DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This office action is in response to the application filed on September 28, 2023. Claims 1-20 are presently pending and are presented for examination.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on September 28, 2023, March 9, 2026, and September 8, 2026. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement are being considered by the examiner.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The 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.
Claims 1-18 and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Henry et al., US 20210263488 A1 (Hereinafter “Henry”).
Regarding Claims 1 and 14, Henry discloses a model obtaining method, comprising: controlling a movable object carrying a load to move along a first path, and control the load, while moving, to collect first information of a target object during a movement; See [0041-0045], “FIG. 1 illustrates an example system 100 able to perform autonomous scanning using an unmanned aerial vehicle (UAV) 102 according to some implementations … the system 100 may also include a controller 104 and a docking station 106. The controller 104 may be controlled by a user 108 and may be configured to communicate with the UAV 102 via a wireless communication link … The controller 104 may receive images (which may include video or still images) from the UAV 102 via the wireless communication link … the UAV 102 includes a propulsion mechanism, one or more image sensors, and one or more processors able to control the propulsion mechanism for navigating the UAV 102, such as based on input from the one or more image sensors and/or other sensors onboard the UAV 102. In some examples, the user 108 may use the controller 104 to select or otherwise indicate to the UAV 102 that the scan target 110 is a scan target for executing a scan … The controller 104 may further be used to indicate a specified scanning distance (e.g., a ground sampling distance (GSD)) from the surface of the scan target 110 for the scan to be performed, as well as other scan parameters as discussed additionally below … The processor(s) onboard the UAV 102 may be configured by executable instructions to generate, receive, or otherwise access a lower-resolution 3D model (not shown in FIG. 1) of the scan target 110 for performing the scan of the scan target 110.”
establishing, based on the first information, an initial model of the target object; planning, based on the initial model and a preset condition, at least one second path; See [0045-0046], “The processor(s) onboard the UAV 102 may be configured by executable instructions to generate, receive, or otherwise access a lower-resolution 3D model (not shown in FIG. 1) of the scan target 110 for performing the scan of the scan target 110 … The lower-resolution 3D model generated or otherwise accessed by the UAV 102 may include a set of points in 3D space corresponding to surfaces of the scan target 110 detected during an initial scan of the scan target 110 at a first, lower resolution … Based on the lower-resolution 3D model, the processor(s) may determine and execute a scan plan for scanning the scan target 110 by capturing a series of images of the scan target 110 at a second, higher resolution. The scan plan may include a series of poses determined by the processor(s) for the UAV 102 to adopt to capture, using the one or more image sensors, the series of images of the scan target 110.” + [0028] here teaches that the initial model is/can be generated via a first rough scan (i.e. from a first path corresponding first information flown/collected by the UAV)
controlling the movable object to move along the at least one second path, and controlling the load, while moving, to collect second information of the target object; and determining, based on at least the second information, a target model of the target object. See [0047], “The UAV 102 may use the one or more image sensors to capture one or more images of the scan target 110 from each pose in the scan plan. As one example, a position of the pose may be determined to be along the respective normal for the selected point (e.g., a selected center point of a respective image), and at a selected distance from the selected point corresponding to the scanning distance parameter of the scan plan.” And [0050], “the processor(s) may generate the scan plan to cover all points based on balancing various considerations such as obtaining full coverage of all accessible surfaces of the scan target 110, having a regular and predictable pattern for the poses, and enabling efficient navigation of the UAV 102 during execution of the scan plan. In some cases, the processor may determine the entirety of the scan plan in advance before beginning scanning of the scan target 110 according to the scan plan. “ Also [0051], “the scan plan and the 3D model may be iteratively updated during flight. For example, as mentioned above, the UAV 102 may determine an initial scan plan to ensure surface coverage on the surface(s) corresponding to the lower-resolution 3D model defined by the TSDF. The UAV 102 may traverse at least a portion of the initial scan plan while continuing to update the 3D model based on additional range distance measurements determined as the UAV 102 navigates the scan plan.”
Regarding Claim 2, Henry discloses the following limitation dependent on Claim 1:
wherein the load includes a camera; the load collecting the first information of the target object includes the load shooting a plurality of primary images of the target object; and the load collecting the second information of the target object includes the load shooting a plurality of supplementary images of the target object. See [0035], “The UAV may use the lower-resolution 3D model to generate and dynamically update a scan plan for scanning the scan target. For instance, scanning may include capturing a series of images of the scan target from a desired distance (e.g., a specified ground sampling distance) between the UAV and the scan target for capturing images of a desired resolution, detail, or the like. As one example, determining the scan plan may include determining a sequence of poses for the UAV to assume to for performing a higher-resolution scan than the initial scan for capture a plurality of images of the scan target at a specified distance from the scan target surface using one or more image sensors onboard the UAV.”
Regarding Claim 3, Henry discloses the following limitation dependent on Claim 1:
wherein the preset condition includes at least one preset distance, and the at least one preset distance is a distance between the movable object and the target object. See [0044], “The controller 104 may further be used to indicate a specified scanning distance (e.g., a ground sampling distance (GSD)) from the surface of the scan target 110 for the scan to be performed, as well as other scan parameters as discussed additionally below.”
Regarding Claim 4, Henry discloses the following limitation dependent on Claim 3:
wherein the at least one second path includes a plurality of position points, and distances from the plurality of location points to a surface of the target object are substantially equal. See [0046], “the scan plan may select points to use as center points for respective images, while selecting the successive center points to be sufficiently close to preceding center points to provide a desired amount of overlap of images taken at a specified ground sampling distance and at a desired resolution. For each pose, the processor(s) may control the propulsion mechanism to cause the UAV 102 to fly to assume the pose corresponding to the pose for traversing the sequence of poses of the scan plan.”
Regarding Claim 5, Henry discloses the following limitation dependent on Claim 3:
wherein the at least one preset distance is smaller than distances between position points on the first path and the target object. See [0099], “the UAV 102 may first perform an initial low-resolution scan of the scan target 110 to generate a rough lower-resolution 3D model of the scan target 110. As discussed additionally below, the UAV 102 may then determine a scan plan based on the lower-resolution 3D model, and may proceed to scan the scan target 110 based on the poses determined for the scan plan to attempt to cover every surface of the scan target 110 within the bounding volume 702 using the specified image capture parameters. In some cases, the image capture parameters and poses for performing image captures may be adaptively determined to ensure high quality 3D reconstruction of the captured scan target 110. For instance, the user interface 602 may further be used to specify semantic segmentation for capturing different types of scan targets or different portions of scan targets at different resolutions, e.g., trees with low-resolution/far distance, concrete with maximum resolution/close distance, steel beams with medium resolution/medium distance, bolts or other fasteners with maximum resolution/close distance etc. In some examples, these different resolutions may be set in advance as default settings for certain types of scan targets, or the like. For instance, a machine learning model executable onboard the UAV 102 may be trained to recognize the above-mentioned different portions of scan targets, and automatically provide a recommended scan distance and image resolution for particular recognized target portions.“
Regarding Claim 6, Henry discloses the following limitation dependent on Claim 3:
wherein the planning of the at least one second path based on the initial model and the preset condition includes: planning a plurality of the second paths based on the initial model and a plurality of the preset distances. See [0046-0049] for scan plan development.
Regarding Claim 7, Henry discloses the following limitation dependent on Claim 6:
wherein the plurality of the preset distances satisfy an equal proportion relationship. See [0049], “During development of the scan plan, for determining a next pose, the processor(s) of the UAV 102 may select a next center point from the subset of uncovered points, and may determine the next pose based on the selected next center point and a respective normal for the selected next center point. For example, determining the next center point may be performed as a function of the designated distance of the image sensor from the surface of the scan target 110, the amount of area the FOV of the image sensor will cover at the designated distance, the desired amount of overlap between consecutive images, and the distance between the next center point and one or more adjacent covered center points.”
Regarding Claim 8, Henry discloses the following limitations dependent on Claim 1:
wherein the initial model includes position information of surface points of the target object; and the planning of the at least one second path based on the initial model and the preset condition includes: planning the at least one second path based on the position information and the preset condition.
See [0032], “Based on the received indication of the scan target, the UAV may correlate the indication of the scan target with one or more positions in space, such as based on correlation with a global coordinate system, or through various other techniques. For instance, the UAV may autonomously perform an initial coarse scan of the scan target, e.g., by performing the initial scan with a range sensor or the like to determine a location of the scan target surface in 3D space … In case that the image sensors include a stereo imaging pair, the UAV may use input from the image sensors to determine a parallax between two related images of the same surface for determining a relative distance from the UAV to one or more points on the surface of the scan target. Alternatively, images from one or more monovision image sensors may be used, and/or various other distance sensing and 3D reconstruction techniques may be used, for determining the locations of surfaces of the scan target in 3D space, such as relative to a known location of the UAV.”
Regarding Claim 9, Henry discloses the following limitations dependent on Claim 8:
wherein the planning of the at least one second path based on the position information and the preset condition includes: planning the at least one second path based on the position information, a region of interest selected from the initial model, and the at least one preset distance, wherein position points on the at least one second path are distributed within the region of interest. See [0106], “Furthermore, the techniques in this example and in the example of FIG. 7 may also be used to specify no-fly zones that the UAV 102 is not permitted to enter. For example, in the case that the scan target is a bridge, the upper surface of the bridge may be specified as a no-fly zone to avoid possible contact of the UAV 102 with traffic on the bridge. For instance, the ceiling for the pillars discussed above, may establish a geofence that the UAV 102 is not permitted to cross. Similarly, one or more surfaces of the bounding volume of FIG. 7 may also be designated as a geofence. Accordingly, in addition to specifying to the UAV 102 a target to be scanned, the user interface 602 may also be used to specify regions of the scan target 110 or regions around the scan target 110 that the UAV 102 is not allowed to enter.”
Regarding Claims 10 and 17, Henry discloses the following limitation dependent on Claims 1 and 14:
wherein the first path and the at least one second path meet at least one of the following two conditions: the first path includes a plurality of position points, wherein the plurality of position points are distributed in different directions with respect to the target object, are in substantially a same distance from the target object, and are substantially located at a same altitude, and the first path is configured to guide the movable object to move around the target object on a horizontal plane; or the at least one second path includes a plurality of vertical paths, wherein the plurality of vertical paths are distributed in different directions with respect to the target object, and each vertical path is configured to guide the load to move upward or downward in a vertical direction. See [0121], “the lower-resolution 3D model 1300 may include a set of a plurality of points 1302 in 3D space corresponding to surfaces of the scan target 110. Further, the lower-resolution 3D model 1300 may include respective normals 1304 to some or all of the points 1302 in the set of points 1302. As one example, each normal 1304 may be a virtual line extending outward from the surface on which a respective point 1302 is located at an approximately normal (perpendicular) angle relative to the surface of the scan target 110 on which the respective point 1302 is located. For instance, the normal 1304 may extend outward from the respective surface point 1302 approximately perpendicular to a plane corresponding to the surface of the scan target 110 in an area surrounding the point 1302.” And [0122] As one example, the UAV 102 may be configured to determine the initial lower-resolution 3D model 1300 of the scan target 110 based on a several images captured at locations above or otherwise around the scan target 110 and that are spaced apart to facilitate multi-view stereo analysis … the respective positions for the plurality of images may be selected by adjusting spacing between two or more positions to achieve a parallax disparity between two or more images of the scan target 110 within a predetermined range. Also [0123], “The UAV 102 may determine the lower-resolution 3D model 1300 of the scan target 110 based on fusing range images into a TSDF or using other techniques for determining the location of the surface of the scan target in 3D space. In some implementations, the plurality of positions above or otherwise around the scan target 110, from which the plurality of images of the scan target 110 are captured, may be located along a straight line. In some implementations, the plurality of positions around the scan target 110, from which the plurality of images of the scan target are captured, are located on a circle around the scan target 110.”
Regarding Claim 11, Henry discloses the following limitation dependent on Claim 1:
wherein the determining, based on at least the second information, a target model of the target object includes: optimizing the initial model of the target object based on the second information to obtain the target model of the target object. See [0155] At 1512, the UAV 102 may update the 3D model based on the images captured during execution of the scan plan. For example, while the UAV 102 is using the image sensor 208 for capturing high-resolution images of the scan target surface, the UAV 102 may also employ the additional image sensors 212, 214, 216, 302, 304, and 306 for gathering additional range measurements of the distance from the known location of the UAV 102 to the surfaces of the scan target. The UAV 102 may employ 3D reconstruction techniques, such as fusing the additional range images from the image sensors 212, 214, 216, 302, 304, and 306 into the volumetric TSDF, to generate additional points respective normals for the 3D model. Accordingly, as the UAV 102 executes the scan plan, the 3D model may be transformed from the lower-resolution 3D model to a higher-resolution 3D model.” Also [0188-0191] regarding the 3D model generating and updating program 1702.
Regarding Claim 12, Henry discloses the following limitation dependent on Claim 11:
wherein the first information includes primary images; the second information includes supplementary images; and the optimizing of the initial model of the target object based on the second information includes: performing feature point matching on a plurality of the supplementary images, and optimizing the initial model of the target object based on a result of the feature point matching. See [0184], “the autonomy program 1608 may determine ranges from the UAV 102 to surfaces of the scan target. For example, the autonomy program 1608 may dynamically select stereo pairs of the image sensors 212, 214, 216, 302, 304, and 306 to use images obtained from the selected image sensors 212, 214, 216, 302, 304, and 306 to predict the range (distance) from the UAV 102 to one or more points on the surface of the scan target for determining the location of those points in 3D space relative to a known location of the UAV 102. In some cases, the autonomy program 1608 may employ an optical flow technique for determining the ranges of points of the surface of the scan target with respect to the location of the UAV 102, which may include feature matching in some examples. For instance, accurate localization of the UAV 102 for avoiding drift may help to achieve an accurate 3D model that is consistent regarding the determined locations of the identified points of the surface of the 3D model in 3D space.” Also [0188-0191] regarding the 3D model generating and updating program 1702.
Regarding Claim 13, Henry discloses the following limitation dependent on Claim 12:
wherein the performing of the feature point matching on the plurality of the supplementary images includes performing feature point matching among the plurality of the supplementary images based on the initial model. See [0188], “the 3D model generating and updating program 1702 may adjust a location estimate of where the matching pixels or corresponding features in the two images are relative to each other and relative to the 3D model to improve the depth estimation of the features in the images for inclusion in the 3D model and for making the 3D model more globally consistent … the locations of points in the 3D model corresponding to features in the plurality of images may be adjusted relative to each other based on the differences between the plurality of images to improve the global consistency of the 3D model. Accordingly, the 3D model generating and updating program 1702 may compute drift-free poses and a consistent global map that combines the TSDF and comparison and optimization results for refining the locations of points of the 3D model to adjust for possible drift or other inconsistencies. And [0190], “During the flight, the 3D model generating and updating program 1702 may construct the TSDF 3D model of the scan target. The TSDF extent and resolution may be fixed at the start of execution of the 3D model generating and updating program 1702, and as the UAV 102 performs additional scanning of the scan target, the TSDF may be updated using range data received from the autonomy program 1608, such as by using the best optimized pose at the time.” Also [0191], “The 3D model generating and updating program 1702 may perform additional iterations to refine the poses used by the UAV according to the scan plan based on the real-time 3D reconstruction and pose adjustment analysis discussed above. For example, the 3D model generating and updating program 1702 may determine pose refinements for performing additional TSDF fusion based on newly captured images processed by the autonomy program 1608.”
Regarding Claim 15, Henry discloses the following limitation dependent on Claim 14:
wherein the load includes a camera; the load collecting the information of the target object includes: the camera shooting a plurality of images of the target object; and that the first information collected by the load on the first path and second information collected by the load on the second path share information of the at least one point of the target object includes: a first image captured by the camera on the movable object along the first path and a second image captured by the camera on the movable object along the second path share homologous image points of the target object. See [0184], “the autonomy program 1608 may employ an optical flow technique for determining the ranges of points of the surface of the scan target with respect to the location of the UAV 102, which may include feature matching in some examples. For instance, accurate localization of the UAV 102 for avoiding drift may help to achieve an accurate 3D model that is consistent regarding the determined locations of the identified points of the surface of the 3D model in 3D space.“ Also [0188] The 3D model generating and updating program 1702 may further be executed to determine a difference or similarity between matching features captured in a pair of stereo images for determining where matching pixels in the first image should be relative to the second image. Based on this determination, the 3D model generating and updating program 1702 may adjust a location estimate of where the matching pixels or corresponding features in the two images are relative to each other and relative to the 3D model to improve the depth estimation of the features in the images for inclusion in the 3D model and for making the 3D model more globally consistent.”
Regarding Claim 16, Henry discloses the following limitation dependent on Claim 14:
wherein the movable object maintains a first distance from the target object while moving along the first path, the movable object maintains a second distance from the target object while moving along the second path, and the first distance is greater than the second distance. See [0152], “At 1506, in response to receiving the indication of the scan target, the UAV 102 may generate a lower-resolution model based on an initial rough scan of the specified scan target. For example, depending on the type of indication received, the UAV may navigate proximate to the scan target to capture one or more range images using the onboard image sensors. For instance, the UAV may fuse range images from stereo pair navigation image sensors and/or wide baseline MultiView Stereo (MVS) image sensor pairs into a volumetric TSDF, which is used to generate a surface mesh estimate including a plurality of points and respective normals for each of the points. The initial TSDF-generated 3D model may typically be a lower-resolution 3D model and may have lower accuracy because the scan target has not yet been imaged or otherwise scanned from sufficiently diverse points of view or at a sufficiently close distance for generating a higher accuracy and thereby higher-resolution 3D model. For example, the more images that the UAV 102 captures of the target surface, and the closer the UAV 102 flies to a surface, the more accurate the estimate of the surface location and shape becomes in the TSDF as the UAV 102 continues to fuse stereo pair range images into the 3D model.”
Regarding Claim 18, Henry discloses the following limitation dependent on Claim 14:
wherein position information of surface points of the target object is determined based on an initial model of the target object, and the initial model is determined in advance based on information collected along the first path. See [0050], “the processor(s) may generate the scan plan to cover all points based on balancing various considerations such as obtaining full coverage of all accessible surfaces of the scan target 110, having a regular and predictable pattern for the poses, and enabling efficient navigation of the UAV 102 during execution of the scan plan. In some cases, the processor may determine the entirety of the scan plan in advance before beginning scanning of the scan target 110 according to the scan plan. “ + [0028]which discloses that the initial rough model is created through a first scan (information collected along a first path)
Regarding Claim 20, Henry discloses the following limitations dependent on Claim 14:
wherein the target model includes a three-dimensional model. See [0027] Some implementations herein are directed to techniques and arrangements for configuring a UAV to scan three-dimensional (3D) scan targets, such as structures, buildings, bridges, pipelines, equipment, objects, sites, geographic features, crime scenes, accident scenes, or any other scan target that may be designated by an operator.”
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The 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 19 is rejected under 35 U.S.C. 103 as being unpatentable over Henry in view of Chosid et al., WO 2020051208 A1 (Hereinafter, “Chosid”).
Regarding Claim 19, Henry discloses a system for obtaining a model of a target object, but does not explicitly disclose third path information. However, Chosid teaches the following limitation dependent on Claim 14: planning a third path based a region of interest on a surface of the target object; and controlling the movable object to move along the third path to allow the load, while moving, to collect third information of the target object. See [0078], “FIG. 6 is a flow chart illustrating a high-level overview of an embodiment of how data is acquired on various flight paths. In some embodiments, the path of the camera along the calculated paths is not limited to the use of a UAV. The camera may travel the path routes, either manually or robotically along a guided rail or track or be moved via a flexible robotic arm when modeling smaller objects for example. [0079], “Once the flight path 280 is set, the UAV follows a predetermined route. The UAV can fly the route autonomously, through the use of software, or a UAV operator can manually fly the UAV along the predetermined routes around the object or building through the use of a remote control. And [0080], “The following routes for the inner and outer orbit passes, high and low nadir passes, and texture passes can be conducted in any order. In some embodiments, the inner orbital pass is first, the outer orbital pass is second, the low nadir pass is third, the high nadir pass is fourth, the texture pass is fifth, and the texture nadir pass is sixth. In some embodiments, the texture nadir pass is not required, as per project parameters. On orbital passes the camera faces inward (toward the center of the orbit path) toward the object or building, and in some embodiments be angled downward at 45 degrees to keep the target object in view, or at any angle appropriate to keep the target in view. On nadir passes (including texture nadir passes) above the object or building, the camera faces straight down toward the object or building without any angle or tilt. On texture passes, the camera faces inward and straight toward the object or building without any tilt or angle. In some embodiments, the number and type of passes conducted are based on the selected aF parameter, as described above. In some embodiments, data is associated with each picture taken during any of the passes. The data can include but is not limited to the longitude, latitude, and altitude corresponding to each picture. The data can be obtained from the sensors on the UAV (such as GPS, altimeter, and/or barometer), corresponding to the time stamp of the picture.”
As both are in the same field of endeavor, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine Henry’s device with the third path information limitations disclosed in Chosid with reasonable expectation of success. The motivation for doing so would have been to allow a user to input the desired resolution for the final 3D model and obtain the required distances and flight paths necessary to achieve this resolution from the disclosed method and system., see Chosid [0008].
Additional Relevant Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and may be found on the accompanying PTO-892 Notice of References Cited:
US Publication US 20170366751 A1 by Terry et al.
US Publication US 20180046187 A1 by Martiroysian et al.
US Publication US 20180182163 A1 by Tung et al.
US Publication US 20200066169 A1 by Li et al.
WIPO Publication WO 2017020856 A1 by Huang et al.
Chinese Publication CN 110703805 A by Peng et al.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRIAN KEITH PALMARCHUK whose telephone number is (571)272-6261. The examiner can normally be reached M-F 7 AM - 5 PM EST.
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, NAVID MEHDIZADEH can be reached at 571-272-7691. 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.
/B.K.P./Examiner, Art Unit 3669
/KENNETH M DUNNE/Primary Examiner, Art Unit 3669
