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 .
Status of Claims
This action is responsive to Applicant’s amendment and remarks filed 07/22/2026. Claims 1, 2, 7, 8, 9, 11, 14 and 17 have been amended. Claims 1–20 are pending and have been examined.
Response to Arguments
I. Withdrawn Rejection – 35 U.S.C. § 101
The rejection of claims 1–20 under 35 U.S.C. § 101 as directed to a judicial exception without significantly more is withdrawn in view of Applicant’s amendment. The eligibility of the amended claims has been reevaluated under the framework set forth in MPEP § 2106, as follows.
Step 1. Claims 1–13 are directed to a process (method), and claims 14–20 are directed to a machine (system). Each claim falls within a statutory category of invention.
Step 2A, Prong One. Independent claims 1, 11 and 14 continue to recite a judicial exception. Claim 1 recites “calculating navigation space coordinates of points associated with the crop rows by combining the position and orientation of the agricultural vehicle with the locations associated with the crop rows” and “generating guidance data … comprising an original guidance line and a series of georeferenced offset values between the original guidance line and the calculated navigation space coordinates of the crop rows.” Claims 11 and 14 recite substantially similar subject matter. These limitations describe mathematical calculations, which fall within the mathematical-concepts grouping of abstract ideas. See MPEP § 2106.04(a)(2)(I).
Step 2A, Prong Two. The amended independent claims integrate the recited judicial exception into a practical application. See MPEP § 2106.04(d). As amended, each independent claim requires that the result of the calculation control a physical machine in a specific manner:
Claim 1: “automatically steering an agricultural vehicle during the subsequent agricultural operation, using an automatic steering system, along the original guidance line as adjusted by the series of georeferenced offset values.”
Claim 11: “automatically guiding a second agricultural vehicle, using an automatic steering system, along the original guidance line as adjusted by the series of georeferenced offset values,” during a second agricultural operation performed during a post-canopy growth stage.
Claim 14: “an automatic steering system configured to automatically steer an agricultural vehicle during a subsequent agricultural operation along the original guidance line as adjusted by the series of offset values.”
These limitations do not merely link the calculation to a technological environment or instruct that it be “applied.” See MPEP § 2106.05(f), (h). The calculated offset values define the specific path along which the automatic steering system steers the vehicle: the original guidance line, adjusted at each location by the corresponding offset value. The claims therefore use the mathematical result to control the operation of a physical machine in a particular way, which is a meaningful limitation beyond the exception itself. See MPEP § 2106.05(e); cf. Diamond v. Diehr, 450 U.S. 175, 187 (1981). The automatic steering system, the positioning sensor and the crop detection sensor mounted on the agricultural vehicle are integral to the claimed operation rather than a generic computing environment. See MPEP § 2106.05(b). The claimed arrangement also reflects the improvement described in the specification: reliable automatic steering between crop rows during later operations, including post-canopy operations, when visual identification of the rows is difficult. See Spec. [0008]–[0009], [0031]; MPEP § 2106.05(a).
Considered as a whole, each of independent claims 1, 11 and 14 integrates the recited judicial exception into a practical application and is therefore not directed to a judicial exception. Analysis under Step 2B is not required. Claims 2–10, 12, 13 and 15–20 depend from claim 1, 11 or 14, include all the limitations of their respective parent claims, including the automatic-steering limitation, and are eligible for the same reasons. Accordingly, the rejection of claims 1–20 under 35 U.S.C. § 101 is withdrawn.
II. Rejections under 35 U.S.C. § 103
Applicant’s arguments regarding the rejections under 35 U.S.C. § 103 have been fully considered but are not persuasive. The present rejections rely on Maeder, Susko, Mas and Han, with their application to the amended claims explained in the rejections below and in this response.
A. The stored original-line-plus-offset arrangement and its reuse in a later operation
Applicant argues that the cited references do not disclose an original guidance line stored together with a series of georeferenced offset values and reused to automatically steer a later operation.
The Examiner agrees that no single applied reference expressly discloses that complete arrangement. The rejection relies instead on a modification of the combined teachings, made for the following reasons drawn from the references.
Maeder retains the guidance line followed during the initial operation, which Maeder calls the original guidance line (Maeder [0047]–[0048], [0066], [0074]). Maeder treats that line as the reference against which the actual crop rows deviate, stating that “crop row locations may not be evenly distributed around the original guidance line” (Maeder [0074]).
Maeder identifies causes of that deviation, including drift on curves, slopes and uneven implement loading, so the deviation varies along the row (Maeder [0029]). Maeder also recognizes that “utilizing the same original guidance lines in the subsequent operation fails to account for the actual crop row locations” (Maeder [0032]).
Maeder stores data gathered in one operation and reuses it to guide later operations, so that the guidance system can “anticipate upcoming changes … in crop row locations, rather than relying upon … a sensor” (Maeder [0033], [0034], [0051]).
Han supplies the technique of revising preliminary guidance data using vision-derived crop-row information, determining “the offset of the crop row relative to a reference row position” and adjusting the preliminary guidance data accordingly to control the steering system (Han [0045], [0057], [0100]). Han’s reference is a planted row position, not Maeder’s vehicle guidance line, and the rejection does not equate the two.
Mas teaches obtaining metric coordinates of points sensed by a vehicle-mounted stereo camera (Mas [0189]), transforming them into global coordinates using the camera position and orientation (Mas [0178]), and associating sensed data with specific geographic locations (Mas [0079]).
In the proposed combination, the offsets are calculated as the differences between the globally located crop-row points and the corresponding positions on Maeder’s original guidance line. They are stored with their geographic associations together with the original guidance line, retrieved in the subsequent operation, and applied to the original guidance line to steer the vehicle using Han’s guidance-revision technique. That storage and later application constitute the proposed modification; neither Maeder nor Han expressly discloses it. One of ordinary skill in the art would have had reason to make the modification for the following reasons:
Maeder already retains the original guidance line and evaluates the crop rows against it.
Maeder teaches that the departures of the rows vary along the field and that the original line alone does not account for the actual rows.
Maeder teaches preparing later-operation guidance from stored earlier data.
Han teaches that a reference path may be revised by measured row information to control steering.
Retaining the original guidance line and recording the location-indexed departures preserves, in the combination, both the common reference line and the measured corrections at the locations where they apply. These are the inputs from which later operations, including operations using implements of different widths (see Maeder [0032], [0067]–[0071]), can be guided. The result is the predictable use of known techniques according to their established functions. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 416–17 (2007); MPEP 2143.
Applicant’s identification of the absence of an express disclosure of the complete arrangement has been considered. The rejection rests on the combined teachings and the articulated reasons for the proposed modification explained above, rather than on an assertion that any individual reference expressly discloses the complete arrangement.
B. Susko, Mas and Han as single-pass systems
Applicant argues that Susko, Mas and Han each operate within a single pass and retain no guidance data for a separate later operation. The Examiner does not rely on Susko, Mas or Han for storage and reuse across operations. Maeder supplies that teaching (Maeder [0033], [0051], [0095]). The secondary references are relied on for crop-row detection (Susko), spatial and geographic registration of the sensed rows (Mas), and the technique of revising guidance by measured row information (Han).
Applicant also argues that Susko expresses cross-track error in image pixels. In the combination, the metric positions of the detected rows are obtained from Mas’s stereo disparity and camera calibration (Mas [0189]) and transformed into navigation coordinates using the camera pose (Mas [0178]), as set forth in the rejections of claims 1, 5, 14 and 20.
C. Claim 11
Applicant argues that the combination does not teach generating guidance data during a pre-canopy operation and retrieving it to automatically steer a post-canopy operation. These limitations are addressed in the rejection of claim 11. Susko teaches camera row guidance in “crop growth stages where the cyclical row pattern is visible” (Susko [0013]), and Mas separates crop rows “from the background or Soil” (Mas [0257]). One of ordinary skill would therefore have performed the detection pass early, while soil remains visible between the rows. That person would also have reused the stored guidance in a later operation after the canopy has developed, when real-time row detection is least reliable. This is consistent with Maeder’s teaching of anticipating row locations from stored data rather than relying on a sensor (Maeder [0034]).
Applicant further characterizes claim 11 as steering the later operation without detecting the crop rows during that later operation. Claim 11 requires retrieving the guidance data and automatically guiding the second vehicle along the original guidance line as adjusted by the series of georeferenced offset values. It does not exclude sensing during the second operation. Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. In re Van Geuns, 988 F.2d 1181, 1184 (Fed. Cir. 1993).
D. Motivation to combine and alleged teaching away
Applicant argues that the stated motivation was to add Susko’s real-time detection to obtain crop-row information during operation, and that Maeder [0030] and [0034] teach away from that modification.
First, Applicant mischaracterizes the motivation. The prior Office action stated that “[m]apping sensed crop-row points into the navigation frame used by the stored field map would predictably improve alignment of later guidance paths with actual rows.” The present rejection likewise uses the crop detection sensor during the earlier, data-gathering operation to produce stored guidance data, and steers the subsequent operation from that stored data.
Second, the proposed combination keeps Maeder’s map-based approach rather than replacing it. Maeder [0030] states that conventional systems “attempt to sense locations of crop rows as they operate” and that “such real-time sensing is insufficient to avoid crop damage, and fails to reliably address unique crop row locations.” The proposed combination does not substitute contemporaneous sensing for Maeder’s stored map during the subsequent operation. The sensor is used to build the stored data, as Maeder itself builds its field maps from sensor and location data gathered during an earlier operation (Maeder [0033], [0041]). The subsequent operation is then guided from the stored data, which is the advantage Maeder describes in [0034]. Maeder does not criticize, discredit or otherwise discourage using a crop detection sensor to produce the stored map. See In re Fulton, 391 F.3d 1195, 1201 (Fed. Cir. 2004); MPEP 2141.02(VI), 2145(X)(D)(1).
Third, one of ordinary skill would have had a reasonable expectation of success. Susko teaches locating crop-row centers and determining vehicle-relative heading and cross-track information (Susko [0072], [0081]), and describes its approach as “largely impervious to row imperfections and variance in weeds” (Susko [0013]). Mas teaches obtaining calibrated three-dimensional coordinates of sensed points and registering them in a global frame (Mas [0178], [0189]), and states that three-dimensional imagery provides information “with far greater reliability than two-dimensional images” (Mas [0239]).
E. Hindsight
Applicant argues that the combination reflects hindsight reconstruction. Any judgment on obviousness is in a sense necessarily a reconstruction based on hindsight reasoning, but it is proper so long as it takes into account only knowledge within the level of ordinary skill at the time of the claimed invention and does not include knowledge gleaned only from Applicant’s disclosure. In re McLaughlin, 443 F.2d 1392, 1395 (CCPA 1971). Each element of the reasoning above is drawn from the applied references: retaining the original line and recognizing that the row departures vary (Maeder [0029], [0032], [0074]); storing and reusing data across operations (Maeder [0033], [0034], [0051]); revising guidance by measured row information (Han [0057], [0100]); and spatial and geographic registration of the sensed rows (Mas [0079], [0178], [0189]).
F. Dependent claims
Applicant presents no separate argument identifying a particular dependent limitation that overcomes its rejection. The dependent claims remain rejected for the claim-specific reasons set forth in the rejections below.
G. Art made of record but not relied upon
Keller (US 6,553,299) and Dickson (US 6,385,515) are not relied upon in any rejection, so Applicant’s arguments regarding those documents do not bear on the rejections of record.
Claim Interpretation
The terms “pre-canopy growth stage” and “post-canopy growth stage” are given their broadest reasonable interpretation consistent with the specification. The specification describes the pre-canopy stage as the early-season stage in which the lanes between the crop rows remain visible (Spec. [0008], “early season corn (i.e. pre-canopy)”; Spec. [0093], “early in the season (i.e. before canopy)”), and describes the post-canopy stage as the later stage after the crop has canopied and “the ground is no longer visible between rows” (Spec. [0008]), giving spraying and harvest as examples (Spec. [0009]). The specification is relied on only to construe these terms; the prior-art findings regarding the growth stages are set forth in the rejections below. As used herein, “Spec.” refers to the specification of the instant application (US 2025/0306601 A1).
Claim Objections
Claim 3 is objected to because of the following informality: claim 3 recites “the later growth state,” which appears to be a typographical error for “the later growth stage” recited in claim 2. The claim is examined as reciting “the later growth stage.” Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claims 6, 8 and 12 are rejected under 35 U.S.C. 112(d) as being of improper dependent form for failing to further limit the subject matter of the claim upon which they depend.
Claim 6 recites “using the guidance data in the subsequent agricultural operation.” Claim 1, as amended, already requires “automatically steering an agricultural vehicle during the subsequent agricultural operation, using an automatic steering system, along the original guidance line as adjusted by the series of georeferenced offset values,” the original guidance line and the series of georeferenced offset values being the guidance data. Claim 6 therefore specifies no further limitation of the subject matter of claim 1.
Claim 8 recites that “the series of georeferenced offset values are to be applied to the original guidance line during the subsequent agricultural operation.” Claim 1, incorporated into claim 8 through claim 7, already requires steering during the subsequent agricultural operation along the original guidance line as adjusted by the series of georeferenced offset values. Claim 8 therefore specifies no further limitation of the subject matter of claim 7.
Claim 12 recites that “the first agricultural operation is performed during a pre-canopy growth stage when soil is visible between crop rows; and the second agricultural operation is performed during a post-canopy growth stage.” Claim 11, as amended, already recites “the first agricultural operation being performed during a pre-canopy growth stage when soil is visible between crop rows” and “the second agricultural operation being performed during a post-canopy growth stage.” Claim 12 therefore specifies no further limitation of the subject matter of claim 11.
Applicant may cancel the claims, amend the claims to place them in proper dependent form, rewrite the claims in independent form, or present a sufficient showing that the dependent claims comply with the statutory requirements.
Claim Rejections – 35 U.S.C. § 103
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; and (4) considering objective evidence present in the application indicating obviousness or nonobviousness. Graham v. John Deere Co., 383 U.S. 1 (1966).
Claims 1–20 are rejected under 35 U.S.C. 103 as being unpatentable over Maeder et al. (US 2020/0352082 A1) (hereinafter “Maeder”) in view of Susko et al. (US 2022/0377962 A1) (hereinafter “Susko”), Mas et al. (US 2004/0264763 A1) (hereinafter “Mas”), and Han et al. (US 2008/0065287 A1) (hereinafter “Han”).
Regarding Claim 1,
Disclosure by Maeder
Maeder teaches:
A method for generating agricultural guidance data,
See at least:
“Example methods, apparatus, systems, and articles of manufacture (e.g., physical storage media) disclosed herein generate guidance lines for automatic execution of subsequent operations on a field based on field maps determined during previous operations.” ([0033])
Rationale:
Express. Maeder describes methods that generate guidance lines, i.e., agricultural guidance data, for automatic execution of later field operations. The guidance lines are generated from field maps of an agricultural field, so the method is one for generating agricultural guidance data.
the method comprising:
See at least:
“Example machine readable instructions 800 that may be executed by the controller 116 to perform an operation on a field using a field map are illustrated in FIG. 8.” ([0092])
Rationale:
Express. Maeder sets out its method as a sequence of machine-executed steps (FIG. 8, blocks 802-822). The flowchart is an open-ended series of steps that the “comprising” transition reads on.
during a primary agricultural operation,
See at least:
“At block 806, the example controller 116 generates a field map during a first operation.” ([0094])
Rationale:
Express. Maeder collects the vehicle data and generates the field map while the vehicle is performing a first field operation (e.g., planting, tilling or fertilizing, [0027], [0047]). That first operation is a primary agricultural operation during which the vehicle data are gathered.
determining a position and orientation of an agricultural vehicle in a field
See at least:
“the location data analyzer 204 receives GPS data and inertial data from the location sensor 114, and analyzes the GPS data and inertial data to determine precise locations of the vehicle 102 and/or the implement 108.” ([0046])
Rationale:
Express as to position; implicit as to orientation. Maeder determines precise vehicle locations from GPS and inertial data. The inertial data compensate for vehicle tilt ([0040]), and extrapolating implement-row positions across the implement width ([0064]) requires the vehicle heading. A PHOSITA would therefore understand Maeder’s GPS/inertial solution to supply both the position and the orientation (pose) of the vehicle in the field.
using at least one positioning sensor;
See at least:
“The location sensor 114 of the illustrated example is a global positioning system (GPS) sensor combined with an inertial sensor.” ([0040])
Rationale:
Express. The GPS sensor combined with an inertial sensor is at least one positioning sensor.
determining actual locations of crop rows in the field
See at least:
“The crop row lines 404 accurately illustrate locations of crop rows on the field. For example, the crop row lines 404 can accurately represent crop row locations based on location data determined directly on the implement, therefore accounting for potential implement drift during the operation.” ([0066])
Rationale:
Express. Maeder determines crop-row locations that “accurately illustrate locations of crop rows on the field” and that account for implement drift, i.e., the actual rather than the planned row locations (contrast [0029], which explains that planned and actual row locations differ).
calculating navigation space coordinates of points associated with the crop rows
See at least:
“the field map generated by the field map generator 206 can indicate (a) precise locations (e.g., accounting for displacements in all three-axes) of the vehicle's guidance line that was followed during an initial operation, (b) precise locations of portions of the implement 108 corresponding to crop rows” ([0048])
Rationale:
Express. Maeder computes precise three-axis locations of points corresponding to the crop rows and records them in the field map in the global (GPS) frame used for navigation. These are navigation space coordinates of points associated with the crop rows.
by combining the position and orientation of the agricultural vehicle
See at least:
“For example, if the vehicle 102 is tilted on a hill, the inertial sensor can compensate for this tilt to enable accurate determination of a location of the vehicle 102, and more specifically, accurate determination of locations of portions of the implement 108.” ([0040])
Rationale:
Express. Maeder computes the row-related point locations from both the GPS position and the inertial (attitude) data of the vehicle. Locating a ground point offset from the sensor requires both the position and the orientation of the vehicle, so Maeder’s calculation combines the position and orientation of the agricultural vehicle. The vehicle-relative row locations with which the pose is combined are addressed under limitation 12 below.
generating guidance data
See at least:
“The controller 116 of the illustrated example generates field maps and utilizes such field maps to automatically generate guidance lines based on the field maps and the type of implement in use by the vehicle 102.” ([0041])
Rationale:
Express. Controller 116 automatically generates guidance lines, which are guidance data.
based on the calculated navigation space coordinates,
See at least:
“At block 812, the example controller 116 determines guidance line(s) based on crop row locations” ([0097])
Rationale:
Express. The guidance lines are determined from the crop-row locations, which are the calculated row coordinates stored in the field map (limitation 10 above).
the guidance data comprising an original guidance line
See at least:
“The field map generator 206 of the illustrated example stores (a) location data including the guidance line which the vehicle 102 followed while performing the initial operation (e.g., planting, tilling, etc.).” ([0047])
Rationale:
Express. Maeder stores, as part of the field map, the guidance line the vehicle followed during the initial operation, which Maeder calls the “original guidance line” ([0066], [0074]). The guidance data therefore comprise an original guidance line.
between the original guidance line and the calculated navigation space coordinates of the crop rows;
See at least:
“For example, due to drift of the implement, crop row locations may not be evenly distributed around the original guidance line. In some such examples, when a subsequent operation is performed, the guidance lines may be generated in different locations than the original guidance lines to better target the actual locations of the crop rows.” ([0074])
Rationale:
Express as to the relationship; obvious as to its numerical expression. Maeder expressly recognizes the lateral deviation between the original guidance line and the actual crop rows (“crop row locations may not be evenly distributed around the original guidance line”) and uses that deviation to place later guidance lines. That deviation is the difference between the original guidance line and the calculated row coordinates. Computing it as numerical values from the two stored coordinate sets is ordinary coordinate arithmetic with a predictable result.
storing the guidance data
See at least:
“The field map generator 206 stores the field map in the map data store 208 and/or another location accessible to the controller 116.” ([0049])
Rationale:
Express. The field map, including the guidance line and row locations, is stored in map data store 208.
for use in a subsequent agricultural operation; and
See at least:
“The map data store 208 of the illustrated example of FIG. 2 stores field maps, which can be subsequently accessed to enable automated operation of the vehicle 102 (e.g., via generation and utilization of accurate, crop row specific guidance lines).” ([0051])
Rationale:
Express. The stored maps are accessed later to enable automated operation and to generate crop-row-specific guidance lines for subsequent operations.
automatically steering an agricultural vehicle
See at least:
“In some examples, the drive commander 222 may operate autonomously (e.g., cause the vehicle 102 to automatically follow guidance lines generated by the guidance line generator 218)” ([0059])
Rationale:
Express. The drive commander operates autonomously to cause the vehicle to automatically follow guidance lines, i.e., automatically steering an agricultural vehicle.
during the subsequent agricultural operation,
See at least:
“the vehicle 102 is operating in an automated mode, automatically generating and following guidance lines and performing operations with the implement 108 based on existing field maps.” ([0087])
Rationale:
Express. The automated guidance is performed “based on existing field maps”, i.e., during a subsequent operation that uses the data stored from the earlier operation.
using an automatic steering system,
See at least:
“the controller 116 can issue commands to the drive controller 118 for the vehicle 102 to move according to a guidance line generated by the controller 116. In such examples, the drive controller 118 responds to these commands and causes movement of the vehicle 102 (e.g., movement of the wheels, steering adjustments, etc.).” ([0042])
Rationale:
Express. Drive controller 118 responds to guidance-line commands by “steering adjustments”, which is an automatic steering system.
along the original guidance line
See at least:
“While the guidance lines 510 of the illustrated example substantially overlap the original guidance lines 406” ([0074])
Rationale:
Express as to retaining the original guidance line and guiding the later operation from the mapped crop-row locations; the claimed adjustment is supplied by the proposed modification. Maeder retains the original guidance line and generates the subsequent-operation guidance from the mapped crop-row locations; the later guidance lines may “substantially overlap the original guidance lines 406” or may be generated “in different locations than the original guidance lines” ([0074]). Maeder does not expressly disclose steering along the retained original guidance line as adjusted by a stored offset series. The phrase “along the original guidance line” is treated together with the following phrase “as adjusted by the series of georeferenced offset values” as one functional relationship, which is supplied by the proposed modification of the combined teachings addressed under limitation 24 below.
Claim Limitations Not Explicitly Disclosed by Maeder
Maeder does not explicitly teach the following claim limitations:
relative to the agricultural vehicle
using at least one crop detection sensor
mounted on the agricultural vehicle;
with the locations associated with the crop rows in the field relative to the agricultural vehicle;
and a series of georeferenced offset values
as adjusted by the series of georeferenced offset values.
Disclosure by Susko
Susko teaches:
relative to the agricultural vehicle
See at least:
“FIG. 8 also shows step 308 including sub-step 812, which includes estimating, by the processor, a heading error and a cross track at a selected look ahead distance of the agricultural vehicle based on the fit.” ([0081])
Rationale:
Express. Susko determines the located crop rows relative to the vehicle: the heading error and cross track are measured “of the agricultural vehicle” with respect to the crop-row centers located in the image of a camera fixed to the vehicle ([0072], [0082]). In the combination, the actual crop-row locations of limitation 6 are therefore determined relative to the agricultural vehicle by the vehicle-mounted crop detection sensor.
using at least one crop detection sensor
See at least:
“the processor is configured to operate with the camera to implement a monocular computer vision system to determine an attribute of a crop row according to a signal processing filter.” ([0042])
Rationale:
Express. Susko’s camera operates with the processor as a computer vision system that determines an attribute of a crop row (its center line). A sensor whose output is used to locate crop rows is a crop detection sensor.
mounted on the agricultural vehicle;
See at least:
“Method 300 starts with step 302, which includes capturing images of a crop row, one image at a time, by a camera attached to a part of an agricultural vehicle, an implement attached to the agricultural vehicle, or a boom attached to the agricultural vehicle” ([0066])
Rationale:
Express. The crop-row camera is attached to a part of the agricultural vehicle, i.e., mounted on the agricultural vehicle.
Motivation to Combine Maeder and Susko
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder and Susko before them, to determine the actual crop-row locations in Maeder’s method, relative to the vehicle, with Susko’s vehicle-mounted crop-row camera instead of inferring them only from implement position. Maeder’s objective is guidance that targets “the actual locations of the crop rows” ([0074]), but Maeder infers those locations indirectly from where the implement was ([0064]). Susko teaches directly sensing crop-row centers with an inexpensive monocular camera attached to the vehicle ([0042], [0066]). Sensing the rows themselves removes the error left by implement-position inference and allows the method to be used on fields not planted with Maeder’s instrumented planter. Both references are directed to automatic row-crop guidance with compatible vehicle controllers (Susko [0041]), so the substitution is the use of a known sensor for its established function with predictable results (KSR), and it improves the accuracy and reliability of the stored row locations.
Claim Limitations Not Explicitly Disclosed by the Combination of Maeder and Susko
After combining the teachings of Maeder and Susko, the following claim limitations are not explicitly disclosed:
with the locations associated with the crop rows in the field relative to the agricultural vehicle;
and a series of georeferenced offset values
as adjusted by the series of georeferenced offset values.
Disclosure by Mas
Mas teaches:
with the locations associated with the crop rows in the field relative to the agricultural vehicle;
See at least:
“After the camera's center of coordinates has been converted to a global frame, coordinates of any point sensed in an image can be referred to a global frame. To do so, a transformation can be made between camera coordinates (centered at the left frame) and global coordinates (East, North) for the sensed points in the images captured by the camera.” ([0178])
“The camera calibration information is then retrieved (step 86) and used with the disparity image to produce the camera coordinates (step 88) for sensed points found in the images.” ([0189])
Rationale:
Express as to the transformation; obvious as to its application to the detected rows. In the combination, the crop detection camera is implemented as Mas’s stereo camera, rigidly mounted on the vehicle ([0119]), with Susko’s row-center processing applied to one channel of the stereo pair (Mas references its camera coordinates to the left frame, [0178]). Mas obtains spatial (metric) camera coordinates for each sensed point from the disparity image and the camera calibration ([0189]); a monocular image alone does not supply that distance. Mas then transforms those camera coordinates into global (East, North) coordinates using the camera’s global position and its yaw angle ([0178]): N = N_n + X_c·sinΘ + Y_c·cosΘ and E = E_n + X_c·cosΘ − Y_c·sinΘ. Because the camera is rigidly mounted at a known location on the vehicle, its position and yaw are the vehicle position and orientation offset by a fixed mounting transform, the same known-offset principle Maeder applies to its location sensor ([0064]). In the combination, the transformed points are the camera-detected row locations relative to the vehicle (limitation 7), so Mas’s transformation combines the vehicle position and orientation (limitations 10-11) with those locations to calculate the navigation space coordinates of the row points. Two paragraphs are cited because the limitation requires both the vehicle-relative spatial locations ([0189]) and their combination with the pose ([0178])
and a series of georeferenced offset values
See at least:
“The location tracking device 18 is configured for providing geographic location information of the camera 12 So that the coordinate array information can be mapped to Specific geographic locations.” ([0079])
Rationale:
Express as to georeferencing; the series of offsets is the proposed modification. Mas ties sensed coordinate data to “Specific geographic locations.” In the combination, the camera-detected row points are located at successive positions along the rows ([0178]), and Maeder measures row deviation against the original guidance line (limitation 17). Recording the deviation at each successive georeferenced row point yields a series of offset values, each associated with its field position, i.e., a series of georeferenced offset values. No reference expressly discloses storing such a series; the limitation is met by the articulated modification. The reason a PHOSITA would choose this representation, rather than storing only a newly computed corrected line, comes from Maeder itself. Maeder keeps the original guidance line as the reference about which row deviation is assessed ([0074]). Maeder explains that the original line alone is inadequate, because “utilizing the same original guidance lines in the subsequent operation fails to account for the actual crop row locations” ([0032]). Maeder also explains that the deviation arises from drift on curves, slopes and uneven implement loads ([0029]), so it varies along the row. Retaining the unchanged original line as the common reference and recording the spatially varying departures from it, each tied to its field position, gives later operations, including those using implements of different widths ([0032], [0067]-[0071]), the reference line and the measured corrections from which to build their own guidance.
Motivation to Combine Maeder, Susko, and Mas
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, and Mas before them, to (1) convert Susko’s vehicle-relative row detections into navigation space coordinates by combining them with the vehicle position and orientation, as Mas teaches for points sensed by a vehicle-carried camera ([0178], [0221]), and (2) record the departure of those georeferenced row points from Maeder’s original guidance line as a series of offset values tied to geographic locations (Mas [0079]). Maeder stores its rows and guidance line in a global (GPS) field map ([0048]), so camera-relative detections must be transformed into that frame before they can be compared with the original line, stored or reused; Mas supplies the known transformation ([0178]) and the stereo disparity and calibration processing that yield the spatial camera coordinates the transformation needs ([0189]). A PHOSITA would implement the crop detection camera as Mas’s stereo camera for that reason and because Mas teaches that three-dimensional imagery provides information “with far greater reliability than two-dimensional images” ([0239]). Susko’s row-center processing operates on a single image, so it is applied to one channel of Mas’s stereo pair (Mas references its camera coordinates to the left frame, [0178]), while Mas’s paired-image disparity processing supplies the spatial coordinates of the points Susko identifies. Susko prefers a monocular camera to limit cost and processing load ([0005], [0012], “some embodiments ... using a mono (non-stereo) camera”). The combination accepts the added stereo processing because it yields metric, geographically registered row measurements that can be stored and reused in later operations, which a single image without depth does not provide. Weighing that known cost-versus-capability tradeoff is an ordinary design choice; Susko does not criticize or discourage stereo cameras. Maeder keeps the original line as the reference for assessing row deviation ([0074]), teaches that the original line alone “fails to account for the actual crop row locations” ([0032]), and identifies causes of deviation that vary along the row ([0029]). Recording the departures from the retained original line at their georeferenced positions is therefore a predictable way to preserve both the reference line and the spatially varying corrections for reuse at the corresponding place in the field. This improves the accuracy with which later operations, including those with different implement widths ([0032]), can be guided.
Claim Limitations Not Explicitly Disclosed by the Combination of Maeder, Susko, and Mas
After combining the teachings of Maeder, Susko, and Mas, the following claim limitations are not explicitly disclosed:
as adjusted by the series of georeferenced offset values.
Disclosure by Han
Han teaches:
as adjusted by the series of georeferenced offset values.
See at least:
“The observed intensity profile (e.g., of FIG. 10) is compared to a reference intensity profile, called a template (e.g., FIG. 11 or FIG. 12), to determine the offset of the crop row relative to a reference row position. The reference row position may be established when the crop, a seed, or precursor was planted, for instance.” ([0100])
“In step S206, an adjuster 110 or vehicle controller 25 adjusts the preliminary guidance data (e.g. preliminary location data) to a revised guidance data (e.g., revised location data) based on the vision guidance data (e.g., vision-derived location data)” ([0057])
Rationale:
Express as to adjusting a reference path by a measured row offset; PHOSITA-obvious as to the claimed arrangement. Han determines “the offset of the crop row relative to a reference row position” that may be established at planting ([0100]). Han keeps the preliminary (reference) guidance data and adjusts it by the vision-derived correction to obtain revised guidance data ([0057]), which controls the steering system ([0045]). Han’s reference is a planted row position, not the vehicle’s path, and the mapping does not equate the two. In the combination, the offsets are computed directly in the global frame, as the difference between each georeferenced row point (Mas [0178]) and the corresponding point of Maeder’s original guidance line (limitation 17). Each offset value therefore includes both the nominal row spacing from the line and any drift-induced displacement; the claim does not require separating them. Han is relied on for the known technique of adjusting a reference path by a measured row offset to steer the vehicle. Han measures and applies its correction within a single pass; Han permits application to lag measurement ([0059]) but does not teach storing the correction for a different operation. Carrying the stored offset series from the earlier operation into the subsequent operation and applying it there to the original guidance line is the proposed modification. It is supplied by Maeder’s teaching of storing data in one operation and reusing it to guide a later operation ([0033], [0051]), as explained in the motivation below. Two paragraphs are cited because the limitation recites both the offset relationship and its application.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to automatically steer the subsequent-operation vehicle along Maeder’s stored original guidance line as adjusted by the stored series of georeferenced offset values. Han teaches implementing row guidance by retaining a reference path ([0027]) and adjusting it by the measured offset of the actual crop row ([0057], [0100]) to control the steering system ([0045]). Han’s offsets are measured and applied within one pass. Maeder, however, teaches preparing guidance for a later operation from data gathered in an earlier operation, so that the system can “anticipate upcoming changes ... in crop row locations, rather than relying upon ... a sensor” ([0034]), and storing that data for later automated operation ([0051]). A PHOSITA would therefore apply Han’s known correction technique to the offsets stored in the earlier operation: the subsequent vehicle follows the retained original line, corrected at each field position by the stored offset for that position. This achieves Maeder’s stated goal without real-time row sensing in the later operation, keeps Han’s known correction structure, and uses each element for its established function. The result is predictable and improves guidance accuracy and reliability (KSR).
Regarding Claim 2,
The combination of Maeder, Susko, Mas, and Han establishes the method of Claim 1, which is the basis for Claim 2.
Disclosure by Maeder
Maeder teaches:
wherein the subsequent agricultural operation
See at least:
“Most operations are subsequent operations performed on a field (e.g., most operations are performed on existing crops that are planted in the field).” ([0028])
Rationale:
Express. Maeder’s subsequent operations are performed on existing crops already planted in the field, i.e., the subsequent agricultural operation of claim 1.
is performed at a later growth stage of the crops.
See at least:
“As an example, a planter implement may plant crops at the beginning of a season. A sprayer implement may subsequently spray the crops, and/or a fertilizer implement may subsequently fertilize the crops.” ([0027])
Rationale:
Express. Crops are planted “at the beginning of a season” and the sprayer or fertilizer operations are performed “subsequently” on those crops, i.e., after the crops have grown, at a later growth stage.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to perform the subsequent, offset-guided operation of the claim 1 combination at a later growth stage of the crops, as Maeder expressly schedules spraying and fertilizing after planting ([0027]). The stored guidance exists precisely so that it can be reused later in the season ([0033], [0051]). Using it at a later growth stage is the predictable use of the combination for its intended purpose and avoids re-mapping the field.
Regarding Claim 3,
The combination of Maeder, Susko, Mas, and Han establishes the method of Claim 2, which is the basis for Claim 3.
Disclosure by Maeder
Maeder teaches:
wherein the primary agricultural operation
See at least:
“At block 806, the example controller 116 generates a field map during a first operation.” ([0094])
Rationale:
Express. Maeder’s first operation on the field, during which the data are gathered, is the primary agricultural operation of claim 1.
is performed during a pre-canopy growth stage
See at least:
“In some examples, a planting operation, a strip/till operation, or a fertilizer operation may be performed first, followed by a spraying operation, a harvesting operation (e.g., a combine or forage harvester), a side/top dress fertilizing operation, or any other field operation.” ([0027])
Rationale:
Express as to an early-season first operation; obvious as to its growth stage. Maeder performs planting, strip/till or fertilizer operations first, early in the season, before later spraying and harvesting. In the parent combination, the data-gathering pass uses a camera, and Susko teaches that camera row guidance is used at “crop growth stages where the cyclical row pattern is visible” ([0013]); Mas separates crop rows from visible soil ([0257]). Performing the primary (data-gathering) operation early, while the crop is small and the rows are visible, i.e., during the pre-canopy stage, is therefore an obvious selection of a known operating condition with the predictable result of reliable detection. As to claim meaning, the specification uses “pre-canopy” for the early-season stage before the crop canopy closes (Spec. [0008], “early season corn (i.e. pre-canopy)”; Spec. [0093], “early in the season (i.e. before canopy)”). The specification is relied on only to construe the term, not as evidence of what the prior art teaches.
and wherein the later growth state
See at least:
“As an example, a planter implement may plant crops at the beginning of a season. A sprayer implement may subsequently spray the crops, and/or a fertilizer implement may subsequently fertilize the crops.” ([0027])
Rationale:
Express. The subsequent spraying or fertilizing occurs after planting, at a later growth state of the crops. “The later growth state” is read as referring to the “later growth stage” of claim 2, its only possible antecedent.
is a post-canopy growth stage.
See at least:
“Additionally, some crops, such as corn, require highly precise positioning of the implement (e.g., a harvesting head, a platform for small grain harvesting, etc.) during harvesting.” ([0034])
Rationale:
Express as to a later harvesting operation; obvious as to its growth stage. Maeder’s later operations include spraying, side/top-dress fertilizing and harvesting ([0027]), and Maeder specifically addresses harvesting corn. Susko’s restriction of camera guidance to “crop growth stages where the cyclical row pattern is visible” ([0013]) recognizes that at later growth stages the row pattern may not be visible to the camera. Performing the later operation, in which the stored guidance is reused, after the canopy has developed, when real-time row sensing is least reliable, is the obvious application of the stored data. As to claim meaning, the specification uses “post-canopy” for the later stage after the canopy has developed, giving spraying and harvest as examples (Spec. [0009], “post-canopy spraying or harvest”). The specification is relied on only to construe the term; that the later operation is performed post-canopy rests on the obviousness rationale.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to gather the claim guidance data in an early-season, pre-canopy pass and reuse it in a later, post-canopy operation such as harvesting. Maeder teaches this early/late sequence of field operations ([0027]) and the reuse of earlier data in later operations so that the system need not rely on a sensor ([0034]). Susko and Mas teach that camera row detection depends on a visible row pattern and visible soil between the rows (Susko [0013]; Mas [0257]). A PHOSITA would therefore gather the data when that visibility exists and reuse it when real-time sensing becomes unreliable. This is the optimization of a known operating condition, with the predictable result of reliable guidance in late-season operations.
Regarding Claim 4,
The combination of Maeder, Susko, Mas, and Han establishes the method of Claim 1, which is the basis for Claim 4.
Claim Limitations Not Explicitly Disclosed by Maeder
Maeder does not explicitly teach the following additional limitations of Claim 4:
wherein the at least one crop detection sensor
includes a camera system
configured to identify visual boundaries
between crop vegetation and soil.
Disclosure by Susko
Susko teaches:
wherein the at least one crop detection sensor
See at least:
“In some embodiments, the sensors 222 include a camera or another type of optical instrument that implement functionality of a camera in any one of the methodologies described herein.” ([0061])
Rationale:
Express. Susko’s sensors include a camera used in the crop-row guidance methodology, i.e., the at least one crop detection sensor of claim 1.
includes a camera system
See at least:
“the processor is configured to operate with the camera to implement a monocular computer vision system to determine an attribute of a crop row according to a signal processing filter.” ([0042])
Rationale:
Express. The camera and processor implement a computer vision system, i.e., a camera system.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to implement the crop detection sensor of the claim 1 combination as Susko’s camera system, which Susko teaches for exactly this purpose ([0042], [0066]). A camera is a known, inexpensive sensor for locating crop rows, and using it for that purpose yields predictable results.
Claim Limitations Not Explicitly Disclosed by the Combination of Maeder and Susko
After combining the teachings of Maeder and Susko, the following claim limitations are not explicitly disclosed:
configured to identify visual boundaries
between crop vegetation and soil.
Disclosure by Han
Han teaches:
configured to identify visual boundaries
See at least:
“The vision module 22 or image processing system 33 may use color discrimination to organize or segment the collected image into crop pixels and non-crop pixels. Crop pixels may be defined by reference vegetation colors (e.g., green hues), or the like.” ([0086])
Rationale:
Express. Han’s vision module segments the collected image into crop pixels, defined by vegetation colors, and non-crop pixels. Segmenting an image into those two classes identifies the visual boundaries between them.
between crop vegetation and soil.
See at least:
“In one embodiment, the observed intensity profile may indicate one or more crop edges or a generally linear boundary between the crop pixels and non-crop pixels.” ([0087])
Rationale:
Express as to boundaries between crop and non-crop pixels; obvious as to soil. Han identifies “crop edges or a generally linear boundary between the crop pixels and non-crop pixels.” In a row-crop field imaged between the rows, the non-crop pixels adjacent to the crop rows are the visible inter-row soil, so the identified boundaries are between crop vegetation and soil.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to configure the camera system to identify the boundaries between crop vegetation and soil by segmenting crop pixels from non-crop pixels and locating the crop edges, as Han teaches ([0086]-[0087]). Han’s segmentation is directly compatible with Susko’s camera imagery, and isolating the vegetation from the inter-row soil predictably improves the accuracy of the row positions used to calculate the navigation space coordinates.
Regarding Claim 5,
The combination of Maeder, Susko, Mas, and Han establishes the method of Claim 1, which is the basis for Claim 5.
Disclosure by Maeder
Maeder teaches:
wherein calculating the navigation space coordinates comprises:
See at least:
“the field map generated by the field map generator 206 can indicate (a) precise locations (e.g., accounting for displacements in all three-axes) of the vehicle's guidance line that was followed during an initial operation, (b) precise locations of portions of the implement 108 corresponding to crop rows” ([0048])
Rationale:
Express. Maeder calculates precise coordinates of the row-related points in the field map, i.e., the calculation of the navigation space coordinates of claim 1, which the claim 1 combination performs through Mas’s transformation ([0178], [0189]).
between the agricultural vehicle
See at least:
“The navigation display portion 704 includes an example vehicle position indicator 706 displaying a current position of the vehicle 102 relative to the field” ([0080])
Rationale:
Express. Maeder tracks the current position of the vehicle, the vehicle-side reference of the recited error.
and centers of lanes between crop rows; and
See at least:
“The guidance line generator 218 of the illustrated example of FIG. 2 can generate the guidance line 620 centrally such that the twelve-row implement of the subsequent vehicle 610 can operate upon all of the twelve crops rows without the subsequent vehicle 610 running over any of the crop rows” ([0078])
Rationale:
Express. Maeder places the guidance line centrally between crop rows, i.e., at the center of the lane between them. In the combination, the lane center is the midpoint between adjacent row centers located by Susko ([0072]).
Claim Limitations Not Explicitly Disclosed by Maeder
Maeder does not explicitly teach the following claim limitations:
determining a cross-track error
applying the cross-track error
to the position and orientation of the agricultural vehicle.
Disclosure by Susko
Susko teaches:
determining a cross-track error
See at least:
“The cross track error is computed as the distance (e.g., in pixels) of the polynomial fit at the look ahead distance x” ([0082])
Rationale:
Express. Susko computes a cross-track error from the fitted crop-row centers at a look-ahead distance, i.e., the lateral distance between the vehicle (image center) and the row center. Measured against the lane center of limitation 5, the same computation yields the cross-track error between the vehicle and the lane center.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to determine, from the camera of the claim 1 combination, the cross-track error between the vehicle and the lane center, as Susko teaches for crop-row guidance ([0081]-[0082]). Maeder’s guidance is referenced to lane centers ([0078]), and cross-track error is the standard measure Susko derives from the camera. Using it to locate the lane center is a predictable use of a known measurement.
Claim Limitations Not Explicitly Disclosed by the Combination of Maeder and Susko
After combining the teachings of Maeder and Susko, the following claim limitations are not explicitly disclosed:
applying the cross-track error
to the position and orientation of the agricultural vehicle.
Disclosure by Mas
Mas teaches:
applying the cross-track error
See at least:
“After the camera's center of coordinates has been converted to a global frame, coordinates of any point sensed in an image can be referred to a global frame. To do so, a transformation can be made between camera coordinates (centered at the left frame) and global coordinates (East, North) for the sensed points in the images captured by the camera.” ([0178])
“The camera calibration information is then retrieved (step 86) and used with the disparity image to produce the camera coordinates (step 88) for sensed points found in the images.” ([0189])
Rationale:
Express as to the transformation; PHOSITA-obvious as to applying it with the cross-track error, which is the proposed application of Mas’s teaching. Mas transforms a point sensed by the vehicle-mounted camera into global coordinates by applying its coordinates (X_c, Y_c) to a position (N_n, E_n) and yaw angle Θ: N = N_n + X_c·sinΘ + Y_c·cosΘ and E = E_n + X_c·cosΘ − Y_c·sinΘ ([0178]). This is q = p + R(Θ)·v, where p is a position, R(Θ) the rotation by the heading, and v the point’s local coordinates. In the parent combination the steps are: (i) the lane-center point (the midpoint between adjacent detected rows, limitation 5) is located in metric camera coordinates from the stereo disparity and calibration ([0189]), rather than in image pixels as Susko expresses its cross track ([0082]); (ii) because the camera is rigidly mounted at a known location and attitude on the vehicle (Mas [0119]; the same known-offset principle Maeder applies to its location sensor, [0064]), the camera-frame point is converted into the vehicle frame by that fixed mounting transform; a camera-frame measurement is not used directly as a vehicle measurement; (iii) the lateral component of the lane-center point in the vehicle frame is the cross-track error between the vehicle and the lane center (limitations 3-5); and (iv) applying the vehicle-frame vector v, whose lateral component is that cross-track error, to the vehicle position p and orientation Θ through Mas’s transformation gives the lane-center navigation coordinate. Step (iv) applies the cross-track error to the position and orientation of the vehicle. Mas does not expressly describe using a cross-track error in this way; that use is the proposed obviousness application of Mas’s transformation. The instant specification uses the claim language in the same sense: it places the vehicle position in navigation space using the vehicle pose and adds the reported cross-track error to locate the lane center (Spec. [0079]), and states that “The system may utilize the vehicle’s cross-track error (XTE) to compute points of the desired guidance line” (Spec. [0095]). This mapping relies on the coordinate calculation, not on steering correction; Han’s use of off-track error to compensate heading ([0047]) is not relied on for this limitation.
to the position and orientation of the agricultural vehicle.
See at least:
“Since the local map System of reference is fixed to the vehicle, the relative orientation of the local map axes with the global map axes (fixed with respect to the vehicle) will be different according to the direction of travel of the vehicle.” ([0221])
Rationale:
Express. Mas’s transformation uses the vehicle’s position (image origin) and orientation (orientation angle and direction of travel), because the local frame is fixed to the vehicle ([0215]-[0220]). These are the position and orientation of the agricultural vehicle to which the cross-track error is applied.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to calculate the lane-center navigation coordinates by applying the calibrated cross-track error, as the lateral component of a vehicle-frame vector, to the vehicle position and orientation through Mas’s local-to-global transformation ([0178], [0221]). The stored guidance data are in a global frame (Maeder [0048]), so a vehicle-relative measurement must be combined with the vehicle pose before it can be stored and reused. Mas supplies the known transformation and calibration, and using the measured lateral offset as the transformed quantity is the direct way to obtain the lane-center coordinate, with predictable results.
Regarding Claim 6,
The combination of Maeder, Susko, Mas, and Han establishes the method of Claim 1, which is the basis for Claim 6.
Disclosure by Maeder
Maeder teaches:
further comprising using the guidance data
See at least:
“At block 816, the example controller 116 automatically guides the vehicle 102 along guidance line(s) and perform operation(s).” ([0099])
Rationale:
Express. The controller automatically guides the vehicle along the guidance lines, i.e., uses the guidance data.
in the subsequent agricultural operation.
See at least:
“The map data store 208 of the illustrated example of FIG. 2 stores field maps, which can be subsequently accessed to enable automated operation of the vehicle 102 (e.g., via generation and utilization of accurate, crop row specific guidance lines).” ([0051])
Rationale:
Express. The stored maps are subsequently accessed to enable automated operation, i.e., the guidance data are used in the subsequent operation.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to use the stored guidance data of the claim 1 combination in the subsequent operation, which is the stated purpose of storing it (Maeder [0033], [0051]). Using stored guidance for the operation it was created for is the predictable use of the combination.
Regarding Claim 7,
The combination of Maeder, Susko, Mas, and Han establishes the method of Claim 1, which is the basis for Claim 7.
Disclosure by Maeder
Maeder teaches:
wherein the original guidance line
See at least:
“the field map generated by the field map generator 206 can indicate (a) precise locations (e.g., accounting for displacements in all three-axes) of the vehicle's guidance line that was followed during an initial operation, (b) precise locations of portions of the implement 108 corresponding to crop rows” ([0048])
Rationale:
Express. Maeder’s field map records the precise locations of the guidance line followed during the initial operation, i.e., the original guidance line.
is a guidance line used during planting of the crops.
See at least:
“The field map generator 206 of the illustrated example stores (a) location data including the guidance line which the vehicle 102 followed while performing the initial operation (e.g., planting, tilling, etc.).” ([0047])
Rationale:
Express. The stored guidance line is the one the vehicle followed while performing the initial operation, “e.g., planting”. The original guidance line is therefore a guidance line used during planting of the crops.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to use, as the original guidance line of the claim 1 combination, the guidance line used during planting, as Maeder expressly teaches ([0047]); see also Han [0027], which bases the reference path on an as-planted map collected during planting. The planting line is the reference from which the rows were laid out, so offsets measured from it directly capture planter drift (Maeder [0029], [0074]). Using it is a predictable choice that improves accuracy.
Regarding Claim 8,
The combination of Maeder, Susko, Mas, and Han establishes the method of Claim 7, which is the basis for Claim 8.
Disclosure by Maeder
Maeder teaches:
are to be applied to the original guidance line
See at least:
“For example, due to drift of the implement, crop row locations may not be evenly distributed around the original guidance line. In some such examples, when a subsequent operation is performed, the guidance lines may be generated in different locations than the original guidance lines to better target the actual locations of the crop rows.” ([0074])
Rationale:
Express as to correcting the original line; obvious as to doing so by applying offsets. Maeder places the subsequent-operation guidance “in different locations than the original guidance lines to better target the actual locations of the crop rows”. Shifting the original line to the actual rows is applying the row-to-line deviations to the original guidance line.
during the subsequent agricultural operation.
See at least:
“the vehicle 102 is operating in an automated mode, automatically generating and following guidance lines and performing operations with the implement 108 based on existing field maps.” ([0087])
Rationale:
Express. The guidance is followed during the automated subsequent operation based on existing field maps.
Claim Limitations Not Explicitly Disclosed by Maeder
Maeder does not explicitly teach the following claim limitations:
wherein the series of georeferenced offset values
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to apply the stored offsets to the original guidance line during the subsequent operation. Maeder teaches displacing the subsequent guidance from the original line to target the actual rows ([0074]), and Han teaches adjusting a reference path by the measured row offset ([0057], [0100]). Applying the stored offsets in the later pass is the predictable use of the stored data for its intended purpose.
Disclosure by Mas
Mas teaches:
wherein the series of georeferenced offset values
See at least:
“The location tracking device 18 is configured for providing geographic location information of the camera 12 So that the coordinate array information can be mapped to Specific geographic locations.” ([0079])
Rationale:
Express as to georeferencing; PHOSITA-obvious as to the series (see claim 1, limitation 16). Each deviation is mapped to its specific geographic location, yielding the series of georeferenced offset values.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to apply each georeferenced offset at the field position with which it is associated, as Mas teaches for geographically mapped field data ([0079]). Because the deviation varies along the row (Maeder [0029]), applying each offset at its georeferenced position ensures the correction matches the actual row at that place. This predictably improves accuracy.
Regarding Claim 9,
The combination of Maeder, Susko, Mas, and Han establishes the method of Claim 1, which is the basis for Claim 9.
Disclosure by Maeder
Maeder teaches:
wherein the agricultural vehicle
See at least:
“FIG. 1 is a schematic of an example vehicle 102 constructed in accordance with the teachings of this disclosure.” ([0037])
Rationale:
Express. Vehicle 102, which carries the sensors and performs the primary operation in the claim 1 combination, is “the agricultural vehicle” first introduced in claim 1.
is selected from a set consisting of an unmanned aerial vehicle and an unmanned ground vehicle.
See at least:
“In some examples wherein the vehicle 102 is autonomous, the vehicle 102 may not include the cab 106.” ([0037])
Rationale:
Express/implicit. The limitation is a Markush group of alternatives, and it is met by prior art teaching any one member. When autonomous, Maeder’s ground vehicle 102 may omit the operator cab. Maeder’s vehicles may be “fully-autonomous” ([0002]). A ground vehicle that operates fully autonomously without an operator station carries no on-board operator, i.e., it is an unmanned ground vehicle. The unmanned-ground-vehicle member is therefore taught, and the Markush limitation is satisfied without reliance on the unmanned-aerial-vehicle member.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to perform the claim 1 method with Maeder’s fully autonomous, cabless ground vehicle ([0002], [0037]). Autonomous operation is Maeder’s stated objective ([0002], [0028]), and omitting the operator from an autonomous vehicle is the predictable implementation of that objective, reducing operator labor and fatigue ([0028]).
Regarding Claim 10,
The combination of Maeder, Susko, Mas, and Han establishes the method of Claim 1, which is the basis for Claim 10.
Disclosure by Maeder
Maeder teaches:
wherein the determining locations of crop rows comprises
See at least:
“At block 810, the example controller 116 determines crop row locations.” ([0096])
Rationale:
Express. The controller determines crop row locations (read as the “determining actual locations of crop rows” step of claim 1).
at least one of identifying centers of crop rows and identifying centers of lanes between crop rows.
See at least:
“The guidance line generator 218 of the illustrated example of FIG. 2 can generate the guidance line 620 centrally such that the twelve-row implement of the subsequent vehicle 610 can operate upon all of the twelve crops rows without the subsequent vehicle 610 running over any of the crop rows” ([0078])
Rationale:
Express as to the lane-center alternative. Maeder places the guidance line centrally between rows, which requires identifying the center of the lane between them. The claim requires only “at least one of” the alternatives; the crop-row-center alternative is also met in the combination by Susko’s located “crop row centers” ([0072]).
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to identify the centers of the lanes between crop rows when determining the row locations in the claim 1 combination, as Maeder teaches ([0078]), using Susko’s located row centers ([0072]). A lane-centered reference lets the vehicle travel between rows without contacting the crop (Maeder [0057], [0078]), a predictable improvement in safety and accuracy.
Regarding Claim 11,
Disclosure by Maeder
Maeder teaches:
A method for providing guidance data between agricultural operations
See at least:
“Example methods, apparatus, systems, and articles of manufacture (e.g., physical storage media) disclosed herein generate guidance lines for automatic execution of subsequent operations on a field based on field maps determined during previous operations.” ([0033])
Rationale:
Express. Maeder generates guidance for subsequent operations from field maps determined during previous operations, i.e., it provides guidance data between agricultural operations.
comprising:
See at least:
“Example machine readable instructions 800 that may be executed by the controller 116 to perform an operation on a field using a field map are illustrated in FIG. 8.” ([0092])
Rationale:
Express. Maeder’s method is a sequence of steps (FIG. 8); the “comprising” transition reads on it.
during a first agricultural operation after planting,
See at least:
“Most operations are subsequent operations performed on a field (e.g., most operations are performed on existing crops that are planted in the field).” ([0028])
Rationale:
Express as to operations performed after planting; obvious as to using one as the data-gathering pass. Maeder states that most operations are performed on crops already planted, and identifies post-planting operations such as side/top-dress fertilizing ([0027]). Maeder gathers its data in the first operation on the field ([0094]). Once the crop rows are sensed by a crop detection sensor (Susko, below), the sensing pass can detect rows only after the crop has emerged. The data-gathering pass is therefore a first agricultural operation after planting, such as Maeder’s fertilizing pass; that choice follows from sensing the crop itself.
the first agricultural operation being performed during a pre-canopy growth stage
See at least:
“In some examples, a planting operation, a strip/till operation, or a fertilizer operation may be performed first, followed by a spraying operation, a harvesting operation (e.g., a combine or forage harvester), a side/top dress fertilizing operation, or any other field operation.” ([0027])
Rationale:
Express as to an early-season operation; obvious as to its growth stage. Maeder performs strip/till or fertilizer operations first, early in the season, before later spraying and harvesting. Performing the camera detection pass of the combination during the pre-canopy stage is an obvious selection of operating conditions: Susko teaches that camera row guidance is used at “crop growth stages where the cyclical row pattern is visible” ([0013]), and Mas separates crop rows from visible soil ([0257]). A PHOSITA would therefore conduct the detection pass early, while the crop is small and the rows and soil are visible to the camera (see motivation below). As to claim meaning, the specification uses “pre-canopy” for the early-season stage before the crop canopy closes (Spec. [0008], “early season corn (i.e. pre-canopy)”; Spec. [0093], “early in the season (i.e. before canopy)”); the obvious selection described above is a pass at that stage. The specification is relied on only to construe the term, not as evidence of what the prior art teaches.
determining a position and orientation of a first agricultural vehicle,
See at least:
“the location data analyzer 204 receives GPS data and inertial data from the location sensor 114, and analyzes the GPS data and inertial data to determine precise locations of the vehicle 102 and/or the implement 108.” ([0046])
Rationale:
Express as to position; implicit as to orientation. The GPS/inertial solution establishes the vehicle’s location, and its inertial data and track establish its heading (see [0040], tilt compensation; [0064], extrapolation across the implement width, which requires heading). A PHOSITA would recognize that the GPS/inertial solution determines the pose of the first vehicle.
determining guidance data
See at least:
“At block 812, the example controller 116 determines guidance line(s) based on crop row locations” ([0097])
Rationale:
Express. The controller determines guidance lines, i.e., guidance data.
using the position and orientation of the first agricultural vehicle
See at least:
“The field map handler 202 receives GPS data and/or inertial data from the location sensor 114.” ([0045])
Rationale:
Express/implicit. The guidance data are derived from the field map built from the GPS and inertial data of the first vehicle, which carry its position and orientation.
the guidance data comprising an original guidance line
See at least:
“The field map generator 206 of the illustrated example stores (a) location data including the guidance line which the vehicle 102 followed while performing the initial operation (e.g., planting, tilling, etc.).” ([0047])
Rationale:
Express. The stored field map includes the guidance line followed during the initial operation, which Maeder calls the original guidance line ([0074]).
between the original guidance line and navigation space coordinates of the crop rows or lanes therebetween; and
See at least:
“For example, due to drift of the implement, crop row locations may not be evenly distributed around the original guidance line. In some such examples, when a subsequent operation is performed, the guidance lines may be generated in different locations than the original guidance lines to better target the actual locations of the crop rows.” ([0074])
Rationale:
Express as to the relationship; obvious as to its numerical expression. Maeder recognizes the deviation between the original guidance line and the actual row locations and uses it to place later guidance lines. Expressing that deviation as numerical differences between the original line and the row coordinates in the navigation (global) frame of the field map ([0048]) is ordinary coordinate arithmetic with a predictable result.
during a second agricultural operation,
See at least:
“As an example, a planter implement may plant crops at the beginning of a season. A sprayer implement may subsequently spray the crops, and/or a fertilizer implement may subsequently fertilize the crops.” ([0027])
Rationale:
Express. After the first operations, a sprayer or fertilizer implement subsequently operates on the crops, i.e., a second agricultural operation.
the second agricultural operation being performed during a post-canopy growth stage:
See at least:
“Additionally, some crops, such as corn, require highly precise positioning of the implement (e.g., a harvesting head, a platform for small grain harvesting, etc.) during harvesting.” ([0034])
Rationale:
Express as to a later harvesting operation; obvious as to its growth stage. Maeder’s later operations include spraying, side/top-dress fertilizing and harvesting ([0027]), and Maeder specifically addresses harvesting corn. Susko’s restriction of camera guidance to “crop growth stages where the cyclical row pattern is visible” ([0013]) recognizes that at later growth stages the row pattern may not be visible to the camera. Performing the second operation, i.e., the later-season operation in which the stored guidance is reused, after the crop canopy has developed, when real-time row sensing is least reliable, is the obvious application of the stored data (see motivation below). As to claim meaning, the specification uses “post-canopy” for the later stage after the canopy has developed, giving spraying and harvest as examples (Spec. [0009], “post-canopy spraying or harvest”). The specification is relied on only to construe the term; that a later operation such as Maeder’s is performed post-canopy rests on the obviousness rationale, not on the specification.
retrieving the guidance data, and
See at least:
“At block 808, the example controller 116 retrieves a map associated with the field.” ([0095])
Rationale:
Express. In the subsequent operation, the controller retrieves the stored map associated with the field.
automatically guiding a second agricultural vehicle,
See at least:
“The example guidance lines 612 cause the subsequent vehicle 610 to travel between rows with regular widths” ([0077])
Rationale:
Express. Maeder’s subsequent vehicle 610 is distinct from the original vehicle 604 that generated the map (see also [0049], “in case different vehicles are utilized in subsequent operations”), and it travels along generated guidance lines under automatic control ([0099]). This is automatically guiding a second agricultural vehicle.
using an automatic steering system,
See at least:
“the controller 116 can issue commands to the drive controller 118 for the vehicle 102 to move according to a guidance line generated by the controller 116. In such examples, the drive controller 118 responds to these commands and causes movement of the vehicle 102 (e.g., movement of the wheels, steering adjustments, etc.).” ([0042])
Rationale:
Express. The drive controller performs “steering adjustments” in response to guidance-line commands, which is an automatic steering system.
along the original guidance line
See at least:
“While the guidance lines 510 of the illustrated example substantially overlap the original guidance lines 406” ([0074])
Rationale:
Express as to retaining the original guidance line and guiding the later operation from the mapped crop-row locations; the claimed adjustment is supplied by the proposed modification. Maeder retains the original guidance line and generates the subsequent-operation guidance from the mapped crop-row locations; the later guidance lines may “substantially overlap the original guidance lines 406” or may be generated “in different locations than the original guidance lines” ([0074]). Maeder does not expressly disclose steering along the retained original guidance line as adjusted by a stored offset series. The phrase “along the original guidance line” is treated together with the following phrase “as adjusted by the series of georeferenced offset values” as one functional relationship, which is supplied by the proposed modification of the combined teachings addressed under limitation 22 below.
Claim Limitations Not Explicitly Disclosed by Maeder
Maeder does not explicitly teach the following claim limitations:
when soil is visible between crop rows;
detecting actual positions of crop rows or lanes therebetween
using at least one crop detection sensor
mounted on the first agricultural vehicle,
and the actual positions of crop rows or lanes therebetween,
and a series of georeferenced offset values
as adjusted by the series of georeferenced offset values.
Disclosure by Susko
Susko teaches:
detecting actual positions of crop rows or lanes therebetween
See at least:
“Method 300 then continues with step 308, which includes applying, by the processor, the filter to subsequent image data associated with subsequent images in the captured images to locate crop row centers in the crop row.” ([0072])
Rationale:
Express. Susko processes the images to “locate crop row centers”, i.e., detects the actual positions of the crop rows as they exist in the field.
using at least one crop detection sensor
See at least:
“the processor is configured to operate with the camera to implement a monocular computer vision system to determine an attribute of a crop row according to a signal processing filter.” ([0042])
Rationale:
Express. The camera and processor form a computer vision system that determines an attribute of a crop row, i.e., at least one crop detection sensor.
mounted on the first agricultural vehicle,
See at least:
“Method 300 starts with step 302, which includes capturing images of a crop row, one image at a time, by a camera attached to a part of an agricultural vehicle, an implement attached to the agricultural vehicle, or a boom attached to the agricultural vehicle” ([0066])
Rationale:
Express. The camera is attached to a part of the agricultural vehicle. In the combination it is mounted on the first agricultural vehicle that performs the data-gathering pass.
and the actual positions of crop rows or lanes therebetween,
See at least:
“Finally, method 300 continues with step 310, which includes controlling, by a controller, steering of the agricultural vehicle according to the located crop row centers” ([0088])
Rationale:
Express. Susko uses the located crop-row centers, i.e., the actual row positions, as the basis for guiding the vehicle. In the combination, Maeder’s guidance data (limitation 10) are determined using these sensed actual positions together with the vehicle pose (limitation 11).
Motivation to Combine Maeder and Susko
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder and Susko before them, to detect the actual crop-row positions with Susko’s vehicle-mounted camera during a post-planting operation and to use them, with the vehicle pose, to determine Maeder’s stored between-operation guidance. Maeder seeks guidance that targets “the actual locations of the crop rows” ([0074]) but infers row location from the implement position ([0064]). Susko senses the rows directly with an inexpensive monocular camera ([0042], [0066]) and uses the sensed rows for guidance ([0088]). Direct sensing removes the error left by inference and works on fields not planted with Maeder’s instrumented planter. Because a camera can detect crop rows only once the crop has emerged, the sensing pass follows planting. The combination is the use of a known sensor for its known function with predictable results and improves accuracy and reliability.
Claim Limitations Not Explicitly Disclosed by the Combination of Maeder and Susko
After combining the teachings of Maeder and Susko, the following claim limitations are not explicitly disclosed:
when soil is visible between crop rows;
and a series of georeferenced offset values
as adjusted by the series of georeferenced offset values.
Disclosure by Mas
Mas teaches:
when soil is visible between crop rows;
See at least:
“The first purpose is image Segmentation, which involves the Separation of crop rows from the background or Soil.” ([0257])
Rationale:
Express. Mas’s camera-based guidance segments the image to separate “crop rows from the background or Soil”, i.e., it operates on scenes in which soil is visible between the crop rows. Susko similarly operates in “crop growth stages where the cyclical row pattern is visible” ([0013]). Conducting the camera detection pass of the combination when soil is visible between the rows is therefore the operating condition under which the cited sensing works, and selecting it is obvious (see motivation below).
and a series of georeferenced offset values
See at least:
“The location tracking device 18 is configured for providing geographic location information of the camera 12 So that the coordinate array information can be mapped to Specific geographic locations.” ([0079])
“The camera calibration information is then retrieved (step 86) and used with the disparity image to produce the camera coordinates (step 88) for sensed points found in the images.” ([0189])
Rationale:
Express as to georeferencing and spatial coordinates; the series of offsets is the proposed modification. In the combination, the crop detection camera is Mas’s stereo camera, rigidly mounted on the first vehicle ([0119]), with Susko’s row-center processing applied to one channel of the stereo pair to identify the row points (Mas references its camera coordinates to the left frame, [0178]). Mas obtains metric camera coordinates of each identified point from the disparity image and the camera calibration ([0189]), and transforms them into global coordinates using the camera position and yaw angle ([0178]); because the camera is rigidly mounted at a known location on the vehicle, its position and yaw are the vehicle pose offset by a fixed mounting transform. The resulting global row coordinates are the navigation space coordinates of limitation 15, and Mas ties such data to “Specific geographic locations” ([0079]). Two paragraphs are cited because the limitation requires both the spatial row coordinates and their georeferencing. Recording Maeder’s original-line-to-row deviation (limitation 15) at each successive georeferenced row point yields a series of offset values each associated with its geographic position, i.e., a series of georeferenced offset values. No reference expressly discloses storing such a series; the limitation is met by the articulated modification. The reason a PHOSITA would choose this representation, rather than storing only a newly computed corrected line, comes from Maeder itself. Maeder keeps the original guidance line as the reference about which row deviation is assessed ([0074]). Maeder explains that the original line alone is inadequate, because “utilizing the same original guidance lines in the subsequent operation fails to account for the actual crop row locations” ([0032]). Maeder also explains that the deviation arises from drift on curves, slopes and uneven implement loads ([0029]), so it varies along the row. Retaining the unchanged original line as the common reference and recording the spatially varying departures from it, each tied to its field position, gives later operations, including those using implements of different widths ([0032], [0067]-[0071]), the reference line and the measured corrections from which to build their own guidance.
Motivation to Combine Maeder, Susko, and Mas
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, and Mas before them, to (1) select, as the camera detection pass, an early-season operation in which soil is visible between the rows, and (2) record the departure of the georeferenced row points from Maeder’s retained original guidance line as a series of offset values tied to geographic locations. As to (1), Mas and Susko both teach that camera row detection relies on distinguishing the crop rows from the visible soil background or on a visible row pattern (Mas [0257]; Susko [0013]). Choosing the growth stage at which that contrast exists is the optimization of a known operating condition, with the predictable result of reliable detection. As to (2), Mas teaches obtaining metric coordinates of points identified in a stereo camera’s images from disparity and calibration ([0189]), referring them to the global frame with the camera pose ([0178]), and tying data to geographic locations ([0079]). A PHOSITA would implement the crop detection camera as Mas’s stereo camera, applying Susko’s single-image row processing to one channel of the pair, because a single image without depth does not yield the metric row positions needed to compute and store georeferenced offsets, and because three-dimensional imagery provides information “with far greater reliability than two-dimensional images” (Mas [0239]). Susko prefers a monocular camera to limit cost and processing ([0005], [0012]) but does not discourage stereo cameras; accepting added processing to obtain reusable measurements is an ordinary design tradeoff. Maeder keeps the original line as the reference for assessing row deviation ([0074]), teaches that the original line alone “fails to account for the actual crop row locations” ([0032]), and identifies causes of deviation that vary along the row ([0029]). Recording the departures at their georeferenced positions preserves both the reference and the spatially varying corrections for reuse at the corresponding place in the field, a predictable improvement in accuracy.
Claim Limitations Not Explicitly Disclosed by the Combination of Maeder, Susko, and Mas
After combining the teachings of Maeder, Susko, and Mas, the following claim limitations are not explicitly disclosed:
as adjusted by the series of georeferenced offset values.
Disclosure by Han
Han teaches:
as adjusted by the series of georeferenced offset values.
See at least:
“The observed intensity profile (e.g., of FIG. 10) is compared to a reference intensity profile, called a template (e.g., FIG. 11 or FIG. 12), to determine the offset of the crop row relative to a reference row position. The reference row position may be established when the crop, a seed, or precursor was planted, for instance.” ([0100])
“In step S206, an adjuster 110 or vehicle controller 25 adjusts the preliminary guidance data (e.g. preliminary location data) to a revised guidance data (e.g., revised location data) based on the vision guidance data (e.g., vision-derived location data)” ([0057])
Rationale:
Express as to adjusting a reference path by a measured row offset; PHOSITA-obvious as to the claimed arrangement. Han determines “the offset of the crop row relative to a reference row position” established at planting ([0100]) and adjusts the preliminary (reference) guidance data by the vision-derived correction to obtain the revised guidance used to steer ([0057], [0045]). Han’s reference is a planted row position, not the vehicle’s path, and the mapping does not equate the two. In the combination, the offsets are computed directly in the global frame, as the difference between each georeferenced row point (Mas [0178]) and the corresponding point of Maeder’s original guidance line (limitation 15). Each offset value therefore includes both the nominal row spacing from the line and any drift-induced displacement; the claim does not require separating them. Han is relied on for the known technique of adjusting a reference path by a measured row offset to steer the vehicle. Han measures and applies its correction within a single pass and does not teach storing it for another operation. Retrieving the stored offset series in the second operation and applying it to the original guidance line is the proposed modification, supplied by Maeder’s storage and reuse of first-operation data ([0033], [0051], [0095]), as explained in the motivation below. Two paragraphs are cited because the limitation recites both the offset relationship and its application.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to retrieve the stored data in a later, post-canopy operation and automatically guide the second vehicle along the original guidance line as adjusted by the stored series of georeferenced offsets. Han teaches guiding a vehicle by adjusting a reference path by the measured offset of the actual row ([0057], [0100]) to control steering ([0045]). Maeder teaches preparing guidance for later operations from earlier data so that the system can “anticipate upcoming changes ... in crop row locations, rather than relying upon ... a sensor” ([0034]), and retrieving that data in the later operation ([0095]). Susko teaches that camera guidance is limited to growth stages at which the row pattern is visible ([0013]). A PHOSITA would therefore measure the offsets during the early, visible-soil pass and apply them through Han’s known correction technique in a later operation after the canopy has developed, when real-time row sensing is least reliable. This achieves Maeder’s stated objective, uses each element for its established function, and yields the predictable result of accurate automatic guidance in late-season operations (KSR).
Claim 12
Regarding Claim 12,
The combination of Maeder, Susko, Mas, and Han establishes the method of Claim 11, which is the basis for Claim 12.
Disclosure by Maeder
Maeder teaches:
wherein: the first agricultural operation
See at least:
“At block 806, the example controller 116 generates a field map during a first operation.” ([0094])
Rationale:
Express. The first operation on the field, during which the data are gathered.
is performed during a pre-canopy growth stage
See at least:
“In some examples, a planting operation, a strip/till operation, or a fertilizer operation may be performed first, followed by a spraying operation, a harvesting operation (e.g., a combine or forage harvester), a side/top dress fertilizing operation, or any other field operation.” ([0027])
Rationale:
Express as to an early-season first operation; obvious as to its growth stage. Maeder performs planting, strip/till or fertilizer operations first, early in the season, before later spraying and harvesting. In the parent combination, the data-gathering pass uses a camera, and Susko teaches that camera row guidance is used at “crop growth stages where the cyclical row pattern is visible” ([0013]); Mas separates crop rows from visible soil ([0257]). Performing the primary (data-gathering) operation early, while the crop is small and the rows are visible, i.e., during the pre-canopy stage, is therefore an obvious selection of a known operating condition with the predictable result of reliable detection. As to claim meaning, the specification uses “pre-canopy” for the early-season stage before the crop canopy closes (Spec. [0008], “early season corn (i.e. pre-canopy)”; Spec. [0093], “early in the season (i.e. before canopy)”). The specification is relied on only to construe the term, not as evidence of what the prior art teaches.
the second agricultural operation
See at least:
“As an example, a planter implement may plant crops at the beginning of a season. A sprayer implement may subsequently spray the crops, and/or a fertilizer implement may subsequently fertilize the crops.” ([0027])
Rationale:
Express. A later spraying or fertilizing operation is the second agricultural operation.
is performed during a post-canopy growth stage.
See at least:
“Additionally, some crops, such as corn, require highly precise positioning of the implement (e.g., a harvesting head, a platform for small grain harvesting, etc.) during harvesting.” ([0034])
Rationale:
Express as to a later harvesting operation; obvious as to its growth stage. Maeder’s later operations include spraying, side/top-dress fertilizing and harvesting ([0027]), and Maeder specifically addresses harvesting corn. Susko’s restriction of camera guidance to “crop growth stages where the cyclical row pattern is visible” ([0013]) recognizes that at later growth stages the row pattern may not be visible to the camera. Performing the later operation, in which the stored guidance is reused, after the canopy has developed, when real-time row sensing is least reliable, is the obvious application of the stored data. As to claim meaning, the specification uses “post-canopy” for the later stage after the canopy has developed, giving spraying and harvest as examples (Spec. [0009], “post-canopy spraying or harvest”). The specification is relied on only to construe the term; that the later operation is performed post-canopy rests on the obviousness rationale.
Claim Limitations Not Explicitly Disclosed by Maeder
Maeder does not explicitly teach the following claim limitations:
when soil is visible between crop rows; and
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to gather the claim guidance data in an early-season, pre-canopy pass and reuse it in a later, post-canopy operation such as harvesting. Maeder teaches this early/late sequence of field operations ([0027]) and the reuse of earlier data in later operations so that the system need not rely on a sensor ([0034]). Susko and Mas teach that camera row detection depends on a visible row pattern and visible soil between the rows (Susko [0013]; Mas [0257]). A PHOSITA would therefore gather the data when that visibility exists and reuse it when real-time sensing becomes unreliable. This is the optimization of a known operating condition, with the predictable result of reliable guidance in late-season operations.
Disclosure by Mas
Mas teaches:
when soil is visible between crop rows; and
See at least:
“The first purpose is image Segmentation, which involves the Separation of crop rows from the background or Soil.” ([0257])
Rationale:
Express. Mas’s camera-based guidance separates crop rows from the “Soil” background, i.e., it operates on scenes in which soil is visible between the rows (see also Susko [0013]). Conducting the detection pass under that condition is obvious for the reasons stated for claim 11.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to perform the sensing pass while soil is visible between the rows, because camera row detection depends on the crop/soil contrast (Mas [0257]; Susko [0013]). Selecting that operating condition predictably improves detection reliability.
Claim 13
Regarding Claim 13,
The combination of Maeder, Susko, Mas, and Han establishes the method of Claim 11, which is the basis for Claim 13.
Disclosure by Maeder
Maeder teaches:
calculating centers of lanes between identified crop vegetation.
See at least:
“The guidance line generator 218 of the illustrated example of FIG. 2 can generate the guidance line 620 centrally such that the twelve-row implement of the subsequent vehicle 610 can operate upon all of the twelve crops rows without the subsequent vehicle 610 running over any of the crop rows” ([0078])
Rationale:
Express as to the lane center; obvious as to its calculation from sensed vegetation. Maeder places the guidance line centrally between the rows. In the combination, the rows are the vegetation identified in the camera images, so the lane center is the midpoint between the identified vegetation rows, a simple and predictable computation.
Claim Limitations Not Explicitly Disclosed by Maeder
Maeder does not explicitly teach the following claim limitations:
wherein detecting the actual positions of crop rows or lanes therebetween comprises:
capturing image data
using at least one camera mounted on the first agricultural vehicle;
processing the image data
to identify boundaries between crop vegetation and soil; and
Disclosure by Susko
Susko teaches:
wherein detecting the actual positions of crop rows or lanes therebetween comprises:
See at least:
“Method 300 then continues with step 308, which includes applying, by the processor, the filter to subsequent image data associated with subsequent images in the captured images to locate crop row centers in the crop row.” ([0072])
Rationale:
Express. Susko locates crop-row centers in the camera images, i.e., detects the actual positions of the crop rows.
capturing image data
See at least:
“Method 300 starts with step 302, which includes capturing images of a crop row, one image at a time, by a camera attached to a part of an agricultural vehicle, an implement attached to the agricultural vehicle, or a boom attached to the agricultural vehicle” ([0066])
Rationale:
Express. The camera captures images of the crop row, i.e., image data.
using at least one camera mounted on the first agricultural vehicle;
See at least:
“In some examples, the apparatus is configured to attach to an agricultural vehicle, an agricultural implement, or an agricultural boom.” ([0043])
Rationale:
Express. The camera apparatus attaches to the agricultural vehicle, i.e., the camera is mounted on the first agricultural vehicle.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to detect the actual row positions in the claim 11 combination by capturing images with a vehicle-mounted camera, as Susko teaches ([0066]-[0072]). Susko’s camera pipeline is the known way to locate rows, and using it yields predictable results.
Claim Limitations Not Explicitly Disclosed by the Combination of Maeder and Susko
After combining the teachings of Maeder and Susko, the following claim limitations are not explicitly disclosed:
processing the image data
to identify boundaries between crop vegetation and soil; and
Disclosure by Mas
Mas teaches:
processing the image data
See at least:
“Before attempting any processing for pattern recognition, the original image of FIG. 38(b) is divided into Several windows where further processing is performed.” ([0261])
Rationale:
Express. Mas divides the acquired agricultural image into windows in which further processing is performed for pattern recognition, i.e., processes the image data.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to process the captured agricultural images by dividing them into windows for pattern recognition, as Mas teaches ([0261]). This is a known image-processing technique for locating features in agricultural scenes and predictably improves row localization.
Claim Limitations Not Explicitly Disclosed by the Combination of Maeder, Susko, and Mas
After combining the teachings of Maeder, Susko, and Mas, the following claim limitations are not explicitly disclosed:
to identify boundaries between crop vegetation and soil; and
Disclosure by Han
Han teaches:
to identify boundaries between crop vegetation and soil; and
See at least:
“In one embodiment, the observed intensity profile may indicate one or more crop edges or a generally linear boundary between the crop pixels and non-crop pixels.” ([0087])
Rationale:
Express as to boundaries between crop and non-crop pixels; obvious as to soil. Han identifies “crop edges or a generally linear boundary between the crop pixels and non-crop pixels” (crop pixels being defined by vegetation colors, [0086]). Where the non-crop region between rows is the visible inter-row soil, the identified boundaries are between crop vegetation and soil.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to identify the boundaries between crop vegetation and soil by segmenting crop pixels from non-crop pixels and locating the crop edges, as Han teaches ([0086]-[0087]), and to calculate the lane centers between the identified rows, as Maeder’s centered guidance requires ([0078]). The references respectively furnish lane-centered guidance, vehicle-mounted image capture, agricultural image processing and crop-edge segmentation; these compatible known tools predictably improve lane localization.
Claim 14
Regarding Claim 14,
Disclosure by Maeder
Maeder discloses:
A system for generating agricultural guidance data,
See at least:
“Example methods, apparatus, systems, and articles of manufacture (e.g., physical storage media) disclosed herein generate guidance lines for automatic execution of subsequent operations on a field based on field maps determined during previous operations.” ([0033])
Rationale:
Express. Maeder discloses systems that generate guidance lines, i.e., agricultural guidance data, for automatic execution of field operations.
the system comprising:
See at least:
“The example controller 116 of the illustrated example of FIG. 1 analyzes data from one or more sensors and enables automated operation of the vehicle 102.” ([0041])
Rationale:
Express. Maeder’s system comprises a controller together with sensors and other components that enable automated operation of the vehicle.
at least one positioning sensor
See at least:
“The location sensor 114 of the illustrated example is a global positioning system (GPS) sensor combined with an inertial sensor.” ([0040])
Rationale:
Express. The GPS sensor combined with an inertial sensor is at least one positioning sensor.
mounted on an agricultural vehicle
See at least:
“In some examples, the location sensor 114 is mounted to another part of the vehicle 102 (e.g., the main body 104, the cab 106, etc.).” ([0040])
Rationale:
Express. The location sensor is mounted to the vehicle (main body or cab) or to its implement.
and configured to determine a position and orientation of the agricultural vehicle;
See at least:
“the location data analyzer 204 receives GPS data and inertial data from the location sensor 114, and analyzes the GPS data and inertial data to determine precise locations of the vehicle 102 and/or the implement 108.” ([0046])
Rationale:
Express as to position; implicit as to orientation. The GPS and inertial data determine the precise location of the vehicle, and the inertial sensor measures its attitude (tilt compensation, [0040]). A GPS/inertial unit that determines vehicle pose for row mapping is configured to determine both position and orientation.
a processing system communicatively coupled to the at least one positioning sensor
See at least:
“The location sensor 114 communicates to an example controller 116.” ([0040])
Rationale:
Express. The location sensor communicates with controller 116, a processing system communicatively coupled to the positioning sensor.
the processing system configured to:
See at least:
“The machine readable instructions may be one or more executable programs or portion(s) of an executable program for execution by a computer processor such as the processor 1112” ([0088])
Rationale:
Express. Controller 116 is implemented by a processor executing machine-readable instructions, i.e., a processing system configured (programmed) to perform the recited functions.
receive position and orientation data from the at least one positioning sensor,
See at least:
“The field map handler 202 receives GPS data and/or inertial data from the location sensor 114.” ([0045])
Rationale:
Express. The controller receives GPS and inertial data, i.e., position and orientation data, from the location sensor.
calculate navigation space coordinates of points along the crop rows
See at least:
“the field map generated by the field map generator 206 can indicate (a) precise locations (e.g., accounting for displacements in all three-axes) of the vehicle's guidance line that was followed during an initial operation, (b) precise locations of portions of the implement 108 corresponding to crop rows” ([0048])
Rationale:
Express. The controller computes precise three-axis coordinates of points corresponding to the crop rows and records them in the global field map, i.e., navigation space coordinates of points along the crop rows.
by combining the position and orientation data
See at least:
“For example, if the vehicle 102 is tilted on a hill, the inertial sensor can compensate for this tilt to enable accurate determination of a location of the vehicle 102, and more specifically, accurate determination of locations of portions of the implement 108.” ([0040])
Rationale:
Express. The row-point coordinates are computed using both the vehicle position and its attitude (tilt) data, i.e., by combining the position and orientation data. The crop row position data with which they are combined are addressed under limitation 16 below.
generate guidance data
See at least:
“The controller 116 of the illustrated example generates field maps and utilizes such field maps to automatically generate guidance lines based on the field maps and the type of implement in use by the vehicle 102.” ([0041])
Rationale:
Express. The controller automatically generates guidance lines.
based on the calculated navigation space coordinates,
See at least:
“At block 812, the example controller 116 determines guidance line(s) based on crop row locations” ([0097])
Rationale:
Express. The guidance lines are determined from the stored crop-row locations, which are the calculated coordinates of limitation 14.
the guidance data comprising an original guidance line
See at least:
“The field map generator 206 of the illustrated example stores (a) location data including the guidance line which the vehicle 102 followed while performing the initial operation (e.g., planting, tilling, etc.).” ([0047])
Rationale:
Express. The guidance data include the guidance line followed during the initial operation, which Maeder calls the original guidance line ([0066], [0074]).
between the original guidance line and the calculated navigation space coordinates,
See at least:
“For example, due to drift of the implement, crop row locations may not be evenly distributed around the original guidance line. In some such examples, when a subsequent operation is performed, the guidance lines may be generated in different locations than the original guidance lines to better target the actual locations of the crop rows.” ([0074])
Rationale:
Express as to the relationship; obvious as to its numerical expression. Maeder recognizes the deviation of the actual rows from the original guidance line and uses it to place later guidance lines. That deviation is the difference between the original guidance line and the calculated row coordinates; computing it numerically from the two stored coordinate sets is ordinary coordinate arithmetic.
and store the guidance data
See at least:
“The field map generator 206 stores the field map in the map data store 208 and/or another location accessible to the controller 116.” ([0049])
Rationale:
Express. The field map, including the guidance line, is stored.
in a storage device; and
See at least:
“The map data store 208 may be implemented by a volatile memory” ([0051])
Rationale:
Express. The map data store is implemented by memory, i.e., a storage device.
an automatic steering system
See at least:
“the controller 116 can issue commands to the drive controller 118 for the vehicle 102 to move according to a guidance line generated by the controller 116. In such examples, the drive controller 118 responds to these commands and causes movement of the vehicle 102 (e.g., movement of the wheels, steering adjustments, etc.).” ([0042])
Rationale:
Express. Drive controller 118 performs “steering adjustments” in response to guidance-line commands, i.e., an automatic steering system.
configured to automatically steer an agricultural vehicle
See at least:
“In some examples, the drive commander 222 may operate autonomously (e.g., cause the vehicle 102 to automatically follow guidance lines generated by the guidance line generator 218)” ([0059])
Rationale:
Express. The drive commander operates autonomously to cause the vehicle to automatically follow guidance lines.
during a subsequent agricultural operation
See at least:
“the vehicle 102 is operating in an automated mode, automatically generating and following guidance lines and performing operations with the implement 108 based on existing field maps.” ([0087])
Rationale:
Express. Automated guidance is performed “based on existing field maps”, i.e., during a subsequent agricultural operation.
along the original guidance line
See at least:
“While the guidance lines 510 of the illustrated example substantially overlap the original guidance lines 406” ([0074])
Rationale:
Express as to retaining the original guidance line and guiding the later operation from the mapped crop-row locations; the claimed adjustment is supplied by the proposed modification. Maeder retains the original guidance line and generates the subsequent-operation guidance from the mapped crop-row locations; the later guidance lines may “substantially overlap the original guidance lines 406” or may be generated “in different locations than the original guidance lines” ([0074]). Maeder does not expressly disclose steering along the retained original guidance line as adjusted by a stored offset series. The phrase “along the original guidance line” is treated together with the following phrase “as adjusted by the series of offset values” as one functional relationship, which is supplied by the proposed modification of the combined teachings addressed under limitation 28 below.
Claim Limitations Not Explicitly Disclosed by Maeder
Maeder does not explicitly disclose the following claim limitations:
at least one crop detection sensor
mounted on the agricultural vehicle
and configured to detect actual positions of crop rows relative to the agricultural vehicle;
and the at least one crop detection sensor,
receive crop row position data from the at least one crop detection sensor,
with the crop row position data,
and a series of offset values
as adjusted by the series of offset values.
Disclosure by Susko
Susko discloses:
at least one crop detection sensor
See at least:
“the processor is configured to operate with the camera to implement a monocular computer vision system to determine an attribute of a crop row according to a signal processing filter.” ([0042])
Rationale:
Express. The camera and processor form a computer vision system that determines an attribute of a crop row, i.e., at least one crop detection sensor.
mounted on the agricultural vehicle
See at least:
“In some examples, the apparatus is configured to attach to an agricultural vehicle, an agricultural implement, or an agricultural boom.” ([0043])
Rationale:
Express. The camera apparatus attaches to the agricultural vehicle, i.e., it is mounted on the agricultural vehicle.
and configured to detect actual positions of crop rows relative to the agricultural vehicle;
See at least:
“Method 300 then continues with step 308, which includes applying, by the processor, the filter to subsequent image data associated with subsequent images in the captured images to locate crop row centers in the crop row.” ([0072])
Rationale:
Express/implicit. Susko locates crop-row centers in images from the vehicle-mounted camera. Image coordinates from a camera fixed to the vehicle are positions relative to the vehicle, and Susko uses them to compute the vehicle’s cross-track and heading error relative to the rows ([0081]). These are actual, sensed row positions relative to the agricultural vehicle.
and the at least one crop detection sensor,
See at least:
“In such embodiments, the apparatus is communicatively coupled to a controller or computing system of an agricultural vehicle” ([0041])
Rationale:
Express. The camera apparatus is communicatively coupled to the controller or computing system of the vehicle, i.e., the processing system is coupled to the crop detection sensor.
receive crop row position data from the at least one crop detection sensor,
See at least:
“Method 300 continues with step 304, which includes transmitting image data associated with the captured images over an electronics coupling to a processor, such as a CPU” ([0067])
Rationale:
Express. Image data from the camera are transmitted to the processor, which derives the crop-row centers from them ([0072]). The processor therefore receives crop row position data from the crop detection sensor.
Motivation to Combine Maeder and Susko
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder and Susko before them, to add Susko’s vehicle-mounted crop-row camera, communicatively coupled to the vehicle controller, to Maeder’s guidance system. Maeder’s goal is guidance that targets “the actual locations of the crop rows” ([0074]), but Maeder infers those locations from implement position ([0064]). Susko senses the rows directly with an inexpensive monocular camera that couples to the vehicle’s computing system ([0041]-[0043]). The addition is the use of a known sensor for its established function through a compatible controller interface, with the predictable result of more accurate and reliable stored row data.
Claim Limitations Not Explicitly Disclosed by the Combination of Maeder and Susko
After combining the teachings of Maeder and Susko, the following claim limitations are not explicitly disclosed:
with the crop row position data,
and a series of offset values
as adjusted by the series of offset values.
Disclosure by Mas
Mas discloses:
with the crop row position data,
See at least:
“After the camera's center of coordinates has been converted to a global frame, coordinates of any point sensed in an image can be referred to a global frame. To do so, a transformation can be made between camera coordinates (centered at the left frame) and global coordinates (East, North) for the sensed points in the images captured by the camera.” ([0178])
“The camera calibration information is then retrieved (step 86) and used with the disparity image to produce the camera coordinates (step 88) for sensed points found in the images.” ([0189])
Rationale:
Express as to the transformation; obvious as to its application to the crop row position data. In the combination, the crop detection camera is implemented as Mas’s stereo camera, rigidly mounted on the vehicle ([0119]), with Susko’s row-center processing applied to one channel of the stereo pair (Mas references its camera coordinates to the left frame, [0178]). Mas obtains spatial (metric) camera coordinates for each sensed point from the disparity image and the camera calibration ([0189]); a monocular image alone does not supply that distance. Mas then transforms those camera coordinates into global (East, North) coordinates using the camera’s global position and its yaw angle ([0178]): N = N_n + X_c·sinΘ + Y_c·cosΘ and E = E_n + X_c·cosΘ − Y_c·sinΘ. Because the camera is rigidly mounted at a known location on the vehicle, its position and yaw are the vehicle position and orientation offset by a fixed mounting transform, the same known-offset principle Maeder applies to its location sensor ([0064]). In the combination, the transformed points are Susko’s crop row position data, so the processing system combines the position and orientation data (limitation 15) with the crop row position data to calculate the navigation space coordinates of points along the crop rows. Two paragraphs are cited because the limitation requires both the spatial row-position data ([0189]) and their combination with the pose ([0178]).
Motivation to Combine Maeder, Susko, and Mas
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, and Mas before them, to convert Susko’s vehicle-relative crop row position data into navigation space coordinates by combining them with the vehicle position and orientation data, as Mas teaches for points sensed by a vehicle-carried camera ([0178], [0221]). Maeder stores its row data in a global (GPS) field map ([0048]), so camera-relative row positions must be transformed into that frame before they can be stored, compared with the original guidance line and reused. Mas provides the known transformation for that purpose ([0178]) and the stereo disparity and calibration processing that yield the spatial camera coordinates the transformation needs ([0189]). A PHOSITA would implement the crop detection camera as Mas’s stereo camera for that reason and because Mas teaches that three-dimensional imagery provides information “with far greater reliability than two-dimensional images” ([0239]). Susko’s row-center processing operates on a single image, so it is applied to one channel of Mas’s stereo pair (Mas references its camera coordinates to the left frame, [0178]), while Mas’s paired-image disparity processing supplies the spatial coordinates of the points Susko identifies. Susko prefers a monocular camera to limit cost and processing load ([0005], [0012], “some embodiments ... using a mono (non-stereo) camera”). The combination accepts the added stereo processing because it yields metric, geographically registered row measurements that can be stored and reused in later operations, which a single image without depth does not provide. Weighing that known cost-versus-capability tradeoff is an ordinary design choice; Susko does not criticize or discourage stereo cameras. The result is predictable and enables accurate reuse of the sensed rows in later operations.
Claim Limitations Not Explicitly Disclosed by the Combination of Maeder, Susko, and Mas
After combining the teachings of Maeder, Susko, and Mas, the following claim limitations are not explicitly disclosed:
and a series of offset values
as adjusted by the series of offset values.
Disclosure by Han
Han discloses:
and a series of offset values
See at least:
“The observed intensity profile (e.g., of FIG. 10) is compared to a reference intensity profile, called a template (e.g., FIG. 11 or FIG. 12), to determine the offset of the crop row relative to a reference row position. The reference row position may be established when the crop, a seed, or precursor was planted, for instance.” ([0100])
Rationale:
Express as to determining an offset of a sensed crop row from a planting-established reference; obvious as to the claimed series referenced to the original guidance line. Han determines “the offset of the crop row relative to a reference row position” established at planting. Han’s reference is a planted row position, not the vehicle’s path, and the mapping does not equate the two. In the combination, the offsets are computed directly in the global frame as the difference between each row point’s calculated navigation space coordinates (limitations 14-16) and the corresponding point of Maeder’s original guidance line (limitation 21). Each offset value includes both the nominal row spacing and any drift-induced displacement; the claim does not require separating them. Han shows that representing the sensed row as an offset from a reference established at planting is a known technique. Han determines the offset repeatedly as the vehicle travels (evaluation time intervals, [0049]-[0057]). Repetition alone is not storage; retaining those successive offsets as part of the stored guidance data, as the claim requires, is the proposed modification explained in the motivation below. The reason a PHOSITA would choose this representation, rather than storing only a newly computed corrected line, comes from Maeder itself. Maeder keeps the original guidance line as the reference about which row deviation is assessed ([0074]). Maeder explains that the original line alone is inadequate, because “utilizing the same original guidance lines in the subsequent operation fails to account for the actual crop row locations” ([0032]). Maeder also explains that the deviation arises from drift on curves, slopes and uneven implement loads ([0029]), so it varies along the row. Retaining the unchanged original line as the common reference and recording the spatially varying departures from it, each tied to its field position, gives later operations, including those using implements of different widths ([0032], [0067]-[0071]), the reference line and the measured corrections from which to build their own guidance.
as adjusted by the series of offset values.
See at least:
“In step S206, an adjuster 110 or vehicle controller 25 adjusts the preliminary guidance data (e.g. preliminary location data) to a revised guidance data (e.g., revised location data) based on the vision guidance data (e.g., vision-derived location data)” ([0057])
Rationale:
Express as to adjusting a reference path by a measured offset; PHOSITA-obvious as to the claimed arrangement. Han adjusts the preliminary (reference) guidance data by the vision-derived correction to obtain the revised guidance data used by the steering system ([0045]). Han measures and applies its correction within one pass (application may lag measurement, [0059]) and does not teach storing it for another operation. Configuring the steering system to apply the stored offset series to the original guidance line during the subsequent operation is the proposed modification, supplied by Maeder’s storage and reuse of earlier-operation data ([0033], [0051]).
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to (1) store, as the guidance data, Maeder’s original guidance line together with the series of offset values of the sensed rows from that line, and (2) configure the automatic steering system to steer along the original line as adjusted by those offsets in the subsequent operation. Han teaches the correction structure: a reference path ([0027]) adjusted by the measured offset of the actual row ([0057], [0100]) to control steering ([0045]). Maeder teaches keeping the original line as the reference for row deviation ([0074]), that the original line alone “fails to account for the actual crop row locations” ([0032]), and preparing later-operation guidance from earlier data so that the system can “anticipate upcoming changes ... in crop row locations, rather than relying upon ... a sensor” ([0034]). Storing Han-type offsets with the retained original line in the earlier pass and applying them in the later pass therefore achieves Maeder’s objective with Han’s known correction technique. It preserves the original line as a common reference for implements of different widths (Maeder [0032]). The combination is predictable and improves guidance accuracy, reliability and control (KSR).
Claim 15
Regarding Claim 15,
The combination of Maeder, Susko, Mas, and Han establishes the system of Claim 14, which is the basis for Claim 15.
Claim Limitations Not Explicitly Disclosed by Maeder
Maeder does not explicitly disclose the following additional limitations of Claim 15:
wherein the at least one crop detection sensor
comprises a stereographic depth camera
configured to:
capture three-dimensional depth information of a field; and
identify crop rows
based on height differences between crop vegetation and soil.
Disclosure by Susko
Susko discloses:
wherein the at least one crop detection sensor
See at least:
“In some embodiments, the sensors 222 include a camera or another type of optical instrument that implement functionality of a camera in any one of the methodologies described herein.” ([0061])
Rationale:
Express. Susko’s sensors include a camera used for crop-row guidance, i.e., the at least one crop detection sensor of claim 14.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to use a camera as the crop detection sensor of the claim 14 combination, as Susko teaches ([0061]). This is the predictable use of a known sensor.
Claim Limitations Not Explicitly Disclosed by the Combination of Maeder and Susko
After combining the teachings of Maeder and Susko, the following claim limitations are not explicitly disclosed:
comprises a stereographic depth camera
configured to:
capture three-dimensional depth information of a field; and
identify crop rows
based on height differences between crop vegetation and soil.
Disclosure by Mas
Mas discloses:
comprises a stereographic depth camera
See at least:
“The Stereo camera 12 can be mounted on any Suitable vehicle 16 for obtaining the aerial images.” ([0119])
Rationale:
Express. Mas’s crop-sensing camera is a stereo camera, which yields depth via disparity ([0116]), i.e., a stereographic depth camera.
configured to:
See at least:
“The computer 14 can be configured with an algorithm 26 for capturing and processing the Stereo images from the camera 12 in an image acquisition phase.” ([0117])
Rationale:
Express. The stereo camera and computer are configured, by algorithm 26, to capture and process the stereo images.
capture three-dimensional depth information of a field; and
See at least:
“The image acquisition phase can comprise acquiring Stereo images of an agricultural field Scene, computing a disparity map based on the Stereo images, and obtaining local coordinate arrays of the points of the agricultural field Scene represented in the Stereo images.” ([0116])
Rationale:
Express. The stereo images yield a disparity map and local coordinate arrays of the points of the agricultural field scene, i.e., three-dimensional depth information of a field.
identify crop rows
See at least:
“a System and method according the present invention can use image Segmentation of a disparity image of the type described in detail above in order to Separate crop rows represented in the disparity image from the background.” ([0234])
Rationale:
Express. Mas segments the disparity image to separate the crop rows from the background, i.e., identifies crop rows.
based on height differences between crop vegetation and soil.
See at least:
“Layer 2 is located at medium height and it has a medium thickness of 25 cm. This layer gathers information about the crop, but not about the ground.” ([0319])
Rationale:
Express/implicit. Mas uses height layers of the 3-D data; the layer at crop height “gathers information about the crop, but not about the ground”. Selecting points by height thus separates crop vegetation from the lower soil, i.e., identifies the rows based on height differences between vegetation and soil.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to use Mas’s stereo depth camera as that camera and identify the rows by height layers that separate the crop from the ground ([0116], [0319]). Mas teaches that stereo depth provides information with “far greater reliability than two-dimensional images” ([0239]) and that its disparity processing filters out the background without thresholding ([0235]). Height-based separation is less sensitive to color, lighting and weed variation, a predictable improvement in reliability.
Claim 16
Regarding Claim 16,
The combination of Maeder, Susko, Mas, and Han establishes the system of Claim 14, which is the basis for Claim 16.
Disclosure by Maeder
Maeder discloses:
wherein the agricultural vehicle
See at least:
“The vehicle 102 further includes an example implement 108.” ([0038])
Rationale:
Express. Vehicle 102, which carries the positioning sensor and, in the combination, the crop detection sensor, is the agricultural vehicle first introduced in claim 14. The “agricultural vehicle” of claim 16 is read as that vehicle, consistent with its association with the processing system that generates the guidance data.
is configured to perform a primary agricultural operation
See at least:
“In some examples, a planting operation, a strip/till operation, or a fertilizer operation may be performed first, followed by a spraying operation, a harvesting operation (e.g., a combine or forage harvester), a side/top dress fertilizing operation, or any other field operation.” ([0027])
Rationale:
Express. Maeder’s vehicle carries interchangeable implements ([0038]) and performs field operations such as strip/till or fertilizer operations, i.e., it is configured to perform a primary agricultural operation. In the combination, the crop detection sensor is a camera that can detect rows only after crop emergence, so the primary operation is a post-emergence operation such as Maeder’s fertilizing pass.
while the processing system generates the guidance data.
See at least:
“At block 806, the example controller 116 generates a field map during a first operation.” ([0094])
Rationale:
Express as to generating the field map during the first operation; PHOSITA-obvious as to completing the guidance data in the same pass. Maeder’s controller generates the field map while the first operation is being performed. Computing the original-line-to-row offsets from the map data as they are collected is a predictable configuration that avoids a separate processing step after the operation. Han likewise computes its row offsets continuously during travel ([0057]).
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to configure the processing system to generate the guidance data while the vehicle performs its post-emergence primary operation. Maeder already generates the field map during that operation ([0094]), and Han computes its row offsets during travel ([0057]). Generating the guidance data in the same pass avoids an additional mapping or processing step, a predictable improvement in efficiency.
Claim 17
Regarding Claim 17,
The combination of Maeder, Susko, Mas, and Han establishes the system of Claim 14, which is the basis for Claim 17.
Disclosure by Maeder
Maeder discloses:
wherein the original guidance line
See at least:
“the field map generated by the field map generator 206 can indicate (a) precise locations (e.g., accounting for displacements in all three-axes) of the vehicle's guidance line that was followed during an initial operation, (b) precise locations of portions of the implement 108 corresponding to crop rows” ([0048])
Rationale:
Express. The field map records the guidance line followed during the initial operation, i.e., the original guidance line.
is a guidance line used during planting of the crops.
See at least:
“The field map generator 206 of the illustrated example stores (a) location data including the guidance line which the vehicle 102 followed while performing the initial operation (e.g., planting, tilling, etc.).” ([0047])
Rationale:
Express. That line is the one followed while performing the initial operation, “e.g., planting”, i.e., a guidance line used during planting of the crops.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to use the planting guidance line as the original guidance line of the claim 14 combination, as Maeder expressly teaches ([0047]); see also Han [0027] (as-planted path). Offsets measured from the planting line directly capture planter drift (Maeder [0029], [0074]), a predictable improvement in accuracy.
Claim 18
Regarding Claim 18,
The combination of Maeder, Susko, Mas, and Han establishes the system of Claim 14, which is the basis for Claim 18.
Claim Limitations Not Explicitly Disclosed by Maeder
Maeder does not explicitly disclose the following additional limitations of Claim 18:
wherein the at least one crop detection sensor
comprises a camera system
configured to identify visual boundaries
between crop vegetation and soil.
Disclosure by Susko
Susko discloses:
wherein the at least one crop detection sensor
See at least:
“In some embodiments, the sensors 222 include a camera or another type of optical instrument that implement functionality of a camera in any one of the methodologies described herein.” ([0061])
Rationale:
Express. Susko’s sensors include a camera used for crop-row guidance, i.e., the at least one crop detection sensor.
comprises a camera system
See at least:
“the processor is configured to operate with the camera to implement a monocular computer vision system to determine an attribute of a crop row according to a signal processing filter.” ([0042])
Rationale:
Express. The camera and processor implement a computer vision system, i.e., a camera system.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to implement the crop detection sensor of the claim 14 combination as Susko’s camera system ([0042], [0066]), the predictable use of a known row-sensing device.
Claim Limitations Not Explicitly Disclosed by the Combination of Maeder and Susko
After combining the teachings of Maeder and Susko, the following claim limitations are not explicitly disclosed:
configured to identify visual boundaries
between crop vegetation and soil.
Disclosure by Mas
Mas discloses:
configured to identify visual boundaries
See at least:
“a System and method according the present invention can use image Segmentation of a disparity image of the type described in detail above in order to Separate crop rows represented in the disparity image from the background.” ([0234])
Rationale:
Express. Mas segments the image to separate crop rows from the background, i.e., identifies the visual boundaries of the rows.
between crop vegetation and soil.
See at least:
“The first purpose is image Segmentation, which involves the Separation of crop rows from the background or Soil.” ([0257])
Rationale:
Express. The background is “Soil”, so the boundaries are between crop vegetation and soil.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to configure the camera system to identify vegetation/soil boundaries by segmenting the crop rows from the soil background, as Mas teaches ([0234], [0257]). This is the known way to isolate rows in an image and predictably improves the accuracy of the sensed row positions.
Claim 19
Regarding Claim 19,
The combination of Maeder, Susko, Mas, and Han establishes the system of Claim 14, which is the basis for Claim 19.
Disclosure by Maeder
Maeder discloses:
wherein the at least one positioning sensor
See at least:
“In some examples, the location sensor 114 includes multiple location sensors.” ([0040])
Rationale:
Express. Location sensor 114, which may include multiple location sensors, is the at least one positioning sensor.
includes a global positioning system (GPS) receiver
See at least:
“The location sensor 114 of the illustrated example is a global positioning system (GPS) sensor combined with an inertial sensor.” ([0040])
Rationale:
Express. The location sensor is a GPS sensor; a GPS sensor determines position by receiving satellite signals, i.e., it is a GPS receiver.
and an inertial measurement unit (IMU).
See at least:
“For example, if the vehicle 102 is tilted on a hill, the inertial sensor can compensate for this tilt to enable accurate determination of a location of the vehicle 102, and more specifically, accurate determination of locations of portions of the implement 108.” ([0040])
Rationale:
Implicit/PHOSITA-obvious. Maeder’s inertial sensor measures the vehicle’s tilt to correct the GPS location. An inertial sensor that measures vehicle attitude for GPS correction is conventionally implemented as an inertial measurement unit (accelerometers and gyroscopes); Maeder does not use the term “IMU”, but the IMU is the standard form of the inertial sensor it describes.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to implement the positioning sensor of the claim 14 combination as a GPS receiver with an IMU, as Maeder’s GPS-plus-inertial location sensor teaches ([0040]). An IMU is the conventional inertial device for measuring vehicle attitude, and pairing it with GPS predictably improves the accuracy of the position and orientation used to locate the rows.
Claim 20
Regarding Claim 20,
The combination of Maeder, Susko, Mas, and Han establishes the system of Claim 14, which is the basis for Claim 20.
Disclosure by Maeder
Maeder discloses:
wherein the processing system is further configured
See at least:
“The example controller 116 of the illustrated example of FIG. 1 analyzes data from one or more sensors and enables automated operation of the vehicle 102.” ([0041])
Rationale:
Express. Controller 116 analyzes sensor data for automated guidance, i.e., a processing system configured for the additional functions.
between the agricultural vehicle
See at least:
“The navigation display portion 704 includes an example vehicle position indicator 706 displaying a current position of the vehicle 102 relative to the field” ([0080])
Rationale:
Express. The controller tracks the current position of the vehicle, the vehicle side of the recited error.
and centers of lanes between crop rows,
See at least:
“The guidance line generator 218 of the illustrated example of FIG. 2 can generate the guidance line 620 centrally such that the twelve-row implement of the subsequent vehicle 610 can operate upon all of the twelve crops rows without the subsequent vehicle 610 running over any of the crop rows” ([0078])
Rationale:
Express. The guidance line is placed centrally between crop rows, i.e., at the center of the lane. In the combination, the lane center is the midpoint between adjacent row centers located by Susko ([0072]).
Claim Limitations Not Explicitly Disclosed by Maeder
Maeder does not explicitly disclose the following claim limitations:
to determine cross-track error
and to apply the cross-track error
to the position and orientation data
when calculating the navigation space coordinates.
Disclosure by Susko
Susko discloses:
to determine cross-track error
See at least:
“FIG. 8 also shows step 308 including sub-step 812, which includes estimating, by the processor, a heading error and a cross track at a selected look ahead distance of the agricultural vehicle based on the fit.” ([0081])
Rationale:
Express. The processor estimates the cross track of the vehicle relative to the fitted crop-row centers. Measured against the lane center of limitation 5, the same computation yields the cross-track error between the vehicle and the lane center.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to configure the processing system to determine the cross-track error between the vehicle and the lane center, as Susko teaches ([0081]-[0082]), because Maeder’s guidance is referenced to lane centers ([0078]). This is the predictable use of a known measurement.
Claim Limitations Not Explicitly Disclosed by the Combination of Maeder and Susko
After combining the teachings of Maeder and Susko, the following claim limitations are not explicitly disclosed:
and to apply the cross-track error
to the position and orientation data
when calculating the navigation space coordinates.
Disclosure by Mas
Mas discloses:
and to apply the cross-track error
See at least:
“After the camera's center of coordinates has been converted to a global frame, coordinates of any point sensed in an image can be referred to a global frame. To do so, a transformation can be made between camera coordinates (centered at the left frame) and global coordinates (East, North) for the sensed points in the images captured by the camera.” ([0178])
“The camera calibration information is then retrieved (step 86) and used with the disparity image to produce the camera coordinates (step 88) for sensed points found in the images.” ([0189])
Rationale:
Express as to the transformation; PHOSITA-obvious as to applying it with the cross-track error, which is the proposed application of Mas’s teaching. Mas transforms a point sensed by the vehicle-mounted camera into global coordinates by applying its coordinates (X_c, Y_c) to a position (N_n, E_n) and yaw angle Θ: N = N_n + X_c·sinΘ + Y_c·cosΘ and E = E_n + X_c·cosΘ − Y_c·sinΘ ([0178]). This is q = p + R(Θ)·v, where p is a position, R(Θ) the rotation by the heading, and v the point’s local coordinates. In the parent combination the steps are: (i) the lane-center point (the midpoint between adjacent detected rows, limitation 5) is located in metric camera coordinates from the stereo disparity and calibration ([0189]), rather than in image pixels as Susko expresses its cross track ([0082]); (ii) because the camera is rigidly mounted at a known location and attitude on the vehicle (Mas [0119]; the same known-offset principle Maeder applies to its location sensor, [0064]), the camera-frame point is converted into the vehicle frame by that fixed mounting transform; a camera-frame measurement is not used directly as a vehicle measurement; (iii) the lateral component of the lane-center point in the vehicle frame is the cross-track error between the vehicle and the lane center (limitations 3-5); and (iv) applying the vehicle-frame vector v, whose lateral component is that cross-track error, to the vehicle position p and orientation Θ through Mas’s transformation gives the lane-center navigation coordinate. Step (iv) applies the cross-track error to the position and orientation of the vehicle. Mas does not expressly describe using a cross-track error in this way; that use is the proposed obviousness application of Mas’s transformation. The instant specification uses the claim language in the same sense: it places the vehicle position in navigation space using the vehicle pose and adds the reported cross-track error to locate the lane center (Spec. [0079]), and states that “The system may utilize the vehicle’s cross-track error (XTE) to compute points of the desired guidance line” (Spec. [0095]). This mapping relies on the coordinate calculation, not on steering correction; Han’s use of off-track error to compensate heading ([0047]) is not relied on for this limitation.
to the position and orientation data
See at least:
“Since the local map System of reference is fixed to the vehicle, the relative orientation of the local map axes with the global map axes (fixed with respect to the vehicle) will be different according to the direction of travel of the vehicle.” ([0221])
Rationale:
Express. Mas’s transformation uses the vehicle position (image origin) and orientation (orientation angle and direction of travel), i.e., the position and orientation data to which the cross-track error is applied.
when calculating the navigation space coordinates.
See at least:
“Every camera location implies a local map whose ground coordinates must be transformed to global coordinates.” ([0201])
Rationale:
Express. Every vehicle-relative local map is transformed to global coordinates, i.e., the cross-track error is applied in the course of calculating the navigation space coordinates.
Motivation to Combine Maeder, Susko, Mas, and Han
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Maeder, Susko, Mas, and Han before them, to configure the processing system to apply the calibrated cross-track error, as the lateral component of a vehicle-frame vector, to the position and orientation data in Mas’s local-to-global transformation when calculating the navigation space coordinates ([0178], [0201], [0221]). The guidance data are stored in a global frame (Maeder [0048]), so the vehicle-relative measurement must be combined with the pose before it can be stored and reused. This predictably yields accurate lane-center coordinates.
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 OLUWABUSAYO ADEBANJO AWORUNSE whose telephone number is (571)272-4311. The examiner can normally be reached M - F (8:30AM - 5PM).
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/OLUWABUSAYO ADEBANJO AWORUNSE/Examiner, Art Unit 3662
/JELANI A SMITH/Supervisory Patent Examiner, Art Unit 3662
