is just attorney argument and not the kind of factual evidence that is required to rebut a prima facie case of obviousness.").
Argument pg. 9 par. 1:
The applicant argues that claim 26 cannot be rejected under 35 U.S.C. 102 because it depends on claim 16 rejected under 35 U.S.C. 103.
Response:
Examiner agrees that the rejection of claim 26 of the previous office action included a flawed structure. Because of the current new grounds of rejection of claim 26, the present office action has been submitted as a Non-Final Rejection.
Priority
Receipt is acknowledged that application is a National Stage application of PCT PCT/EP2021/076078. Priority to DE10 2020 215 874.6 with a priority date of 12/15/2020 is acknowledged under 35 USC 119(e) and 37 CFR 1.78.
Information Disclosure Statement
The IDS dated 4/10/2023 that have been previously considered remain placed in the application file.
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 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, and 29 are rejected under 35 U.S.C. 103 as obvious over US Patent Publication 2019 0150357 A1, (Wu et al.) in view of US Patent Publication 2021 0386051 A1, (Seitz et al.).
Claim 16
Regarding claim 16, Wu et al. disclose a method for applying a spray onto agricultural land using at least one spray nozzle unit of an agricultural spraying device, comprising the following steps: (“triggers spray release from spray nozzles, where each nozzle is in communication with one or a few associated image sensor unit,” par. 53) detecting a field section of the agricultural land using at least one optical detection unit to obtain image information on the field section with a depth in a direction of travel of the spraying device; (“FIG. 6 depicts another embodiment method to find anomalies 11 from captured images for detecting and getting rid of or deterring anomalous objects 11 found among plants 10 along a crop row,” par. 102) identifying plants in an image evaluation region of the obtained image information using a control unit, (“the computing device … can plug into a larger, powerful, more centralized controller of the vehicle, where the centralized controller also manages or performs other machine tasks,” par. 47) wherein the image evaluation region represents a corresponding field evaluation region of the detected field section with a depth in the direction of travel of the spraying device; (“FIG. 6 depicts another embodiment method to find anomalies 11 from captured images for detecting and getting rid of or deterring anomalous objects 11 found among plants 10 along a crop row,” par. 102) applying the spray onto the field evaluation region of the detected field section using the spray nozzle unit of the agricultural spraying device (“On a spray boom, two adjacent image sensor 1910 and 1912 or smartphone-electronics can serve to estimate stereo. Spray nozzles are often spaced 15 to 30 inches apart depending on the crop row spacing; adjacent image sensor (e.g. cameras) or smartphone-electronics are placed at least as far apart. For some of the applications, images from image sensor 1910 or smartphone-electronics symmetrically on either side of the boom may be used to determine an action,” par. 49) as a function of the plants identified in the image evaluation region; and (“identification of weeds that triggers spray release from spray nozzles, where each nozzle is in communication with one or a few associated image sensor unit 50,” par. 53) (“spray the area when the spray vehicle reaches the weed location,” par. 99).
Wu et al. do not explicitly teach all of selecting a variable depth of the image evaluation region using the control unit.
However, Seitz et al. teach selecting a variable depth of the image evaluation region (“In order to now increase the maximum traveling and/or operating speed, the present invention does not shorten length L(Field) of monitored field section 32, since, as explained above, it is supposed to be as large as possible for identifying rows of plants, but a new (smaller) evaluation portion 42 of monitored field section 32, having a length L(Evaluation), is specified and/or defined,” par. 58) using the control unit (“Control unit 28 includes a processing unit 30, which is configured to execute computational steps and/or image processing steps for carrying out the method of the present invention,” par. 55).
Therefore, taking the teachings of Wu et al. and Seitz et al. as a whole, it would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify the agricultural spraying device as taught by Wu et al. to use the variable image length as taught by Seitz et al. The suggestion/motivation for doing so would have been that, “34 of spraying device 10 is less than length L(Field) of monitored field section 32, first of all, the necessary processing time and, consequently, reaction time t(max), decrease due to the lower number of pixels in the image of specified evaluation portion 42. In addition, in the exemplary embodiment shown, the position of specified evaluation portion 42 in monitored field section 32 is selected in such a manner, that in direction of travel 34 of spraying device 10, specified evaluation portion 42 has a larger reaction path x(Evaluation) than monitored field section 32 x(Field) with respect to spray region 40 of following spray nozzle 16. This increases the reaction path x relevant to the application capability. The two factors, lower processing time and increased reaction path, increase the maximum possible traveling and/or operating speed” as noted by the Seitz et al. disclosure in paragraph [0059], which also motivates combination because the combination would predictably have a higher efficiency as there is a reasonable expectation that incorporating the variable image length to reduce pixels in the evaluation portion would result in faster processing times, improved reaction speeds, and higher operating efficiency; and/or because doing so merely combines prior art elements according to known methods to yield predictable results.
Claim 17
Regarding claim 17, Wu et al. and Seitz et al. teach the method according to claim 16 as noted above.
Wu et al. do not explicitly teach all of the depth of the depth-variable image evaluation region is selected by the control unit as a function of a speed of the agricultural spraying device in the direction of travel.
[AltContent: textbox (Figure 3. depicts a field section having an evaluated section through the change of the length.)]
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However, Seitz et al. teach the depth of the depth-variable image evaluation region is selected by the control unit as a function of a speed of the agricultural spraying device in the direction of travel (“In order to now increase the maximum traveling and/or operating speed, the present invention does not shorten length L(Field) of monitored field section 32, since, as explained above, it is supposed to be as large as possible for identifying rows of plants, but a new (smaller) evaluation portion 42 of monitored field section 32, having a length L(Evaluation), is specified and/or defined,” par. 58 wherein changing the variable length L(Evaluation) changes the depth within the image).
Wu et al. and Seitz et al. are combined as per claim 16.
Claim 18
Regarding claim 18, Wu et al. and Seitz et al. teach the method according to claim 16 as noted above.
Wu et al. do not explicitly teach all of that the depth of the depth-variable image evaluation region is selected by the control unit as a function of a frame rate of detected field sections or a variable related to a temperature of the control unit.
However, Seitz et al. teach that the depth of the depth-variable image evaluation region is selected by the control unit (“Length L(Evaluation) of the specified evaluation portion may be set either inside downstream image processing software of the processing unit or, if supported by the optical detection unit and/or camera, directly as an ROI (region of interest) definition on the level of the imager chip of the optical detection unit and/or camera,” par. 30) as a function of a frame rate of detected field sections or a variable related to a temperature of the control unit (Since length L(Evaluation) of specified evaluation portion 42 in direction of travel 34 of spraying device 10 is less than length L(Field) of monitored field section 32, first of all, the necessary processing time and, consequently, reaction time t(max), decrease due to the lower number of pixels in the image of specified evaluation portion 42,” par. 59 wherein the control unit processing time is directly proportional control unit temperature).
Wu et al. and Seitz et al. are combined as per claim 16.
Claim 19
Regarding claim 19, Wu et al. and Seitz et al. teach the method according to claim 16 as noted above.
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[AltContent: textbox (Figure 3. depicts a field section having an evaluated section through the change of the length.)]Wu et al. do not explicitly teach all of that a rear edge of the depth-variable image evaluation region in the direction of travel of the agricultural spraying device is aligned with a rear edge of the image information in the direction of travel of the agricultural spraying device (“As FIG. 3 illustrates, the at least one row of plants 44 is identified, e.g., from the measured portion of the color green, with the aid of processing unit 30, in a “processing path” in the (entire) monitored field section 32 and/or the (entire) acquired image of field section 32,” par. 61 wherein the rear edge of the evaluation region is parallel with the rear edge of the image).
However, Seitz et al. teach that a rear edge of the depth-variable image evaluation region in the direction of travel of the agricultural spraying device is aligned with a rear edge of the image information in the direction of travel of the agricultural spraying device.
Wu et al. and Seitz et al. are combined as per claim 16.
Claim 20
Regarding claim 20, Wu et al. and Seitz et al. teach the method according to claim 16 as noted above.
Wu et al. do not explicitly teach all of a rear edge of the depth-variable image evaluation region in the direction of travel of the agricultural spraying device is selected by the control unit as a function of a speed of the agricultural spraying device in the direction of travel.
However, Seitz et al. teach a rear edge of the depth-variable image evaluation region in the direction of travel of the agricultural spraying device is selected by the control unit as a function of a speed of the agricultural spraying device in the direction of travel (“In order to now increase the maximum traveling and/or operating speed, the present invention does not shorten length L(Field) of monitored field section 32, since, as explained above, it is supposed to be as large as possible for identifying rows of plants, but a new (smaller) evaluation portion 42 of monitored field section 32, having a length L(Evaluation), is specified and/or defined,” par. 58 wherein the rear edge of the image changes position when the length L(Evaluation) is increased or decreased).
Wu et al. and Seitz et al. are combined as per claim 16.
Claim 21
Regarding claim 21, Wu et al. and Seitz et al. teach the method according to claim 16 as noted above.
Wu et al. do not explicitly teach all of that the depth-variable image evaluation region has a minimum depth of 20% of the depth of the image information or a maximum depth of 100% of the depth of the image information.
However, Seitz et al. teach the depth-variable image evaluation region has a minimum depth of 20% of the depth of the image information or a maximum depth of 100% of the depth of the image information (“The step of identifying the at least one row of plants is preferably accomplished, using and/or evaluating the entire and/or essentially the entire, monitored field section, that is, in the image having the maximum possible length L(Field), which is determined by the mounting position of the detection unit or camera and the imager chip used,” par. 28 wherein selecting a maximum possible length for an image evaluation region would suggest also containing a depth of 100%).
Wu et al. and Seitz et al. are combined as per claim 16.
Claim 22
Regarding claim 22, Wu et al. and Seitz et al. teach the method according to claim 16 as noted above.
Wu et al. do not explicitly teach all of a width of the depth-variable image evaluation region is less than a width of the image information.
However, Seitz et al. teach a width of the depth-variable image evaluation region is less than a width of the image information (“As FIG. 3 illustrates, the at least one row of plants 44 is identified,
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e.g., from the measured portion of the color green, with the aid of processing unit 30, in a “processing path” in the (entire) monitored field section 32 and/or the (entire) acquired image of field section 32,” par. 61 wherein the [AltContent: textbox (Figure 3. depicts a field section having an evaluated section through the change of the length.)]L(Evaluation) is the width of the image evaluation region and the L(Field) is the width of the image information).
Wu et al. and Seitz et al. are combined as per claim 16.
Claim 23
Regarding claim 23, Wu et al. and Seitz et al. teach the method according to claim 16 as noted above.
Wu et al. do not explicitly teach all of that the field section is detected with an angle of inclination of an optical axis of the optical detection unit of greater than 0 relative to vertical in the direction of travel of the spraying device.
[AltContent: textbox (Figure 2. depicts a layout of the spray nozzle relative to the image sensor.)]
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However, Seitz et al. teach that the field section is detected with an angle of inclination of an optical axis of the optical detection unit of greater than 0 relative to vertical in the direction of travel of the spraying device (“angle of inclination a is the angle between an optical axis 36 of camera 18 and a vertical line 38 in direction of travel 34 of spraying device,” par. 56).
Wu et al. and Seitz et al. are combined as per claim 16.
Claim 24
Regarding claim 24, Wu et al. and Seitz et al. teach the method according to claim 16 as noted above, further comprising: ascertaining a plant index for the depth-variable image evaluation region using the identified plants (“it takes more processing time to identify a crop leaf from a weed leaf if there are many types of weed leaves or are very similar to a particular crop's leaves. In this scenario, fast triggers are instead used to detect height differences, mass (leaf density, number of leaves), and deviations from an expected pattern to determine whether to release herbicide. For example, statistical deviations from an a priori determined normal pattern are used,” par. 105) in the depth-variable image evaluation region using the control unit (“the computing device … can plug into a larger, powerful, more centralized controller of the vehicle, where the centralized controller also manages or performs other machine tasks,” par. 47).
Wu et al. do not explicitly teach all of in the step of applying, the spray is applied onto the field evaluation region as a function of the ascertained plant index, upon reaching or falling below or exceeding a defined threshold value for the plant index.
However, Seitz et al. teach in the step of applying, the spray is applied onto the field evaluation region as a function of the ascertained plant index, upon reaching or falling below or exceeding a defined threshold value for the plant index (“The step of applying may include comparing the ascertained plant value to a threshold value; the step of applying being executed in response to the threshold value's being reached, fallen below, or exceeded. The threshold value may be inputted manually. In this connection, a so-called spraying rule, that is, a relationship between a determined plant value and the decision as to whether, and how much of, a crop protection chemical should be applied, may be stored as a function of the cultivation in the field, the stage of growth, and/or the crop protection chemical utilized,” par. 35).
Wu et al. and Seitz et al. are combined as per claim 16.
Claim 25
Regarding claim 25, Wu et al. and Seitz et al. teach the method according to claim 24 as noted above.
Wu et al. do not explicitly teach all of that the plant index represents a degree of coverage of the field evaluation region of plant material or a quantity of plant material in the respective field evaluation region or a number of identified plants in the field evaluation region.
However, Seitz et al. teach that the plant index represents a degree of coverage of the field evaluation region of plant material or a quantity of plant material in the respective field evaluation region or a number of identified plants in the field evaluation region (“in light of a predetermined NDVI value (normalized differenced vegetation index; it is calculated from reflectance values in the near infrared and visible red wavelength ranges of the light spectrum), plants may be detected by distinguishing biomass from the ground (earth). The row of plants may advantageously be identified, using at least one of the following information items: color portion, in particular, portion of the color green of the detected plants, infrared portion of the detected plants, plant spacing, spacing of plant rows, stage of growth of the plants, geographic coordinates of the seed of the plants,” par. 29).
Wu et al. and Seitz et al. are combined as per claim 16.
Claim 26
Regarding claim 26, Wu et al. and Seitz et al. disclose the method according to claim 16, further comprising: identifying rows of plants in the depth-variable image evaluation region or the image information using the identified plants in the image information by the control unit, (“the computing device … can plug into a larger, powerful, more centralized controller of the vehicle, where the centralized controller also manages or performs other machine tasks,” par. 47) wherein in the step of applying, the spray is also applied as a function of identified rows of plants (“the crop row is identified to perform nutrient (fertilizer) band spraying along the crop row. Using the captured images, the elements of the image first pass a calibrated color threshold (e.g. green). The rows are identified by either a local straight line fit to the pixel images where greenish-colored pixels line up,” par. 105).
Wu et al. and Seitz et al. are combined as per claim 16.
Claim 27
Regarding claim 27, Wu et al. teach a control unit, configured to: (“the computing device … can plug into a larger, powerful, more centralized controller of the vehicle, where the centralized controller also manages or performs other machine tasks,” par. 47) identify plants in an image evaluation region of an obtained item of image information of a detected field section of agricultural land with a depth in a direction of travel of an agricultural spraying device, wherein the image evaluation region represents a corresponding field evaluation region of the detected field section with a depth in the direction of travel of the spraying device; (“the crop row is identified to perform nutrient (fertilizer) band spraying along the crop row. Using the captured images, the elements of the image first pass a calibrated color threshold (e.g. green). The rows are identified by either a local straight line fit to the pixel images where greenish-colored pixels line up,” par. 105) output a control signal to at least one spray nozzle unit of the spraying device as a function of the plants identified in the image evaluation region to apply the spray onto the field evaluation region of the detected field section (“identification of weeds that triggers spray release from spray nozzles, where each nozzle is in communication with one or a few associated image sensor unit 50,” par. 53) (“spray the area when the spray vehicle reaches the weed location,” par. 99).
Wu et al. do not explicitly teach all of to select a variable depth of the image evaluation region as a function of a speed of the spraying device in the direction of travel.
However, Seitz et al. teach to select a variable depth of the image evaluation region as a function of a speed of the spraying device in the direction of travel (“In order to now increase the maximum traveling and/or operating speed, the present invention does not shorten length L(Field) of monitored field section 32, since, as explained above, it is supposed to be as large as possible for identifying rows of plants, but a new (smaller) evaluation portion 42 of monitored field section 32, having a length L(Evaluation), is specified and/or defined,” par. 58).
Wu et al. and Seitz et al. are combined as per claim 16.
Claim 28
Regarding claim 28, Wu et al. teach an agricultural spraying device for applying a spray onto agricultural land, comprising: at least one spray nozzle unit (“On a spray boom, two adjacent image sensor 1910 and 1912 or smartphone-electronics can serve to estimate stereo. Spray nozzles are often spaced 15 to 30 inches apart depending on the crop row spacing; adjacent image sensor (e.g. cameras) or smartphone-electronics are placed at least as far apart. For some of the applications, images from image sensor 1910 or smartphone-electronics symmetrically on either side of the boom may be used to determine an action,” par. 49) and a control unit configured to: identify plants in an image evaluation region of an obtained item of image information of a detected field section of agricultural land with a depth in the direction of travel of the spraying device, wherein the image evaluation region represents a corresponding field evaluation region of the detected field section with a depth in the direction of travel of the spraying device, output a control signal to the at least one spray nozzle unit as a function of the plants identified in the image evaluation region to apply the spray onto the field evaluation region of the detected field section, and select a variable depth of the image evaluation region as a function of a speed of the spraying device in the direction of travel as noted above in claim 27.
Wu et al. do not explicitly teach all of at least one optical detection unit, an optical axis of the optical detection unit having an angle of inclination greater than 00 relative to vertical in a direction of travel of the spraying device.
However, Seitz et al. teach at least one optical detection unit, (“a field section 32 monitored with the aid of camera 18, is desired and/or advantageous for identifying rows of plants,” par. 49) an optical axis of the optical detection unit having an angle of inclination greater than 00 relative to vertical in a direction of travel of the spraying device (“angle of inclination a is the angle between an optical axis 36 of camera 18 and a vertical line 38 in direction of travel 34 of spraying device,” par. 56).
Wu et al. and Seitz et al. are combined as per claim 16.
Claim 29
Regarding claim 29, Wu et al. disclose a non-transitory machine-readable storage medium on which is stored a computer program (“The bank of methods or procedures includes a set of electronic-software programs or algorithms that enable an end-user to add more monitoring or targeted procedures via a portal (e.g. screen or keyboard) to each of the local image sensor units,” par. 45) for applying a spray onto agricultural land using at least one spray nozzle unit of an agricultural spraying device, the computer program, when executed by a processor, causing the processor to perform the following steps: detecting a field section of the agricultural land using at least one optical detection unit to obtain image information on the field section with a depth in a direction of travel of the spraying device; identifying plants in an image evaluation region of the obtained image information using a control unit (“the computing device (external to but in communication with the image sensor units 50),” par. 47), wherein the image evaluation region represents a corresponding field evaluation region of the detected field section with a depth in the direction of travel of the spraying device; (“FIG. 6 depicts another embodiment method to find anomalies 11 from captured images for detecting and getting rid of or deterring anomalous objects 11 found among plants 10 along a crop row,” par. 102) applying the spray onto the field evaluation region of the detected field section using the spray nozzle unit of the agricultural spraying device (“On a spray boom, two adjacent image sensor 1910 and 1912 or smartphone-electronics can serve to estimate stereo. Spray nozzles are often spaced 15 to 30 inches apart depending on the crop row spacing; adjacent image sensor (e.g. cameras) or smartphone-electronics are placed at least as far apart. For some of the applications, images from image sensor 1910 or smartphone-electronics symmetrically on either side of the boom may be used to determine an action,” par. 49) as a function of the plants identified in the image evaluation region; and (“identification of weeds that triggers spray release from spray nozzles, where each nozzle is in communication with one or a few associated image sensor unit 50,” par. 53) (“spray the area when the spray vehicle reaches the weed location,” par. 99).
Wu et al. do not explicitly teach all of selecting a variable depth of the image evaluation region using the control unit.
However, Seitz et al. teach selecting a variable depth of the image evaluation region (“In order to now increase the maximum traveling and/or operating speed, the present invention does not shorten length L(Field) of monitored field section 32, since, as explained above, it is supposed to be as large as possible for identifying rows of plants, but a new (smaller) evaluation portion 42 of monitored field section 32, having a length L(Evaluation), is specified and/or defined,” par. 58) using the control unit (“Control unit 28 includes a processing unit 30, which is configured to execute computational steps and/or image processing steps for carrying out the method of the present invention,” par. 55).
Wu et al. and Seitz et al. are combined as per claim 16.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Karsten F. Lantz whose telephone number is (571)272-4564. The examiner can normally be reached Monday-Friday 8:00-4:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ms. Jennifer Mehmood can be reached on 571-272-2976. 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.
/Karsten F. Lantz/Examiner, Art Unit 2664
Date: 5/4/2026
/JENNIFER MEHMOOD/Supervisory Patent Examiner, Art Unit 2664
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