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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 1/16/2026 has been entered.
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1-2, 4, 6, 11-12, 14-15, 17, 19-20, and 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over He et al. CN 110850894 A (hereinafter He; a translated copy has been provided which the examiner relies upon) in view of Qiu CN 110892284 A (hereinafter Qiu; a translated copy has been provided which the examiner relies upon).
Regarding claims 1 and 14,
He teaches
An aerial vehicle (Abstract "unmanned aerial vehicle") comprising:
an on-board sensor (¶ 0079 "lidar installed on drones");
a memory storing instructions (¶ 0038 "a drone, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method"); and
a processor calls the instructions stored in the memory for realizing following operations (¶ 0038):
obtaining measurement data collected by an on-board sensor of the aerial vehicle, the measurement data including point cloud data (¶ 0079 "Point cloud data of power lines can be obtained by using lidar installed on drones");
obtaining target parameters, the target parameters being determined based on the measurement data (¶ 0026 "The direction of the wire is obtained from the wire point cloud"; ¶ 0067 "Use lidar to obtain the distance from the drone to the power line"), the target parameters comprising a distance between the aerial vehicle and a target object (¶ 0067) and an extension direction of the target object, and the extension direction of the target object being determined based on the point cloud data (¶ 0026);
determining a flight path of the aerial vehicle based on the target parameters (¶ 0027 "The drone's flight direction is adjusted in real time according to the direction of the power line"; ¶ 0074 "Automatically adjust the flight position of the UAV based on the difference between the preset altitude information and the actual altitude information, and the difference between the preset offset information and the actual offset information"), the flight path of the aerial vehicle including a flight direction of the aerial vehicle (¶ 0027), and the flight direction of the aerial vehicle being substantially parallel to the extension direction of the target object (¶ 0074-0075; it is inherent that maintaining a fixed horizontal and vertical displacement from a line would result in a trajectory heading parallel to the line); and
controlling the aerial vehicle to perform an operation based on the flight path of the aerial vehicle (¶ 0027 and 0074).
He does not teach
the on-board sensor including a radar.
Qiu teaches
the on-board sensor including a radar (¶ 0040 "radar").
It would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have modified He to incorporate the teachings of Qui. Since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function, but in the very combination itself, that is in the substitution of the radar of Qui for the lidar of He. Thus, the simple substitution of one known element for another producing a predictable result of detecting 3D objects utilizing sensors that generate a point cloud renders the claim obvious.
Regarding claims 2 and 15, the modified He reference teaches all of claims 1 and 14 as detailed above.
He further teaches that
the target object comprises an electric wire (Abstract "electric wire").
Regarding claims 4 and 17, the modified He reference teaches all of claims 1 and 14 as detailed above.
He does not teach that
the radar comprises at least one of a millimeter wave radar, rotating millimeter wave radar, or an ultrasonic radar.
Qui further teaches that
the radar comprises a millimeter wave radar (¶ 0048 "millimeter-wave radar").
It would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have further modified He to incorporate the further teachings of Qui. Since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function, but in the very combination itself, that is in the substitution of the millimeter wave radar of Qui for the lidar of He. Thus, the simple substitution of one known element for another producing a predictable result of detecting 3D objects utilizing sensors that generate a point cloud renders the claim obvious.
Regarding claims 6 and 19, the modified He reference teaches all of claims 2 and 14 as detailed above.
He further teaches that
the distance between the aerial vehicle and the electric wire includes a horizontal distance between the aerial vehicle and the electric wire (¶ 0069 "calculate the… actual offset information of the UAV relative to the power line"; see also Figure 4) and a vertical height between the aerial vehicle and the electric wire (¶ 0069 "calculate the actual height information… of the UAV relative to the power line"; see also Figure 4).
Regarding claims 11 and 20, the modified He reference teaches all of claims 1 and 14 as detailed above.
He further teaches
determining the flight path of the aerial vehicle based on the target parameters and a predetermined requirement for the aerial vehicle to follow the target object (¶ 0027 "The drone's flight direction is adjusted in real time according to the direction of the power line"; ¶ 0074 "Automatically adjust the flight position of the UAV based on the difference between the preset altitude information and the actual altitude information, and the difference between the preset offset information and the actual offset information").
Regarding claim 12, the modified He reference teaches all of claim 1 as detailed above.
He further teaches
determining a heading direction of the aerial vehicle based on the extension direction of the target object (¶ 0027 "The drone's flight direction is adjusted in real time according to the direction of the power line"); and
determining the flight path of the aerial vehicle in the heading direction based on the target parameters, a position of the aerial vehicle, and a predetermined distance between the aerial vehicle and the target object (¶ 0074 "Automatically adjust the flight position of the UAV based on the difference between the preset altitude information and the actual altitude information, and the difference between the preset offset information and the actual offset information").
Regarding claim 22, the modified He reference teaches all of claim 1 as detailed above.
He further teaches
controlling the aerial vehicle to perform the operation at a preset distance relative to the target object based on the flight path of the aerial vehicle (¶ 0074), the preset distance including a horizontal distance between the aerial vehicle and the target object (¶ 0074 "Automatically adjust the flight position of the UAV based… the difference between the preset offset information and the actual offset information") and a vertical distance between the aerial vehicle and the target object (¶ 0074 "Automatically adjust the flight position of the UAV based on the difference between the preset altitude information and the actual altitude information").
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over He as modified by Qui as applied to claim 1 above, and further in view of Wu et al. CN 104143189 A (hereinafter Wu; a translated copy has been previously provided which the examiner relies upon).
Regarding claim 9, the modified He reference teaches all of claim 1 as detailed above.
He further teaches that
the target parameters are determined based on the target measurement data (¶ 0026 "The direction of the wire is obtained from the wire point cloud"; ¶ 0067 "Use lidar to obtain the distance from the drone to the power line").
He does not teach
determining whether the measurement data is target measurement data based on a dispersion of the measurement data.
Wu teaches
determining whether the measurement data is target measurement data based on a dispersion of the measurement data (Abstract discloses extracting the transmission line data from a 3D point cloud utilizing the dispersion degree of point cloud points).
It would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have further modified He to incorporate the teachings of Wu such that the detected transmission line of He can be detected via the dispersion method of Wu. This modification would be made with a reasonable expectation of success to improve tracking of the transmission device as disclosed in Wu (Abstract).
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over He as modified by Qui and Wu as applied to claim 9 above, and further in view of "Automatic Detection and Classification of Pole-Like Objects in Urban Point Cloud Data Using an Anomaly Detection Algorithm" by Rodriguez-Cuenca et al. (hereinafter Rodriguez).
Regarding claim 10, the modified He reference teaches all of claim 9 as detailed above.
He does not teach that
under a condition that the dispersion is less than or equal to a predetermined threshold, the measurement data is determined to be the target measurement data; and
under a condition that the dispersion is greater than the predetermined threshold, the measurement data is determined to be obstacle measurement data, which is measurement data of an obstacle other than the target object.
Rodriguez teaches that
under a condition that the dispersion is less than or equal to a predetermined threshold, the measurement data is determined to be the target measurement data (pages 12689-12690 disclose the determination of elements based on dispersion of points with vertical poles having a smaller dispersion than roads; this indicates the detection of poles, i.e. "target objects", is based on being smaller than a set dispersion level; Figure 7 also indicates utilization of these dispersions based classifications to distinguish between two different vertical objects, not just horizontal and vertical indicating further flexibility in the taught method); and
under a condition that the dispersion is greater than the predetermined threshold, the measurement data is determined to be obstacle measurement data, which is measurement data of an obstacle other than the target object (pages 12689-12690 disclose the determination of elements based on dispersion of points with vertical poles having a smaller dispersion than roads; this indicates the detection of roads, i.e. obstacles, is based on being larger than a set dispersion level; Figure 7 also indicates utilization of these dispersions based classifications to distinguish between two different vertical objects, not just horizontal and vertical indicating further flexibility in the taught method).
It would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have further modified He to incorporate the teachings of Rodriguez such that objects can be distinguished between based on dispersion of point cloud elements as taught by Rodriguez such that power line poles can be extracted from point cloud data. This modification would be made with a reasonable expectation of success to improve accuracy of object distinguishment to reduce risk of collision with the power line or other objects during following.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over He as modified by Qui as applied to claim 1 above, and further in view of Schmidt et al. US 20210284198 A1 (hereinafter Schmidt).
Regarding claim 13, the modified He reference teaches all of claim 1 as detailed above.
He does not teach
determining presence of an obstacle other than the target object, the obstacle being determined by measurement data collected by the on-board sensor during the movement of the aerial vehicle;
under a condition that the obstacle is determined to be within the flight path of the aerial vehicle, controlling the aerial vehicle to enter an obstacle avoidance mode to avoid the obstacle;
and under a condition that the obstacle is determined to be outside the flight path of the aerial vehicle, controlling the aerial vehicle to ignore the obstacle.
Schmidt teaches
determining presence of an obstacle (Abstract "acquiring object information representing an object shape from one or more sensors"), the obstacle being determined by measurement data collected by the on-board sensor during the movement of the vehicle (Figure 2 210-250 indicate that a vehicle is currently traveling on a path and a projection of the path and sensing of objects on the path occur during travel on this path; ¶ 0112 details that step 220 "may be done in real-time while the vehicle navigates along its path");
under a condition that the obstacle is determined to be within the path of the vehicle, controlling the vehicle to enter an obstacle avoidance mode to avoid the obstacle (Abstract "determining if the object shape overlaps the projected motion polygon. If so, the method includes adjusting the vehicle navigation"; Figure 2 280 "avoid object");
and under a condition that the obstacle is determined to be outside the path of the vehicle, controlling the vehicle to ignore the obstacle (Abstract "determining if the object shape overlaps the projected motion polygon… If not, the method includes, continuing navigation along the path"; Figure 2 290 "ignore object").
It would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have further modified He to incorporate the teachings of Schmidt such that the obstacle avoidance of Schmidt can be performed in the aerial vehicle context of He to avoid any obstacles that aren’t the electric wire of He. This modification would be done with a reasonable expectation of success to allow for obstacle avoidance while also preventing unnecessary interruptions caused by obstacles outside of the vehicle's path as disclosed in Schmidt (¶ 0012).
Claim(s) 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over He as modified by Qui as applied to claim 1 above, and further in view of Moore et al. US 20190033467 A1.
Regarding claim 23, the modified He reference teaches all of claim 1 as detailed above.
He does not teach that
the on-board sensor further includes a multispectral camera.
Moore teaches that
the on-board sensor further includes a multispectral camera (¶ 0028 "multi-spectrum cameras").
It would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have further modified He to incorporate the teachings of Moore such that the sensor system aboard He can further include the multispectral cameras of Moore. This modification would be made with a reasonable expectation of success to improve locating existing or impending electrical arcing faults as disclosed in Moore (¶ 0003).
Claim(s) 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over He as modified by Qui as applied to claim 1 above, and further in view of Wang et al. CN 110427504 A (hereinafter Wang; a translated copy has been provided which the examiner relies upon).
Regarding claim 24, the modified He reference teaches all of claim 1 as detailed above.
He does not teach that
a frequency of the on-board sensor to collect the measurement data is adjusted based on whether there is an object other than the target object in surrounding environment of the aerial vehicle.
Wang teaches that
a frequency of the on-board sensor to collect the measurement data is adjusted based on whether there is an object other than the target object in surrounding environment of the vehicle (¶ 0016 "the vehicle-mounted server is used to determine the obstacle area and the non-obstacle area after receiving the data processing results from the cloud server, and to reduce the scanning frequency of the laser radar device scanning the non-obstacle area"; examiner understands an obstacle as equivalent to an object that is not a target object as obstacle avoidance would be required in reaction to the obstacle, changing the standard flight path).
It would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have further modified He to incorporate the teachings of Wang such that the obstacle detection method with varying detection frequency of Wang can be performed in the aerial vehicle context of He. This modification would be made with a reasonable expectation of success to reduce data acquisition volume while still maintaining vehicle safety, reduce data transmission pressure for any transmitted data, reduce data processing load, reduce hardware latency, and improve data processing speed as disclosed in Wang (¶ 0026).
Claim(s) 25 is/are rejected under 35 U.S.C. 103 as being unpatentable over He in view of Wang.
Regarding claim 25,
He teaches
An operating method of an aerial vehicle (Abstract "unmanned aerial vehicle"), comprising:
obtaining target parameters (¶ 0026 "The direction of the wire is obtained from the wire point cloud"; ¶ 0067 "Use lidar to obtain the distance from the drone to the power line"), the target parameters being acquired by an on-board sensor of the aerial vehicle (¶ 0079 "Point cloud data of power lines can be obtained by using lidar installed on drones") during movement of the aerial vehicle (¶ 0024 "real-time adjustment of the drone's flight direction"), the target parameters comprising a distance between the aerial vehicle and a target object (¶ 0026) and an extension direction of the target object (¶ 0067), and obtaining the target parameter including:
obtaining measurement data collected by the on-board sensor (¶ 0079)
and determining the target parameters based on the measurement data collected by the on-board sensor (¶ 0026 and 0067);
determining a flight path of the aerial vehicle based on the target parameters (¶ 0027 "The drone's flight direction is adjusted in real time according to the direction of the power line"; ¶ 0074 "Automatically adjust the flight position of the UAV based on the difference between the preset altitude information and the actual altitude information, and the difference between the preset offset information and the actual offset information"); and
controlling the aerial vehicle to perform an operation based on the flight path of the aerial vehicle (¶ 0027 and 0074).
He does not teach that
a frequency of the on-board sensor to collect the measurement data being adjusted based on whether there is an object other than the target object in surrounding environment of the aerial vehicle.
Wang teaches that
a frequency of the on-board sensor to collect the measurement data being adjusted based on whether there is an object other than the target object in surrounding environment of the aerial vehicle (¶ 0016 "the vehicle-mounted server is used to determine the obstacle area and the non-obstacle area after receiving the data processing results from the cloud server, and to reduce the scanning frequency of the laser radar device scanning the non-obstacle area"; examiner understands an obstacle as equivalent to an object that is not a target object as obstacle avoidance would be required in reaction to the obstacle, changing the standard flight path).
It would have been prima facie obvious to one of ordinary skill in the art at the time of filing to have further modified He to incorporate the teachings of Wang such that the obstacle detection method with varying detection frequency of Wang can be performed in the aerial vehicle context of He. This modification would be made with a reasonable expectation of success to reduce data acquisition volume while still maintaining vehicle safety, reduce data transmission pressure for any transmitted data, reduce data processing load, reduce hardware latency, and improve data processing speed as disclosed in Wang (¶ 0026).
Response to Arguments
Applicant’s arguments with respect to claim(s) 1 and 14 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.
In response to applicant’s argument, see pages 12-13, that there is no teaching, suggestion, or motivation to combine the references, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). In this case, motivation for combination of references in the Office Action dated 10/20/2025 can be clearly found within each paragraph starting with the phrase “It would have been prima facie obvious to one of ordinary skill in the art”. As applicant has not adequately provided evidence as to why the stated rationale is insufficient or adequately articulated why the references cannot be combined together, the argument is not persuasive. The new grounds of rejection rely upon previously presented references Wu, Rodriguez, and Schmidt wherein motivation for combination is maintained relatively the same. All other relied upon art was not previously presented or relied upon in a manner for this argument to be applicable regardless.
Documents Considered but not Relied Upon
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Bauer et al. US 20180002010 A1 discloses a multispectral camera utilized for utility inspection.
Yang et al. CN 111275821 A discloses fitting a point cloud to obtain a power line extension direction.
Liu et al. CN 207882763 U discloses utilization of ultrasonic sensors and millimeter wave radar in UAVs for obstacle avoidance.
Conclusion
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/A.T.S./Examiner, Art Unit 3669
/Erin M Piateski/Supervisory Patent Examiner, Art Unit 3669