CTNF 18/194,338 CTNF 82700 DETAILED ACTION Response to Arguments 07-42-04 AIA 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 2/23/2026 has been entered. 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. The application has pending claim(s) 1-25. Applicant's arguments with respect to claim(s) 1-25 have been considered but are moot in view of the new ground(s) of rejection because of the Request for Continued Examination (RCE). Applicant’s arguments, see 1-4 of the remarks section, filed 2/23/2026, with respect to the rejection(s) of claim(s) 1-25 under 35 U.S.C. 102 and 103 have been fully considered and are persuasive. Therefore, the rejections have been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in further view of the newly found prior art reference Tran et al (US 2021/0065391 A1). Further discussions are addressed in the prior art rejection section below. Therefore claims 1- 25 are still not in condition for allowance because they are still not patentably distinguishable over the prior art reference(s). Claim Objections 07-29-01 AIA Claim s 2-9 are objected to because of the following informalities: Each of claims 2-9: “The storage medium” should be -- The at least one non-transitory machine-readable storage medium -- to be consistent with claim 1’s language . Appropriate correction is required. Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-21-aia AIA Claim (s) 1, 9-10, 18-21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Endres et al (“An evaluation of the RGB-D SLAM system,” 2012 IEEE International Conference on Robotics and Automation , Saint Paul, MN, USA, 2012, pp. 1691-1696, as applied in previous Office Action - hereinafter referred to as Endres) in view of Tran et al (US 2021/0065391 A1 – hereinafter referred to as Tran) . Regarding claim 1, Endres teaches at least one non-transitory machine - readable storage medium having instructions stored thereon, wherein the instructions, when executed on processing circuitry, cause the processing circuitry to ( Endres, storage embodied in computer and GPU, pgs. 6-7 ): receive, via interface circuitry, a plurality of frames of image data ( Endres, Figs. 1, 2, receive plurality of frames of image data, pgs. 1-2 ), wherein the frames are captured by one or more sensors from a plurality of poses within an environment, and wherein the frames include a current frame and one or more preceding frames ( Endres, Figs. 1, 2, frames are captured by a camera from a plurality of poses within an environment (see Fig. 1(a)), where the frames include a current frame and one or more preceding frames (“previous images”), pgs. 1-2 ); detect one or more keypoints in the current frame ( Endres, Fig. 2, detect features/keypoints of the current frame, pgs. 1-2 ); find one or more matching keypoints in the one or more preceding frames, wherein the one or more matching keypoints match the one or more keypoints in the current frame ( Endres, Fig. 2, “match these [current] features against features from previous images,” pgs. 1-2 ); and determine, based at least in part on depth models, a pose of the current frame within the environment ( Endres, Figs. 1, 2, determine, based in part on the depth models/information, a pose of the current frame within the environment, pgs. 1-3) . However Endres fails to explicitly teach where Tran teaches find one or more matching keypoints in the one or more preceding frames, wherein the one or more matching keypoints match the one or more keypoints in the current frame, and wherein the one or more matching keypoints are associated with one or more parameterized depth models, wherein the one or more parameterized depth models model depths of one or more regions of the environment, wherein individual regions comprise a plurality of contiguous three-dimensional (3D) points ( Tran, abstract, [0026]-[0027], [0046]- [0051], tracking keypoints between current and adjacent frames, depth estimation with depth network parameters are fine-tuned and back projected, and then fed to pose estimation ); and determine, based at least in part on parameters of the one or more parameterized depth models, a pose of the current frame within the environment ( Tran, abstract, [0026]-[0027], [0046]-[0051], the depth map(s) with their associated depth network parameters are fed to a pose estimation, wherein the pose estimation outputs a pose estimate and constructed 3D maps of the surrounding environment ). It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Endres using the teachings of Tran to include Tran’s parameterized depth models processing to Endres’ matched keypoints in regions of the environment modelled by depth models/information processing. Doing so would improve localization across consecutive frames, which would be used to efficiently determine the camera’s pose. Regarding claim 9, Endres teaches the storage medium of Claim 1, wherein the image data comprises color data and depth data ( Endres, Fig. 2, image data comprises color data (RGB) and depth data, pgs. 1-2 ). Regarding claims 10, 18, 21, the rationale provided in the rejection of claims 1, 9 is incorporated herein. In addition, the device of claims 10, 18 ( Endres, interface circuity and processing circuitry embodied in computer and GPU, pgs. 6-7 ) and the method of claim 21 corresponds to the storage medium of claims 1, 9, and performs the steps disclosed herein. Regarding claim 19, Endres teaches the device of Claim 18, wherein the one or more sensors comprise: a camera to capture the color data; and a depth sensor to capture the depth data ( Endres, Microsoft Kinect camera is RBG-D, which includes a camera to capture the color data and a depth sensor to capture the depth data, pgs. 1-2 ). Regarding claim 20, Endres teaches the device of Claim 10, wherein the device is implemented in a robot, a drone, or a vehicle ( Endres, device is implemented in a robot for robot localization, pgs. 1-3, 8 ) . 07-21-aia AIA Claim (s) 2, 4, 11, 13, 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Endres in view of Tran as applied to claims 1, 10, 21 above, in further view of Kajal Sharma. 2018. Improved visual SLAM: a novel approach to mapping and localization using visual landmarks in consecutive frames. Multimedia Tools Appl. 77, 7 (April 2018), 7955–7976. https://doi.org/10.1007/s11042-017-4694-x., hereinafter referred to as Sharma . Regarding claim 2, the combination of Endres and Tran teaches the storage medium of Claim 1. However, the combination of Endres and Tran fails to teach where Sharma teaches wherein: the one or more matching keypoints correspond to one or more landmarks in the environment ( Sharma, Fig. 3, keypoints, matched between frames, correspond to “landmarks,” also matched, in the environment, with the landmarks being “obtained using feature [keypoint] matching,” pgs. 3, 7 ); the one or more landmarks are in one or more regions of the environment ( Sharma, Figs. 3, 5, the landmarks are in regions of the environment, pg. 11 ); and the one or more regions are modeled by the one or more parameterized depth models ( Sharma, Figs. 3, 5, the regions are modelled to be a 3D map using depth information/map/model, pgs. 9-11 ). It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Endres [as modified by Tran] using the teachings of Sharma to include Sharma’s landmarks, in regions of the environment and modelled by depth models/information, corresponding to matched keypoints, to Endres’ [as modified by Tran] matched keypoints in regions of the environment modelled by depth models/information. Doing so would improve localization across frames by providing landmarks in consecutive frames, which would be used to efficiently determine the camera’s pose. Regarding claim 4, the combination of Endres, Tran and Sharma teaches the storage medium of Claim 2, wherein the instructions that cause the processing circuitry to find the one or more matching keypoints in the one or more preceding frames further cause the processing circuitry to: identify the one or more landmarks corresponding to the one or more matching keypoints ( Sharma, Figs. 3, 5, identify landmarks that correspond to the matching keypoints/features, pgs. 3, 7, 11 ); and associate the one or more keypoints in the current frame with the one or more landmarks ( Sharma, Figs. 3, 5, keypoints/features that correspond to the landmark are associated with the landmark and its location for each frame, including the current frame, pgs. 7-11 ). Regarding claims 11, 13, 22, the rationale provided in the rejection of claims 2, 4 is incorporated herein. In addition, the device of claims 11, 13 ( Endres, interface circuity and processing circuitry embodied in computer and GPU, pgs. 6-7 ) and the method of claim 22 corresponds to the storage medium of claims 2, 4, and performs the steps disclosed herein . 07-21-aia AIA Claim (s) 3, 12, 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Endres in view of Tran and Sharma as applied to claims 2, 11, 22 above, further in view of Jan Wietrzykowski, Piotr Skrzypczyński, PlaneLoc: Probabilistic global localization in 3-D using local planar features, Robotics and Autonomous Systems, Volume 113, 2019, Pages 160-173, ISSN 0921-8890, https://doi.org/10.1016/j.robot.2019.01.008., hereinafter referred to as Wietrzykowski . Regarding claim 3, the combination of Endres and Sharma teaches the storage medium of Claim 2. However, the combination of Endres, Tran and Sharma fails to teach where Wietrzykowski teaches wherein the instructions further cause the processing circuitry to: detect one or more surfaces in the one or more preceding frames ( Wietrzykowski, Fig. 2, detect one or more planar segments [planar segments are a type of surface] in a preceding frame (the preceding, different viewpoint), pg. 9 ); identify the one or more regions of the environment corresponding to the one or more surfaces ( Wietrzykowski, Fig. 2, identify that the surface is in a particular region of the environment (e.g. in the proper regions in Fig. 2(b) top and middle examples), pg. 9 ); and generate the one or more parameterized depth models of the one or more regions ( Wietrzykowski, Figs. 5, 9, Eqn. 1, the regions containing the surfaces/planar segments are modelled using depth information (Eqn. 1) and depth images (Fig. 5) to produce a 3D global map, pgs. 11-13, 28 ). It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Endres [as modified by Tran and Sharma] using the teachings of Wietrzykowski to include Wietrzykowski’s detection of planar surfaces/segments across frames in a region of the environment for depth modelling to Endres’ [as modified by Tran and Sharma] detection of keypoints across frames in a region of the environment for depth modelling. Doing so would improve localization across frames by providing surfaces/segments in consecutive frames, which would be used to efficiently determine the camera’s pose. Regarding claims 12, 23, the rationale provided in the rejection of claim 3 is incorporated herein. In addition, the device of claim 12 ( Endres, interface circuity and processing circuitry embodied in computer and GPU, pgs. 6-7 ) and the method of claim 23 corresponds to the storage medium of claim 3 and performs the steps disclosed herein . 07-21-aia AIA Claim (s) 5, 14, 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Endres in view of Tran and Sharma as applied to claims 2, 11, 22 above, further in view of D. Li et al., "A SLAM System Based on RGBD Image and Point-Line Feature," in IEEE Access , vol. 9, pp. 9012-9025, 2021, doi: 10.1109/ACCESS.2021.3049467., hereinafter referred to as Li . Regarding claim 5, the combination of Endres, Tran and Sharma teaches the storage medium of Claim 2. However, the combination of Endres, Tran and Sharma fails to teach where Li teaches wherein the instructions that cause the processing circuitry to determine, based at least in part on the one or more parameterized depth models, the pose of the current frame within the environment further cause the processing circuitry to: compute the pose of the current frame based at least in part on: a pose of a keyframe, wherein the keyframe is one of the preceding frames ( Li, pose of current frame is based on pose of preceding keyframe; “use the map points and lines of the adjacent reference keyframe to track the current frame pose to check if there are enough correspondences to support that pose is correct,” the adjacent frame being a “previous frame,” pg. 7 ); the one or more landmarks ( Li, Fig. 1, “landmarks (points, lines)” (pg. 10) are used to determine pose of current frame, pgs. 4-7, 10-11 ); and the one or more parameterized depth models ( Li, depth information/modelling is used to determine pose of current frame, pgs. 4-5 ). It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Endres [as modified by Tran and Sharma] using the teachings of Li to include Li’s computing of the pose of the current frame using keyframe, landmark, and depth information to Endres’ [as modified by Tran and Sharma] computing of the pose of the current frame using landmark and depth information. Doing so would improve pose computation by providing keyframe information, which would be used to efficiently determine the camera’s pose. Regarding claims 14, 24, the rationale provided in the rejection of claim 5 is incorporated herein. In addition, the device of claim 14 ( Endres, interface circuity and processing circuitry embodied in computer and GPU, pgs. 6-7 ) and the method of claim 24 corresponds to the storage medium of claim 5 and performs the steps disclosed herein . 07-21-aia AIA Claim (s) 6, 15, 25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Endres in view of Tran and Sharma as applied to claims 2, 11, 22 above, further in view of Rafael Munoz-Salinas, Manuel J. Marín-Jimenez, R. Medina-Carnicer, SPM-SLAM: Simultaneous localization and mapping with squared planar markers, Pattern Recognition, Volume 86, 2019, Pages 156-171, ISSN 0031-3203, https://doi.org/10.1016/j.patcog.2018.09.003., hereinafter referred to as Munoz-Salinas . Regarding claim 6, the combination of Endres, Tran and Sharma teaches the storage medium of Claim 2. However, the combination of Endres, Tran and Sharma fails to teach where Munoz-Salinas teaches wherein the instructions that cause the processing circuitry to determine, based at least in part on the one or more parameterized depth models, the pose of the current frame within the environment further cause the processing circuitry to: adjust at least some of the following values to minimize a projection error: poses of keyframes, wherein the keyframes include the current frame and at least one of the preceding frames ( Munoz-Salinas, “adjust both the keyframe and marker poses by minimizing the reprojection error…only those keyframes of the map that observe the markers in the current frame will be affected by this process,” meaning the preceding and current keyframe poses are adjusted to minimize re/projection error, pg. 4 ); the parameters of the one or more parameterized depth models; and coordinates of the one or more landmarks. It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Endres [as modified by Tran and Sharma] using the teachings of Munoz-Salinas to include Munoz-Salinas’ minimization of projection error by adjusting keyframe poses for localization to Endres’ [as modified by Tran and Sharma] keyframe poses for localization. Doing so would improve localization by providing a way to minimize projection error, which would be used to efficiently and accurately determine the camera’s pose with minimum error. Regarding claims 15, 25, the rationale provided in the rejection of claim 6 is incorporated herein. In addition, the device of claim 15 ( Endres, interface circuity and processing circuitry embodied in computer and GPU, pgs. 6-7 ) and the method of claim 25 corresponds to the storage medium of claim 6 and performs the steps disclosed herein . 07-21-aia AIA Claim (s) 7-8, 16-17 , is/are rejected under 35 U.S.C. 103 as being unpatentable over Endres in view of Tran as applied to claims 1, 10 above, in further view of Aswin (US 20190122378 A1) . Regarding claim 7, the combination of Endres and Tran teaches the storage medium of Claim 1. However, the combination of Endres and Tran fails to teach where Aswin teaches wherein the one or more parameterized depth models comprise one or more polynomials, wherein the one or more polynomials model a depth of one or more regions of the environment ( Aswin, depth models for matched points for, among other purposes, determining pose of camera [0019], comprises a system of polynomials, [0062-0065; 0047, 0056] ). It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Endres [as modified by Tran] using the teachings of Aswin to include Aswin’s polynomial system for depth modelling of matched points to Endres’ [as modified by Tran] depth modelling/information of matched points. Doing so would improve pose computation by providing polynomial computation, which would be used to efficiently determine the camera’s pose. Regarding claim 8, the combination of Endres, Tran and Aswin teaches the storage medium of Claim 7, wherein the one or more polynomials comprise at least one of a zero-order polynomial, a first-order polynomial, or a second-order polynomial ( Aswin, system of polynomials comprises second-order polynomials, [0045-0047, 0056, 0065] ). Regarding claims 16-17, the rationale provided in the rejection of claims 7-8 is incorporated herein. In addition, the device of claims 16-17 ( Endres, interface circuity and processing circuitry embodied in computer and GPU, pgs. 6-7 ) corresponds to the storage medium of claims 7-8 and performs the steps disclosed herein . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Liu ‘964 discloses generate model parameter sequence input to the training, obtaining the output result of the depth generating model output, the output result can be the posture parameter of adjusting head of the virtual robot . Any inquiry concerning this communication or earlier communications from the examiner should be directed to BERNARD KRASNIC whose telephone number is (571)270-1357. The examiner can normally be reached on Mon. - Thur. and every other Friday from 8am - 4pm. 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, Vincent Rudolph can be reached on (571)272-8243. 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. /Bernard Krasnic/Primary Examiner, Art Unit 2671 May 21, 2026 Application/Control Number: 18/194,338 Page 2 Art Unit: 2671 Application/Control Number: 18/194,338 Page 3 Art Unit: 2671 Application/Control Number: 18/194,338 Page 4 Art Unit: 2671 Application/Control Number: 18/194,338 Page 5 Art Unit: 2671 Application/Control Number: 18/194,338 Page 6 Art Unit: 2671 Application/Control Number: 18/194,338 Page 7 Art Unit: 2671 Application/Control Number: 18/194,338 Page 8 Art Unit: 2671 Application/Control Number: 18/194,338 Page 9 Art Unit: 2671 Application/Control Number: 18/194,338 Page 10 Art Unit: 2671 Application/Control Number: 18/194,338 Page 11 Art Unit: 2671 Application/Control Number: 18/194,338 Page 12 Art Unit: 2671 Application/Control Number: 18/194,338 Page 13 Art Unit: 2671 Application/Control Number: 18/194,338 Page 14 Art Unit: 2671 Application/Control Number: 18/194,338 Page 15 Art Unit: 2671
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