DETAILED CORRESPONDENCE
This Office action is in response to the application filed 3/21/2025.
Claim Status
Claims 1-15 are pending.
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 .
Priority
Acknowledgment is made of applicant's claim for foreign priority based on an application filed in United Kingdom on 5/08/2024. It is noted, however, that applicant has not filed a certified copy of the GB2406435.4 application as required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 5/07/2025 and 7/28/2025 complies with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-8 and 11-15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Qadir et al., US 2024/0126269 hereinafter “Qadir”.
Claims 1, 13, 14 and 15. Qadir teaches a computer-implemented method of generating directional information for a harvesting vehicle, the computer-implemented method comprising:
receiving point cloud data comprising a representation of a region ahead of the harvesting vehicle (fig. 3 illustrates the region ahead and fig. 2A, item S201 teaches “location-determining receiver, the current observed position data comprising altitude data and attitude data of the ground associated with the front region.” and fig. 2A, item S200 teaches “point cloud” );
processing the point cloud data to identify a target region, in the point cloud data, that bounds a representation of unharvested crop in the point cloud data (fig. 2A, item S212 teaches “a processing system to estimate a yield or differential yield for the front region”); and
generating the directional information by processing an edge of the target region ([0088] teaches “processing system 302” and “edge detector” for detecting the edge.), wherein the directional information indicates a target direction for the harvesting vehicle to harvest the edge of the unharvested crop ([0033]—“unharvest state”).
Furthermore, Qadir teaches in (0087] FIG. 4A illustrates one embodiment of a vehicle 402 ( e.g., combine or harvester) with a sensor for estimating an upper point cloud of a crop canopy in a field of interest (e.g., generally rectangular field of interest) in the direction of travel 414 of the vehicle 402, or a lower point cloud of the ground in the field of interest, or both. The vehicle 402 comprises a header 404 for harvesting (e.g., cutting and gathering) a crop… and system for controlling a vehicle 402 for harvesting of crop such the system of FIG. 1.” While [0048] teaches (0048] The electronic data processor 363 is coupled to a data bus 362 to support communication, execution of software instructions and processing of data associated with the data storage device 361 and the data port(s) 377.
Claim 2. Qadir teaches the computer-implemented method of claim 1 and further teaches, wherein:
the harvesting vehicle (fig. 4A, item 402—“vehicle”) comprises:
a sensor configured to generate the point cloud data (fig. 4A, item 301—“imaging device”); and
a crop cutting arrangement, having a predetermined spatial relationship with respect to the sensor (fig. 4A, item 404—“cutting bar”); and
the target direction indicates a direction in which the crop cutting arrangement is predicted to intersect with the edge of the unharvested crop ([0031] reads on this element as such—“In one embodiment, the region of interest calibration module 308 is configured to collect image data on or to scan the region of interest in front of the vehicle (e.g., combine 402) in the direction of travel 414 to capture the images or stereo images, where the region of interest may extend laterally based on the width 412 of the vehicle 402, or its implement (e.g., header 404 or cutting bar), or the swath of the vehicle 402. The region of interest calibration module 308 may increase the extent or dimension of the forward-most portion along the longitudinal axis in the direction of travel 414 for the full lateral width 412 of the vehicle 402 or its implement. The region of interest calibration module 308 may optionally be configured to align with the extent of adjoining hexagonal cells.”).
Claim 3. Qadir teaches the computer-implemented method of claim 1 further teaches, wherein processing the point cloud data comprises performing segmentation on the point cloud data to identify the representation of unharvested crop ([0041] reads on this element as such—“The ground elevation estimator 314 may comprise an estimator for estimating a lower point cloud, or a ground plane estimator that is configured to estimate a ground plane of the vehicle 402 within the region of interest, such as modeling of a simple ground plane or a complex ground plane with break-lines, curved break-line segments, breaks, slopes or curved slopes, based on the ground elevation data, position data, attitude data, and motion data for one or more cells or points within a region of interest.”).
Claim 4. Qadir teaches the computer-implemented method of claim 1 further teaches, wherein generating the directional information comprises:
processing the target region to identify edge data elements, being data elements of the point cloud data that represent an edge of the target region ([0031] reads on this element as such—“In one embodiment, the region of interest calibration module 308 is configured to collect image data on or to scan the region of interest in front of the vehicle (e.g., combine 402) in the direction of travel 414 to capture the images or stereo images, where the region of interest may extend laterally based on the width 412 of the vehicle 402, or its implement (e.g., header 404 or cutting bar); and
processing the identified edge data elements to generate the directional information ([0088] reads on this element as such “In one embodiment, the image processing system 302 or control system 350 may comprise a color discrimination module 366, alone or in combination with an object edge detector, to detect or identify pixels of the image data.).
Claim 5. Qadir teaches the computer-implemented method of claim 4 further teaches, wherein processing the identified edge data elements comprises:
performing segmentation on the identified edge data elements to identify a line representing the edge of the target region (the element is best illustrated in fig. 4A); and
processing the identified line to generate the directional information ([0041]—“The ground plane estimator may be modeled as a series of points, straight line segments, curved line segments, or corresponding equations.”).
Claim 6. Qadir teaches the computer-implemented method of claim 1 and further teaches, wherein generating the directional information comprises:
monitoring a travel direction of the harvesting vehicle ([0031]—“direction of travel 414”);
processing the monitored travel direction to identify an edge of a harvesting region in the point cloud data ([0031]—“region of interest”, [0034]—“field edges”),
wherein the harvesting region bounds a representation of a zone that the harvesting vehicle would harvest if proceeding in the monitored travel direction ([0034]—“ boundaries (e.g., external or internal boundaries)
of the field or work area”); and
processing the edge of the target region and the edge of the harvesting region to identify a target direction for the harvesting vehicle that would align the edge of the harvesting region with the edge of the target region ([0034]—“ However, the boundaries (e.g., external or internal boundaries) of the field or work area may have exclusion zones that the classifier 312 or electronic data processor 363 will no evaluate for crops or plants. The exclusion zones may comprise waterways, swamps, wetlands, gullies, streams, rivers, steep slopes, hazards, treelined areas, brush, obstacles, or field edges, or terrain features, where crops or plants to be harvested or not propagated or grown.”).
Claim 7. Qadir teaches the computer-implemented method of claim 6 further teaches, wherein:
the monitored travel direction and the point cloud data are defined using different co-ordinate systems ([0031]-[0032] teaches – “In one embodiment, the region of interest calibration module 308 is configured to collect image data on or to scan the region of interest in front of the vehicle (e.g., combine 402) in the direction of travel 414 to capture the images or stereo images, where the region of interest may extend laterally based on the width 412 of the vehicle 402, or its implement (e.g., header 404 or cutting bar), or the swath of the vehicle 402….The camera to world transformation module 310 is configured to transform one or more point clouds ( e.g., preliminary three-dimensional point clouds), such as a lower point cloud (representative of the ground) and an upper point cloud (representative of the crop canopy) in the same region of interest, of the common reference frame of the imaging device 301 to ( e.g., refined three-dimensional point clouds) in a real world reference frame.”); and
generating the directional information comprises transforming the co-ordinate system of the monitored travel direction and/or the point cloud data such that the travel direction and the point cloud data share a common co-ordinate system ([0035]—“[0036] teaches “A location-determining receiver 320 may comprise a satellite receiver, a global satellite system navigation receiver (GNSS), or another receiver for estimating a position ( e.g., three-dimensional geographic coordinates)”).
Claim 8. Qadir teaches the computer-implemented method of claim 7 and further teaches, wherein transforming the co- ordinate system of the monitored travel direction and/or the point cloud data comprises transforming the point cloud data to the co-ordinate system of the monitored travel direction ([0035] and [0036] teaches “A location-determining receiver 320 may comprise a satellite receiver, a global satellite system navigation receiver (GNSS), or another receiver for estimating a position (e.g., three-dimensional geographic coordinates)…. GNSS receiver that uses an RTK real-time kinematic reference station to provide correction data or differential carrier phase corrections to estimate or improve estimates of position, attitude or motion data”).
Claim 11. Qadir teaches the computer-implemented method of claim 1, further comprising controlling a steering of the harvesting vehicle, responsive to the directional information, to follow the target direction ([0052] teaches that “The controller 324 is coupled to a guidance/implement module. The guidance/implement system 359 comprises a steering controller 351 coupled to a steering system 352; a braking controller 355 coupled to a breaking system, a propulsion controller 353 coupled to a propulsion system 354 and an implement controller 357 coupled to an implement system 358.”).
Claim 12. Qadir the computer-implemented method of claim 1, further comprising:
obtaining a target route for the harvesting vehicle, wherein the target route is generating using mapping data of an area for harvesting by the harvesting vehicle ([0039] teaches “Accordingly, each of the lower point cloud and the upper point cloud, or a pair of lower point cloud and upper point cloud for the region of interest or cells within the field can be indexed or references to the position of the vehicle 402, where the three-dimensional position may include the ground elevation that corresponds to the geographic location of a cell or point with the field in each successive region of interest (which shifts as the vehicle 402 progresses through the field or worksite ).”);
controlling a steering of the harvesting vehicle to follow the target route; and
updating the target route responsive to the directional information ([0041] and [0052] teaches that “For example, the stored ground height terrain map can be accessed to provide a correction or compensation to a ground elevation that is derived from the lower point cloud or collected image data of region of interest. One possible correction or compensation to potential height error 590 in the ground elevation data
is set forth in FIG. 5, for instance. The guidance/implement system 359 comprises a steering controller 351 coupled to a steering system 352).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over Qadir in view of Maeder et al, US 2020/0352082 hereinafter “Maeder”.
Claim 9. Qadir teaches the computer-implemented method of claim 1; Qadir is silent on the term display, Yet, Maeder teaches further comprising controlling a display to provide a user-perceptible output of the directional information ([0054] teaches “The example user interface configurator 214 of the illustrated example of FIG. 2 configures the user interface 122. For example, the user interface configurator 214 can communicate data and/or images to be displayed on the user interface 122.” ).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaches of Maeder with the teaching of Qadir because such a combination would provide visual mapping data to an operator (see [0041], Harris).
Claim 10. Qadir teaches the computer-implemented method of any claim 1 and teaches further, comprising:
monitoring a of the harvesting vehicle ([0034] teaches classifier that monitors external and internal boundaries).
However, Qadir does not teach the term deviating. Yet, Maeder teaches controlling an alert system to generate a user-perceptible alert responsive to the monitored direction deviating by more than a predetermined amount from the target direction (fig. 7 best illustrates this element. While [0030] describes a deviation).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaches of Maeder with the teaching of Qadir because such a combination would provide visual mapping data to an operator (see [0041], Harris).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANA D THOMAS whose telephone number is (571)272-8549. The examiner can normally be reached Monday - Friday 8 - 5.
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/A.D.T/Examiner, Art Unit 3661
/RUSSELL FREJD/Primary Examiner, Art Unit 3661
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