Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
This communication is in response to the action filed on 05/29/2026.
Claims 1, 5, 9, 12, 15, 18, 22, 26, 30, and 33 are currently amended. Claims 10, 11, 28, and 29 are canceled. Claims 1, 5, 7, 9, 12, 14-18, 22, 24, 26, 27, 30, and 32-34 are currently pending.
Response to Arguments
Applicant’s arguments filed on 05/29/2026 on pages 7-12, under REMARKS with respect to 35
U.S.C. 102 and 103 claim rejections to claims 1, 5, 7, 9, 12, 14-18, 22, 24, 26-27, 30, and 32-34 have been fully considered and are persuasive. The rejections to the claims have been withdrawn. However, upon further consideration, a new ground of rejection is made in view of US 2024/0042698 A1.
Applicant’s arguments filed on 05/29/2026 on pages 7-12, under REMARKS with respect to claim objections to claims 5, 9, 15, 22, 26, and 33 have been fully considered and are persuasive. The objections to the claims have been withdrawn.
Information Disclosure Statement
The information disclosure statement (IDS) filed on 03/30/2026 has been fully considered.
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 non-obviousness.
Claims 1, 5, 12, 14, 17-18, 22, 24, 27, 30, 32 are rejected under 35 § U.S.C. 103 as being obvious over US 2020/0041649 A1 to GREEN et al. (hereinafter “GREEN”) in view of US 2024/0042698 A1 to LAPPAS et al. (hereinafter “LAPPAS”).
As per claim 1, GREEN discloses a method of detecting surface deformation of a production asset (a system and corresponding method for generating a geometry model of an object of interest using 3D point cloud scans of the object which is acting as the asset; abstract; figs 3-5 and 15; paragraphs [0036], [0043], [0074-0075]), the method comprising: receiving a point cloud for a surface of the production asset (the computing system comprising a LIDAR sensor is used to acquire (receive) a plurality of points from a 3D point cloud situated about the object of interest; abstract; figs 3-5 and 15; paragraphs [0036], [0043], [0074-0075]); determining a model surface for the production asset from the point cloud (forming a surface geometry model of the candidate object based on the points collected from the LIDAR point cloud of the object; paragraphs [0034], [0037], [0043]), the model surface being an estimate of a deformation free representation of the surface of the production asset (forming a range hypothesis test comparing an expected range from the geometry model of the candidate object in comparison with the measured range of points in the LiDAR point cloud scan and deriving an error measure there between; paragraph [0043]), the model surface being determined from points in the point cloud including points representing a surface deformation (testing the range hypothesis for a series of expected locations for the surface geometry model of the candidate object and determining a likely lowest error measure; paragraph [0043]); determining a distance between at least one point in the point cloud and the model surface (the system and method is adapted to determine a mismatch distance between the kinematic reference and the machine geometry, the length (a determined distance) of the pitch-brace is altered to optimize the rake angle of the dipper teeth and updated to the internal model; paragraph [0080]); and outputting the distance (the parameters include limb/element length and would be output to be displayed via a output of device A going into an input of device B to be displayed or viewed by users; paragraphs [0036], [0154]). GREEN fails to disclose wherein the distance between the at least one point in the point cloud and the model surface is compensated for the model surface being determined from points in the point cloud including points representing the surface deformation and the distance is compensated independent of a location of the at least one point in the point cloud.
LAPPAS discloses wherein the distance between the at least one point in the point cloud and the model surface is compensated for the model surface being determined from points in the point cloud including points representing the surface deformation (the system is directed to computer based models which generate a 3D point cloud based object model and adjusts for alterations such as welding on the real object by performing model compensation to match the alteration made, this is done by using parameters of the object such as distance to modify the forming instructions (e.g., in these regions) to at least partially compensate for such deformations, where the test objects/models are used for comparison between the test model and the test object, and comparison of a metrological characteristics such as, distance and/or shape between at least two markers (points) in test model and the respective at least two markers of the test object; abstract; paragraphs [0125], [0143-0144], [0149]) and the distance is compensated independent of a location of the at least one point in the point cloud (the model and corresponding distance is compensated for alterations using markers on the model not points of the point cloud used to generate the model and therefore is independent of the at least one point in the point cloud; abstract; paragraphs [0125], [0143-0144], [0149]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify GREEN to have distance between the at least one point in the point cloud and the model surface is compensated of LAPPAS reference. The Suggestion/motivation for doing so would have been to provide the ability to provide compensation/alteration information which can be used to modify the forming instructions, in the desired regions to at least partially compensate for such deformations made on the real object so they are accurately reflected in the object model as suggested by paragraph [0143] of LAPPAS. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine LAPPAS with GREEN to obtain the invention as specified in claim 1.
As per claim 5, GREEN in view of LAPPAS discloses the method according to claim 1. Modified GREEN further discloses further comprising: smoothing points in the point cloud using locations of a plurality of neighboring points in the point cloud (the point cloud geometry model parameters include a smoothing parameter among others; paragraph [0108]).
As per claim 7, GREEN in view of LAPPAS discloses the method according to claim 1. Modified GREEN further discloses further comprising: calculating a maximum distance between points in the point cloud and the model surface (a maximum displacement distance is calculated between the object and the point cloud generated via lidar sensor; fig 14; paragraphs [0124]); and associating the maximum distance with the production asset (the maximum displacement is indicated by a number included in each cell of the object of interest; fig 14; paragraphs [0060], [0124]).
As per claim 12, GREEN in view of LAPPAS discloses the method according to claim 1. Modified GREEN further discloses wherein the distance is compensated using a linear transform applied to an initial distance between the at least one point in the point cloud and the model surface (a linear transform such as a linear least squares minimization is applied to the model and the corresponding point cloud of the object; paragraph [0120]).
As per claim 14, GREEN in view of LAPPAS discloses the method according to claim 1. Modified GREEN further discloses wherein the model surface is determined using a model selected from a plurality of models (the geometry model is selected from six base models and adjusted to fit the point cloud data of the object accordingly; paragraph [0037]).
As per claim 17, GREEN in view of LAPPAS discloses the method according to claim 1. Modified GREEN further discloses wherein outputting the distance further comprises: determining a maximum distance between point in the point cloud and the model surface (a maximum displacement distance is calculated between the object and the point cloud generated via lidar sensor; fig 14; paragraphs [0124]); classifying the point cloud for the surface according to the maximum distance (the point cloud point is classified as within the error tolerance or not within the error tolerance according to the displacement distance maximum that was calculated; fig 14; paragraphs [0037-0039], [0124]); and displaying the point cloud to a user according to the classification (the parameters including those associated with the maximum distance to the point cloud and would be output to be displayed via a output of device A going into an input of device B to be displayed or viewed by users; paragraphs [0036], [0154]).
As per claim 18, GREEN discloses a system for detecting surface deformation of a production asset comprising at least one processing system configured to: receive a point cloud for a surface of the production asset; determine a model surface for production asset from the point cloud, the model surface being an estimate of a deformation free representation of the surface of the production asset, the model surface being determined from points in the point cloud including points representing a surface deformation; and determine a distance between at least one point in the point cloud and the model surface; and output the distance. GREEN fails to disclose wherein the distance between the at least one point in the point cloud and the model surface is compensated for the model surface being determined from points in the point cloud including points representing the surface deformation and the distance is compensated independent of a location of the point in the point cloud.
LAPPAS discloses wherein the distance between the at least one point in the point cloud and the model surface is compensated for the model surface being determined from points in the point cloud including points representing the surface deformation (the system is directed to computer based models which generate a 3D point cloud based object model and adjusts for alterations such as welding on the real object by performing model compensation to match the alteration made, this is done by using parameters of the object such as distance to modify the forming instructions (e.g., in these regions) to at least partially compensate for such deformations, where the test objects/models are used for comparison between the test model and the test object, and comparison of a metrological characteristics such as, distance and/or shape between at least two markers (points) in test model and the respective at least two markers of the test object; abstract; paragraphs [0125], [0143-0144], [0149]) and the distance is compensated independent of a location of the point in the point cloud (the model and corresponding distance is compensated for alterations using markers on the model not points of the point cloud used to generate the model and therefore is independent of the at least one point in the point cloud; abstract; paragraphs [0125], [0143-0144], [0149]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify GREEN to have distance between the at least one point in the point cloud and the model surface is compensated of LAPPAS reference. The Suggestion/motivation for doing so would have been to provide the ability to provide compensation/alteration information which can be used to modify the forming instructions, in the desired regions to at least partially compensate for such deformations made on the real object so they are accurately reflected in the object model as suggested by paragraph [0143] of LAPPAS. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine LAPPAS with GREEN to obtain the invention as specified in claim 18.
As per claim 22, GREEN in view of LAPPAS discloses the system according to claim 18. Modified GREEN further discloses wherein the at least one processing system is further configured to: smooth points in the point cloud using locations of a plurality of neighboring points in the point cloud (the point cloud geometry model parameters include a smoothing parameter among others; paragraph [0108]).
As per claim 24, GREEN in view of LAPPAS discloses the system according to claim 18. Modified GREEN further discloses wherein the at least one processing system is further configured to: calculate a maximum distance between points in the point cloud and the model surface (a maximum displacement distance is calculated between the object and the point cloud generated via lidar sensor; fig 14; paragraphs [0124]); and associating the maximum distance with the production asset (the maximum displacement is indicated by a number included in each cell of the object of interest; fig 14; paragraphs [0060], [0124]).
As per claim 27, GREEN in view of LAPPAS discloses the system according to claim 18. Modified GREEN further discloses wherein the at least one processing system is further configured to, when outputting the distance: determine a maximum distance between point in the point cloud and the model surface (a maximum displacement distance is calculated between the object and the point cloud generated via lidar sensor; fig 14; paragraphs [0124]); classify the point cloud for the surface according to the maximum distance (the point cloud point is classified as within the error tolerance or not within the error tolerance according to the displacement distance maximum that was calculated; fig 14; paragraphs [0037-0039], [0124]); and display the point cloud to a user according to classification (the parameters including those associated with the maximum distance to the point cloud and would be output to be displayed via a output of device A going into an input of device B to be displayed or viewed by users; paragraphs [0036], [0154]).
As per claim 30, GREEN in view of LAPPAS discloses the system according to claim 18. Modified GREEN further discloses wherein the distance is compensated using a linear transform applied to an initial distance between the at least one point in the point cloud and the model surface (a linear transform such as a linear least squares minimization is applied to the model and the corresponding point cloud of the object; paragraph [0120]).
As per claim 32, GREEN in view of LAPPAS discloses the system according to claim 18. Modified GREEN further discloses wherein the model surface is determined using a model selected from a plurality of models (the geometry model is selected from six base models and adjusted to fit the point cloud data of the object accordingly; paragraph [0037]).
Claims 9, 15-16, 26, 33-34 are rejected under 35 § U.S.C. 103 as being obvious over US 2020/0041649 A1 to GREEN et al. (hereinafter “GREEN”) in view of US 2024/0042698 A1 to LAPPAS et al. (hereinafter “LAPPAS”) in view of US 2017/0193699 A1 to MEHR et al. (hereinafter “MEHR”).
As per claim 9, GREEN in view of LAPPAS discloses the method according to claim 1. Modified GREEN fails to disclose wherein the model surface may be fitted to a curved surface and is a parameterized polynomial model.
MEHR discloses wherein the model surface may be fitted to a curved surface and is a parameterized polynomial model (the system is adapted to apply 3D mesh models adapted to detect curvature on the surface of the mesh, and is based on a polynomial deformation model; paragraphs [0054] [0087], [0098]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to further modify GREEN to have the model fitted to a curved surface using a polynomial model of MEHR reference. The Suggestion/motivation for doing so would have been to provide ability to more accurately measure curvature or lack thereof using mesh models and to provide a best fit model as suggested by paragraphs [0054], [0059]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine MEHR with modified GREEN to obtain the invention as specified in claim 9.
As per claim 15, GREEN in view of LAPPAS discloses the method according to claim 14. Modified GREEN fails to disclose wherein the plurality of models includes at least two models selected from the set including a parameterized polynomial model, a piecewise polynomial model and a rigid shape defined by a set of parameters.
MEHR discloses wherein the plurality of models includes at least two models selected from the set including a parameterized polynomial model, a piecewise polynomial model and a rigid shape defined by a set of parameters (the system is adapted to generate a parameterized model of polynomial to find that of best fit to match the shape of the object which would be rigid; paragraphs [0054], [0059-0061], [0087], [0098]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to further modify GREEN to have a piecewise polynomial model and a rigid shape defined by a set of parameters of MEHR reference. The Suggestion/motivation for doing so would have been to provide ability to more accurately measure curvature or lack thereof using mesh models and to provide a best fit model as suggested by paragraphs [0054], [0059]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine MEHR with modified GREEN to obtain the invention as specified in claim 15.
As per claim 16, GREEN in view of LAPPAS discloses the method according to claim 14. Modified GREEN fails to disclose wherein each of the plurality of models is compared to the point cloud and the model is selected according to a best fit.
MEHR discloses wherein each of the plurality of models is compared to the point cloud and the model is selected according to a best fit (the system is adapted to based on selected parameters chosen by the user choose a polynomial model of best fit to fit the object of interest; paragraphs [0054], [0059-0061]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to further modify GREEN to have wherein each of the plurality of models is compared to the point cloud and the model is selected according to a best fit of MEHR reference. The Suggestion/motivation for doing so would have been to provide ability to more accurately measure curvature or lack thereof using mesh models and to provide a best fit model as suggested by paragraphs [0054], [0059]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine MEHR with modified GREEN to obtain the invention as specified in claim 16.
As per claim 26, GREEN in view of LAPPAS discloses the system according to claim 18. Modified GREEN fails to disclose wherein the model surface may be fitted to a curved surface and is a parameterized polynomial model.
MEHR discloses wherein the model surface may be fitted to a curved surface and is a parameterized polynomial model (the system is adapted to apply 3D mesh models adapted to detect curvature on the surface of the mesh, and is based on a polynomial deformation model; paragraphs [0054] [0087], [0098]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to further modify GREEN to have wherein the model surface may be fitted to a curved surface and is a polynomial model of MEHR reference. The Suggestion/motivation for doing so would have been to provide ability to more accurately measure curvature or lack thereof using mesh models and to provide a best fit model as suggested by paragraphs [0054], [0059]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine MEHR with modified GREEN to obtain the invention as specified in claim 26.
As per claim 33, GREEN in view of LAPPAS discloses the system according to claim 32. Modified GREEN fails to disclose wherein the plurality of models includes at least two models selected from the set including a parameterized polynomial model, a piecewise polynomial model and a rigid shape defined by a set of parameters.
MEHR discloses wherein the plurality of models includes at least two models selected from the set including a parameterized polynomial model, a piecewise polynomial model and a rigid shape defined by a set of parameters (the system is adapted to generate a parameterized model of polynomial to find that of best fit to match the shape of the object which would be rigid; paragraphs [0054], [0059-0061], [0087], [0098]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to further modify GREEN to have a piecewise polynomial model and a rigid shape defined by a set of parameters of MEHR reference. The Suggestion/motivation for doing so would have been to provide ability to more accurately measure curvature or lack thereof using mesh models and to provide a best fit model as suggested by paragraphs [0054], [0059]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine MEHR with modified GREEN to obtain the invention as specified in claim 33.
As per claim 34, GREEN in view of LAPPAS discloses the system according to claim 32. Modified GREEN fails to disclose wherein each of the plurality of models is compared to the point cloud and the model is selected according to a best fit.
MEHR discloses wherein each of the plurality of models is compared to the point cloud and the model is selected according to a best fit (the system is adapted to based on selected parameters chosen by the user choose a polynomial model of best fit to fit the object of interest; paragraphs [0054], [0059-0061]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to further modify GREEN to have wherein each of the plurality of models is compared to the point cloud and the model is selected according to a best fit of MEHR reference. The Suggestion/motivation for doing so would have been to provide ability to more accurately measure curvature or lack thereof using mesh models and to provide a best fit model as suggested by paragraphs [0054], [0059]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine MEHR with modified GREEN to obtain the invention as specified in claim 34.
Conclusion
Examiner's Note: Examiner has cited figures, and paragraphs in the references as applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested for the applicant, in preparing the responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. Examiner has also cited references in PTO892 but not relied on, which are relevant and pertinent to the applicant’s disclosure, and may also be reading (anticipatory/obvious) on the claims and claimed limitations. Applicant is advised to consider the references in preparing the response/amendments in-order to expedite the prosecution.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DEVIN JACOB DHOOGE whose telephone number is (571) 270-0999. The examiner can normally be reached 7:30-5:00.
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/D J DHOOGE/Examiner, Art Unit 2677
/ANDREW W BEE/Supervisory Patent Examiner, Art Unit 2677
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