DETAILED ACTION
Claims 1-2, 5-8, 11-12, 15-18, and 20-21 are presented for examination. This Final Office Action is made in response to the communication filed on November 6, 2025.
Claims 1, 5, 7, 11, 15, 17, and 21 are objected to.
Claims 1-2, 5-8, 11-12, 15-18, and 20-21 are rejected under 35 USC 112(a).
Claims 1-2, 5-8, 11-12, 15-18, and 20-21 are rejected under 35 USC 112(b).
Claims 1-2, 5-8, 11-12, 15-18, and 20-21 are rejected under 35 USC 101.
Claims 1-2, 5-6, 11-12, 15-16, and 20-21 are rejected under 35 USC 102(a)(1) as anticipated by Dine.
Claims 7-8 and 17-18 are technically incorrect, as described in the 35 USC 112(a) rejection, so claims 7-8 and 8-18 cannot be effectively searched for art rejections without significant speculation.
Response To Arguments
35 USC 112(a): The Applicant’s arguments and amendments have been considered and are persuasive. The rejection has been withdrawn. New 35 USC 112(a) rejections are presented herein.
35 USC 112(b): The Applicant’s arguments and amendments have been considered and are persuasive. The rejection has been withdrawn. New 35 USC 112(b) rejections are presented herein.
35 USC 101: The Applicant’s arguments and amendments have been considered but are not persuasive. The arguments will be addressed in the order they were presented.
The Claims Allegedly Do Not Recite A Mental Process: The Applicant argues that the determination of Schur matrices for SLAM can only be done by a SLAM accelerator. However, this is not the case. While it would not be ideal, a person can practically perform these operations with pen, paper, and a calculator. The idea that calculations are performed in real time does not render their performance impractical under the eligibility case law. The claim at issue recites a mental process. Also, claim 1 recites math. One cannot derive a Schur matrix from a Hessian matrix without performing mathematical calculations.
The Applicant confuses the recitation of additional limitations in addition to the abstract idea as not reciting an abstract idea at all. That there are generic computing elements to conduct the abstract idea does not eliminate the recitation of an abstract idea.
The Claims Are Allegedly Integrated Into A Practical Application: The Applicant asserts that the claims are wholly integrated into the alleged practical application of improving a SLAM accelerator.
The Applicant asserts that the method saves time, power, and computational resources by not calculating all elements of a Hessian matrix. However, this improvement is contained entirely in the calculation itself, which is the abstract idea. Step 2A, Prong 2 requires that the additional limitations integrate the abstract idea into a practical application, which requires that some of the improvement be conferred by the additional limitations themselves. Unfortunately, nothing in the independent claims does this. The recitation of a processor and memory is clearly a recitation of generic computing elements. In claim 1, the Applicant has further recited a pipelined vision factor generator, a camera constraint generator, and a Schur-complement operator, but they are not used for anything in the claim. Even if they were, they are merely functionally defined processing modules that amount to processors recited at a high level. Similarly, the wherein clauses merely state that the determinations are broken down in pieces the processors can handle. This would be done regardless of the machinations of the Applicant’s because Operating Systems, as generic computing elements, conduct these operations, especially for parallel processing, without explicit instructions. Therefore, these also represent generic computing elements.
The independent claims are similar to the subject matter eligibility example 47, claim 2, which was found to be ineligible, because the claims merely receive, process, and output data. The Applicant attempts to identify the SLAM accelerator as a known computing element that is somehow modified by this claim, but it is an algorithm executed on a generic processor, and the claimed improvement is provided entirely by the reduced mathematical evaluation of the algorithm, not any other additional limitation.
The instant claims are directed to improved math that reduces the amount of inference the processor would need to perform to conduct SLAM. This is an improvement to SLAM, as an algorithm, if anything, not an improvement to the computer itself, which is no different from any other computer that can execute these instructions in the same way. The estimation of a position, regardless of the circumstances, is merely an evaluation of a mathematical calculation that is practically performable in the mind or with the aid of pen, paper, and/or a calculator, so it is a mental process and a mathematical concept, making it an element of the abstract idea.
Even if the estimation step were to be characterized as an additional limitation, it would be insignificant extra-solution activity (MPEP 2106.05(g) Example: Cutting hair after first determining the hair style); well-understood, routine, and conventional activity (WURC) – See the references on the record for examples of estimating a location of a mobile device in real time); and an apply it operation (MPEP 2106.05(f) Example: A method of assigning hair designs to balance head shape with a final step of using a tool (scissors) to cut the hair). That is, the improvement comes merely from the abstract idea, and the additional limitations do nothing to integrate the abstract idea into a practical application at Step 2A, Prong 2 or combine with the other elements of the claims to provide significantly more than the abstract idea that would confer an inventive concept at Step 2B.
Accordingly, the Applicant’s arguments are not persuasive, and the rejections are maintained.
35 USC 102/103 Art Rejections: The Applicant has extensively amended the claims. It is plausible that the existing references teach all of the features of the present Applicant reconstructed claims, but new art is applied in this application.
Claim Objections
Claims 1, 5, 7, 11, 15, 17, and 21 are objected to because of the following informalities:
Claims 1, 11, and 21 recite, “based on a number of camera poses the processor is able to perform operations simultaneously.” This appears to be a typo. This will be interpreted to mean that the data determinations are parsed into sub-operations, a known procedure performed by operating systems even without explicit instruction from a user or user-programmed application.
Claims 5 and 15 recite, “perform the optimization operations one the states of the first map…” This appears to be a typo.
Claims 7 and 17 recite, “the processor is further configured to divide the first measurement into a first part affected by both of the camera and the IMU, and a second part affected only by the IMU.” It is not possible to determine that something is only affected by an IMU. Those data will be affected by any number of elements. For example, all image data is affected by the camera, even if the camera does not perform post processing on the data the Applicant intends the claim to recite.
Appropriate correction is required.
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Enablement:
Claims 1-2, 5-8, 11-12, 15-18, and 20-21 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the enablement requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention.
Claims 1, 11, and 21
Claims 1, 11, and 17 recite, “divide operations to compute the elements of the Schur matrix into a plurality of sub-tracks” and “track length.” These are not terms of art and are insufficiently defined in the specification to provide a person of ordinary skill in the art guidance as to how one would divide these operations. Even the Applicant’s specification paragraphs [0147]-[0149] and corresponding equation 9 fail to stipulate what a sub-track of operations or a corresponding length thereof are. That is, a person of ordinary skill in the art could never be sure if they were practicing the invention at all.
The following are the most important Wands factors for consideration:
(F) Amount of direction provided by the inventor: The inventor teaches how to calculate a number of tracks but does not illustrate what the tracks are.
(G) The existence of working examples: The inventor has provided no working examples that demonstrate what a “sub-track” or “track length” are. They are defined with respect to frames in paragraphs [0147]-[0149] and [0162]-[0164], equations 9 and 11, and element 1920 in FIG. 19. For example, the track 1920 in FIG. 19 extends from a number of W values to a number of V values, and it is unclear from the specification how to use these “sub-tracks” to determine the Schur matrix. Also, the sub-track and track length are defined relative to a “frame,” which is also not a term of art, and which the specification fails to define. It is also unclear what the relationship between a camera pose and a frame is. Paragraph [0147] states, “[f]or example, when the Slam accelerator is capable of performing operations simultaneously only for two camera poses (or frames)…” It is unclear from this whether frames are camera poses are alternatives thereto. Even if the frames were poses, it is unclear how to limit the calculations to sub-tracks that, like 1920 in FIG. 19, extend between multiple elements of both the W and V matrices.
(H) The quantity of experimentation needed to make or use the invention based on the content of the disclosure: The disclosure does not teach with certainty what a frame, sub-track, track, or track length are, or how they are calculated as independent sub-tracks separately of other elements around them in the Hessian matrix, so it is likely no amount of experimentation that would render this feature enabled. That is a person of ordinary skill in the art could not be certain that they had practiced or infringed on the invention.
For these reasons, the features of claims 1, 11, and 21 are not enabled.
Further, claims 1, 11, and 21 recite, “transmitting… directly to the Schur complement operator.” It is unclear what directly means in this context, especially between software modules. Every computation requires direct and indirect communication between different elements, so there is no clear way to accomplish this. With respect to the most important Wands factors:
(F) Amount of direction provided by the inventor: The inventor does not indicate how to transfer data “directly” to a software module.
(G) The existence of working examples: The inventor has provided no working examples.
(H) The quantity of experimentation needed to make or use the invention based on the content of the disclosure: The disclosure does not teach with any certainty what directly means in this context, so it is likely no amount of experimentation that would render this feature enabled. That is a person of ordinary skill in the art could not be certain that they had practiced or infringed on the invention because of this uncetainty.
For these reasons, the features of claims 1, 11, and 21 are not enabled.
Claims 7 and 17
Claims 7 and 17 recite, “the processor is further configured to divide the first measurement into a first part affected by both of the camera and the IMU, and a second part affected only by the IMU.” However, it is unclear how anything can only be affected by one thing to the exclusion of all others. The Applicant has not provided any disclosure how anything can only be affected by an IMU and nothing else, and it is likely impossible.
The following are the most important Wands factors for consideration:
(F) Amount of direction provided by the inventor: The inventor does not teach how to account for only an IMU to the exclusion of all else.
(G) The existence of working examples: The inventor has provided no working examples that demonstrate how to account for only an IMU to the exclusion of all else.
(H) The quantity of experimentation needed to make or use the invention based on the content of the disclosure: Again, this is likely an impossibility. There is likely no amount of enabling disclosure that could enable a person of ordinary skill in the art to make and use something impossible.
Accordingly, Claims 7 and 17 are not enabled. Further, because the claim is technically incorrect, the claim cannot be searched for prior art.
Claims 8 and 18
Claims 8 and 18 recite, “accumulate the first elements, the second elements and the third elements into the Schur matrix.” However, the Schur matrix does not include the elements from the Hessian. The Schur matrix is based on a calculation on what the Applicant claims are the first, second, and third elements. This is technically incorrect, so it is clearly not enabled.
The following are the most important Wands factors for consideration:
(F) Amount of direction provided by the inventor: The inventor does not teach how to use a Schur matrix, which has been populated with Hessian matrix elements, rather than elements calculated from the elements of the Hessian matrix elements.
(G) The existence of working examples: The inventor has provided no working examples for something that is incorrect.
(H) The quantity of experimentation needed to make or use the invention based on the content of the disclosure: No amount of experimentation can make an incorrect operation valid.
Accordingly, Claims 8 and 18 are not enabled. Further, because claims 8 and 18 are non-sense, art cannot reasonably be presented to reject the claims.
Dependent claims are rejected based on their dependency from rejected claims.
Written Description: New Matter
Claims 1-2, 5-8, 11-12, 15-18, and 20-21 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
The independent claims 1, 11, and 21 recite, “divide operations to compute the elements of the Schur matrix into a plurality of sub-tracks” and “track length.” However, the uncertainty in how to determine frames, sub-tracks, and track lengths or even what they are demonstrates that the Applicant was not in possession of “divide operations to compute the elements of the Schur matrix into a plurality of sub-tracks” and “track length.”
Similarly, with regard to claims 7 and 17, it is likely impossible to determine that any element is only affected by an IMU to the exclusion of all else. For example, ambient temperature could, and almost certainly would, also affect the first measurement.
Dependent claims are rejected based on their dependency from rejected claims.
Claim Rejections - 35 USC § 112(b)
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 1-2, 5-8, 11-12, 15-18, and 20-21 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.
Claims 1, 11, and 21 recite, “directly,” but directly is a relative term, which is a term of degree, not a term of approximation. A person of ordinary skill in the art would not understand the metes and bounds of the term directly in the claim. For purposes of examination, the term directly will be ignored.
Dependent claims are rejected based on their dependency from rejected claims.
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 1-2, 5-8, 11-12, 15-18, and 20-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 (Statutory Category – Machine)
Step 2A – Prong 1: Judicial Exception Recited?
Yes, the claims recite a mental process and a mathematical operation.
MPEP 2106.04(a)(2)(Ill) “Accordingly, the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, Judgments, and opinions. […] The courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation.”
MPEP 2106.04(a)(2)(I) “When determining whether a claim recites a mathematical concept (i.e., mathematical relationships, mathematical formulas or equations, and mathematical calculations), examiners should consider whether the claim recites a mathematical concept or merely limitations that are based on or involve a mathematical concept […] a mathematical concept need not be expressed in mathematical symbols, because "[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula." In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989). See, e.g., SAP America, Inc. v. InvestPic, LLC, 898 F.3d 1161, 1163, 127 USPQ2d 1597, 1599 (Fed. Cir. 2018) (holding that claims to a ‘‘series of mathematical calculations based on selected information’’ are directed to abstract ideas); Digitech Image Techs., LLC v. Elecs. for Imaging, Inc., 758 F.3d 1344, 1350, 111 USPQ2d 1717, 1721 (Fed. Cir. 2014) (holding that claims to a ‘‘process of organizing information through mathematical correlations’’ are directed to an abstract idea).
MPEP 2106.04(a)(2)(I)(A) “Mathematical Relationships. A mathematical relationship is a relationship between variables or numbers. A mathematical relationship may be expressed in words or using mathematical symbols.”
Claim 1 recites, (claim features in italics):
computing, by the camera constraint generator based on the first measurement, first elements of a first Hessian matrix block U for the at least one camera pose, second elements of a second Hessian matrix block V for the first map point, and third elements of a third Hessian matrix block W representing a relationship between the at least one camera pose and the first map point, without generating an entirety of a Hessian matrix based on all of the plurality of measurements,
[…]
computing, by the Schur-complement operator, elements of a Schur matrix based on the transmitted first elements, second elements, and third elements according to S = U -W V -1 W T, and updating the computed elements of the Schur matrix into the memory, and
Partial determinations of a matrix, based on measurement data and computation of a Schur complement therefrom, are evaluations, which can be performed in the mind or with pencil and paper, and are, therefore, mental processes. These partial determinations are also mathematical relationships expressed in words, which are mathematical concepts.
estimating a location of the electronic apparatus moving in a map in real time by performing optimization operations for states of the first map point and the at least one camera pose based on the Schur matrix.
Estimating a numerical data point, such as a location, based on mathematical matrix operations, includes evaluations, which can be performed in the mind or with pencil and paper, and are, therefore, mental processes. These numerical data point estimations, based on mathematical matrix operations, are also mathematical calculations on mathematical relationships expressed in words, which are mathematical concepts.
Therefore, claim 1 recites a mental process and a mathematical concept, which are abstract ideas.
Claim 1 recites an abstract idea.
Step 2A – Prong 2: Integrated into a Practical Solution?
No.
MPEP 2106.04(d) “[A]fter determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception. Whether or not a claim integrates a judicial exception into a practical application is evaluated using the considerations set forth in subsection I below, in accordance with the procedure described below in subsection II.
MPEP 2106.05(f) Mere Instructions To Apply An Exception has found simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.
MPEP 2106.05(g): “Another consideration when determining whether a claim integrates the judicial exception into a practical application in Step 2A Prong Two or recites significantly more in Step 2B is whether the additional elements add more than insignificant extra-solution activity to the judicial exception. The term "extra-solution activity" can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity includes both pre-solution and post-solution activity. An example of pre-solution activity is a step of gathering data for use in a claimed process, e.g., a step of obtaining information about credit card transactions, which is recited as part of a claimed process of analyzing and manipulating the gathered information by a series of steps in order to detect whether the transactions were fraudulent.”
The additional elements:
A simultaneous localization and mapping (SLAM) accelerator of an electronic apparatus, the SLAM accelerator comprising:
a memory; and
a processor comprising a pipelined vision factor generator including a camera constraint generator and a Schur-complement operator, the processor configured to perform SLAM by:
[…]
wherein the processor is further configured to divide operations to compute the elements of the Schur matrix into a plurality of sub-tracks, and
wherein a track length of the plurality of sub-tracks is set based on a number of camera poses the processor is able to perform operations simultaneously, the number being determined based on a hardware resource constraint of the processor.
The memory and processor and the functional modules are general-purpose computer components recited at a high level. Under MPEP 2106.05(f), these do not integrate the abstract idea into a practical application at Step 2A, Prong 2. The wherein clauses merely state that the system allocates processing resources based on the size of the data. The OS automatically optimizes the size of data for processing regardless of what the top-level programming requires, so this is just a generic element of the computer. Should it be found that the SLAM accelerator of the electronic apparatus or the operations of the wherein clauses are other than a generic computer element, they merely recite computational elements at high levels that isolate the system to a particular technological field and, under 2106.05(h), fail to integrate the abstract idea into a practical application at Step 2A, Prong 2.
obtaining, from the memory, a first measurement, among a plurality of measurements, of a map point and a camera pose,
Obtaining a measurement from memory is data gathering, which is pre-solution activity that qualifies as insignificant extra solution activity under MPEP 2106.05(g). Insignificant extra solution activity does not integrate an abstract idea into a practical application.
transmitting the computed first elements, second elements, and third elements directly to the Schur-complement operator,
Transmitting data elements, whether into a matrix or otherwise, regardless of the potential (unclaimed) application of the matrix is also mere data gathering, post-solution activity (e.g., akin to “updating an activity log”) that qualifies as insignificant extra-solution activity under MPEP 2106.05(g). Insignificant extra solution activity does not integrate an abstract idea into a practical application.
None of the additional limitations of claim 1, whether in isolation or combination, integrate the abstract idea into a practical application.
Accordingly, claim 1 is directed to the abstract idea.
Step 2B: Claim provides an Inventive Concept?
No.
MPEP 2106.05(I) “An inventive concept "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself. […] Instead, an "inventive concept" is furnished by an element or combination of elements that is recited in the claim in addition to (beyond) the judicial exception, and is sufficient to ensure that the claim, as a whole, amounts to significantly more than the judicial exception itself.”
MPEP 2106.05(f) “Mere Instructions To Apply An Exception has found simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.”
MPEP 2106.05(g): “As explained by the Supreme Court, the addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional. Parker v. Flook, 437 U.S. 584, 588-89, 198 USPQ 193, 196 (1978).”
MPEP 2106.05(d): On the other hand, Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 67, 101 USPQ2d 1961, 1964 (2010) provides an example of additional elements that were not an inventive concept because they were merely well-understood, routine, conventional activity previously known to the industry, which were not by themselves sufficient to transform a judicial exception into a patent eligible invention. Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 79-80, 101 USPQ2d 1969 (2012) (citing Parker v. Flook, 437 U.S. 584, 590, 198 USPQ 193, 199 (1978) (the additional elements were "well known" and, thus, did not amount to a patentable application of the mathematical formula)).”
The additional elements:
A simultaneous localization and mapping (SLAM) accelerator of an electronic apparatus, the SLAM accelerator comprising:
a memory; and
a processor comprising a pipelined vision factor generator including a camera constraint generator and a Schur-complement operator, the processor configured to perform SLAM by:
[…]
wherein the processor is further configured to divide operations to compute the elements of the Schur matrix into a plurality of sub-tracks, and
wherein a track length of the plurality of sub-tracks is set based on a number of camera poses the processor is able to perform operations simultaneously, the number being determined based on a hardware resource constraint of the processor.
The memory and processor and modules are general-purpose computer components are generic computing elements recited at a high level. Under MPEP 2106.05(f), these do not combine with the other elements of the claim to provide significantly more than the abstract idea that would confer an inventive concept at Step 2B. Should it be found that the SLAM accelerator and associated modules of the electronic apparatus are other than a generic computer element, they merely recite computational elements at high levels that isolate\ the system to a particular technological field and, under 2106.05(h), fail to combine with the other elements of the claim to provide significantly more than the abstract idea that would confer an inventive concept at Step 2B.
obtain, from the memory, a first measurement, among a plurality of measurements, for a map point and a camera pose,
[…]
transmitting the computed first elements, second elements, and third elements directly to the Schur-complement operator,
These data gathering steps are also well-understood, routine, and conventional (WURC) activities, as in the MPEP 2106.05(h) examples: “i. Receiving or transmitting data over a network,” “iii. Electronic recordkeeping,“ “iv. Storing and retrieving information in memory,” “vi. Arranging a hierarchy of groups, sorting information, eliminating less restrictive pricing information and determining the price,”
Because the additional limitations of the processor, memory, and SLAM accelerator of the electronic apparatus are general-purpose computer components under MPEP 2106.05(f) (and/or are elements that merely limit the abstract idea to a particular field under MPEP 2106.05(h)) and the obtaining and accumulation steps are WURC activity under MPEP 2106.05(d) and insignificant extra-solution activity under MPEP 2106.05(g), the additional limitations of claim 21 do not combine with the other elements of the claim to provide significantly more than the abstract idea to render claim 1 inventive.
Accordingly, claim 1 is ineligible.
Independent claims 11 and 21 (Statutory Categories: Machine and Process, respectively) recite features analogous to the features of claim 21 and are ineligible for at least the same reasons as claim 1.
Claim 2 (and in method form 12) recite, wherein the processor comprises a pipeline structure configured to sequentially perform first operations on the first measurement over consecutive cycles after the first measurement is loaded in a first cycle, and
wherein the pipeline structure is configured to perform second operations on a second measurement, following the first operations regarding the first measurement after the second measurement is loaded in a second cycle which follows the first cycle.
The pipeline structure is not claimed as a hardware structure and, under the broadest reasonable interpretation, includes software emulators configured to execute the first process and the second process in the manner claimed. This represents an evaluation that can be performed in the mind or with pencil and paper (sans the already treated general-purpose processor that is demonstrated herein to neither integrate the abstract idea into a practical application nor confer inventiveness), which is a mental process. It is therefore an abstract idea that merges with the abstract idea of claim 1 and is not an additional limitation that can integrate the abstract idea into a practical application or render the abstract idea inventive. Claim 2 is ineligible. Claim 12 recites the operational features of claim 2 in an analogous method and is ineligible for at least the same reasons as claim 2.
Claim 5 (and in method form 15) recites, wherein the processor is further configured to perform the optimization operations one the states of the map point and the at least one camera pose by using the Schur matrix elements computed for each of the plurality of measurements have been sequentially accumulated into the Schur matrix.
Optimization using an optimization matrix is an evaluation that can be performed in the mind of a person or with pencil and paper. This is an evaluation, which is a mental process. Additionally, optimization using an optimization matrix is a mathematical calculation exploiting mathematical relationships, a mathematical concept. Claim 5 is, therefore, an abstract idea that merges with the abstract idea of claim 1 and is not an additional limitation that can integrate the abstract idea into a practical application or render the abstract idea inventive. Claim 5 is ineligible. Claim 15 recites the operational features of claim 5 in an analogous method and is ineligible for at least the same reasons as claim 5.
Claim 6 (and in method form 16) recites, wherein the first measurement corresponds to a result of performing front-end operations on data obtained from a sensor including at least one of a camera, an inertial measurement unit (IMU), a depth sensor, a global positioning system (GPS), or an odometer.
This claim merely describes the nature of the first measurement and does not recite an operation by the apparatus. Characterizing data as representing a measurement is merely indicating a field of use or technological environment for the data. This does not integrate the abstract idea into a practical application or combine with the abstract idea to amount to significantly more than the abstract idea under MPEP 2106.05(h). Accordingly, claim 6 is ineligible. Claim 16 recites the operational features of claim 6 in an analogous method and is ineligible for at least the same reasons as claim 6.
Claim 7 (and in method form 17) recites, [t]he SLAM accelerator of claim 6, wherein, based on the first measurement corresponding to the result of performing the front-end operations on the data obtained from the camera and the IMU, the processor is further configured to divide the first measurement into a first part affected by both of the camera and the IMU, and a second part affected only by the IMU.
Dividing data into different parts is selecting a particular data source or type of data to be manipulated (e.g., akin to selecting information, based on types of information [in a SLAM environment), which is insignificant extra-solution activity under MPEP 2106.05(g). “[T]he addition of insignificant extra-solution activity does not amount to an inventive concept.” It is also WURC under 2106.05(d) according to the examples provided for claim 1. Accordingly, claim 7 is ineligible. Claim 17 recites the operational features of claim 7 in an analogous method and is ineligible for at least the same reasons as claim 7.
Claim 8 (and in method form 18) recites,
[t]he apparatus of claim 7,
wherein the processor is further configured to:
based on the first part:
determine the first elements of the first Hessian matrix block U for the at least one camera pose,
determine the second elements of the second Hessian matrix block V for the first map point,
determine the third elements of the third Hessian matrix block W representing the relationship between the at least one camera pose and the first map point,
These determination steps that determine matrix blocks are evaluations that can be performed in the mind with pencil and paper, making them mental processes, and the steps are also mathematical calculations, which are mathematical operations. These are abstract ideas that merge with the abstract idea of the claims from which claim 8 depends. They are not additional limitations that integrate the abstract idea into a practical application or provide significantly more to render the abstract idea inventive.
accumulate the first elements, the second elements and the third elements into the Schur matrix, and
Accumulation of the elements of matrix blocks is mere data gathering, which is insignificant extra-solution activity under MPEP 2106.05(g). It is also WURC according to the examples from MPEP 2106.05(d) presented with respect to claim 1. Therefore, the accumulation step does not integrate the abstract idea into a practical application or combine with the other elements of the claim to provide significantly more and generate an inventive concept.
based on the second part:
determine fourth elements of a fourth matrix block for the at least one camera pose, and accumulate the fourth elements into the Schur matrix.
This determination step, like the prior determination steps, that determines a matrix block is an evaluations that can be performed in the mind with pencil and paper, making it a mental processes, and the step is also mathematical calculations, which is a mathematical operation. This step is an abstract idea that merges with the abstract idea of the claims from which claim 8 depends and the other determination steps. This determination step is an not additional limitation that integrates the abstract idea into a practical application or provides significantly more to render the abstract idea inventive.
None of the additional limitations of claim 8 integrate the abstract ideas recited in claim 8 and the claims from which claim 8 depends into a practical application or combine with them to provide significantly more to render the abstract idea an inventive concept. Accordingly, claim 8 is ineligible. Claim 18 recites the operational features of claim 8 in an analogous method and is ineligible for at least the same reasons as claim 8.
Claim 20 recites, [a] non-transitory computer-readable recording medium on which a program for executing the method of claim 11 in a computer is recorded.
The features of claim 11 were already demonstrated to be ineligible. A computer readable recording medium is a general-purpose computer added after the fact to the abstract idea (e.g., a fundamental economic practice or mathematical equation) and does not integrate a judicial exception into a practical application or provide significantly more under MPEP 2106.05(f). Therefore, the CRM is an additional limitation that cannot integrate the abstract idea into a practical application or provide significantly more to combine with the abstract idea to render the claim inventive. Accordingly, even if, arguendo, the Applicant amends claim 11 to recite “non-transitory,” claim 11 is still ineligible.
Claim Rejections - 35 USC § 102
(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.
Claim(s) 1-2, 5-6, 11-12, 15-16, and 20-21 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by NPL: “Graph-based SLAM embedded implementation on low-cost architectures: A practical approach” by Dine et al. (Dine).
Claims 1, 11, and 21
Regarding Claim 1 (And Claims 11 and 21, Which Recites Similar Limitations), R1 teaches:
A simultaneous localization and mapping (SLAM) accelerator of an electronic apparatus, the SLAM accelerator comprising: a memory; and a processor comprising a pipelined vision factor generator including a camera constraint generator and a Schur-complement operator, the processor configured to perform SLAM by: (Dine Abstract “The graph-based SLAM (Simultaneous Localization and Mapping) method uses a graph to represent and solve the SLAM problem. The SLAM allows building a map of an unknown environment and simultaneously localizing the robot on this map. This paper presents a temporal analysis of the 3D graph-based SLAM method. We also propose an efficient implementation, on an OMAP embedded architecture, which is a widely used open multimedia applications platform. We provide an optimized data structure and an efficient memory access management to solve the nonlinear least squares problem related to the algorithm.” – SLAM methods. Page 4616, Left Column, Last Paragraph - Right Column, First Paragraph “To implement the algorithm, we used the OMAP4430 architecture. It has a dual core ARM Cortex-A9 operating at 1GHz. Each core has dedicated NEON and FPU co processors (MPE). To accelerate more the processing time on this architecture, we parallelized the functional blocks of the algorithm on the two Cortex-A9 using the OpenMP API (Open Multi-Processing).” – Executed by a computer which includes a processor that conducts processing for SLAM.)
obtaining, from the memory, a first measurement, among a plurality of measurements, including a first map point and at least one camera pose at which the first map point is observed, (Dine Page 4612, Introduction “The graph-based SLAM allows refining, at each updating step, all the robot poses related to the performed trajectory, and the landmarks locations in the map.” Page 4613, II. Graph-Based SLAM “The graph-based SLAM uses a graph to represent and solve the SLAM problem. The poses of the robot and the landmarks are modeled as nodes and the edges represent spatial constraints between the nodes.” – Map points and camera poses are used as input data.)
computing, by the camera constraint generator based on the first measurement, first elements of a first Hessian matrix block U for the at least one camera pose, second elements of a second Hessian matrix block V for the first map point, and third elements of a third Hessian matrix block W representing a relationship between the at least one camera pose and the first map point, without generating an entirety of a Hessian matrix based on all of the plurality of measurements, (Dine Page 4614, Linear System Construction “The goal of this block (FB5) is to compute the linear system (Eq. 4). In other words, we calculate the information matrix H and the information vector b. H is a matrix of (p + n) × (p +n) blocks where p is the number of robot poses and n is the number of landmarks in the map. Each block in the information matrix is itself a 3 × 3 matrix. The information vector b is a (p+n) block vector where each block consists of 3 elements corresponding to the world frame coordinates. In order to construct the matrix H and the vector b, we first linearize the errors by computing their corresponding Jacobians. The construction incrementally fills the matrix H and the vector b. Each edge in the graph additively contributes to the filling of the corresponding elements in the matrix. For example, an edge linking the nodes i and j updates the elements H(i,i), H(j,j), H(i,j) and H(j,i). However, the matrix H is, by construction, symmetric. This allows to compute only the upper (or the lower) triangular part of the matrix.” – The information matrix of this problem is a Hessian matrix, structured in the manner claimed ( (p+n) x (p+n) with H(i,i), H(i,j), H(j,i) and H(j,j) ), and the symmetry of the matrix makes it so that several values do not need to be and are not computed.)
transmitting the computed first elements, second elements, and third elements directly to the Schur-complement operator, computing, by the Schur-complement operator, elements of a Schur matrix based on the transmitted first elements, second elements, and third elements according to S = U -W V -1 W T, and updating the computed elements of the Schur matrix into the memory, and (Dine Page 4614, Schur Complement “The Schur complement permits to transform the constructed system into a smaller one [2], [6]. The system includes two types of variables, namely the poses p of the robot and the landmarks locations l.
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This block (FB6) consists in calculating the system of Eq. (7). The new system requires less time to be resolved be cause in general the landmarks outnumbers the robot poses. Solving this new system gives the increments ∆yp of the poses p. The landmarks locations can be then deduced using the system of Eq. (8). Note that the inverse of Hll is easy to calculate as it is a block-diagonal matrix.
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- The reference illustrates that the claim merely claims a Schur operation in a SLAM context, which is well known. The boxed portion of equation seven shows this relationship for the Schur determinations. Because the Hessian is symmetrical about its diagonal, the definition of the Schur incorporates that by using a Transposed Hpl, written as
H
p
l
T
, representing the fourth quadrant of the Hessian. This is also evident from the Schur Decomposition Wiki reference made of record, which explicitly demonstrates, on Page 1, “ A = QUQ-1 where Q is a unitary matrix (so that its inverse Q-1 is also the conjugate transpose Q* of Q)”)
estimating a location of the electronic apparatus moving in a map in real time by performing optimization operations for states of the first map point and the at least one camera pose based on the Schur matrix, (Dine Page 4614, Right Column, System state updating “The increments of the solved system are added to the current graph configuration which represents the state of the system (FB9)” Page 4614, III Algorithm and Functional Blocks Partitioning “The algorithm that we established for the 3D graph based SLAM considers a wheeled robot embedding two odometers and a monocular camera. In order to best evaluate and optimize our implementation, we have analyzed and partitioned the algorithm into functional blocks [10].” Page 4612, Introduction “Simultaneous Localization and Mapping (SLAM) allows building a map of an unknown environment while simulta neously estimating the pose of the robot on this map. The map includes particular elements of the environment called landmarks which can be detected using an exteroceptive sensor such as a camera. The graph-based SLAM is a method introduced by Lu and Milios [1]. [2] and [3] have used and developed later this method with the aim to enhance accuracy, consistency and execution time. The graph-based SLAM allows refining, at each updating step, all the robot poses related to the performed trajectory, and the landmarks locations in the map.” – The methods optimize the system to determine SLAM, which is simultaneous location and mapping, which determines locations in real time b definition.)
wherein the processor is further configured to divide operations to compute the elements of the Schur matrix into a plurality of sub-tracks, and wherein a track length of the plurality of sub-tracks is set based on a number of camera poses the processor is able to perform operations simultaneously, the number being determined based on a hardware resource constraint of the processor. (Dine Page 4616, Memory Access Management “Since the matrix blocks are separately stored in tables, we need to know the location of each matrix block. To do this, we did a trade-off between space memory and memory access time. To avoid location blocks resolving, we use an index matrix as shown in figure 4. This index matrix is (p+ n)×(p+n), where each cell contains a pointer to the block data in the corresponding table. Note here that, as the index matrix is also symmetric, we store only its upper (or lower) triangular part. Storing only a pointer is more efficient than the whole data block in terms of memory space and allows to directly access the matrix blocks. The matrix is initially initialized with null values and is incrementally filled when inserting new graph elements (nodes and edges). When a new node or edge is created, we simply copy the address of its block matrix in the index matrix. However, this matrix may contain null values if there is no corresponding edge. But, the use of a compressed representation of the index matrix to eliminate null pointers would complicate accessing and updating this table.” – The allocation of elements to memory and for processing is managed based on the processing and memory resources available. Page 4616, Multi-Core Parallelization “To implement the algorithm, we used the OMAP4430 architecture. It has a dual core ARM Cortex-A9 operating at 1GHz. Each core has dedicated NEON and FPU co processors (MPE). To accelerate more the processing time on this architecture, we parallelized the functional blocks of the algorithm on the two Cortex-A9 using the OpenMP API (Open Multi-Processing). The analysis of the algorithm shows that the calculation of an error or its Jacobian of an edge depends only on this edge. Thereby, we can fully parallelize these operations.” Page 4617, B. Schur Complement “To get efficient results, the Schur complement computing should be highly optimized. Algorithm 3 depicts the calculation of the new system resulting from the Schur complement (Eq.7,8). The new system matrix blocks are stored in a new block matrix Hpp, where p is the number of the robot poses in the graph. First of all, the Hpp structure is initialized with the corresponding blocks of the original information matrix H. The index matrix is initialized as well. The aim of the Algorithm is to take advantage of the present data structure and the characteristics of the new system to calculate, in order to reduce arithmetic and memory access operations. […] Finally, this block was parallelized using OpenMP where each robot pose can be independently processed. Note that, equation8 is included in the system solving block (FB8) and it is not detailed in algorithm3. – The track size is determined based on the available computing resources.
Regarding claims 1 and 11, claims 1 and 11 recite similar features to claim 21 and are rejected for at least the same reasons.
Claims 2 and 12
Regarding claim 2, Dine teaches the features of claim 1 and further teaches:
wherein the processor comprises a pipeline structure configured to sequentially perform first operations on the first measurement over consecutive cycles after the first measurement is loaded in a first cycle, and wherein the pipeline structure is configured to perform second operations on a second measurement, following the first operations regarding the first measurement after the second measurement is loaded in a second cycle which follows the first cycle. (NOTE Using a processing pipeline to process information in chronological order is a basic operation. Also, the claim is broad enough for the first measurement to be a first measurement and the second measurement to be 10,000th cycle, which would be done in that order. ALSO, Dine Page 4617 “Therefore, a robot pose block matrix is updated by adding Hi and Hj due to the fact that a robot pose can be, at the same time, a first node in one edge(observation or motion) and a second node in another motion edge. In the latter case, Hj and sj are respectively added to Hii and bi (notdetailedinalgorithm2).In contrast, a landmark can be only a second node in an observation edge” Page 4617 “To get efficient results, the Schur complement computing should be highly optimized. Algorithm 3 depicts the calculation of the new system resulting from the Schur complement (Eq.7,8). The new system matrix blocks are stored in a new block matrix Hpp, where p is the number of the robot poses in the graph. First of all, the Hpp structure is initialized with the corresponding blocks of the original information matrix H. The index matrix is initialized as well. The aim of the algorithm is to take advantage of the present data structure and the characteristics of the new system to calculate, in order to reduce arithmetic and memory access operations.” – The processes are pipelined to be sequential, essentially conducting the calculations in chronological order as the object moves.
Regarding claim 12, claim 12 recites features similar to claim 2 and is rejected for at least the same reasons.
Claims 5 and 15
Regarding claim 5, Dine teaches the features of claim 1 and further teaches:
wherein the processor is further configured to perform the optimization operations one (sic) the states of the first map point and the at least one camera pose by using the Schur matrix after elements computed for each of the plurality of measurements have been sequentially accumulated into the Schur matrix. (Dine Page 4617, B. Schur Complement “To get efficient results, the Schur complement computing should be highly optimized. Algorithm 3 depicts the calculation of the new system resulting from the Schur complement (Eq.7,8). The new system matrix blocks are stored in a new block matrix Hpp, where p is the number of the robot poses in the graph. First of all, the Hpp structure is initialized with the corresponding blocks of the original information matrix H. The index matrix is initialized as well. The aim of the algorithm is to take advantage of the present data structure and the characteristics of the new system to calculate, in order to reduce arithmetic and memory access operations. We start computing the new system by inversing the matrix Hll. Since Hll is a block-diagonal matrix, we simply have to inverse the diagonal blocks (line 3 through 5). – The operations are performed sequentially after the Schur matrix is populated.)
Regarding claim 15, claim 15 recites features similar to claim 5 and is rejected for at least the same reasons.
Claims 6 and 16
Regarding claim 6, Dine teaches the features of claim 1 and further teaches:
wherein the first measurement corresponds to a result of performing front-end operations on data obtained from a sensor including at least one of a camera, an inertial measurement unit (IMU), a depth sensor, a global positioning system (GPS), or an odometer. (Dine Page 4613, III. Algorithm And Functional Blocks Pertitioning “The algorithm that we established for the 3D graph based SLAM considers a wheeled robot embedding two odometers and a monocular camera. In order to best evaluate and optimize our implementation, we have analyzed and partitioned the algorithm into functional blocks [10]. […] 1) Sensors Data Processing: In this task, sensors data are processed (FB1 through FB3). In our implementation, the acquired image is processed to extract interest points using the Fast detector [11]. – The measurements are made by sensors, including a camera.)
Regarding claim 16, claim 16 recites features similar to claim 6 and is rejected for at least the same reasons.
Claim 20
Regarding claim 20, Dine teaches the features of claim 11, and further teaches:
A non-transitory computer-readable recording medium on which a program for executing the method of claim 11 in a computer is recorded. (Dine
Art Rejections Too Speculative
As demonstrated with respect to the 35 USC 112(a) rejections, claims 7-8 and 17-18 are technically incorrect, so art cannot be applied to claims 7-8 and 17-18 without significant speculation in interpretation. The Applicant is invited to amend the claims to be technically correct, with support from the Applicant’s original specification or cancel the claims.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
(From This Action)
NPL: “GNSS/IMU/ODO/LiDAR-SLAM Integrated Navigation System Using IMU/ODO Pre-Integration” by Chang et al. (Teaches the use of an IMU with an odometer (such as the one in Dine for better preprocessing and better SLAM results)
(From Prior Actions)
US 2016/0305784 A1 to Roumeliotis et al;
US 2017/0261324 A1 to Roumeliotis et al;
US 2017/0294023 A1 to Roumeliotis et al; and
Youyang F, Qing W, Gaochao Y. Incremental 3-D pose graph optimization for SLAM algorithm without marginalization. International Journal of Advanced Robotic Systems. 2020;17(3). doi:10.1177/1729881420925304 (Year: 2020).
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