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 Interpretation The following is a quotation of 35 U.S.C. 112(f): (f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph: An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked. As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph: (A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non- structural term having no specific structural meaning) for performing the claimed function; (B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and (C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function. Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function. Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function. Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: a calibration unit in claim 1. Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. See Applicant’s specification Par. 20, 49, and 51, “ The controller 50 may be one or more processing devices such as one or more microprocessors, and the techniques of the present invention may be implemented in hardware software, or application-specific integrated circuitry ”. If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. 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 appl icant regards as his invention. Claim s 1-8 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claims 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. Claim 1 recites , however it is not clear what I th represents as the claims do not recite what the variable represents nor does the specification. For the purposes of examining it is considered to be the next iteration. Claims 2-8 are rejected based on their inherited issues. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Under step 1, claim 1 belongs to a statutory category of an apparatus. Under Step 2A prong 1, the claims as a whole are identified as being directed to a judicial exception as c laim 1 recite(s) “ generating an offset mesh; setting an iteration index t of an iteration loop, wherein t is an integer; generating a point cloud matrix of a tth iteration; generating measurement errors of the tth iteration, wherein the measurement errors of the tth iteration comprise a set of range and incident angle information that is computed according to the point cloud matrix of the tth iteration; generating an offset profile of the tth iteration in form of a function of a range and an incident angle according to the measurement errors of the tth iteration; refining the point cloud matrix of the tth iteration by using the offset profile of the tth iteration with substituting the measurement errors of the tth iteration, such that a point cloud matrix of a t+lth iteration is obtained; updating the offset mesh by introducing the offset profile of the tth iteration thereto; and determining whether to output the point cloud matrix of the t+lth iteration and the updated offset mesh ” which are directed to mathematical concepts and/or mental processes per applicants specification see pages 11-14 as examples . Under Step 2A prong 2, e valuat ing whether the claim as a whole integrates the exception into a practical application of that exception , t h e judicial exception is not integrated into a practical application because “ a light detection and ranging (LiDAR) apparatus, comprising: a laser source configured to generate a laser light; a scanner configured to scan the laser light beam along a three- dimensional (3D) target surface; a photodetector configured to detect a point cloud of reflected light from the target surface; ” are considered to be data gathering steps required to use the correlation do not add a meaningful limitation to the method as they are insignificant extra-solution activity. The elements of “ a controller including a calibration unit that is configured to execute at least the following: ” are considered to be generically recited computer elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. Under Step 2 B , evaluating additional elements to determine whether they amount to an inventive concept both individually and in combination, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because a light detection and ranging (LiDAR) apparatus, comprising: a laser source configured to generate a laser light; a scanner configured to scan the laser light beam a long a three-dimensional (3D) target surface; a photodetector configured to detect a point cloud of reflected light from the target surface; ” are considered to be adding insignificant extra-solution activity to the judicial exception per MPEP 2106.05(g) and are well-understood, routine, conventional activities/elements previously known to the industry per MPEP 2106.05(d)( see prior art of record ). The elements of “ a controller including a calibration unit that is configured to execute at least the following: ” are considered to be well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d) . Claims 2-7 are also directed to the abstract ideas cited above. In claim 8, “ wherein the scanner is selected from a mirror, a polygonal mirror, or a MEMS device ” t h e judicial exception is not integrated into a practical application and do not include additional elements that are sufficient to amount to significantly more than the judicial exception because are considered to be generally linking the use of a judicial exception to a particular technological environment or field of use and are considered to be merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself per MPEP 2106.05(h) and are well-understood, routine, and conventional activities/elements previously known to the industry per MPEP 2106.05(d) (see prior art of record). 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) 1-8 are rejected under 35 U.S.C. 103 as being unpatentable over Nolan Lunscher Deep Learning 3D Scans for Footwear Fit Estimation January 2018 hence forth NPL1 in view of Robust Extrinsic Parameter Calibration of 3d LIDAR using Lie Algebres June 2019 , Hence forth NPL 2 . In claim 1, NPL1 discloses a light detection and ranging (LiDAR) apparatus (Section 2.4.3 “LIDAR”) , comprising: a laser source configured to generate a laser light (Section 2. 4.2 to 2 . 4.3 “ la s er sources”) ; a scanner configured to scan the laser light beam along a three- dimensional (3D) target surface (Section 2. 4.2 “ 3D Scanner ” Fig. 2.6) ; a photodetector configured to detect a point cloud of reflected light from the target surface (Section 2.4.3 “ pr o jecting light int o , a scene or onto an object, and m easuring how long that light takes to reflect and return to a sensor”) ; generating an offset mesh (Section 3.1 Page 24 “Mesh body”) ; setting an iteration index t of an iteration loop, wherein t is an integer (Section 4.4 Page 47, see Fig. 3.4) ; generating a point cloud matrix of a tth iteration (Section 4.4 Page 47, see Fig. 3.7) ; generating measurement errors of the tth iteration, wherein the measurement errors of the tth iteration comprise a set of range and incident angle information that is computed according to the point cloud matrix of the tth iteration (Table 4.1, Section 3.3 “ elevation angle”) ; generating an offset profile of the tth iteration in form of a function of a range and an incident angle according to the measurement errors of the tth iteration (See Fig. 3.3, 4.5 and 4.7, page 44-45) ; refining the point cloud matrix of the tth iteration by using the offset profile of the tth iteration with substituting the measurement errors of the tth iteration, such that a point cloud matrix of a t+lth iteration is obtained (Section 4.5.1, Fig. 4.8 and 4.9 also see Fig. 3.7 and pages 30-32 “train a convolution neural network encoder and decoder”) ; updating the offset mesh by introducing the offset profile of the tth iteration thereto (page 49 “fine tuning on real data, Fig. 4.11”). NPL 1 does not explicitly disclose a controller including a calibration unit that is configured to execute and determining whether to output the point cloud matrix of the t+lth iteration and the updated offset mesh. NPL2 teaches a controller including a calibration unit that is configured to execute ( See Fig. 3, examiner notes that the VELODYNE VLP-32C has a Linux-based processing core ) and determining whether to output the point cloud matrix of the t+lth iteration and the updated offset mesh (Fig. 1, “optimal matrix X? yes/no”) . Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filled to have a controller including a calibration unit that is configured to execute and determining whether to output the point cloud matrix of the t+lth iteration and the updated offset mesh as taught by NPL2 in NPL1 in order to optimize the LIDAR matrix (NPL2 see Fig. 1) thus leading to an improved system. In claim 2, NPL1 does not explicitly disclose wherein the calibration unit is further configured to execute the following: setting a convergence criterion; and comparing the offset meshes before and after the updating; wherein when a comparing result is in the convergence criterion, the point cloud matrix of the t+ltn iteration and the updated offset mesh are outputted. NPL2 teaches wherein the calibration unit is further configured to execute the following: setting a convergence criterion (See Fig. 4 Section IV A) ; and comparing the offset meshes before and after the updating ( Section IV A ) ; wherein when a comparing result is in the convergence criterion, the point cloud matrix of the t+ltn iteration and the updated offset mesh are outputted (See Eqn . 7) . Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filled to have wherein the calibration unit is further configured to execute the following: setting a convergence criterion; and comparing the offset meshes before and after the updating; wherein when a comparing result is in the convergence criterion, the point cloud matrix of the t+ltn iteration and the updated offset mesh are outputted as taught by NPL2 in NPL1 in order to optimize the LIDAR matrix (NPL2 see Fig. 1) thus leading to an improved system. In claim 2, NPL1 discloses generating measurement errors of the t+Itn iteration, wherein the measurement errors of the t+] th iteration comprise a set of range and incident angle information that is computed according to the point cloud matrix of the t+lth iteration Table 4.1, Section 3.3 “elevation angle”) ; generating an offset profile of the t+h iteration in form of a function of a range and an incident angle according to the measurement errors of the t+h iteration (Table 4.1, Section 3.3 “elevation angle) ; refining the point cloud matrix of the t+Ath iteration by using the offset profile of the t+] th iteration with substituting the measurement errors of the t+h iteration, such that a point cloud matrix of a t+2th iteration is obtained (Section 4.5.1, Fig. 4.8 and 4.9 also see Fig. 3.7 and pages 30-32 “train a convolution neural network encoder and decoder”) ; updating the offset mesh by introducing the offset profile of the t+h iteration thereto (page 49 “fine tuning on real data, Fig. 4.11”). NPL1 does not explicitly disclose wherein the calibration unit is further configured to execute the following: setting a convergence criterion; and comparing the offset meshes before and after the updating; wherein when a comparing result is out the convergence criterion, the calibration unit is further configured to execute the following: and determining whether to output the point cloud matrix of the t+2thiteration and the updated offset mesh according to the convergence criterion. NPL2 teaches wherein the calibration unit is further configured to execute the following: setting a convergence criterion (See Fig. 4 Section IV A) ; and comparing the offset meshes before and after the updating; wherein when a comparing result is out the convergence criterion (See Fig. 4 Section IV A) , the calibration unit is further configured to execute the following: and determining whether to output the point cloud matrix of the t+2thiteration and the updated offset mesh according to the convergence criterion (Fig. 1, “optimal matrix X? yes/no”) . Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filled to have wherein the calibration unit is further configured to execute the following: setting a convergence criterion (See Fig. 4 Section IV A) ; and comparing the offset meshes before and after the updating; wherein when a comparing result is out the convergence criterion (See Fig. 4 Section IV A) , the calibration unit is further configured to execute the following: and determining whether to output the point cloud matrix of the t+2thiteration and the updated offset mesh according to the convergence criterion as taught by NPL2 in NPL1 in order to optimize the LIDAR matrix (NPL2 see Fig. 1) thus leading to an improved system. In claim 4, NPL1 discloses wherein the refining is executed by computing the difference between the range values of the point cloud matrix of the tth iteration and the offset profile of the tth iteration with substituting the measurement errors of the tth iteration , such that the point cloud matrix of the tt h iteration have the range values different from those of the point cloud matrix of the t+lth iteration (See Fig. 3.3, 4.5 and 4.7, page 44-45) . In claim 5, NPL1 discloses herein the point cloud of the tth iteration and the point cloud of the t+lth iteration have the same altitude values and the same azimuth values (See Fig. 3.3, 4.5 and 4.7, page 44-45) . In claim 6, NPL1 discloses wherein the iteration loop is executed such that the offset mesh is updated more than once (Section 4.5.1, Fig. 4.8 and 4.9 also see Fig. 3.7 and pages 30-32 “train a convolution neural network encoder and decoder”) . In claim 7, NPL1 discloses herein the point cloud matrix of a first iteration is generated according to the point cloud detected by the photodetector (Section 2.4.3 “ pr o jecting light int o , a scene or onto an object, and m easuring how long that light takes to reflect and return to a sensor”) . In claim 8, NPL1 discloses wherein the scanner is selected from a mirror, a polygonal mirror, or a MEMS device (Section 2.4.3) . Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 20190370614 A1 Method And System For Classification Of An Object In A Point Cloud Data Set ; US 20150084884 A1 EXTENDING THE FREE FINGERS TYPING TECHNOLOGY AND INTRODUCING THE FINGER TAPS LANGUAGE TECHNOLOGY Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Examiner name" \* MERGEFORMAT BRANDON J BECKER whose telephone number is FILLIN "Phone number" \* MERGEFORMAT (571)431-0689 . 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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.J.B/ Examiner, Art Unit 2857 /SHELBY A TURNER/ Supervisory Patent Examiner, Art Unit 2857