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 Status
The status of claims 1-20 is:
Claims 1-20 are pending.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 11/18/2024, 01/30/2025, 05/22/2025, and 09/16/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Examiner notes that the foreign patent documents and non-patent literature documents in the IDS received 11/18/2024 are present in the parent application of this continuation.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 5-6 and 12-13 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 5 and 12 recite the limitation "UAV" in line 4 and line 3 respectively. There is insufficient antecedent basis for this limitation in the claim. The term “UAV” is not defined or referenced in the claims that claims 5 and 12 are dependent on.
Claims 6 and 13 are rejected for being dependent on claims 5 and 12 respectively.
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(s) 1-2, 8-9, and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Razmara et al. (U.S. Patent Publication No 2022/0202294, hereinafter “Razmara”) in view of Cantrell et al. (U.S. Patent Publication No 2019/0210725, hereinafter “Cantrell”).
Regarding claim 1, Razmara discloses an aerial vehicle (Razmara [0014]: “One aspect of the invention provides an imaging system comprising: an unmanned aerial drone, the drone comprising: a drone body; four rotors mounted to the drone body; a digital camera mounted to the drone body”) comprising:
a camera mounted on the aerial vehicle (Razmara [0014]: “One aspect of the invention provides an imaging system comprising: an unmanned aerial drone, the drone comprising: a drone body; four rotors mounted to the drone body; a digital camera mounted to the drone body”);
and one or more processors (Razmara [0142]: “UAV 200 further comprises one or more sensors 212, transceiver 214, and onboard computer 216. Computer 216 comprises a memory and a processor”) configured by executable instructions to:
determine a plurality of contour paths spaced apart from each other along at least one axis associated with a scan target, each contour path spaced away from a surface of the scan target (Razmara [0013]: “One aspect of the invention provides a method of photographing at least a portion of a subject with a platform carrying an imaging system, the method comprising: generating a photography scheme, the photography scheme comprising a set of photography control points, each of the photography control points comprising: a location of the platform relative to the subject; an orientation of the platform relative to the subject; and one or more photography parameters”; Razmara [0178]: “To generate the photography scheme, computer 220 may determine a number of images required of the subject. For example, computer 220 may determine that thirty images of the subject are required, where ten images are taken at a first elevation, ten images are taken at a second elevation greater than the first elevation, and ten images are taken at a third elevation greater than the second elevation. Each of the ten images at each elevation may be separated by an equal angle about the subject. For example: a first image may be taken at a starting position, a second image may be taken at a second position 36° around the subject from the starting position, a third image may be taken at a third position 72° around the subject from the starting position, and so on with each image being taken at a position (n×36°) around the subject from the starting position, where n is an index identifying the image with 0≤n≤9 in this example”);
determine image capture locations for each contour path, each image capture location indicating a location at which an image of the surface of the scan target is to be captured (Razmara [0179]: “Once computer 220 has determined the number of images of the subject required, computer 220 may determine the photography control points required to capture each of the required images. For example, computer 220 may determine a position and an orientation of drone 200 required to capture each of the thirty images referenced above. To determine the position and orientation of drone 200 required to capture each image, computer 220 may determine a distance from the subject for each image”); and
operating the camera to capture images of the surface of the scan target based at least on the image capture locations (Razmara [0014]: “the drone computer configured to: control the four rotors to navigate the drone; control the digital camera to capture one or more digital images”).
Razmara does not explicitly disclose the vehicle configured to:
navigate the aerial vehicle along one or more of the contour paths at a speed that is based at least in part on a detected lighting condition.
However, Cantrell teaches the vehicle configured to:
navigate the aerial vehicle along one or more of the contour paths at a speed that is based at least in part on a detected lighting condition (Cantrell [0030]: “In step 230, the system detects condition parameters. In some embodiments, condition parameters may be detected by a sensor system on the UAV. In some embodiments, condition parameters may comprise one or more of: wind speed, wind direction, air pressure, visibility, lighting condition, precipitation, weather condition, ground condition, distance to a charging station, and locations of one or more other aerial vehicles. In some embodiments, the sensor system may comprise one or more environmental sensors such as a wind sensor, a light sensor, an image sensor, a visibility sensor, a weather sensor, a barometric pressure sensor, a range sensor, a humidity sensor, a sound sensor, a thermal image sensor, a night vision camera, etc. In some embodiments, the sensor system on the UAV may comprise a wireless data transceiver for receiving condition parameters from a remote data source. In some embodiments, the condition parameters may further comprise information received from one or more of: a stationary sensor, a weather reporting service, an air traffic control signal, and one or more other aerial vehicles. In some embodiments, the condition parameters may comprise data collected by field sensors 130 and/or the central computer system 110 described with reference to FIG. 1 or similar devices. In some embodiments, condition parameters collected by a UAV may be shared with multiple UAVs in the system. In some embodiments, condition parameters may comprise condition parameters associated with different areas of the UAV's field of operation. In some embodiments, step 230 may be performed while the UAV is in flight”).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to incorporate adjusting speed with lighting conditions as taught by Cantrell with the vehicle of Razmara because it would improve the quality of images capture by the vehicle. This motivation for the combination of Razmara and Cantrell is supported by KSR exemplary rationale (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Regarding claim 8, it is rejected under the same analysis as claim 1 above.
Regarding claim 2, Razmara does not explicitly disclose the method, the one or more processors further configured by the executable instructions to:
detect a change in the lighting condition; and
and based at least on the change in the lighting condition, change the speed of the aerial vehicle and continue to operate the camera to capture the images.
However, Cantrell teaches the method, the one or more processors further configured by the executable instructions to:
detect a change in the lighting condition (Cantrell [0030]: “In step 230, the system detects condition parameters. In some embodiments, condition parameters may be detected by a sensor system on the UAV. In some embodiments, condition parameters may comprise one or more of: wind speed, wind direction, air pressure, visibility, lighting condition, precipitation, weather condition, ground condition, distance to a charging station, and locations of one or more other aerial vehicles. In some embodiments, the sensor system may comprise one or more environmental sensors such as a wind sensor, a light sensor, an image sensor, a visibility sensor, a weather sensor, a barometric pressure sensor, a range sensor, a humidity sensor, a sound sensor, a thermal image sensor, a night vision camera, etc. In some embodiments, the sensor system on the UAV may comprise a wireless data transceiver for receiving condition parameters from a remote data source. In some embodiments, the condition parameters may further comprise information received from one or more of: a stationary sensor, a weather reporting service, an air traffic control signal, and one or more other aerial vehicles. In some embodiments, the condition parameters may comprise data collected by field sensors 130 and/or the central computer system 110 described with reference to FIG. 1 or similar devices. In some embodiments, condition parameters collected by a UAV may be shared with multiple UAVs in the system. In some embodiments, condition parameters may comprise condition parameters associated with different areas of the UAV's field of operation. In some embodiments, step 230 may be performed while the UAV is in flight); and
and based at least on the change in the lighting condition, change the speed of the aerial vehicle and continue to operate the camera to capture the images (Cantrell [0035]: “In step 250, the system determines a motor state for the UAV. In some embodiments, the motor state may be determined based on the task profile retrieved in step 210 and/or the condition parameters detected in step 230. In some embodiments, the motor state may be determine separately for each of the two or more motors on the UAV. In some embodiments, the motor state may comprise on, off, and/or a specified speed. In some embodiments, the system may be configured to reduce the amount of power that needs to be supplied to the motor to perform the task. For example, if the UAV may enter a glide mode with motors turned off and still perform the assigned task(s), the system may cause the UAV to enter glide mode and turn off the motors. In some embodiments, the state of the motors may be determined similar to a conventional multicopter to control the speed and/or direction of the UAV. In some embodiments, the motor state may comprise a rotation of the motor and the UAV may comprise a set of motors configured to rotate relative to the body of the UAV to an angle determine based on one or more of the task profile and/or the condition parameters. In some embodiments, the rotation of the motors may be determined separately for each motor on the UAV”; Cantrell [0036]: “In step 255, the system adjusts the motors on the UAV based on the motor state determined in step 250. In some embodiments, in step 255, the system may selectively turn the motors on or off, and/or adjust the speed of one or more motors. In some embodiments, in step 255, the system may cause one or more motors to rotate the change the direction of the motor's propulsion”).
It would have been obvious to combine Razmara and Cantrell for the same reasons as used for claim 1 above.
Regarding claim 9, it is rejected under the same analysis as claim 9 above.
Regarding claim 15, Razmara discloses an unmanned aerial vehicle (UAV) (Razmara [0014]: “One aspect of the invention provides an imaging system comprising: an unmanned aerial drone, the drone comprising: a drone body; four rotors mounted to the drone body; a digital camera mounted to the drone body”) comprising:
a UAV body including a propulsion mechanism (Razmara [0014]: “One aspect of the invention provides an imaging system comprising: an unmanned aerial drone, the drone comprising: a drone body; four rotors mounted to the drone body; a digital camera mounted to the drone body”);
a camera mounted on the UAV body (Razmara [0014]: “One aspect of the invention provides an imaging system comprising: an unmanned aerial drone, the drone comprising: a drone body; four rotors mounted to the drone body; a digital camera mounted to the drone body”); and
and one or more processors able to communicate with the propulsion mechanism and the camera (Razmara [0142]: “UAV 200 further comprises one or more sensors 212, transceiver 214, and onboard computer 216. Computer 216 comprises a memory and a processor”), the one or more processors configured by executable instructions to:
determine a plurality of contour paths spaced apart from each other along at least one axis associated with a scan target (Razmara [0013]: “One aspect of the invention provides a method of photographing at least a portion of a subject with a platform carrying an imaging system, the method comprising: generating a photography scheme, the photography scheme comprising a set of photography control points, each of the photography control points comprising: a location of the platform relative to the subject; an orientation of the platform relative to the subject; and one or more photography parameters”; Razmara [0178]: “To generate the photography scheme, computer 220 may determine a number of images required of the subject. For example, computer 220 may determine that thirty images of the subject are required, where ten images are taken at a first elevation, ten images are taken at a second elevation greater than the first elevation, and ten images are taken at a third elevation greater than the second elevation. Each of the ten images at each elevation may be separated by an equal angle about the subject. For example: a first image may be taken at a starting position, a second image may be taken at a second position 36° around the subject from the starting position, a third image may be taken at a third position 72° around the subject from the starting position, and so on with each image being taken at a position (n×36°) around the subject from the starting position, where n is an index identifying the image with 0≤n≤9 in this example”), each contour path spaced away from a surface of the scan target (Razmara [0179]: “Once computer 220 has determined the number of images of the subject required, computer 220 may determine the photography control points required to capture each of the required images. For example, computer 220 may determine a position and an orientation of drone 200 required to capture each of the thirty images referenced above. To determine the position and orientation of drone 200 required to capture each image, computer 220 may determine a distance from the subject for each image”);
determine image capture locations for each contour path, each image capture location indicating a location at which an image of the surface of the scan target is to be captured (Razmara [0179]: “Once computer 220 has determined the number of images of the subject required, computer 220 may determine the photography control points required to capture each of the required images. For example, computer 220 may determine a position and an orientation of drone 200 required to capture each of the thirty images referenced above. To determine the position and orientation of drone 200 required to capture each image, computer 220 may determine a distance from the subject for each image”); and
while operating the camera to capture images of the surface of the scan target based at least on the image capture locations (Razmara [0014]: “the drone computer configured to: control the four rotors to navigate the drone; control the digital camera to capture one or more digital images”).
Razmara does not explicitly disclose the UAV configured to:
control the propulsion mechanism to navigate the aerial vehicle along one or more of the contour paths at a speed that is based at least in part on a detected lighting condition.
However, Cantrell teaches the UAV configured to:
control the propulsion mechanism to navigate the aerial vehicle along one or more of the contour paths at a speed that is based at least in part on a detected lighting condition (Cantrell [0030]: “In step 230, the system detects condition parameters. In some embodiments, condition parameters may be detected by a sensor system on the UAV. In some embodiments, condition parameters may comprise one or more of: wind speed, wind direction, air pressure, visibility, lighting condition, precipitation, weather condition, ground condition, distance to a charging station, and locations of one or more other aerial vehicles. In some embodiments, the sensor system may comprise one or more environmental sensors such as a wind sensor, a light sensor, an image sensor, a visibility sensor, a weather sensor, a barometric pressure sensor, a range sensor, a humidity sensor, a sound sensor, a thermal image sensor, a night vision camera, etc. In some embodiments, the sensor system on the UAV may comprise a wireless data transceiver for receiving condition parameters from a remote data source. In some embodiments, the condition parameters may further comprise information received from one or more of: a stationary sensor, a weather reporting service, an air traffic control signal, and one or more other aerial vehicles. In some embodiments, the condition parameters may comprise data collected by field sensors 130 and/or the central computer system 110 described with reference to FIG. 1 or similar devices. In some embodiments, condition parameters collected by a UAV may be shared with multiple UAVs in the system. In some embodiments, condition parameters may comprise condition parameters associated with different areas of the UAV's field of operation. In some embodiments, step 230 may be performed while the UAV is in flight”).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to incorporate adjusting speed with lighting conditions as taught by Cantrell with the vehicle of Razmara because it would improve the quality of images capture by the vehicle. This motivation for the combination of Razmara and Cantrell is supported by KSR exemplary rationale (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Regarding claim 16, Razmara does not explicitly disclose the UAV, the one or more processors further configured by the executable instructions to:
detect a change in the lighting condition;
and based at least on the change in the lighting condition, change the speed of the aerial vehicle and continue to operate the camera to capture the images.
However, Cantrell teaches the UAV, the one or more processors further configured by the executable instructions to:
detect a change in the lighting condition (Cantrell [0030]: “In step 230, the system detects condition parameters. In some embodiments, condition parameters may be detected by a sensor system on the UAV. In some embodiments, condition parameters may comprise one or more of: wind speed, wind direction, air pressure, visibility, lighting condition, precipitation, weather condition, ground condition, distance to a charging station, and locations of one or more other aerial vehicles. In some embodiments, the sensor system may comprise one or more environmental sensors such as a wind sensor, a light sensor, an image sensor, a visibility sensor, a weather sensor, a barometric pressure sensor, a range sensor, a humidity sensor, a sound sensor, a thermal image sensor, a night vision camera, etc. In some embodiments, the sensor system on the UAV may comprise a wireless data transceiver for receiving condition parameters from a remote data source. In some embodiments, the condition parameters may further comprise information received from one or more of: a stationary sensor, a weather reporting service, an air traffic control signal, and one or more other aerial vehicles. In some embodiments, the condition parameters may comprise data collected by field sensors 130 and/or the central computer system 110 described with reference to FIG. 1 or similar devices. In some embodiments, condition parameters collected by a UAV may be shared with multiple UAVs in the system. In some embodiments, condition parameters may comprise condition parameters associated with different areas of the UAV's field of operation. In some embodiments, step 230 may be performed while the UAV is in flight”);
and based at least on the change in the lighting condition, change the speed of the aerial vehicle and continue to operate the camera to capture the images (Cantrell [0035]: “In step 250, the system determines a motor state for the UAV. In some embodiments, the motor state may be determined based on the task profile retrieved in step 210 and/or the condition parameters detected in step 230. In some embodiments, the motor state may be determine separately for each of the two or more motors on the UAV. In some embodiments, the motor state may comprise on, off, and/or a specified speed. In some embodiments, the system may be configured to reduce the amount of power that needs to be supplied to the motor to perform the task. For example, if the UAV may enter a glide mode with motors turned off and still perform the assigned task(s), the system may cause the UAV to enter glide mode and turn off the motors. In some embodiments, the state of the motors may be determined similar to a conventional multicopter to control the speed and/or direction of the UAV. In some embodiments, the motor state may comprise a rotation of the motor and the UAV may comprise a set of motors configured to rotate relative to the body of the UAV to an angle determine based on one or more of the task profile and/or the condition parameters. In some embodiments, the rotation of the motors may be determined separately for each motor on the UAV”; Cantrell [0036]: “In step 255, the system adjusts the motors on the UAV based on the motor state determined in step 250. In some embodiments, in step 255, the system may selectively turn the motors on or off, and/or adjust the speed of one or more motors. In some embodiments, in step 255, the system may cause one or more motors to rotate the change the direction of the motor's propulsion”).
It would have been obvious to combine Razmara and Cantrell for the same reasons as used for claim 15 above.
Claim(s) 3-4, 10-11, and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over the Razmara and Cantrell combination in view of Bouffard et al. (U.S. Patent Publication No 2017/0334559 presented in the IDS received 11/18/2024, hereinafter “Bouffard”).
Regarding claim 3, Razmara disclose the vehicle, wherein each contour path is spaced away from the surface of the scan target by a selected distance (Razmara [0067]: “Where platform 120 is at least partially controlled by a user, guidance system 130 may comprise one or more systems which provide instructions to a user controlling platform 120. Instructions provided by guidance system 130 to control platform 120 may include: [0068] an instruction to translate platform 120 by a certain distance in a certain direction; [0069] an instruction to rotate platform 120 by a certain angle in a certain direction; [0070] an instruction to pitch platform 120 by a certain angle in a certain direction; and/or [0071] an instruction to yaw platform 120 by a certain angle in a certain direction”), the one or more processors further configured by the executable instructions to:
determine an overlap for the images of the surface (Razmara [0230]: “The input of 3D reconstruction algorithm 602 is a set of images 604 captured from different angles with varying degree of overlap. In first step 606 of the 3D reconstruction algorithm, a set of sparse key points is generated for each image in the set of overlapping images, and a set of feature descriptors (compact numerical representations) is generated from the set of sparse key points”); and
determine a distance between adjacent image capture locations of the respective contour paths based at least on the overlap (Razmara [0230]: “The input of 3D reconstruction algorithm 602 is a set of images 604 captured from different angles with varying degree of overlap. In first step 606 of the 3D reconstruction algorithm, a set of sparse key points is generated for each image in the set of overlapping images, and a set of feature descriptors (compact numerical representations) is generated from the set of sparse key points”) and the selected distance (Razmara [0179]: “Once computer 220 has determined the number of images of the subject required, computer 220 may determine the photography control points required to capture each of the required images. For example, computer 220 may determine a position and an orientation of drone 200 required to capture each of the thirty images referenced above. To determine the position and orientation of drone 200 required to capture each image, computer 220 may determine a distance from the subject for each image”).
The Razmara and Cantrell combination does not explicitly disclose the vehicle configured to:
and determine a distance between adjacent image capture locations of the respective contour paths based on a field of view of the camera operated to capture the images of the surface.
However, Bouffard teaches the vehicle configured to:
and determine a distance between adjacent image capture locations of the respective contour paths based on a field of view of the camera operated to capture the images of the surface (Bouffard [0079]: “To determine the particular width, the flight plan determination engine 302 can ensure that a field of view of a camera will capture images from adjacent legs that encompasses the area between the legs. For instance, if the ground sampling distance indicates a particular altitude the UAV is to fly at to capture images while navigating along each leg, the flight plan determination engine 302 can determine that a width between each leg is set at a distance such that captured images, at the particular altitude, will include the entirety of the area between each leg. Optionally, and as will be described, the flight plan determination engine 302 can further reduce the width, such that legs are spaced closer together. The reduction in width can create an overlap area between each leg, such that images captured in adjacent legs will include a same overlap area between the legs. The overlap area can be useful to ensure that the entirety of the location is imaged, for instance if a UAV gets temporarily off course (e.g., due to wind, or a temporary autopilot malfunctioning, a contingency condition, and so on), a captured image could otherwise fail to include sufficient area. The overlap can act as a buffer against such situations”).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to incorporate using the field of view as taught by Bouffard with the vehicle of Razmara and Cantrell because it would improve the accuracy of the overlap so that the entire object is captured. This motivation for the combination of Razmara, Cantrell, and Bouffard is supported by KSR exemplary rationale (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Regarding claim 10, it is rejected under the same analysis as claim 10 above.
Regarding claim 4, Razmara discloses the vehicle, wherein each contour path is spaced away from the surface of the scan target by a selected distance (Razmara [0067]: “Where platform 120 is at least partially controlled by a user, guidance system 130 may comprise one or more systems which provide instructions to a user controlling platform 120. Instructions provided by guidance system 130 to control platform 120 may include: [0068] an instruction to translate platform 120 by a certain distance in a certain direction; [0069] an instruction to rotate platform 120 by a certain angle in a certain direction; [0070] an instruction to pitch platform 120 by a certain angle in a certain direction; and/or [0071] an instruction to yaw platform 120 by a certain angle in a certain direction”), the one or more processors further configured by the executable instructions to:
determine a sidelap between the images of the surface (Razmara [0230]: “The input of 3D reconstruction algorithm 602 is a set of images 604 captured from different angles with varying degree of overlap. In first step 606 of the 3D reconstruction algorithm, a set of sparse key points is generated for each image in the set of overlapping images, and a set of feature descriptors (compact numerical representations) is generated from the set of sparse key points”); and
determine a distance between adjacent contour paths based at least on the sidelap (Razmara [0230]: “The input of 3D reconstruction algorithm 602 is a set of images 604 captured from different angles with varying degree of overlap. In first step 606 of the 3D reconstruction algorithm, a set of sparse key points is generated for each image in the set of overlapping images, and a set of feature descriptors (compact numerical representations) is generated from the set of sparse key points”) and the selected distance (Razmara [0179]: “Once computer 220 has determined the number of images of the subject required, computer 220 may determine the photography control points required to capture each of the required images. For example, computer 220 may determine a position and an orientation of drone 200 required to capture each of the thirty images referenced above. To determine the position and orientation of drone 200 required to capture each image, computer 220 may determine a distance from the subject for each image”).
The Razmara and Cantrell combination does not explicitly disclose the vehicle configured to:
and determine a distance between adjacent contour paths based on a field of view of the camera operated to capture the images of the surface.
However, Bouffard teaches the vehicle configured to:
determine a distance between adjacent contour paths based on a field of view of the camera operated to capture the images of the surface (Bouffard [0079]: “To determine the particular width, the flight plan determination engine 302 can ensure that a field of view of a camera will capture images from adjacent legs that encompasses the area between the legs. For instance, if the ground sampling distance indicates a particular altitude the UAV is to fly at to capture images while navigating along each leg, the flight plan determination engine 302 can determine that a width between each leg is set at a distance such that captured images, at the particular altitude, will include the entirety of the area between each leg. Optionally, and as will be described, the flight plan determination engine 302 can further reduce the width, such that legs are spaced closer together. The reduction in width can create an overlap area between each leg, such that images captured in adjacent legs will include a same overlap area between the legs. The overlap area can be useful to ensure that the entirety of the location is imaged, for instance if a UAV gets temporarily off course (e.g., due to wind, or a temporary autopilot malfunctioning, a contingency condition, and so on), a captured image could otherwise fail to include sufficient area. The overlap can act as a buffer against such situations”).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to incorporate using the field of view as taught by Bouffard with the vehicle of Razmara and Cantrell because it would improve the accuracy of the sidelap so that the entire object is captured. This motivation for the combination of Razmara, Cantrell, and Bouffard is supported by KSR exemplary rationale (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Regarding claim 11, it is rejected under the same analysis as claim 4 above.
Regarding claim 17, Razmara discloses the UAV, wherein each contour path is spaced away from the surface of the scan target by a selected distance (Razmara [0067]: “Where platform 120 is at least partially controlled by a user, guidance system 130 may comprise one or more systems which provide instructions to a user controlling platform 120. Instructions provided by guidance system 130 to control platform 120 may include: [0068] an instruction to translate platform 120 by a certain distance in a certain direction; [0069] an instruction to rotate platform 120 by a certain angle in a certain direction; [0070] an instruction to pitch platform 120 by a certain angle in a certain direction; and/or [0071] an instruction to yaw platform 120 by a certain angle in a certain direction”), the one or more processors further configured by the executable instructions to:
determine an overlap for the images of the surface (Razmara [0230]: “The input of 3D reconstruction algorithm 602 is a set of images 604 captured from different angles with varying degree of overlap. In first step 606 of the 3D reconstruction algorithm, a set of sparse key points is generated for each image in the set of overlapping images, and a set of feature descriptors (compact numerical representations) is generated from the set of sparse key points”); and
determine a distance between adjacent image capture locations of the respective contour paths based at least on the overlap (Razmara [0230]: “The input of 3D reconstruction algorithm 602 is a set of images 604 captured from different angles with varying degree of overlap. In first step 606 of the 3D reconstruction algorithm, a set of sparse key points is generated for each image in the set of overlapping images, and a set of feature descriptors (compact numerical representations) is generated from the set of sparse key points”) and the selected distance (Razmara [0179]: “Once computer 220 has determined the number of images of the subject required, computer 220 may determine the photography control points required to capture each of the required images. For example, computer 220 may determine a position and an orientation of drone 200 required to capture each of the thirty images referenced above. To determine the position and orientation of drone 200 required to capture each image, computer 220 may determine a distance from the subject for each image”).
The Razmara and Cantrell combination does not explicitly disclose the vehicle configured to:
and determine a distance between adjacent image capture locations of the respective contour paths based on a field of view of the camera operated to capture the images of the surface.
However, Bouffard teaches the vehicle configured to:
and determine a distance between adjacent image capture locations of the respective contour paths based on a field of view of the camera operated to capture the images of the surface (Bouffard [0079]: “To determine the particular width, the flight plan determination engine 302 can ensure that a field of view of a camera will capture images from adjacent legs that encompasses the area between the legs. For instance, if the ground sampling distance indicates a particular altitude the UAV is to fly at to capture images while navigating along each leg, the flight plan determination engine 302 can determine that a width between each leg is set at a distance such that captured images, at the particular altitude, will include the entirety of the area between each leg. Optionally, and as will be described, the flight plan determination engine 302 can further reduce the width, such that legs are spaced closer together. The reduction in width can create an overlap area between each leg, such that images captured in adjacent legs will include a same overlap area between the legs. The overlap area can be useful to ensure that the entirety of the location is imaged, for instance if a UAV gets temporarily off course (e.g., due to wind, or a temporary autopilot malfunctioning, a contingency condition, and so on), a captured image could otherwise fail to include sufficient area. The overlap can act as a buffer against such situations”).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to incorporate using the field of view as taught by Bouffard with the vehicle of Razmara and Cantrell because it would improve the accuracy of the overlap so that the entire object is captured. This motivation for the combination of Razmara, Cantrell, and Bouffard is supported by KSR exemplary rationale (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Regarding claim 18, Razmara discloses the UAV, wherein each contour path is spaced away from the surface of the scan target by a selected distance (Razmara [0067]: “Where platform 120 is at least partially controlled by a user, guidance system 130 may comprise one or more systems which provide instructions to a user controlling platform 120. Instructions provided by guidance system 130 to control platform 120 may include: [0068] an instruction to translate platform 120 by a certain distance in a certain direction; [0069] an instruction to rotate platform 120 by a certain angle in a certain direction; [0070] an instruction to pitch platform 120 by a certain angle in a certain direction; and/or [0071] an instruction to yaw platform 120 by a certain angle in a certain direction”), the one or more processors further configured by the executable instructions to:
determine a sidelap between the images of the surface (Razmara [0230]: “The input of 3D reconstruction algorithm 602 is a set of images 604 captured from different angles with varying degree of overlap. In first step 606 of the 3D reconstruction algorithm, a set of sparse key points is generated for each image in the set of overlapping images, and a set of feature descriptors (compact numerical representations) is generated from the set of sparse key points”); and
determine a distance between adjacent contour paths based at least on the sidelap (Razmara [0230]: “The input of 3D reconstruction algorithm 602 is a set of images 604 captured from different angles with varying degree of overlap. In first step 606 of the 3D reconstruction algorithm, a set of sparse key points is generated for each image in the set of overlapping images, and a set of feature descriptors (compact numerical representations) is generated from the set of sparse key points”) and the selected distance (Razmara [0179]: “Once computer 220 has determined the number of images of the subject required, computer 220 may determine the photography control points required to capture each of the required images. For example, computer 220 may determine a position and an orientation of drone 200 required to capture each of the thirty images referenced above. To determine the position and orientation of drone 200 required to capture each image, computer 220 may determine a distance from the subject for each image”).
Razmara does not explicitly disclose the UAV configured to:
determine a distance between adjacent contour paths based on a field of view of the camera operated to capture the images of the surface.
However, Bouffard teaches the UAV configured to:
determine a distance between adjacent contour paths based on a field of view of the camera operated to capture the images of the surface (Bouffard [0079]: “To determine the particular width, the flight plan determination engine 302 can ensure that a field of view of a camera will capture images from adjacent legs that encompasses the area between the legs. For instance, if the ground sampling distance indicates a particular altitude the UAV is to fly at to capture images while navigating along each leg, the flight plan determination engine 302 can determine that a width between each leg is set at a distance such that captured images, at the particular altitude, will include the entirety of the area between each leg. Optionally, and as will be described, the flight plan determination engine 302 can further reduce the width, such that legs are spaced closer together. The reduction in width can create an overlap area between each leg, such that images captured in adjacent legs will include a same overlap area between the legs. The overlap area can be useful to ensure that the entirety of the location is imaged, for instance if a UAV gets temporarily off course (e.g., due to wind, or a temporary autopilot malfunctioning, a contingency condition, and so on), a captured image could otherwise fail to include sufficient area. The overlap can act as a buffer against such situations”).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to incorporate using the field of view as taught by Bouffard with the vehicle of Razmara and Cantrell because it would improve the accuracy of the sidelap so that the entire object is captured. This motivation for the combination of Razmara, Cantrell, and Bouffard is supported by KSR exemplary rationale (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Claim(s) 5, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over the Razmara and Cantrell combination in view of Claybrough et al. (U.S. Patent Publication No. 2021/0261251 presented in the IDS received 11/18/2024, hereinafter “Claybrough”).
Regarding claim 5, the Razmara and Cantrell combination does not explicitly disclose the vehicle, the one or more processors further configured by the executable instructions to:
in response to receiving the indication of the scan target, determine a location of a plurality of points on the surface of the scan target relative to the UAV and based on one or more images of the scan target; and
associate a coordinate system with the scan target based at least on a configuration of the scan target determined from the plurality of points.
However, Claybrough teaches the vehicle, the one or more processors further configured by the executable instructions to:
in response to receiving the indication of the scan target (Claybrough [0055]: “Advantageously and according to the invention, the craft further comprises a module for accessing a three-dimensional model of said surface of said object and a module for locating the relative position of the craft with respect to said three-dimensional model of said surface of said object to be inspected, so as to be able to associate, with each region of interest targeted by said measurement apparatus, the coordinates of the region of interest in a reference point of said three-dimensional model of said surface”), determine a location of a plurality of points on the surface of the scan target relative to the UAV and based on one or more images of the scan target (Claybrough [0055]: “Advantageously and according to the invention, the craft further comprises a module for accessing a three-dimensional model of said surface of said object and a module for locating the relative position of the craft with respect to said three-dimensional model of said surface of said object to be inspected, so as to be able to associate, with each region of interest targeted by said measurement apparatus, the coordinates of the region of interest in a reference point of said three-dimensional model of said surface”); and
associate a coordinate system with the scan target based at least on a configuration of the scan target determined from the plurality of points (Claybrough [0055]: “Advantageously and according to the invention, the craft further comprises a module for accessing a three-dimensional model of said surface of said object and a module for locating the relative position of the craft with respect to said three-dimensional model of said surface of said object to be inspected, so as to be able to associate, with each region of interest targeted by said measurement apparatus, the coordinates of the region of interest in a reference point of said three-dimensional model of said surface”).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the coordinate system and points as taught by Claybrough with the vehicle of Razmara and Cantrell because it would make it possible to have three-dimensional models of surfaces that can be saved to memory and used for future planning (Claybrough [0056]). This motivation for the combination of Razmara, Cantrell, and Claybrough is supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention and rationale (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Regarding claim 12, it is rejected under the same analysis as claim 12 above.
Regarding claim 19, the Razmara and Cantrell combination does not explicitly disclose the UAV, the one or more processors further configured by the executable instructions to:
in response to receiving the indication of the scan target, determine a location of a plurality of points on the surface of the scan target relative to the UAV and based on one or more images of the scan target; and
associate a coordinate system with the scan target based at least on a configuration of the scan target determined from the plurality of points.
However, Claybrough teaches the UAV, the one or more processors further configured by the executable instructions to:
in response to receiving the indication of the scan target (Claybrough [0055]: “Advantageously and according to the invention, the craft further comprises a module for accessing a three-dimensional model of said surface of said object and a module for locating the relative position of the craft with respect to said three-dimensional model of said surface of said object to be inspected, so as to be able to associate, with each region of interest targeted by said measurement apparatus, the coordinates of the region of interest in a reference point of said three-dimensional model of said surface”), determine a location of a plurality of points on the surface of the scan target relative to the UAV and based on one or more images of the scan target (Claybrough [0055]: “Advantageously and according to the invention, the craft further comprises a module for accessing a three-dimensional model of said surface of said object and a module for locating the relative position of the craft with respect to said three-dimensional model of said surface of said object to be inspected, so as to be able to associate, with each region of interest targeted by said measurement apparatus, the coordinates of the region of interest in a reference point of said three-dimensional model of said surface”); and
associate a coordinate system with the scan target based at least on a configuration of the scan target determined from the plurality of points (Claybrough [0055]: “Advantageously and according to the invention, the craft further comprises a module for accessing a three-dimensional model of said surface of said object and a module for locating the relative position of the craft with respect to said three-dimensional model of said surface of said object to be inspected, so as to be able to associate, with each region of interest targeted by said measurement apparatus, the coordinates of the region of interest in a reference point of said three-dimensional model of said surface”).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the coordinate system and points as taught by Claybrough with the vehicle of Razmara and Cantrell because it would make it possible to have three-dimensional models of surfaces that can be saved to memory and used for future planning (Claybrough [0056]). This motivation for the combination of Razmara, Cantrell, and Claybrough is supported by KSR exemplary rationale (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention and rationale (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Claim(s) 7, 14, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over the Razmara and Cantrell combination in view of Wang et al. (U.S. Patent Publication No 2021/0116943, hereinafter “Wang”).
Regarding claim 7, the Razmara and Cantrell combination does not explicitly disclose the vehicle, the one or more processors further configured by the executable instructions to further determine the speed at which to navigate the aerial vehicle based on at least one of:
exposure time settings of the camera, or a threshold level of motion blur determined to be acceptable for the captured images.
However, Wang teaches the vehicle, the one or more processors further configured by the executable instructions to further determine the speed at which to navigate the aerial vehicle based on at least one of:
exposure time settings of the camera, or a threshold level of motion blur determined to be acceptable for the captured images (Wang [0087]: “The imaging device may have adjustable parameters. Under differing parameters, different images may be captured by the imaging device while subject to identical external conditions (e.g., location, lighting). The adjustable parameter may comprise exposure (e.g., exposure time, shutter speed, aperture, film speed), gain, gamma, area of interest, binning/subsampling, pixel clock, offset, triggering, ISO, etc. Parameters related to exposure may control the amount of light that reaches an image sensor in the imaging device. For example, shutter speed may control the amount of time light reaches an image sensor and aperture may control the amount of light that reaches the image sensor in a given time. Parameters related to gain may control the amplification of a signal from the optical sensor. ISO may control the level of sensitivity of the camera to available light. Parameters controlling for exposure and gain may be collectively considered and be referred to herein as EXPO”).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to incorporate adjusting the speed of the vehicle based on exposure as taught by Wang with the vehicle of Razmara and Cantrell it would improve the quality of images capture by the vehicle. This motivation for the combination of Razmara, Cantrell, and Wang is supported by KSR exemplary rationale (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Regarding claim 14, it is rejected under the same analysis as claim 7 above.
Regarding claim 20, the Razmara and Cantrell combination does not explicitly disclose the UAV, the one or more processors further configured by the executable instructions to further determine the speed at which to navigate the aerial vehicle based on at least one of:
exposure time settings of the camera,
or a threshold level of motion blur determined to be acceptable for the captured images.
However, Wang teaches the UAV, the one or more processors further configured by the executable instructions to further determine the speed at which to navigate the aerial vehicle based on at least one of:
exposure time settings of the camera (Wang [0087]: “The imaging device may have adjustable parameters. Under differing parameters, different images may be captured by the imaging device while subject to identical external conditions (e.g., location, lighting). The adjustable parameter may comprise exposure (e.g., exposure time, shutter speed, aperture, film speed), gain, gamma, area of interest, binning/subsampling, pixel clock, offset, triggering, ISO, etc. Parameters related to exposure may control the amount of light that reaches an image sensor in the imaging device. For example, shutter speed may control the amount of time light reaches an image sensor and aperture may control the amount of light that reaches the image sensor in a given time. Parameters related to gain may control the amplification of a signal from the optical sensor. ISO may control the level of sensitivity of the camera to available light. Parameters controlling for exposure and gain may be collectively considered and be referred to herein as EXPO”),
or a threshold level of motion blur determined to be acceptable for the captured images.
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to incorporate adjusting the speed of the UAV based on exposure as taught by Wang with the vehicle of Razmara and Cantrell it would improve the quality of images capture by the vehicle. This motivation for the combination of Razmara, Cantrell, and Wang is supported by KSR exemplary rationale (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-9, 11-13, and 17 of U.S. Patent No. 12,148,205. Although the claims at issue are not identical, they are not patentably distinct from each other because the instant claims are anticipated by the patent.
Claim Number
Instant
Claim Number
Parent
1
An aerial vehicle comprising: a camera mounted on the aerial vehicle;
1
An unmanned aerial vehicle (UAV) comprising: a UAV body including a propulsion mechanism; a camera mounted on the UAV body;
and one or more processors configured by executable instructions to: determine a plurality of contour paths spaced apart from each other along at least one axis associated with a scan target, each contour path spaced away from a surface of the scan target;
and one or more processors configured by executable instructions to: receive an indication of a scan target; determine a plurality of contour paths spaced apart from each other along at least one axis associated with the scan target, each contour path spaced away from a surface of the scan target based on a selected distance;
determine image capture locations for each contour path, each image capture location indicating a location at which an image of the surface of the scan target is to be captured;
determine a plurality of image capture locations for each contour path, each image capture location indicating a location at which an image of a surface of the scan target is to be captured;
and navigate the aerial vehicle along one or more of the contour paths at a speed that is based at least in part on a detected lighting condition,
determine, in advance, a maximum speed for the UAV to use for traversing the plurality of image capture locations of the plurality of contour paths, wherein the maximum speed is determined based at least in part on the selected distance and lighting associated with the surface;
and while operating the camera to capture images of the surface of the scan target based at least on the image capture locations.
and operate the propulsion mechanism to navigate the UAV along the plurality of contour paths at a speed based at least in part on the maximum speed while capturing images of the surface of the scan target with the camera based on the image capture locations of respective ones of the contour paths.
2
The aerial vehicle as recited in claim 1, the one or more processors further configured by the executable instructions to: detect a change in the lighting condition;
4
The UAV as recited in claim 1, the one or more processors further configured by the executable instructions to: determine a change in the lighting associated with at least a portion of the surface of the scan target;
and based at least on the change in the lighting condition, change the speed of the aerial vehicle and continue to operate the camera to capture the images.
and change the speed of the UAV based at least in part on determining the change in the lighting.
3
The aerial vehicle as recited in claim 1, wherein each contour path is spaced away from the surface of the scan target by a selected distance,
1
each contour path spaced away from a surface of the scan target based on a selected distance;
the one or more processors further configured by the executable instructions to: determine an overlap for the images of the surface;
2
The UAV as recited in claim 1, the one or more processors further configured by the executable instructions to: determine an overlap for the images of the surface;
and determine a distance between adjacent image capture locations of the respective contour paths based at least on the overlap, the selected distance, and a field of view of the camera operated to capture the images of the surface.
2
and determine a distance between adjacent image capture locations of the respective contour paths based at least on the overlap, the selected distance, and a field of view of the camera used to capture the images of the surface.
4
The aerial vehicle as recited in claim 1, wherein each contour path is spaced away from the surface of the scan target by a selected distance,
1
each contour path spaced away from a surface of the scan target based on a selected distance;
the one or more processors further configured by the executable instructions to: determine a sidelap between the images of the surface;
3
The UAV as recited in claim 1, the one or more processors further configured by the executable instructions to: determine a sidelap between the images of the surface;
and determine a distance between adjacent contour paths based at least on the sidelap, the selected distance, and a field of view of the camera operated to capture the images of the surface.
and determine a distance between adjacent contour paths based at least on the sidelap, the selected distance, and a field of view of the camera used to capture the images of the surface.
5
The aerial vehicle as recited in claim 1, the one or more processors further configured by the executable instructions to: in response to receiving the indication of the scan target,
5
The UAV as recited in claim 1, the one or more processors further configured by the executable instructions to: in response to receiving the indication of the scan target,
determine a location of a plurality of points on the surface of the scan target relative to the UAV and based on one or more images of the scan target;
determine a location of a plurality of points on the surface of the scan target relative to the UAV and based on one or more images of the scan target;
and associate a coordinate system with the scan target based at least on a configuration of the scan target determined from the plurality of points.
and associate a coordinate system with the scan target based at least on a configuration of the scan target determined from the plurality of points.
6
The aerial vehicle as recited in claim 5, the one or more processors further configured by the executable instructions to associate a selected axis of the coordinate system with at least one of: a longest edge of the scan target; or a longest element of the scan target.
6
The UAV as recited in claim 5, the one or more processors further configured by the executable instructions to associate a selected axis of the coordinate system with at least one of: a longest edge of the scan target; or a longest element of the scan target.
7
The aerial vehicle as recited in claim 1, the one or more processors further configured by the executable instructions to further determine the speed at which to navigate the aerial vehicle based on at least one of: exposure time settings of the camera, or a threshold level of motion blur determined to be acceptable for the captured images.
17
The UAV as recited in claim 15, wherein the one or more processors are further configured by the executable instructions to determine the maximum speed based on a threshold level of motion blur determined to be acceptable for the captured images.
(Claim 15 has the same limitations as claim 1)
8
A method comprising: determining, by one or more processors of an aerial vehicle, a plurality of contour paths spaced apart from each other along at least one axis associated with a scan target, each contour path spaced away from a surface of the scan target;
7
A method comprising: determining, by one or more processors of an unmanned aerial vehicle (UAV), a plurality of contour paths spaced apart from each other along at least one axis associated with a scan target, each contour path spaced away from a surface of the scan target based on a selected distance;
determining image capture locations for each contour path, each image capture location indicating a location at which an image of the surface of the scan target is to be captured;
determining a plurality of image capture locations for each contour path, a respective image capture location indicating a respective location at which a respective image of a surface of the scan target is to be captured;
and navigating the aerial vehicle along one or more of the contour paths at a speed that is based at least in part on a detected lighting condition,
determining, prior to traversing a least a portion of the plurality of contour paths, and based at least on lighting associated with the surface and the selected distance, a speed to use for traversing at least the portion of the plurality of contour paths;
and while operating the camera to capture images of the surface of the scan target based at least on the image capture locations.
and navigating the UAV along at least the portion of the plurality of contour paths at the determined speed while capturing images of the surface of the scan target based on the image capture locations.
9
The method as recited in claim 8, further comprising: detecting a change in the lighting condition;
8
The method as recited in claim 7, further comprising: determining a maximum speed for traversing a least the portion of the plurality of contour paths based at least on the lighting associated with the surface and the selected distance;
and based at least on the change in the lighting condition, changing the speed of the aerial vehicle and continue to operate the camera to capture the images.
and navigating the UAV along the plurality of contour paths at the determined speed by traversing at least the portion of the plurality of contour paths at or below the maximum speed.
10
The method as recited in claim 8, wherein each contour path is spaced away from the surface of the scan target by a selected distance, the method further comprising:
7
a plurality of contour paths spaced apart from each other along at least one axis associated with a scan target, each contour path spaced away from a surface of the scan target based on a selected distance;
determining an overlap for the images of the surface;
11
The method as recited in claim 7, further comprising: determining an overlap for the images of the surface;
and determining a distance between adjacent image capture locations of the respective contour paths based at least on the overlap, the selected distance, and a field of view of the camera operated to capture the images of the surface.
and determining a distance between adjacent image capture locations of the respective contour paths based at least on the overlap, the selected distance, and a field of view of a camera used to capture the images of the surface.
11
The method as recited in claim 8, wherein each contour path is spaced away from the surface of the scan target by a selected distance, the method further comprising:
7
a plurality of contour paths spaced apart from each other along at least one axis associated with a scan target, each contour path spaced away from a surface of the scan target based on a selected distance;
determining a sidelap between the images of the surface;
12
determining a sidelap between the images of the surface;
and determining a distance between adjacent contour paths based at least on the sidelap, the selected distance, and a field of view of the camera operated to capture the images of the surface.
and determining a distance between adjacent contour paths based at least on the sidelap, the selected distance, and a field of view of a camera used to capture the images of the surface.
12
The method as recited in claim 8, further comprising: in response to receiving the indication of the scan target, determining a location of a plurality of points on the surface of the scan target relative to the UAV and based on one or more images of the scan target;
5
The UAV as recited in claim 1, the one or more processors further configured by the executable instructions to: in response to receiving the indication of the scan target,
(vehicle claim includes the method claim)
and associating a coordinate system with the scan target based at least on a configuration of the scan target determined from the plurality of points.
determine a location of a plurality of points on the surface of the scan target relative to the UAV and based on one or more images of the scan target; and associate a coordinate system with the scan target based at least on a configuration of the scan target determined from the plurality of points.
13
The method as recited in claim 12, further comprising associating a selected axis of the coordinate system with at least one of: a longest edge of the scan target; or a longest element of the scan target.
13
The method as recited in claim 7, further comprising: associating a coordinate system with the scan target based at least on a configuration of the scan target, the coordinate system including the at least one axis, wherein the coordinate system is associated with the scan target based at least on at least one of: aligning the at least one axis with at least one of: a longest edge of the scan target; or a longest element of the scan target.
14
The method as recited in claim 8, further comprising determining the speed at which to navigate the aerial vehicle based on the detected lighting condition and at least one of: exposure time settings of the camera, or a threshold level of motion blur determined to be acceptable for the captured images.
9
The method as recited in claim 8, wherein determining the maximum speed is further based on a threshold level of motion blur determined to be acceptable for the captured images.
15
An unmanned aerial vehicle (UAV) comprising: a UAV body including a propulsion mechanism; a camera mounted on the UAV body;
1
An unmanned aerial vehicle (UAV) comprising: a UAV body including a propulsion mechanism; a camera mounted on the UAV body;
and one or more processors able to communicate with the propulsion mechanism and the camera,
and one or more processors configured by executable instructions to:
the one or more processors configured by executable instructions to: determine a plurality of contour paths spaced apart from each other along at least one axis associated with a scan target,
determine a plurality of contour paths spaced apart from each other along at least one axis associated with the scan target,
each contour path spaced away from a surface of the scan target;
each contour path spaced away from a surface of the scan target based on a selected distance;
determine image capture locations for each contour path, each image capture location indicating a location at which an image of the surface of the scan target is to be captured;
determine a plurality of image capture locations for each contour path, each image capture location indicating a location at which an image of a surface of the scan target is to be captured;
and control the propulsion mechanism to navigate the aerial vehicle along one or more of the contour paths at a speed that is based at least in part on a detected lighting condition,
determine, in advance, a maximum speed for the UAV to use for traversing the plurality of image capture locations of the plurality of contour paths, wherein the maximum speed is determined based at least in part on the selected distance and lighting associated with the surface; and operate the propulsion mechanism to navigate the UAV along the plurality of contour paths at a speed based at least in part on the maximum speed while capturing images of the surface of the scan target with the camera based on the image capture locations of respective ones of the contour paths.
and while operating the camera to capture images of the surface of the scan target based at least on the image capture locations.
while capturing images of the surface of the scan target with the camera based on the image capture locations of respective ones of the contour paths.
16
The UAV as recited in claim 15, the one or more processors further configured by the executable instructions to: detect a change in the lighting condition;
4
The UAV as recited in claim 1, the one or more processors further configured by the executable instructions to: determine a change in the lighting associated with at least a portion of the surface of the scan target;
and based at least on the change in the lighting condition, change the speed of the aerial vehicle and continue to operate the camera to capture the images.
and change the speed of the UAV based at least in part on determining the change in the lighting.
17
The UAV as recited in claim 15, wherein each contour path is spaced away from the surface of the scan target by a selected distance,
1
each contour path spaced away from a surface of the scan target based on a selected distance;
the one or more processors further configured by the executable instructions to: determine an overlap for the images of the surface;
2
determine an overlap for the images of the surface;
and determine a distance between adjacent image capture locations of the respective contour paths based at least on the overlap, the selected distance, and a field of view of the camera operated to capture the images of the surface.
and determine a distance between adjacent image capture locations of the respective contour paths based at least on the overlap, the selected distance, and a field of view of the camera used to capture the images of the surface.
18
The UAV as recited in claim 15, wherein each contour path is spaced away from the surface of the scan target by a selected distance,
1
each contour path spaced away from a surface of the scan target based on a selected distance;
the one or more processors further configured by the executable instructions to: determine a sidelap between the images of the surface;
3
The UAV as recited in claim 1, the one or more processors further configured by the executable instructions to: determine a sidelap between the images of the surface;
and determine a distance between adjacent contour paths based at least on the sidelap, the selected distance, and a field of view of the camera operated to capture the images of the surface.
and determine a distance between adjacent contour paths based at least on the sidelap, the selected distance, and a field of view of the camera used to capture the images of the surface.
19
The UAV as recited in claim 15, the one or more processors further configured by the executable instructions to: in response to receiving the indication of the scan target, determine a location of a plurality of points on the surface of the scan target relative to the UAV and based on one or more images of the scan target;
5
The UAV as recited in claim 1, the one or more processors further configured by the executable instructions to: in response to receiving the indication of the scan target, determine a location of a plurality of points on the surface of the scan target relative to the UAV and based on one or more images of the scan target;
and associate a coordinate system with the scan target based at least on a configuration of the scan target determined from the plurality of points.
and associate a coordinate system with the scan target based at least on a configuration of the scan target determined from the plurality of points.
20
The UAV as recited in claim 15, the one or more processors further configured by the executable instructions to further determine the speed at which to navigate the aerial vehicle based on at least one of: exposure time settings of the camera, or a threshold level of motion blur determined to be acceptable for the captured images.
17
The UAV as recited in claim 15, wherein the one or more processors are further configured by the executable instructions to determine the maximum speed based on a threshold level of motion blur determined to be acceptable for the captured images.
Allowable Subject Matter
Claims 6 and 13 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, and the double patenting set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AIDAN KEUP whose telephone number is (703)756-4578. The examiner can normally be reached Monday - Friday 8:00-4:00.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Emily Terrell can be reached at (571) 270-3717. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/AIDAN KEUP/ Examiner, Art Unit 2666 /Molly Wilburn/Primary Examiner, Art Unit 2666
Prosecution Insights