DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 1-8 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. This is a result of claim 1 reciting the limitation "the small set of alignment points " in last limitation. There is insufficient antecedent basis for this limitation in the claim. The limitation is being considered for examination purposes herein as referring to the “set of alignment points”.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-3 and 5-8 are rejected under 35 U.S.C. 102(a)(1) / 102(a)(2) as being anticipated by Pompe et al (US 20200408913).
Regarding Claim 1:
Pompe et al disclose a method of using a scanning system (abstract) comprising:
creating at least two scans of a single environment by scanning the single environment from multiple locations using a scanning system (see par. 6 - generating a three-dimensional (3D) scan of an environment includes a set of 3D scanners that includes a first 3D scanner at a first position and a second 3D scanner at a second position, the first position being different from the second position; par. 52 - a 3D scan of the environment is captured using multiple data capture devices; par. 61 - This facilitates the multiple devices to scan the environment simultaneously; and par. 63 - the scanning system 20A, 20B captures respective data capture 233A, 233B corresponding to the view that each of the scanning systems 20A, 20B faces);
selecting a set of alignment points, wherein each alignment point is present in more than one of the at least two scans (see par. 76 - The partial data captures are aligned for being combined based on a starting point 251 in one or more examples. Alternatively, or in addition, the alignment of the data captures is performed using one or more overlapping regions from the data captures. The reference coordinate systems of the data captures are matched/registered with each other so that the data captures can be combined; par. 77 - The alignment can be performed automatically using such features. For example, the geometrical structure of a data capture is matched against second data capture until an overlay is reached within a predetermined probability threshold. In this embodiment a line matching methodology such as Iterative Closest Point (ICP) for example, may be used for the alignment of the data sets; and par. 58 - The multiple data captures (scans) from the respective scanning systems 20 further have to be registered (aligned) in 3D space for combining the data into the single global data capture); and
using the small set of alignment points to combine the at least two scans in near real time to form a single representation of the environment (par. 73 - The combining of the captured data [using the set of alignment points] from each respective scanning system 20 can be done using... directly the 3D points (like Iterative Closest Points (ICP), Normal Distributions Transform (NDT) or similar) are used; par. 76 - The reference coordinate systems of the data captures are matched/registered with each other so that the data captures can be combined; and par. 57 - multiple scanning systems 20, to scan separate portions of the environment and combine such separate data captures from the respective scanning system to generate a global/combined "global data capture" for the overall environment in real time).
Regarding Claim 2:
Pompe et al disclose the method of claim 1, wherein the alignment points are selected from static elements in the single environment (Fig. 8 and Fig. 9).
Regarding Claim 3:
Pompe et al disclose the method of claim 1, wherein the alignment points are fiducial markers added to the single environment (see par. 2 - generating a point cloud of the scanned environment by combining scanned data of the environment; and par. 23 - multiple three-dimensional (3D) scanners that work cooperatively to capture 3D point cloud data of an environment. The point cloud(s) can be used to generate a map of an environment).
Regarding Claim 5:
Pompe et al disclose the method of claim 1, wherein the alignment points are identified by a user in each of the at least two scans (see par. 69 - the operator can select what portions of the captured data is to be transferred from the one or more data capture devices. For example, the operator, on the controller 235, is shown a list of one or more data captures from the scanning system 20A and the operator can then choose a data capture from those data captures. A partial data capture i.e. a subset of the points from the chosen data capture are transferred to the controller 235 in response. A predetermined set of points from the point cloud that is captured by the scanning system 20A is transferred; and par. 78 - the operator aligns the data captures using the one or more common/overlapping features via the user interface 237 in the controller 235).
Regarding Claim 6:
Pompe et al disclose the method of claim 3, wherein the alignment points are automatically identified in each of the at least two scans (see par. 23 - multiple three-dimensional (3D) scanners that work cooperatively to capture 3D point cloud data of an environment. The point cloud(s) can be used to generate a map of an environment; par. 76 - the alignment of the data captures is performed using one or more overlapping regions from the data captures. The reference coordinate systems of the data captures are matched/registered with each other so that the data captures can be combined; and par. 77 - The alignment can be performed automatically using such features).
Regarding Claim 7:
Pompe et al disclose the method of claim 1, wherein the at least two scans are combined by applying a transformation to one or more of the at least two scans to align each of the alignment points from the at least two scans in the single representation (see par. 76 - Alternatively, or in addition, the alignment of the data captures is performed using one or more overlapping regions from the data captures. The reference coordinate systems of the data captures are matched/registered with each other so that the data captures can be combined; and par. 77 - The alignment can be performed automatically using such features ... the geometrical structure of a data capture is matched against second data capture until an overlay is reached within a predetermined probability threshold. In this embodiment a line matching methodology such as Iterative Closest Point (ICP) for example, may be used for the alignment of the data sets. Once the second data capture is in the correct position the offset vector from the previous data capture origin to the new data capture origin is determined in the coordinate system of the previous data capture).
Regarding Claim 8:
Pompe et al disclose the method of claim 7, wherein the transformation is iteratively calculated until each of the alignment points from the at least two scans are aligned within a preselected threshold (see par. 77 - The alignment can be performed automatically using such features. For example, the geometrical structure of a data capture is matched against second data capture until an overlay is reached within a predetermined probability threshold. In this embodiment a line matching methodology such as Iterative Closest Point (ICP) for example, may be used for the alignment of the data sets).
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 4 is rejected under 35 U.S.C. 103 as being unpatentable over Pompe et al as applied to claim 1 above, and further in view of well-known prior art (MPEP 2144.03).
Regarding Claim 4:
Pompe et al the method of claim 1, the set of alignment points has alignment points and at least a threshold of alignment points are visible from each of the at least two scans (see par. 63 - the scanning systems 20A, 20B are located such that the areas scanned by each respective system 20A, 20B overlap [at least two scans]; par. 76 - The partial data captures are aligned for being combined based on a starting point 251 in one or more examples... in addition, the alignment of the data captures is performed using one or more overlapping regions from the data captures. The reference coordinate systems [the set of alignment points] of the data captures are matched/registered with each other so that the data captures can be combined; and par. 77 - The alignment can be performed automatically using such features. For example, the geometrical structure of a data capture is matched against second data capture until an overlay is reached within a predetermined probability threshold. In this embodiment a line matching methodology such as Iterative Closest Point (ICP) for example, may be used for the alignment of the data sets [the set of alignment points has alignment points and at least a threshold of alignment points are visible from each of the at least two scans]), but fails to explicitly disclose the set of alignment points has at least four alignment points and at least three alignment points are visible from each of the at least two scans.
However, having as a set alignment points "at least four alignment points and at least three alignment points are visible from each of the at least two scans", would have been well known to one of ordinary skill in the art at the time of the invention in order to provide redundancy for increased accuracy, error detection, and stable, constrained alignment (registration) of the scan data, and moreover in Pompe et al, to have an optimal number of points to determine a high probability threshold (par. 77). For these reasons, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified Pompe et al to wherein the set of alignment points has at least four alignment points and at least three alignment points are visible from each of the at least two scans.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 16 April 2024 was filed in compliance with the provisions of 37 CFR 1.97 and 1.98. Accordingly, the IDS has been considered by the examiner.
The relevance of the cited document(s), in addition to any applied above, can be found in the International Search Report and/or Written Opinion from the ISA dated 26 March 2024 for PCT/US2024/010475 (of record).
Cited Art
The prior art and other references made of record and not relied upon are considered pertinent to applicant's disclosure.
Selviah et al (US 11049267 B2) disclose 3D surveying, mapping, and imaging, in particular, relating to the rotational alignment of 3D datasets, and optionally also translational alignment of 3D datasets. The 3D datasets are stored as point clouds, transformed into vector sets, and the vector sets are represented as a unit sphere or Gaussian sphere and compared for best alignment. The found best alignment is used to rotate the two 3D datasets into rotational and translational alignment with one another.
Li et al (US 11501492 B1) disclose automated operations to analyze visual data combined from multiple images captured in a room to determine the room shape, such as by iteratively refining alignment of the multiple images' visual data into a common coordinate system until alignment differences satisfy one or more defined criteria, and for subsequently using the determined room shape information in further automated manners. The images may be panorama images in an equirectangular or other spherical format, and determined room shapes for one or more rooms of a building may be fully closed three-dimensional shapes and used to improve navigation of the building (e.g., as part of a generated building floor plan)—the automated room shape determination may be further performed without having or using information from any distance-measuring devices about distances from an image's acquisition location to walls or other objects in the surrounding room.
Foster et al (US 11714193 B1) disclose a method for registering distance scan data that includes: accessing a first distance scan recorded, at a first time, by a first depth sensor defining a first field of view; accessing a second distance scan recorded, at approximately the first time, by a second depth sensor defining a second field of view overlapping a portion of the first field of view; calculating a first set of lines represented by points in a first portion of the first distance scan overlapping a second portion of the second distance scan; calculating a second set of lines represented by points in the second portion of the second distance scan; calculating skew distances between each pair of corresponding lines in the first and second sets of lines; and calculating an alignment transformation that aligns the first distance scan and the second distance scan to minimize skew distances between corresponding pairs of lines.
Wohlfeld et al (US 12412288 B2) disclose a method that includes receiving a first plurality of coordinate measurement points capturing a portion of an environment and a reference object within the environment, the first plurality of coordinate measurement points defining at least a portion of a first point cloud. The method further includes receiving a second plurality of coordinate measurement points from a position other than the at least one aerial position, the second plurality of coordinate measurement points capturing at least some of the portion of the environment and the reference object within the environment, the second plurality of coordinate measurement points defining at least a portion of a second point cloud. The method further includes aligning the first point cloud and the second point cloud based at least in part on the reference object captured in the first point cloud and the reference object captured the second point cloud to generate a combined point cloud.
Cai et al (US 20180101934 A1) disclose a method for creating an image that includes identifying data representing an overlapping region in each of a first set and second set of image data, wherein the first and second sets of image data are arranged to represent a first image and a second image respectively, and at least one common feature in both the first image and the second image is identified in the overlapping region. A portion of the data representing a portion of the overlapping region in each of the first and the second sets of image data is discarded to obtain a first set and a second set of modified image data. The first and the second sets of modified image data are combined to a third set of image data arranged to represent a third image including at least a portion of each of the first image and the second image.
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/Scott A Rogers/
Primary Examiner, Art Unit 2681
13 December 2025