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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 04/15/2026 has been entered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 05/12/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Amendments
Submission dated 04/15/2026 amends claims 1, 14 and 20. Claims 1-20 are pending.
Response to Arguments
Applicant's arguments filed on 04/15/2026 have been fully considered but they are not persuasive.
On pages 9-11, the applicant argues that Kwon, Isei and Cho do not teach or suggest “obtaining first depth data of a monument and a part from a first sensor and second depth data of the monument and the part from a second sensor, wherein the monument is a real-world object that is distinct from the part.”
The examiner disagrees because Cho as applied teaches the quoted limitations. For example, the cited portion of Cho teaches obtaining multiple depth image pairs of an environment at multiple positions/poses from the sensors, wherein the environment includes large surfaces, such as walls and floors, and a target object (see, e.g., pars. 34-37, 42-43, 56-57, 64, and 81 and FIGS. 4 and 5 of Cho). Here, the large surfaces and target object in the environment correspond to the claimed monument and part, respectively. As such, the examiner finds the applicant’s arguments unpersuasive.
On pages 11-15, the applicant argues that Yoshimoto, Xu, Weingaertner, Duan and Christoph do not teach or suggest “obtaining first depth data of a monument and a part from a first sensor and second depth data of the monument and the part from a second sensor, wherein the monument is a real-world object that is distinct from the part.”
The examiner finds these arguments moot because the examiner have not applied and does not apply those references to the quoted limitations.
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, 4, 7, 12-14, 16, 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Us patent application publication no. 2023/0306626 to Cho et al. (hereinafter Cho) in view of us patent application publication no. 2025/0067614 to Isei et al. (hereinafter Isei).
For claims 1 and 14, Cho as applied teaches, at a computing system (see, e.g., FIG. 1), a method of obtaining a measurement of a part using depth data from a plurality of sensors (see, e.g., pars. 20-21 and 26-27), the method comprising:
obtaining first depth data of a monument and a part from a first sensor and second depth data of the monument and the part from a second sensor (see, e.g., pars. 34-37, 42-43 and 56-57 and FIGS. 4 and 5, which teach obtaining multiple depth image pairs of an environment at multiple positions/poses from the sensors, wherein the sensors include a TOF sensor), wherein the monument is a real-world object that is distinct from the part (see, e.g., pars. 64 and 81, which teach that the environment includes large surfaces such as walls and floors and a target object; the examiner interprets the large surfaces and target object in the environment as the claimed monument and part, respectively);
detecting a plurality of planes in the first depth data and the second depth data, wherein each plane of the plurality of planes corresponds to a corresponding face on the monument (see, e.g., pars. 37 and 81 and FIGS. 1 and 9, which teach identifying large planes corresponding to the large surfaces, such as floors and walls, from each 3d point cloud);
performing a rotational alignment of the plurality of planes (see, e.g., pars. 75 and 81-82 and FIGS. 6 and 9, which teach determining a relative rotation between the 3d point clouds, wherein each clouds includes the large planes);
performing a translational alignment of the rotationally aligned plurality of planes (see, e.g., pars. 75 and 81-82 and FIGS. 6 and 9, which teach determining a relative translation between the 3d point clouds);
determining one or more transformations that align the first depth data and the second depth data to a common coordinate system based upon the rotational alignment and the translational alignment (see, e.g., pars. 76-78 and 81-82 and FIGS. 6 and 9, which teach aligning the 3d point clouds within a common coordinate system based on the relative rotation and translation);
using the one or more transformations to align the first depth data and the second depth data and thereby form aligned depth data (see, e.g., pars. 37, 76-78 and 81-82 and FIGS. 6 and 9, which teach generating the common 3d point cloud by aligning the 3d point clouds);
determining a measurement of the part based upon the aligned depth data (see, e.g., pars. 37-38 and 92 and FIG. 9, which teach computing the dimensional measurement of the target object within the common 3d point cloud); and
outputting the measurement of the part (see, e.g., pars. 37-38 and 93 and FIG. 9, which teach displaying an indication of the dimensional measurements).
While Cho as applied teaches obtaining first and second depth data of a monument and a part from the sensors (see, e.g., pars. 34-37, 42-43 and 56-57 and FIGS. 4 and 5), it does not explicitly teach that “the first sensor and the second sensor scan the part along an axis of measurement to obtain the first depth data and the second depth data.” Isei in the analogous art teaches scanning the object, e.g., a crankshaft, along an axis of measurement, e.g., the direction of a rotation center axis L (X-axis direction) to obtain multiple sets of 3D data from multiple sensors (see, e.g., pars. 48-59 and FIGS. 3A-B of Isei).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Cho to obtain sensor data as taught by Isei because doing so would allow measuring the entire surface of the object at high speed, facilitating a total inspect of the object (see, e.g., pars. 50 and 53 of Isei).
For claim 20, Cho as applied teaches a system (see, e.g., FIG. 1), comprising:
a plurality of depth sensors arranged in a constellation at least partially surrounding a part and a monument (see, e.g., pars. 26-29 and 35-36 and FIG. 1, which teach a TOF sensor and a camera arranged to at least partially surround one or more objects in the environment);
one or more processors (see, e.g., pars. 28 and 34 and FIG. 1); and
a memory (see, e.g., pars. 26 and 31 and FIG. 1) storing instructions executable by the one or more processors to,
obtain depth data of the monument and the part from the plurality of depth (see, e.g., pars. 34-37, 42-43 and 56-57 and FIGS. 4 and 5, which teach obtaining multiple depth image pairs of an environment at multiple positions/poses from the sensors, wherein the sensors include a TOF sensor), wherein the monument is a real-world object that is distinct from the part (see, e.g., pars. 64 and 81, which teach that the environment includes large surfaces such as walls and floors and a target object; the examiner interprets the large surfaces and target object in the environment as the claimed monument and part, respectively);
detect a plurality of planes in the depth data, wherein each plane of the plurality of planes corresponds to a corresponding face on the monument(see, e.g., pars. 37 and 81 and FIGS. 1 and 9, which teach identifying large planes corresponding to the large surfaces, such as floors and walls, from each 3d point cloud);
perform a rotational alignment of the depth data based upon the plurality of planes (see, e.g., pars. 75 and 81-82 and FIGS. 6 and 9, which teach determining a relative rotation between the 3d point clouds, wherein each clouds includes the large planes);
perform a translational alignment of the rotationally aligned depth data based upon the plurality of planes (see, e.g., pars. 75 and 81-82 and FIGS. 6 and 9, which teach determining a relative translation between the 3d point clouds);
determine one or more transformations that align the depth data to a common coordinate system based upon the rotational alignment and the translational alignment (see, e.g., pars. 64, 75-78 and 81-83 and FIGS. 4 and 9-11 which teach searching for transformations that minimize a distance the point clouds, wherein the transformations include matching the point clouds into a single coordinate, e.g., by rotating and translating the planes to match with x and y planes and matching centers and locations of the planes to one another);
use the one or more transformations to align the depth data and thereby form aligned depth data (see, e.g., pars. 37, 76-78 and 81-82 and FIGS. 6 and 9, which teach generating the common 3d point cloud by aligning the 3d point clouds);
determine a measurement of the part based upon the aligned depth data (see, e.g., pars. 37-38 and 92 and FIG. 9 of Cho, which teach computing the dimensional measurement of the target object within the common 3d point cloud); and
output the measurement of the part (see, e.g., pars. 37-38, 93 and FIG. 9 of Cho, which teach displaying an indication of the dimensional measurements).
While Cho as applied teaches obtaining first and second depth data of a monument and a part from the sensors (see, e.g., pars. 34-37, 42-43 and 56-57 and FIGS. 4 and 5), it does not explicitly teach a plurality of depth sensors that “scan the part along an axis of measurement to obtain the depth data.” Isei in the analogous art teaches scanning the object, e.g., a crankshaft, along an axis of measurement, e.g., the direction of a rotation center axis L (X-axis direction) to obtain 3D data from multiple sensors (see, e.g., pars. 48-59 and FIGS. 3A-B of Isei).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Cho to obtain depth data using multiple depth sensors as taught by Isei because doing so would allow measuring the entire surface of the object at high speed, facilitating a total inspect of the object (see, e.g., pars. 50 and 53 of Isei).
For claim 4, while Cho does not explicitly teach, Isei in the analogous art teaches obtaining the first depth data and the second depth data from a constellation of sensors at least partially surrounding the part (see, e.g., pars. 48-59 and FIGS. 3A-B of Isei, which teach obtaining depth data from at least two sensors, e.g., surface shape measuring part 1, placed in different locations with respect to an object).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Cho to obtain sensor data as taught by Isei because doing so would allow measuring the entire surface of the object at high speed, facilitating a total inspect of the object (see, e.g., pars. 50 and 53 of Isei).
For claims 7 and 16, Cho in view of Isei teaches:
identifying one or more connected point clouds in the first depth data and the second depth data (see, e.g., pars. 70-74 and FIGS. 6-7 of Cho, which teach determining whether the distances between the points in the point clouds are within threshold correspondences); and
removing outliers from the one or more connected point clouds before aligning the first depth data and the second depth data (see, e.g., pars. 70-74 and FIGS. 6-7 of Cho, which teach removing outliers from the point clouds before aligning the point clouds).
For claim 12, while Cho does not explicitly teach, Isei in the analogous art teaches that the first sensor and the second sensor are located at fixed positions relative to one another (see, e.g., pars. 48-59 and FIGS. 3A-B of Isei, which teach obtaining depth data from at least two sensors, e.g., surface shape measuring part 1, placed in different locations relative to one another).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Cho to obtain sensor data as taught by Isei because doing so would allow measuring the entire surface of the object at high speed, facilitating a total inspect of the object (see, e.g., pars. 50 and 53 of Isei).
For claim 13, Cho in view of Isei teaches that the monument comprises at least three non-parallel faces (see, e.g., pars. 64 of Cho, which teach identifying a ground plane and wall planes).
Claim(s) 3, 9, 10, 18, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cho in view of Isei and further in view of Us patent application publication no. 2023/0196699 to Kwon.
For claim 3, while Cho in view of Isei does not explicitly teach, Kwon in the analogous art teaches that using the one or more transformations to align the first depth data and the second depth data comprises aligning the first depth data and the second depth data in six degrees of freedom (see, e.g., pars. 64-66 and 76 of Kwon, which teach that aligning two point cloud data in seven degrees of freedom).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Cho to align the 3d point clouds in at least six DoF as taught by Kwon because doing so would improve the computation efficiency of solving the 6DoF problem (see, e.g., par. 66 of Kwon).
For claims 9 and 18, while Cho in view of Isei does not explicitly teach, Kwon in the analogous art teaches that performing the rotational alignment comprises:
(1) determining rotational error between one or more of the plurality of planes in the first depth data and the second depth data and each corresponding face on the monument;
(2) rotating the one or more of the plurality of planes;
(3) determining an updated rotational error; and
(4) repeating (1)-(3) until the updated rotational error is within a predetermined rotational error threshold or a predetermined number of iterations is reached (see, e.g., pars. 78-86 and FIGS. 9 and 11-12 of Kwon, which teach repeatedly performing, e.g., using an ICP technique, the direction optimization by minimizing the error, e.g., a predefined degree of precision, between iterations).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Cho in view of Isei to repeatedly perform the error minimization as taught by Kwon because doing so would yield predictable results of achieving the optimized rotation/direction (see, e.g., pars. 78-86 of Kwon).
For claims 10 and 19, while Cho in view of Isei does not explicitly teach, Kwon in the analogous art teaches that performing the translational alignment comprises translating one or more of the plurality of planes in the first depth data and the second depth data until a distance between the one or more of the plurality of planes and each corresponding face on the monument satisfies a threshold condition (see, e.g., pars. 78-86 and FIGS. 9 and 11-12 of Kwon, which teach repeatedly performing, e.g., using an ICP technique, the location optimization by minimizing the error, e.g., a predefined degree of precision, between iterations).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Cho in view of Isei to repeatedly perform the error minimization as taught by Kwon because doing so would yield predictable results of achieving the optimized translation/location (see, e.g., par. 78-86 of Kwon).
Claim(s) 2 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cho in view of Isei and further in view of Us patent application publication no. 2018/0106595 to Christoph et al. (hereinafter Christoph).
For claims 2 and 15, while Cho in view of Isei does not explicitly teach, Christoph in the analogous art teaches determining the measurement within a tolerance of 0.01 inches or less (see, e.g., pars. 22, 36, 42, and 63 of Christoph, which teach measuring micro-features of a workpiece in the unit of tens of micrometers (μm)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Cho in view of Isei to measure a workpiece in the micro units as taught by Christoph because doing so would yield predictable results of improving accuracy and precision of the measurement (see MPEP 2143(I)(D)).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cho in view of Isei and further in view of Us patent application publication no. 2023/0377122 to Duan et al. (hereinafter Duan).
For claim 5, while Cho in view of Isei does not explicitly teach, Duan in the analogous art teaches before obtaining the first depth data and the second depth data, positioning the first sensor and the second sensor at a predetermined cross-section of the part (see, e.g., pars. 112-118 of Duan, which teach positioning lidar sensors along the length of the part).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Cho in view of Isei to position the lidar sensors along the length of the part as taught by Duan because doing so would yield predictable results of obtaining depth distances of a cross section of the part, ensuring the quality and good product rate of the end products (see MPEP 2143(I)(D) and par. 115 of Duan).
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cho in view of Isei and further in view of us patent application publication no. 2007/0176130 to Weingaertner et al. (hereinafter Weingaertner).
For claim 6, Cho in view of Isei does not explicitly obtaining depth data from ten or more sensors.
Weingaertner in the analogous art teaches obtaining distance/depth data using ten or more distance sensors (see, e.g., par. 13 of Weingaertner). It would have been obvious to modify Kwon in view of Isei and Cho to use at least 10 sensors as taught by Weingaertner because doing so would yield predictable results of being able to obtain data from more diverse sources, rendering the obtainment process more robust and stable (MPEP 2143(I)(D)).
Claim(s) 8 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cho in view of Isei and further in view of Us patent application publication no. 2017/0186234 to Xu.
For claim 8, Cho in view of Isei teaches rotating the depth data before aligning the depth data (see, e.g., pars. 67 and 75-76 and FIGS. 4 and 9, which teach rotating the point clouds so that the corresponding planes match with X-Y plane before the full registration ).
Cho in view of Isei, however, does not explicitly teach that the rotation is by an installation angle of the sensor. Xu in the analogous art teaches using the installation angle of a sensor as a rotation angle (see, e.g., par. 15 and FIG. 1 of Xu).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Cho in view of Isei to rotate the point clouds by the installation angle as taught by Xu because doing so would yield the predictable results of alleviating the deviation caused by the installation angle of sensor (see MPEP 2143(I)(D)).
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cho in view of Isei and further in view of Us patent application publication no. 2023/0267593 to Yoshimoto et al. (hereinafter Yoshi).
For claim 11, while Cho in view of Isei does not explicitly teach, Yoshi in the analogous art teaches that determining the measurement of the part comprises identifying a flange on the part, and determining the measurement at a location of the flange (see, e.g., pars. 54 and 74 and FIGS. 6-8 of Yoshi, which teach identifying a flange of a workpiece and estimating its outline and size).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Cho in view of Isei to identify and measure a portion of point cloud corresponding to a flange of a workpiece as taught by Yoshi because doing so would allow measure a workpiece without referencing CAD data (see, e.g., pars. 5, 9 and 98 of Yoshi).
Conclusion
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/WOO C RHIM/Examiner, Art Unit 2676
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