DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This Office Action is in response to the Response to Non-Final Rejection filed October 9, 2025. Claims 1-20 are presently pending and presented for examination.
Response to Arguments
Applicant’s arguments with respect to claims 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
A detailed and updated rejection follows below.
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 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 1-4, 6, 8-11, 13, and 15-18, are rejected under 35 U.S.C. 103 as being unpatentable over Tan et al. (US 20190220019; hereinafter Tan, already of record in IDS), in view of Schwarz et al. (US 20200041560; hereinafter Schwartz, already of record), further in view of Koo et al. (US 20210266461; hereinafter Koo, already of record), further in view of White (US 20200279367, already of record), further in view of Das et al. (US 20220083774; hereinafter Das, already of record), and further in view of Bauer et al. (US 20220148445; hereinafter Bauer).
Regarding Claim 1,
Tan teaches
A system, comprising a processor configured to: (Tan: Abstract)
...
generate unmanned aerial vehicle (UAV)-specific commands based on the inspection mission; (Tan: Paragraph [0020]-[0021])
transmit the UAV-specific commands to an unmanned aerial vehicle (UAV) platform; (Tan: Paragraph [0035]-[0036])
receive images and sensor data from the UAV; (Tan: Paragraph [0015]-[0016])
…
Tan does not teach
receive an inspection request from an asset management system, wherein the inspection request includes target asset information comprising an asset ID of a target asset corresponding to a model in the asset management system, and wherein the target asset information further comprises feedback from previously completed inspection missions;
automatically generate an inspection mission based on the target asset information;
…
send the images and sensor data to an artificial intelligence (AI) services module;
detect one or more defects in the target asset and generate a three dimensional reconstruction of the target asset with the one or more detected defects via the AI services module, wherein the one or more defects comprise one or more cracks in the target asset;
receive feedback from the Al services module, wherein the feedback comprises information of the one or more detected defects and the generated three dimensional reconstruction;
dynamically modify the inspection mission based on the feedback, and
update the target asset information and the model based on the feedback and based on AI model requirements of the AI services module, wherein the updated target asset information comprises at least one modified inspection parameter and a position of the at least one crack on a surface of the target asset relative to offsets from surface corners of the target asset.
However in the same field of endeavor, Schwartz teaches
...
receive an inspection request from an asset management system, (Schwartz: Paragraph [0038], [0052]-[0053]; The asset management system (inspection manager) monitors data about the status of several components of the system, referred to as AOI data. When the system determines that at least one AOI requires inspection, it outputs an inspection request to an inspection/monitoring device in the form of an inspection path.) wherein the inspection request includes target asset information comprising an asset ID of a target asset corresponding to a model in the asset management system... (Schwartz: Paragraph [0050], FIG. 6)
automatically generate an inspection mission based on the target asset information; (Schwartz: Paragraph [0036], [0054])
...
It would be obvious for one with ordinary skill in the art before the effective filling date of the claimed invention to modify the UAV system of Tan, with the asset management system of Schwartz for the benefit of autonomous detection of damage to the components. (Schwartz: Abstract)
Tan, in view of Schwartz, does not teach
...
...and wherein the target asset information further comprises feedback from previously completed inspection missions;
...
send the images and sensor data to an artificial intelligence (AI) services module;
detect one or more defects in the target asset and generate a three dimensional reconstruction of the target asset with the one or more detected defects via the AI services module, wherein the one or more defects comprise one or more cracks in the target asset;
receive feedback from the Al services module, wherein the feedback comprises information of the one or more detected defects and the generated three dimensional reconstruction, and wherein the information comprises detection of a change in size of at least one crack, of the one or more cracks, from a previous size of the at least one crack included as part of the feedback from the previously completed inspection missions;
dynamically modify the inspection mission based on the feedback, and
update the target asset information and the model based on the feedback and based on AI model requirements of the AI services module, wherein the updated target asset information comprises at least one modified inspection parameter a position of the at least one crack on a surface of the target asset relative to offsets from surface corners of the target asset.
However in the same field of endeavor, Koo teaches
...
...and wherein the target asset information further comprises feedback from previously completed inspection missions; (Koo: Paragraph [0058]-[0061]; The “scan area” and “no scan area” are determined by the results of the calibration procedure.)
...
send the images and sensor data to an artificial intelligence (AI) services module; (Koo: Paragraph [0031])
detect one or more defects in the target asset via the AI services module; (Koo: Paragraph [0031])
receive feedback from the Al services module, wherein the feedback comprises information of the one or more detected defects in the target asset; (Koo: Paragraph [0031])
dynamically modify the inspection mission based on the feedback, (Koo: Paragraph [0059]-[0061]; The modifies the flight plan by determining a “scan area” (which requires scanning for defects) and a “no-scan area” which does not require scanning for defects and instructing the drone to only fly and scan the “scan area.”) wherein dynamically modifying the inspection mission comprises modifying a payload parameter based on the feedback to obtain improved images of the target asset, (Koo: Paragraph [0069], [0095]) and
update the target asset information based on the feedback and based on AI model requirements of the AI services module, wherein the modified target asset information comprises at least one modified inspection parameter... (Koo: Paragraph [0060]-[0061]; The determination of a “scan area” acts as the modified inspection parameter as the system is instructing the drone to only scan the newly defined “scan area” and ignore the “no-scan area” because the no-scan area is an area that has been determined to not contain defects.)
It would be obvious for one with ordinary skill in the art before the effective filling date of the claimed invention to modify the UAV system of Tan, in view of Schwarz, with the AI services module and flight plan modification of Koo for the benefit of enhanced defect detection utilizing a UAV. (Koo: Abstract and Paragraph [0001])
Tan, in view of Schwarz, and further in view of Koo, does not teach
...
...and generate a three dimensional reconstruction of the target asset with the one or more detected defects via the AI services module, wherein the one or more defects comprise one or more cracks in the target asset;
receive feedback from the Al services module, wherein the feedback comprises information of ... the generated three dimensional reconstruction, and wherein the information comprises detection of a change in size of at least one crack, of the one or more cracks, from a previous size of the at least one crack included as part of the feedback from the previously completed inspection missions;
update the...model based on the feedback and based on AI model requirements of the AI services module,...and a position of the at least one crack on a surface of the target asset relative to offsets from surface corners of the target asset.
However, in the same field of endeavor, White teaches
...
...and generate a three dimensional reconstruction of the target asset with the one or more detected defects via the AI services module, (White: Paragraph [0044], [0064], [0093]-[0094], [0103]) wherein the one or more defects comprise one or more cracks in the target asset; (White: Paragraph [0071]; “...types of damage may be classified as grease, cracking, or erosion, and quantified in terms of severity using a scale of 1-10, or other suitable scale.”)
receive feedback from the Al services module, wherein the feedback comprises information of ... the generated three dimensional reconstruction... (White: Paragraph [0044], [0063]-[0064], [0070], [0079])
update the...model based on the feedback and based on AI model requirements of the AI services module,... (White: Paragraph [0064]-[0065], [0095]-[0097])
It would be obvious for one with ordinary skill in the art before the effective filling date of the claimed invention to modify the UAV system and real-time AI feedback of Tan, in view of Schwartz, and further in view of Koo, with the 3D model generation and post-flight AI feedback of White for the benefit of an optimized and less time-consuming system for analyzing image data received from a drone. (White: Paragraph [0007])
Tan, in view of Schwartz, further in view of Koo, and even further in view of White, does not teach
...
...and wherein the information comprises detection of a change in size of at least one crack, of the one or more cracks, from a previous size of the at least one crack included as part of the feedback from the previously completed inspection missions;
...
update the target asset information and the model based on...a position of the at least one crack on a surface of the target asset relative to offsets from surface corners of the target asset.
However in the same field of endeavor, Das teaches
...
...and wherein the information comprises detection of a change in size of at least one crack, of the one or more cracks, from a previous size of the at least one crack included as part of the feedback from the previously completed inspection missions; (Das: Paragraph [0005], [0007], [0035], [0038]; “...the method detects defects observed with the one or more objects of interests based on the change observed in each 2D image frame from the plurality 2D image frames in a specific view with an identical objects of interest of the 2D image frame representing the same asset based on varying time stamps and a EXIF data based closest possible pairing.”; “find closest matched image pairs between the sessions of flight for any arbitrary target asset…a correspondence has been established through the aforementioned method and defect magnitude is compared.”)
...
It would be obvious for one with ordinary skill in the art before the effective filling date of the claimed invention to modify the UAV system and real-time AI feedback of Tan, in view of Schwartz, further in view of Koo, and further in view of White, with the defect change over time analysis of Das for the benefit of reducing equipment failures to ensure safe operating conditions and to plan and prioritize scheduled or emergency maintenance. (Das: Paragraph [0003])
Tan, in view of Schwarz, further in view of Koo, further in view of White and even further in view of Das, does not teach
...
update the target asset information and the model based on...a position of the at least one crack on a surface of the target asset relative to offsets from surface corners of the target asset.
However in the same field of endeavor, Bauer teaches
...
update the target asset information and the model based on...a position of the at least one crack on a surface of the target asset relative to offsets from surface corners of the target asset. (Bauer: Paragraph [0023], [0030]-[0031], [0062], [0078]-[0079], [0086]-[0087]; The system allows for a user to select a boundary (i.e. the corners of a roof of a building) for the UAV to scan within. The UAV finds the position of a defect within said boundary and knows the position of the defect based on the corners of the selected boundary.)
It would be obvious for one with ordinary skill in the art before the effective filling date of the claimed invention to modify the UAV system and real-time AI feedback of Tan, in view of Schwartz, further in view of Koo, further in view of White, and further in view of Das, with the defect location relative to the corners of a boundary of Bauer for the benefit of greatly reducing the risk of harm to the UAV or damage to surrounding people and property. (Bauer: Paragraph [0003])
Regarding Claim 2,
Tan, in view of Schwartz, further in view of Koo, further in view of White, further in view of Das, and even further in view of Bauer, teaches
The system of claim 1, wherein the processor is to receive both real-time feedback (Koo: Paragraph [0014]) and post-flight feedback from the Al services module. (White: Paragraph [0072], [0144], [0180], FIG. 13; post-processing occurs post-flight.)
It would be obvious for one with ordinary skill in the art before the effective filling date of the claimed invention to modify the UAV system and real-time AI feedback of Tan, in view of Schwartz, and further in view of Koo, with the post-flight AI feedback of White for the benefit of an optimized and less time-consuming system for analyzing image data received from a drone. (White: Paragraph [0007])
The motivation to combine Tan, Schwartz, Koo, White, Das, and Bauer, is the same as stated for Claim 1 above.
Regarding Claim 3,
Tan, in view of Schwartz, further in view of Koo, further in view of White, further in view of Das, and even further in view of Bauer, teaches
The system of claim 1, wherein the target asset information comprises a geometry and asset ID of the target asset. (Tan: Paragraph [0008], [0015]-[0016], [0021]; The asset ID would be what kind of structure it and the geometry would be the configuration of the asset.)
Regarding Claim 4,
Tan, in view of Schwartz, further in view of Koo, further in view of White, further in view of Das, and even further in view of Bauer, teaches
The system of claim 1, wherein the processor is to generate a second inspection mission for the target asset based on the feedback from the AI services module. (White: Paragraph [0041]-[0042])
The motivation to combine Tan, Schwartz, Koo, White, Das, and Bauer, is the same as stated for Claim 1 above.
Regarding Claim 6,
Tan, in view of Schwartz, further in view of Koo, further in view of White, further in view of Das, and even further in view of Bauer, teaches
The system of claim 1, wherein the processor is to generate the inspection mission based on a previously executed inspection mission for a similar target asset, wherein the similarity of the similar target asset is determined based on a comparison of corresponding models in the information of the asset management system. (Tan: Paragraph [0027])
Regarding Claim 8, the claim is analogous to Claim 1 limitations and is therefore rejected under the same premise as Claim 1.
Regarding Claim 9,
Tan, in view of Schwartz, further in view of Koo, further in view of White, further in view of Das, and even further in view of Bauer, teaches
The computer-implemented method of claim 8, comprising transmitting, via the processor, the updated commands to the UAV. (Tan: Paragraph [0035])
Regarding Claim 10,
Tan, in view of Schwartz, further in view of Koo, further in view of White, further in view of Das, and even further in view of Bauer, teaches
The computer-implemented method of claim 9, wherein the target asset information is based in part on a previous inspection mission. (Tan: Paragraph [0027]-[0028])
Regarding Claim 11, the claim is analogous to Claim 2 limitations and is therefore rejected under the same premise as Claim 2.
Regarding Claim 13,
Tan, in view of Schwartz, further in view of Koo, further in view of White, further in view of Das, and even further in view of Bauer, teaches
The computer-implemented method of claim 8, wherein the feedback comprises real-time feedback received during the inspection mission. (Tan: Paragraph [0035]-[0036])
Regarding Claim 15, the claim is analogous to Claim 1 limitations and is therefore rejected under the same premise as Claim 1.
Regarding Claim 16, the claim is analogous to Claim 9 limitations and is therefore rejected under the same premise as Claim 9.
Regarding Claim 17, the claim is analogous to Claim 2 limitations and is therefore rejected under the same premise as Claim 2.
Regarding Claim 18, the claim is analogous to Claim 10 limitations and is therefore rejected under the same premise as Claim 10.
Claims 5, 7, 12, 14, and 19-20, are rejected under 35 U.S.C. 103 as being unpatentable over Tan, in view of Schwartz, further in view of Koo, further in view of White, further in view of Das, and further in view of Bauer, as applied to claims 1-4, 6, 8-11, 13, and 15-18, above, and further in view of Kugelmass (20140316616; already of record).
Regarding Claim 5,
Tan, in view of Schwartz, further in view of Koo, further in view of White, further in view of Das, and further in view of Bauer, teaches
The system of claim 1,...
Tan, in view of Schwartz, further in view of Koo, further in view of White, further in view of Das, and further in view of Bauer, does not teach
...wherein the feedback from the Al services module is based on an Al services requirement.
However in the same field of endeavor, Kugelmass teaches
...wherein the feedback from the Al services module is based on an Al services requirement. (Kugelmass: Paragraph [0040])
It would be obvious for one with ordinary skill in the art before the effective filling date of the claimed invention to modify the UAV system of Tan, in view of Schwarz, further in view of Koo, further in view of White, further in view of Das, and further in view of Bauer, with the AI services requirement of Kugelmass for the benefit of imaging an area of interest. (Kugelmass: Abstract)
Regarding Claim 7,
Tan, in view of Schwartz, further in view of Koo, further in view of White, further in view of Das, further in view of Bauer, and further in view of Kugelmass, teaches
The system of claim 1, wherein the UAV platform is to dynamically generate updated commands for the UAV based on the inspection mission (Tan: Paragraph [0023]-[0024], [0035]; Reactive Planning) and the feedback from the Al services module. (Kugelmass: Paragraph [0040])
The motivation to combine Tan, Schwartz, Koo, White, Das, Bauer, and Kugelmass, is the same as stated for Claim 5 above.
Regarding Claim 12,
Tan, in view of Schwartz, further in view of Koo, further in view of White, further in view of Das, further in view of Bauer, and further in view of Kugelmass, teaches
The computer-implemented method of claim 8, comprising receiving, via the processor, the feedback in real-time from an Al services module (Kugelmass: Paragraph [0040]) and sending the updated commands to the UAV during the inspection mission. (Tan: Paragraph [0023]-[0024], [0035]-[0036])
The motivation to combine Tan, Schwartz, Koo, White, Das, Bauer, and Kugelmass, is the same as stated for Claim 5 above.
Regarding Claim 14, the claim is analogous to Claim 5 limitations and is therefore rejected under the same premise as Claim 5.
Regarding Claim 19, the claim is analogous to Claim 12 limitations and is therefore rejected under the same premise as Claim 12.
Regarding Claim 20, the claim is analogous to Claim 5 limitations and is therefore rejected under the same premise as Claim 5.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 PAULO ROBERTO GONZALEZ LEITE whose telephone number is (571)272-5877. The examiner can normally be reached Mon-Fri: 8:00 am - 4:30 pm.
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/P.R.L./Examiner, Art Unit 3663
/ABBY J FLYNN/Supervisory Patent Examiner, Art Unit 3663
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