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 .
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 1-7, 9-13 and 28 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Hebb, et al., US 2023/0011137 A1.
As per Claim 1, Hebb teaches a mapping system for mapping a farm (¶¶ 28, 33; for “agricultural path planning”), the mapping system comprising:
a processing structure (¶ 41; processing apparatus 130 of Figure 1);
at least one sensor system providing sensor data to the processing structure (¶ 41; with motion sensors 142 or image sensors 144 or distance sensors 146 of Figure 1);
at least one communication device (¶¶ 45-46);
a power platform for propelling the mapping system through the farm (¶ 43; “engines”);
the at least one sensor system comprises a field of view relative to the power platform (¶ 47; with “respective fields of view that overlap”);
at least one tangible computer-readable memory device storing a plurality of instructions to be executed by the processing structure (¶ 44);
wherein the processing structure retrieves at least one overview map of the farm via the at least one communication device (¶¶ 52-53; per “a boundary data structure that encodes a polygon on a map”).
As per Claim 2, Hebb teaches that the processing structure determines at least one estimated field feature from the at least one overview map (¶ 69; “border”).
As per Claim 3, Hebb teaches:
that the processing structure displays the at least one overview map on a user interface (¶ 56); and
receives user inputs corresponding to drawing of at least one estimated field feature (¶ 57; a “user can also specify using exact GPS coordinates of a line and the precise offsets from this line that the set of parallel lines should be generated on”).
As per Claim 4, Hebb the estimated field features are selected from at least one of: an estimated external field boundary (¶¶ 32, 69; “border”), an estimated internal field boundary, an estimated field entrance, and an estimated starting point location.
As per Claim 5, Hebb teaches:
that the processing structure detects a portion of the estimated field features within the field of view of the sensor data (¶ 55; “obstacles represented by exclusionary polygons”);
calculates a position of the portion of the estimated field features based on the sensor data (¶ 74); and
adjusts the portion of the estimated field features to determine a calculated field feature for the portion of the estimated field features (¶ 74; ” the distance of the unfitting curves may be moved further from the obstacle and along the path proceeding towards or away from the polygon”).
As per Claim 6, Hebb teaches that the processing structure creates and updates a local map of the estimated field features around the power platform using the sensor data (¶¶ 47-48; after taking data from image sensors 144 and distance sensors 146 of Figure 1).
As per Claim 7, Hebb teaches that the processing structure creates and updates a global map of the estimated field features at the farm using the sensor data and the local map (¶¶ 56-57).
As per Claim 9, Hebb teaches that the processing structure calculates the position of the portion of the estimated field features by determining a non-field area and a field area (¶¶ 70-72; based on areas inside and “outside of the border”).
As per Claim 10, Hebb teaches that the processing structure determines at least one crop row and determines a crop row space between crop rows (¶ 57).
As per Claim 11, Hebb teaches that the processing structure calculates the position of the portion of the estimated field features based on the crop rows and the crop row space (¶ 74; for the purposes of “[a]voiding obstacles”).
As per Claim 12, Hebb teaches that the processing structure calculates the position of the portion of the estimated field features based on a position of an attached implement and a relative position of a tip of the attached implement (¶ 53).
As per Claim 13, Hebb teaches that the at least one sensor system comprises at least one of: a magnetometer (¶ 46), an imaging sensor (¶ 144; image sensors 144 of Figure 1), a range sensor, a radio detection and ranging (radar), a sound navigation and ranging (sonar), inertial sensors, and a global positioning sensor (¶ 46).
As per Claim 28, Hebb teaches that the estimated field features are selected from at least one of: an estimated external field boundary (¶¶ 32, 69; “border”), an estimated internal field boundary, an estimated field entrance, and an estimated starting point location.
Claim Rejections - 35 USC § 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.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Hebb as applied to Claim 1 above, and further in view of Boardman, et al., US 2022/0301192 A1.
As per Claim 8, Hebb does not expressly teach that the processing structure calculates the position of the portion of the estimated field features using an artificial neural network-based model. Boardman teaches that the processing structure calculates the position of the portion of the estimated field features using an artificial neural network-based model (¶ 155). At the time of the invention, a person of skill in the art would have thought it obvious to combine the mapping system of Hebb with the neural network system of Boardman, in order to recognize and categorize specific types of obstacles based on patterns.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ATUL TRIVEDI whose telephone number is (313)446-4908. The examiner can normally be reached Mon-Fri; 9:00 AM-5:00 PM EST.
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ATUL TRIVEDI
Primary Examiner
Art Unit 3661
/ATUL TRIVEDI/Primary Examiner, Art Unit 3661
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