DETAILED ACTION
Continued Examination Under 37 CFR 1.114
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 4/23/2026 has been entered.
Status of Claims
The following is a Non-final Office action in response to the communication filed 4/23/2026. Claims 1, 15, 17-18, and 43 have been amended. Claims 8-9, 11, 16, 20-21, 27-42 have been cancelled. Claim 44 has been added.
Information Disclosure Statement
Information Disclosure Statement received 7/6/2026 has been reviewed and considered. It is noted, however, that the provided Yilmaz reference did not align with the associated reference number in the IDS.
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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d).
Response to Arguments
Applicant’s amendments and associated arguments, filed 4/23/2026, with respect to the rejection of the claims under 35 U.S.C. §101 have been considered but they are not persuasive.
Applicant argues that the limitations of the independent claims recite operations that the human mind is not equipped to practically perform. Examiner respectfully disagrees. While the presently claimed invention may enable the abstract processes to be performed more quickly and accurately, the claims recite steps could be functionally executed by a human. Relying on a computer to perform routine tasks more quickly or more accurately is insufficient to render a claim patent eligible. Examiner also notes that the provided analysis also identified limitations as mathematical processes, which need not be performed in the human mind to be identified as abstract.
Applicant argues that the limitations recite elements that would integrate the alleged mental process into a practical application. Examiner respectfully disagrees. As recited, the claimed are directed to a process for improving trajectory mapping in the field of mobile devices, which is an abstract process applied using generic computing functions (i.e., collecting, processing and providing information).
Applicant argues that the limitations recite particular methods and systems that can provide better map matching of mobile device trajectories that improve upon current mobile device localization techniques and are clearly directed to improvements in a computer-related technology. More specifically, applicant argues that the claims amount to significantly more than the abstract idea itself because the recite an inventive way of locating a plurality of mobile device trajectories relative to each other and a map by performing specific operations (e.g., performing a non-linear optimization process based on first constraints, generating second constraints, combining the first and second constraints, and then repeating the non-linear optimization process using the combined constraints). Examiner respectfully disagrees. Examiner initially notes that the specific operations identified in this argument are abstract and represent an improvement to the abstract process rather than an improvement to computer-related technology. As recited, the claimed invention does not improve the performance of the system itself, but rather recites elements operating using well-understood, routine and conventional functions such as receiving and processing data for the purpose of generating and providing pose graphs. Making a specific improvement to a process for generating pose graphs represents an improvement to the abstract idea rather than an improvement to the technology utilized for implementing said abstract idea.
Regarding arguments directed to Example 4 (i.e., The present claims are analogous to those in Example 4, at least because they also recite meaningful limitations placed upon the use of the non-linear optimization process recited by the claims, and improve the usefulness of mobile device trajectory localization on a map as described above.), unlike the fact pattern in Example 4 where GPS techniques were improved by enabling the mobile GPS receiver to determine its position more accurately and improve its signal-acquisition sensitivity to operate even in weak signal environments, the instant applications recites an alternate process (i.e. abstract concept – mental process and/or math) that can be performed where GNSS positioning is unavailable.
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 1-7, 10, 12-15, 17-19, 22-26 and 43-44 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 of the Subject Matter Eligibility Test entails considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter.
Claims 1-7, 10, 12-15, 18-19, 22-26 and 43-44 recite a series of steps, therefore claims 1-7, 10, 12-15, 18-19, 22-26 and 43-44 are a method/process which is within at least one of the four statutory categories.
Claim 17 recites a system/ machine, therefore claim 17 is a system/ machine which is within at least one of the four statutory categories.
If the claim recites a statutory category of invention, the claim requires further analysis in Step 2A. Step 2A of the Subject Matter Eligibility Test is a two-prong inquiry. In Prong One, examiners evaluate whether the claim recites a judicial exception.
Independent claim 1 includes limitations that recite an abstract idea (emphasized below):
A computer implemented method of locating a plurality of mobile device trajectories relative to each other and a map, the mobile device trajectories comprising a time series of position nodes joined by edges, the method comprising:
obtaining sensor data from a plurality of mobile devices;
generating an input pose graph based on the sensor data from the plurality of mobile devices, the input pose graph comprising a plurality of mobile device trajectories and a plurality of first constraints defining the position and orientation of nodes and edges of the trajectories relative to each other;
generating a modified pose graph by performing a non-linear optimisation process on the input pose graph based on the first constraints, the non-linear optimisation process to reduce a cost function associated with the first constraints;
extracting one or more sub-graphs from the modified pose graph, and for each sub-graph, modifying the nodes and edges of the sub-graph based on features defined in the map;
generating second constraints based on the one or more modified sub-graphs, the second constraints defining the position and orientation of nodes and edges of the sub-graph relative to each other;
combining the first constraints and second constraints to form new fused constraints; and
repeating the non-linear optimisation process using the new fused constraints, to reduce the cost function, the processing providing a second modified pose graph.
Independent claim 17 includes limitations that recite an abstract idea (emphasized below):
A data processing system for locating a plurality of mobile device trajectories relative to each other and a map, the mobile device trajectories comprising a time series of position nodes joined by edges, the data processing system comprising:
processing circuitry arranged to:
obtain device sensor data from a plurality of mobile devices;
generate, based on the device sensor data, an input pose graph comprising a plurality of mobile device trajectories and a plurality of first constraints defining the position and orientation of nodes and edges of the trajectories relative to each other;
perform a non-linear optimisation process on the input pose graph based on the first constraints, to reduce a cost function associated with the first constraints, the non-linear optimization process providing a modified pose graph;
extract one or more sub-graphs from the modified pose graph, and for each sub- graph, individually processing the sub-graph to map match the nodes and edges of the sub-graph to features defined in the map;
generate second constraints based on the one or more map matched sub-graphs;
combine the first constraints and second constraints to form new fused constraints; and
repeat the non-linear optimisation process using the new fused constraints, to reduce the cost function, the processing providing a second modified pose graph;
process the second modified pose graph to match the nodes and edges of the second modified pose graph to features defined in the map, and
provide a visualization of the map matching trajectories of the second modified pose graph overlaid on the map.
Independent claim 18 includes limitations that recite an abstract idea (emphasized below):
A computer implemented method of locating a plurality of mobile device trajectories relative to each other and a map, the mobile device trajectories comprising a time series of position nodes joined by edges, the method comprising:
a. generating an input pose graph based on sensor data from a plurality of mobile devices, the input pose graph comprising a plurality of mobile device trajectories and a plurality of first constraints defining the position and orientation of nodes and edges of the trajectories relative to each other;
b. performing a non-linear optimisation process on the input pose graph based on the first constraints, to reduce a cost function associated with the first constraints, the non-linear optimisation process providing a modified pose graph;
c. extracting one or more sub-graphs from the modified pose graph, and for each sub-graph, individually processing the sub-graph to map match the nodes and edges of the sub- graph to features defined in the map;
d. generating second constraints based on the one or more map matched sub-graphs;
e. calculating a cost function based on the second constraints;
if the cost function based on the second constraints is above a threshold iteratively repeating the process; and
if the cost function based on the second constraints is below the threshold,
terminating the method and outputting the one of the input pose graph and the modified pose graph; and
f. providing a visual of the output pose graph overlaid on the map.
These limitations, as drafted, is a system that, under its broadest reasonable interpretation, covers performance of the limitation as certain mental process. That is, nothing in the claim elements preclude the steps from practically being performed as certain mental process. For example, “generate….” “perform…” “extract …” “generate …” “combine …” and “repeat …” encompass a human repeating a process to reduce error for generating trajectory pose graph. Thus, the claims recite at least one abstract idea.
These limitations, as drafted, are a process that, under its broadest reasonable interpretation, also represent mathematical relationships (e.g., the recitation of a non-linear optimization process to reduce a cost function associated with the first constraints, creating and generating graphs with nodes and edges based on constraints, etc.) and are therefore mathematical concepts. The mere recitation of a generic computer does not take the claim out of the mathematical concepts grouping. Thus, the claim recites an abstract idea.
If the claim recites a judicial exception in step 2A Prong One , the claim requires further analysis in step 2A Prong Two. In step 2A Prong Two, examiners evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
Independent claim 1 includes limitations that recite additional elements (underlined below):
A computer implemented method of locating a plurality of mobile device trajectories relative to each other and a map, the mobile device trajectories comprising a time series of position nodes joined by edges, the method comprising:
obtaining sensor data from a plurality of mobile devices;
generating an input pose graph based on the sensor data from the plurality of mobile devices, the input pose graph comprising a plurality of mobile device trajectories and a plurality of first constraints defining the position and orientation of nodes and edges of the trajectories relative to each other;
generating a modified pose graph by performing a non-linear optimisation process on the input pose graph based on the first constraints, the non-linear optimisation process to reduce a cost function associated with the first constraints;
extracting one or more sub-graphs from the modified pose graph, and for each sub-graph, modifying the nodes and edges of the sub-graph based on features defined in the map;
generating second constraints based on the one or more modified sub-graphs, the second constraints defining the position and orientation of nodes and edges of the sub-graph relative to each other;
combining the first constraints and second constraints to form new fused constraints; and
repeating the non-linear optimisation process using the new fused constraints, to reduce the cost function, the processing providing a second modified pose graph.
Independent claim 17 includes limitations that recite additional elements (underlined below):
A data processing system for locating a plurality of mobile device trajectories relative to each other and a map, the mobile device trajectories comprising a time series of position nodes joined by edges, the data processing system comprising:
processing circuitry arranged to:
obtain device sensor data from a plurality of mobile devices;
generate, based on the device sensor data, an input pose graph comprising a plurality of mobile device trajectories and a plurality of first constraints defining the position and orientation of nodes and edges of the trajectories relative to each other;
perform a non-linear optimisation process on the input pose graph based on the first constraints, to reduce a cost function associated with the first constraints, the non-linear optimization process providing a modified pose graph;
extract one or more sub-graphs from the modified pose graph, and for each sub- graph, individually processing the sub-graph to map match the nodes and edges of the sub-graph to features defined in the map;
generate second constraints based on the one or more map matched sub-graphs;
combine the first constraints and second constraints to form new fused constraints; and
repeat the non-linear optimisation process using the new fused constraints, to reduce the cost function, the processing providing a second modified pose graph;
process the second modified pose graph to match the nodes and edges of the second modified pose graph to features defined in the map, and
provide a visualization of the map matching trajectories of the second modified pose graph overlaid on the map.
Independent claim 18 includes limitations that recite additional elements (underlined below):
A computer implemented method of locating a plurality of mobile device trajectories relative to each other and a map, the mobile device trajectories comprising a time series of position nodes joined by edges, the method comprising:
a. generating an input pose graph based on sensor data from a plurality of mobile devices, the input pose graph comprising a plurality of mobile device trajectories and a plurality of first constraints defining the position and orientation of nodes and edges of the trajectories relative to each other;
b. performing a non-linear optimisation process on the input pose graph based on the first constraints, to reduce a cost function associated with the first constraints, the non-linear optimisation process providing a modified pose graph;
c. extracting one or more sub-graphs from the modified pose graph, and for each sub-graph, individually processing the sub-graph to map match the nodes and edges of the sub- graph to features defined in the map;
d. generating second constraints based on the one or more map matched sub-graphs;
e. calculating a cost function based on the second constraints;
if the cost function based on the second constraints is above a threshold iteratively repeating the process; and
if the cost function based on the second constraints is below the threshold,
terminating the method and outputting the one of the input pose graph and the modified pose graph; and
f. providing a visual of the output pose graph overlaid on the map.
The claim recites the additional element(s) of “computer implemented” and “A data processing system for locating a plurality of mobile device trajectories relative to each other and a map, the mobile device trajectories comprising a time series of position nodes joined by edges, the data processing system comprising: processing circuitry arranged to” perform a process. These additional elements amount to merely indicating a field of use or technological environment in which to apply a judicial exception and cannot integrate the judicial exception into a practical application (see MPEP 2106.05(h)). These functions of these additional elements merely act to apply the above-noted abstract idea by merely using a general processor to perform the process (MPEP § 2106.05). In particular, the devices recited at a high-level of generality (i.e., as a generic processor processing repeating a mathematical process to reduce error for generating trajectory pose graph with constraints) such that it amounts no more than mere instructions to apply the exception using a generic computer component.
The claims also recite additional elements of “obtaining sensor data from a plurality of mobile devices” and “obtain device sensor data from a plurality of mobile devices,” which amounts extra-solution activity. In particular, the obtaining functions are recited at a high-level of generality (i.e., as a generic means of gathering and sending data information) such that it amounts no more than mere data gathering.
The claims also recite additional elements of “provide a visualization of the map matching trajectories of the second modified pose graph overlaid on the map,” which amounts to extra-solution activity. In particular, the providing functions are recited at a high level of generality (i.e., as a generic means of presenting information) such that it amounts to no more than generic display.
Accordingly, in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
If the additional elements do not integrate the exception into a practical application in step 2A Prong Two, then the claim is directed to the recited judicial exception, and requires further analysis under Step 2B to determine whether they provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself).
As discussed above limitations reciting that the method is “computer implemented” and “A data processing system for locating a plurality of mobile device trajectories relative to each other and a map, the mobile device trajectories comprising a time series of position nodes joined by edges, the data processing system comprising: processing circuitry arranged to” perform a process amount to merely indicating a field of use or technological environment in which to apply a judicial exception and merely act to apply the above-noted abstract idea using a general processor. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). In addition, the Flook and Bancorp Services court decision cited in MPEP 2106.05(d)(II) indicate that performing repetitive calculations is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here).
As discussed above, additional elements of “obtaining sensor data from a plurality of mobile devices” and “obtain device sensor data from a plurality of mobile devices,” amounts to extra-solution activity. The Symantec, TLI, OIP Techs. and buySAFE court decisions cited in MPEP 2106.05(d)(II) indicate that mere collection or receipt of data over a network is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is here).
As discussed above, additional elements of “provide a visualization of the map matching trajectories of the second modified pose graph overlaid on the map” and “f. providing a visual of the output pose graph overlaid on the map” amounts to extra-solution activity. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). In addition, Aldana et al. (US 20140206389) discloses conventional approaches for providing position and/or tracking targets includes simply overlaying the position information on a planar map (see [0006]) and Yoshihashi (US 20040225436) discloses it is well-known to display map information where a current position is overlaid on a displayed map (see [0004]).
The specification also demonstrates the well-understood, routine, conventional nature of additional elements as it describes the additional elements as well-understood or routine or conventional (or an equivalent term), as a commercially available product, or in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. §112(a).
Thus, even when viewed as an ordered combination, nothing in the claims add significantly more (i.e. an inventive concept) to the abstract idea.
Dependent claims 2-7, 10, 12-15, 19, 22-26 and 44 specify limitations that elaborate on the abstract idea of their respective independent parent claim (as identified in the analysis above) without reciting any further additional elements. For the reasons described above with respect to the independent claims, this judicial exception is not meaningfully integrated into a practical application, or significantly more than the abstract idea.
Dependent claim 43 further characterizes the data collected from the mobile devices, which acts to further define the data collection step (see case law provided with respect to this specific function above), and establishes a field of use or technological environment in which to apply a judicial exception, which does not amount to significantly more than the exception itself. (see MPEP 2106.05(h)).
Potentially Allowable Subject Matter
Claims 1-7, 10, 12-15, 17-19, 22-26 and 42-43 currently stand rejected under 35 USC 101, but would be allowable if rewritten to overcome current rejection under 35 USC 101.
See reasons for indicating potentially allowable subject matter in Non-Final Office action mailed 9/23/2024.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ABBY J FLYNN whose telephone number is (571)272-9855. The examiner can normally be reached Monday - Friday 8:30-5:00-3:00.
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/ABBY J FLYNN/ Examiner, Art Unit 3663
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