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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 October 21, 2025 has been entered.
Claims 1-3, 5-6, 9, 11, 13, 15-17, and 19-20 have been amended.
Claims 1-20 are pending.
The effective filing date of the claimed invention is December 20, 2022.
Response to Amendment
Amendments to Claims 1-3, 5-6, 9, 11, 13, 15-17, and 19-20 are acknowledged.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed a judicial exception (i.e., an abstract idea) without significantly more.
Step 1
As indicated in the preamble of the claim, the examiner finds the claim is directed to a process, machine, manufacture, or composition of matter.(Claims 1-10 are processes (typically methods) and Claims 11-20 are machines (typically systems or devices)). Accordingly, step 1 is satisfied.
Step 2A – Prong 1
Claim 1 (and similarly Claims 11 and 20) recites the following abstract concepts that are found to include “abstract idea.” Any additional elements will be analyzed under Step 2A-Prong 2 and Step 2B:
A method comprising, at a computer system comprising a processor and a computer-readable medium:
receiving, from a plurality of client devices associated with an online system, a plurality of data points comprising a first set of data points and a second set of data points (See MPEP 2106.04(a)(2)(II)(C) – organizing human activity, The sub-grouping “managing personal behavior or relationships or interactions between people” include social activities, teaching, and following rules or instructions. Other examples of following rules or instructions recited in a claim include: i. assigning hair designs to balance head shape, In re Brown, 645 Fed. Appx. 1014, 1015-16 (Fed. Cir. 2016) (non-precedential); and ii. a series of instructions of how to hedge risk, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010).), wherein;
the first set of data points is associated with arriving outside of one or more locations of a plurality of locations (See MPEP 2106.04(a)(2)(II)(C) – organizing human activity, The sub-grouping “managing personal behavior or relationships or interactions between people” include social activities, teaching, and following rules or instructions. Other examples of following rules or instructions recited in a claim include: i. assigning hair designs to balance head shape, In re Brown, 645 Fed. Appx. 1014, 1015-16 (Fed. Cir. 2016) (non-precedential); and ii. a series of instructions of how to hedge risk, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010).);
the second set of data points is associated with picking up items from one or more locations of the plurality of locations and delivering items to one or more locations of the plurality of locations (See MPEP 2106.04(a)(2)(II)(C) – organizing human activity, The sub-grouping “managing personal behavior or relationships or interactions between people” include social activities, teaching, and following rules or instructions. Other examples of following rules or instructions recited in a claim include: i. assigning hair designs to balance head shape, In re Brown, 645 Fed. Appx. 1014, 1015-16 (Fed. Cir. 2016) (non-precedential); and ii. a series of instructions of how to hedge risk, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010).); and
each data point includes a set of motion data captured by sensors of the respective client device that the data point was received from (See MPEP 2106.04(a)(2)(II)(C) – organizing human activity, The sub-grouping “managing personal behavior or relationships or interactions between people” include social activities, teaching, and following rules or instructions. Other examples of following rules or instructions recited in a claim include: i. assigning hair designs to balance head shape, In re Brown, 645 Fed. Appx. 1014, 1015-16 (Fed. Cir. 2016) (non-precedential); and ii. a series of instructions of how to hedge risk, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010).);
executing a clustering process on one or more of the first set of data points and the second set of data points (See MPEP 2106.04(a)(2)(I) – mathematical concepts, 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); see also IBM v. Zillow Inc., App. No. 2021-2350, page 3 (Fed. Cir. Oct. 17, 2022) (such clustering shown as e.g.
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), the clustering process comprising:
generating, from the one or more of the first set of data points and the second set of data points, one or more clusters associated with each location of the plurality of locations (See MPEP 2106.04(a)(2)(I) – mathematical concepts, 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)), and
identifying a cluster associated with each location of the plurality of locations based at least in part on the one or more of the first set of data points and the second set of data points included in each cluster of the one or more clusters (See MPEP 2106.04(a)(2)(I) – mathematical concepts, 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); see also IBM v. Zillow Inc., App. No. 2021-2350, page 3 (Fed. Cir. Oct. 17, 2022) (such clustering shown as e.g.
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);
determining a geolocation associated with each location of the plurality of locations based at least in part on the one or more of the first set of data points and the second set of data points included in the identified cluster, wherein the geolocation is associated with a facility and the cluster of the associated location (See MPEP 2106.04(a)(2)(II)(C) – organizing human activity, The sub-grouping “managing personal behavior or relationships or interactions between people” include social activities, teaching, and following rules or instructions. Other examples of following rules or instructions recited in a claim include: i. assigning hair designs to balance head shape, In re Brown, 645 Fed. Appx. 1014, 1015-16 (Fed. Cir. 2016) (non-precedential); and ii. a series of instructions of how to hedge risk, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010); see also Sanderling Management v. Snap Inc., App. No. 2021-2173, page 7 (Fed. Cir. Apr. 12, 2023)(“ As the district court articulated, in a formulation we agree with, the claims are directed to the abstract idea “‘of providing information – in this case, a processing function – based on meeting a condition,’ e.g., matching a GPS location indication with a geographic location.” Appx11. Even though the information being distributed is of a particular variety – here, digital imaging processing based on a distribution rule that determines when a condition is met – distribution of information is an abstract idea. See Intell. Ventures I LLC v. Cap. One Bank, 792 F.3d 1363, 1369 (Fed. Cir. 2015) (“Providing this minimal tailoring – e.g., providing different newspaper inserts based on the location of the individual – is an abstract idea.”).”);
detecting, for at least one determined geolocation, whether each of set of motion data associated with the data points of the cluster of the geolocation is indicative of a type of movement of the respective client device, wherein a first type of movement is associated with vertical motion (See 2106.04(a)(2)(III)(A) – Mental Processes, Claims do recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions. Examples of claims that recite mental processes include a claim to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016);
in response to detecting that each of set of motion data associated with the data points of the cluster of the geolocation is indicative of the type of movement of the respective client device, identifying a point of interest at the location associated with the geolocation, wherein each point of interest represents a different access point configured for a user to transition between typed of movement in the facility (See 2106.04(a)(2)(III)(A) – Mental Processes, Claims do recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions. Examples of claims that recite mental processes include a claim to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016);
receiving item information associated with a new item associated with the online system, the item information describing a location associated with the new item (See MPEP 2106.04(a)(2)(II)(C) – organizing human activity, The sub-grouping “managing personal behavior or relationships or interactions between people” include social activities, teaching, and following rules or instructions. Other examples of following rules or instructions recited in a claim include: i. assigning hair designs to balance head shape, In re Brown, 645 Fed. Appx. 1014, 1015-16 (Fed. Cir. 2016) (non-precedential); and ii. a series of instructions of how to hedge risk, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010).);
identifying, from the plurality of data points, one or more pairs of data points associated with the location, wherein each pair of data points is associated with an item and includes a first data point from the first set of data points and a second data point from the second set of data points (See MPEP 2106.04(a)(2)(II)(C) – organizing human activity, The sub-grouping “managing personal behavior or relationships or interactions between people” include social activities, teaching, and following rules or instructions. Other examples of following rules or instructions recited in a claim include: i. assigning hair designs to balance head shape, In re Brown, 645 Fed. Appx. 1014, 1015-16 (Fed. Cir. 2016) (non-precedential); and ii. a series of instructions of how to hedge risk, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010); see also Sanderling Management v. Snap Inc., App. No. 2021-2173, page 7 (Fed. Cir. Apr. 12, 2023)(“ As the district court articulated, in a formulation we agree with, the claims are directed to the abstract idea “‘of providing information – in this case, a processing function – based on meeting a condition,’ e.g., matching a GPS location indication with a geographic location.” Appx11. Even though the information being distributed is of a particular variety – here, digital imaging processing based on a distribution rule that determines when a condition is met – distribution of information is an abstract idea. See Intell. Ventures I LLC v. Cap. One Bank, 792 F.3d 1363, 1369 (Fed. Cir. 2015) (“Providing this minimal tailoring – e.g., providing different newspaper inserts based on the location of the individual – is an abstract idea.”).”);
determining a difference between a pair of times associated with each pair of data points (See MPEP 2106.04(a)(2)(I) – mathematical concepts, 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));
identifying a navigation path comprising a sequence of points of interest for accessing the new item based at least in part on the point of interest associated with the location and the difference between the pair of times associated with each pair of data points (See MPEP 2106.04(a)(2)(II)(C) – organizing human activity, The sub-grouping “managing personal behavior or relationships or interactions between people” include social activities, teaching, and following rules or instructions. Other examples of following rules or instructions recited in a claim include: i. assigning hair designs to balance head shape, In re Brown, 645 Fed. Appx. 1014, 1015-16 (Fed. Cir. 2016) (non-precedential); and ii. a series of instructions of how to hedge risk, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010).); and
sending, to a client device associated with a accessing the new item, the geolocation associated with the location and the navigation path for accessing the new item (See MPEP 2106.04(a)(2)(II)(C) – organizing human activity, The sub-grouping “managing personal behavior or relationships or interactions between people” include social activities, teaching, and following rules or instructions. Other examples of following rules or instructions recited in a claim include: i. assigning hair designs to balance head shape, In re Brown, 645 Fed. Appx. 1014, 1015-16 (Fed. Cir. 2016) (non-precedential); and ii. a series of instructions of how to hedge risk, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010).).
Claim 1 (and similarly Claims 11 and 20) is directed to a series of steps for identifying and sending a navigation path to a picker, which manages personal behavior and thus a method of organizing human activity and determined using mental processes calculated by mathematical concepts. The mere nominal recitation of an input device, controller, transmitter, and display does not take the claim out of the mathematical concepts, method of organizing human interactions, nor mental processes. Thus, Claim 1 (and similarly Claims 11 and 20) recites an abstract idea.
Step 2A – Prong 2
Limitations that are indicative of integration into a practical application:
Improvements to the functioning of a computer, or to any other technology or technical field - see MPEP 2106.05(a)
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition – see Vanda Memo
Applying the judicial exception with, or by use of, a particular machine - see MPEP 2106.05(b)
Effecting a transformation or reduction of a particular article to a different state or thing - see MPEP 2106.05(c)
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception - see MPEP 2106.05(e) and Vanda Memo
Limitations that are not indicative of integration into a practical application:
Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f)
Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g)
Generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h)
The identified abstract idea of exemplary Claim 1 (and similarly Claims 11 and 20) is not integrated into a practical application. The additional elements are: a processor, computer-readable medium, picker client device, and an online concierge system that implements the underlying abstract idea. These additional elements are broadly recited computer elements that do not add a meaningful limitation to the abstract idea because they amount to merely using a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application. Claim 1 (and similarly Claims 11 and 20) is directed to an abstract idea.
Step 2B
Claim 1 (and similarly Claims 11 and 20) does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and in combination, receiving a plurality of data points from a plurality of client devices associated with an online system; executing a clustering process by generating one or more clusters associated with each location and identifying a cluster associated with each location; determining a geolocation associated with each location included in the identified cluster; identifying points of interest; receiving item information associated with a new item placed with the online system; identifying pairs of data points associated with the location; determining a difference between a pair of times; identifying a navigation path; and sending the geolocation associated with the location and the navigation path for accessing the new item to a client device associated with accessing the new item , do not add significantly more to the exception because they amount to merely using a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). Claim 1 (and similarly Claims 11 and 20) is ineligible.
Claim 2 (and similarly Claim 12) recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim 3 (and similarly Claim 13) recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim 4 (and similarly Claim 14) recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim 5 (and similarly Claim 15) recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim 6 (and similarly Claim 18) recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim 7 (and similarly Claim 17) recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim 8 (and similarly Claim 18) recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim 9 (and similarly Claim19) recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim 10 recites the abstract idea of organizing human activity. See MPEP 2106.04(a)(2)(II).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over US Pat Pub 2024/0144354 “Glaser” in view of US Pat Pub 2024/0119411 “Francis”, also in view of US Pat Pub 2011/0087431 “Gupta”.
As per Claims 1, 11, and 20, Glaser discloses a method, computer program product, and computer system comprising, at a computer system comprising a processor and a computer-readable medium:
receiving, from a plurality of client devices associated with an online system, a plurality of data points comprising a first set of data points and a second set of data points, wherein:
the first set of data points is associated with arriving outside of one or more locations of a plurality of locations (Glaser: [0212] using real-time conditions and/or historical tracking so that calculation can be dynamic and reactive to store and/or conditions (e.g., the agent, how crowded store is, current placement options of products, physical locations of items, etc.). This implementation may include generating a graph with node-link mappings that can be based on physical location data, historical CV measured traversal speeds between nodes, detected or predicted congestion levels (used to augment link scores), detected performance of an agent (speed, instruction following performance, crowd navigation, etc.), and/or other detected aspects as shown in FIG. 5 and FIG. 6.);
the second set of data points is associated with picking up items from one or more locations of the plurality of locations and delivering items to one or more locations of the plurality of locations (Glaser: [0212] using real-time conditions and/or historical tracking so that calculation can be dynamic and reactive to store and/or conditions (e.g., the agent, how crowded store is, current placement options of products, physical locations of items, etc.). This implementation may include generating a graph with node-link mappings that can be based on physical location data, historical CV measured traversal speeds between nodes, detected or predicted congestion levels (used to augment link scores), detected performance of an agent (speed, instruction following performance, crowd navigation, etc.), and/or other detected aspects as shown in FIG. 5 and FIG. 6.); and
executing a clustering process on one or more of the first set of data points and the second set of data points (Glaser: [0464] In another variation, the method involves outputting a likely location or locations for a queried product identifier. In this variation, a product identifier is received as part of a data query. In response, location markers associated with the product identifier are accessed, and the clustering of the location markers is analyzed to determine predicted locations. These clusters can be scored using confidence scores, time weighting, and other aspects like the number of location markers to determine confidence of a product being located at a storage location.), the clustering process comprising:
generating, from the one or more of the first set of data points and the second set of data points, one or more clusters associated with each location of the plurality of locations (Glaser: [0464] In another variation, the method involves outputting a likely location or locations for a queried product identifier. In this variation, a product identifier is received as part of a data query. In response, location markers associated with the product identifier are accessed, and the clustering of the location markers is analyzed to determine predicted locations. These clusters can be scored using confidence scores, time weighting, and other aspects like the number of location markers to determine confidence of a product being located at a storage location.), and
identifying a cluster associated with each location of the plurality of locations based at least in part on the one or more of the first set of data points and the second set of data points included in each cluster of the one or more clusters (Glaser: [0464] In another variation, the method involves outputting a likely location or locations for a queried product identifier. In this variation, a product identifier is received as part of a data query. In response, location markers associated with the product identifier are accessed, and the clustering of the location markers is analyzed to determine predicted locations. These clusters can be scored using confidence scores, time weighting, and other aspects like the number of location markers to determine confidence of a product being located at a storage location.);
determining a location of the plurality of locations based at least in part on the one or more of the first set of data points and the second set of data points included in the identified cluster (Glaser: [0464] In another variation, the method involves outputting a likely location or locations for a queried product identifier. In this variation, a product identifier is received as part of a data query. In response, location markers associated with the product identifier are accessed, and the clustering of the location markers is analyzed to determine predicted locations. These clusters can be scored using confidence scores, time weighting, and other aspects like the number of location markers to determine confidence of a product being located at a storage location.);
identifying one or more points of interest associated with each location of the plurality of locations based at least in part on one or more rules applied to the plurality of data points (Glaser: [0206] As shown in FIG. 4, a method for reactive route planning using a sensor-derived planogram can include generating, using a CV monitoring system, a product location map P110; mapping agent path directions for a set of waypoints within the environment based on the product location map P120; and updating a navigation system of an agent with the agent path directions P130. This method can function to generate a recommended path (e.g., path guidance) for the agent.);
receiving item information associated with a new item associated with the online system, the item information describing a location associated with the new item (Glaser: [0133] the system may include an order interface 1500. The order interface 1500 functions to provide a digital interface for collection and management of order data. In one preferred variation, the order interface 1500 uses an online ordering system that collects online orders from customer client devices. and [;0138] The agent management system 1500 functions to be a computing system configured for using the product location map in connection with order data and agent data for calculating enhanced order fulfillment instructions, communicating instructions, and/or managing digital interactions related to fulfillment and updating instructions.);
identifying, from the plurality of data points, one or more pairs of data points associated with the location, wherein each pair of data points is associated with an item and includes a first data point from the first set of data points and a second data point from the second set of data points (Glaser: [0249] In one variation the waypoint graph is a graph data structure with node-link mappings where the waypoints are represented as nodes and links are representations of travel scores. A travel score may be a measure of estimated travel time, travel distance, or other metrics. In some instances, the travel score may be a score that weighs multiple factors such as time, distance, complexity, risk of changing conditions, cart or robotic agent navigation challenges, and the like. Performing the graph traversal process can include performing a traveling salesperson process minimizing travel cost for navigating the waypoints.);
determining a difference between a pair of times associated with each pair of data points (Glaser: [0249] In one variation the waypoint graph is a graph data structure with node-link mappings where the waypoints are represented as nodes and links are representations of travel scores. A travel score may be a measure of estimated travel time, travel distance, or other metrics. In some instances, the travel score may be a score that weighs multiple factors such as time, distance, complexity, risk of changing conditions, cart or robotic agent navigation challenges, and the like. Performing the graph traversal process can include performing a traveling salesperson process minimizing travel cost for navigating the waypoints. );
identifying a navigation path comprising a sequence of points of interest for accessing the new item based at least in part on the point of interest associated with the location and the difference between the pair of times associated with each pair of data points (Glaser: [0250] Determining a waypoint graph for the set of waypoints based on the product location map can include generating a graph with node-link mappings based on physical location data of the waypoints (e.g., locations of the products), historical computer vision measured traversal speeds of an agent between nodes, detected or predicted congestion levels (used to augment link scores), detected performance of a particular agent (speed, instruction following performance, crowd navigation, etc.), and/or other aspects.); and
sending, to a client device associated with a accessing the new order, the geolocation associated with the location and the navigation path for accessing the new item (Glaser: [0139] The Picker interface functions as an agent client with a user interface updated in coordination with instructions from the agent management system. The picker interface is a user interface of one or more mediums used in communicating requests, instructions, status, and/or other data related to order fulfillment.).
Glaser fails to disclose a method, computer program product, and computer system comprising, at a computer system comprising a processor and a computer-readable medium:
each data point includes a set of motion data captured by sensors of the respective client device that the data point was received from;
determining a geolocation associated with each location of the plurality of locations based at least in part on the one or more of the first set of data points and the second set of data points, wherein the geolocation is associated with a facility and the cluster of the associated location;
detecting, for at least one determined geolocation, whether each of set of motion data associated with the data points of the cluster of the geolocation is indicative of a type of movement of the respective client device, wherein the first type of movement is associated with vertical motion;
in response to detecting that each of set of motion data associated with the data points of the cluster of the geolocation is indicative of the type of movement of the respective picker client device, identifying a point of interest at the location associated with the geolocation, wherein each point of interest represents a different access point configured for a user to transition between typed of movement in the facility.
Francis teaches a method, computer program product, and computer system comprising, at a computer system comprising a processor and a computer-readable medium:
determining a geolocation associated with each location of the plurality of locations based at least in part on the one or more of the first set of data points and the second set of data points, wherein the geolocation is associated with a facility and the cluster of the associated location (Francis: [0547]: locations of the MSDs and items may be defined in terms of geolocation values (e.g., latitude/longitude values using GPS). For example, the items may be mapped according to GPS geolocations as described above. In a specific example, each item may be associated with a geolocation value and/or range of geolocation values (e.g., latitude/longitude values), such as a geolocation value and/or range of values associated with an MSD when scanning the item in the past.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Glaser to include geolocation order attribute details as taught by Francis, with identifying the navigation path as taught by Glaser with the motivation of improving efficiency of the order filling operations (e.g., picking and/or packing efficiency) (Francis: [0082]).
Glaser and Francis fail to disclose a method, computer program product, and computer system comprising, at a computer system comprising a processor and a computer-readable medium:
each data point includes a set of motion data captured by sensors of the respective client device that the data point was received from;
detecting, for at least one determined geolocation, whether each of set of motion data associated with the data points of the cluster of the geolocation is indicative of a type of movement of the respective client device, wherein a first type of movement is associated with vertical motion;
in response to detecting that each of set of motion data associated with the data points of the cluster of the geolocation is indicative of the type of movement of the respective client device, identifying a point of interest at the location associated with the geolocation, wherein each point of interest represents a different access point configured for a user to transition between types of movement in the facility.
Gupta teaches a method, computer program product, and computer system comprising, at a computer system comprising a processor and a computer-readable medium:
each data point includes a set of motion data captured by sensors of the respective client device that the data point was received from (Gupta: [0100] In some implementations, a mobile device may transmit sensor measurements in addition to location estimates to a server. A server may utilize such sensor measurements to determine whether a mobile device was in motion when a location estimate was determined.);
detecting, for at least one determined geolocation, whether each of set of motion data associated with the data points of the cluster of the geolocation is indicative of a type of movement of the respective client device (Gupta: [0101] In some implementations, a server may request that location estimates only be transmitted to the server if sensor readings for a mobile device indicate that the mobile device was in motion when the location estimates were determined.), wherein a first type of movement is associated with vertical motion (Gupta: [0038] movement of a user between a first location estimate and a second location estimate may be identified and a direction of the movement may be determined with respect to a Cartesian coordinate system. If an individual vector is determined, the individual vector may be associated with one or more points on a Cartesian coordinate system. It is well known that the Cartesian Coordinate system is 3 dimensional (x axis, y axis, and z axis));
in response to detecting that each of set of motion data associated with the data points of the cluster of the geolocation is indicative of the type of movement of the respective picker client device, identifying a point of interest at the location associated with the geolocation, wherein each point of interest represents a different access point configured for a user to transition between types of movement in the facility (Gupta: [0025] An "electronic map," as used herein may refer to an electronic representation of a map depicting an area. For example, an electronic map may depict locations of one or more offices, rooms, or other structural elements and/or pathways within an area such as a structure or an outdoor area. In one particular implementation, an electronic map may depict locations of structural elements on one or more floors of a building. An electronic map may be presented to a user on a display device, such as a display screen of a mobile device. An electronic map may include or be associated with a grid, such as a Cartesian grid showing coordinates, such as x, y coordinates in a 2-dimensional place. It is understood that other embodiments may utilize non-Cartesian maps or multiple dimensions. A processing device, such as a processor of a map server, for example, may analyze and/or manipulate an electronic map to infer locations of certain map features, such as locations of point of interest and/or corridors between such points of interest, as discussed below. and [0026] . A "corridor," as used herein, may refer to a pathway along which a user may travel to or from a point of interest. A corridor may comprise a hallway along which one or more offices, meeting rooms, stores, bathrooms, or other points of interest are accessible. A corridor may comprise a pathway along one or more floors of a structure such as an office building, for example.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Glaser and Francis to include identifying points of interest as taught by Gupta, with identifying the navigation path as taught by Glaser and Francis with the motivation of determining navigation directions within an indoor environment for which a corresponding map or grid indicating locations of structural elements is not available (Gupta: [0006]).
As per Claims 2 and 12, Glaser discloses a method and computer program product, wherein the movement data of each data point of the plurality of data points comprises one or more selected from the group consisting of information describing an action performed by a picker, a longitude, a latitude, an elevation, a speed, and a time (Glaser: [0082]).
As per Claims 3 and 13, Glaser discloses a method and computer program product, wherein the plurality of data points are received from the plurality of client devices based on one or more selected from the group consisting of: a periodic interval, a signal detected by a sensor of a picker client device, and a manual entry of data into a picker client device (Glaser: [0082]).
As per Claims 4 and 14, Glaser fails to disclose, but Francis teaches a method and computer program product, wherein the one or more points of interest associated with each location of the plurality of locations comprise one or more access points selected from the group consisting of: a parking spot, an entrance, an exit, an elevator, a staircase, a security desk, and a congestion area (Francis: [0762]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Glaser to include order attribute details as taught by Francis, with identifying the navigation path as taught by Glaser with the motivation of improving efficiency of the order filling operations (e.g., picking and/or packing efficiency) (Francis: [0082]).
As per Claims 5 and 15, Glaser discloses a method and computer program product, wherein identifying the navigation path comprising the sequence of points of interest for accessing the new item comprises:
inserting a point of interest in the navigation path if the point of interest is associated with a minimum of one or more of: the difference between the pair of times associated with each pair of data points and a number of steps included in the navigation path (Glaser: [0206]).
As per Claims 6 and 16, Glaser fails to disclose, but Francis teaches a method and computer program product, wherein detecting, for at least one determined geolocation, whether each of set of movement data associated with the data points of the cluster of the geolocation is indicative of the type of movement of the respective client device comprises applying one or more rules to data points of the cluster and the one or more rules are selected from the group consisting of: identifying a point of interest corresponding to a parking spot when a client device loses connection with a vehicle, identifying a point of interest corresponding to an entrance of a building when a client device enters a geofence associated with the building, identifying a point of interest corresponding to an exit of the building when a client device exits the geofence associated with the building, identifying a point of interest corresponding to an elevator when a picker client device changes elevation at a speed that is at least a threshold speed, identifying a point of interest corresponding to a staircase when a client device changes elevation at a speed that is less than a threshold speed, identifying a point of interest corresponding to a security desk when a client device stops moving within a building and subsequently moves to a delivery location, and identifying a point of interest corresponding to a congestion area when a client device moves less than a threshold speed (Francis: [0762]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Glaser to include order attribute details as taught by Francis, with identifying the navigation path as taught by Glaser with the motivation of improving efficiency of the order filling operations (e.g., picking and/or packing efficiency) (Francis: [0082]).
As per Claims 7 and 17, Glaser discloses a method and computer program product, further comprising:
determining an association among a set of locations based at least in part on an address associated with each location of the set of locations (Glaser: [0212]);
identifying a point of interest associated with a location included among the set of locations (Glaser: [0212]); and
associating the point of interest with each location of the set of locations (Glaser: [0212]).
As per Claims 8 and 18, Glaser fails to disclose, but Francis teaches a method and computer program product, wherein determining the geolocation associated with each location of the plurality of locations comprises:
identifying a latitude and a longitude associated with each data point of the one or more of the first set of data points and the second set of data points included in the identified cluster (Francis: [0547]); and
determining the geolocation associated with each location of the plurality of locations based at least in part on an average latitude and an average longitude associated with the one or more of the first set of data points and the second set of data points included in the identified cluster (Francis: [0547]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Glaser to include order attribute details as taught by Francis, with identifying the navigation path as taught by Glaser with the motivation of improving efficiency of the order filling operations (e.g., picking and/or packing efficiency) (Francis: [0082]).
As per Claims 9 and 19, Glaser fails to disclose, but Francis teaches a method and computer program product, wherein identifying the navigation path comprising the sequence of points of interest for accessing the new item is further based at least in part on a set of attributes associated with one or more of the new item, wherein the set of attributes comprises one or more selected from the group consisting of: a weight associated with the new item, a number of items included in the new item, a volume associated with the new item, a physical limitation associated with a user of the client device, an age of the user, and a preference associated with the user (Francis: [0733]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Glaser to include order attribute details as taught by Francis, with identifying the navigation path as taught by Glaser with the motivation of improving efficiency of the order filling operations (e.g., picking and/or packing efficiency) (Francis: [0082]).
As per Claim 10, Glaser fails to disclose but Francis teaches a method, further comprising:
eliminating one or more data points from the plurality of data points, wherein each data point of the one or more data points is associated with a speed that is at least a threshold speed (Francis: [0585]); and
eliminating one or more additional data points from the plurality of data points based at least in part on a Union-Find algorithm and a Haversine distance between a pair of data points (Francis: [0585]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Glaser to include order attribute details as taught by Francis, with identifying the navigation path as taught by Glaser with the motivation of improving efficiency of the order filling operations (e.g., picking and/or packing efficiency) (Francis: [0082]).
Response to Arguments
Applicant's arguments filed October 21, 2025 have been fully considered but they are not persuasive.
35 USC 101
Applicant argues that the claim
recites a technical improvement in the identification process by using motion data associated with picker client devices to infer the locations of access points. Specifically, the claim recites detecting that motion data associated with clusters of geolocation points is "indicative of the type of movement" of picker client devices and using this determination to automatically identify points of interest at those geolocations. This improves the accuracy and adaptiveness of facility mapping by leveraging empirical motion data signals (e.g., trajectories, movement speeds, dwell patterns) rather than static metadata and constitutes a technological improvement in spatial inference and location identification that allows the system to more precisely identify points of interest without manual calibration or human input.
In transforming raw sensor-based motion data into structured spatial relationships, claim 1 describes performance of a specific series of data transformations tied to sensor motion signals that yield a new and useful result: automated, data-driven identification of points of interest representing distinct access points.
Accordingly, claim 1 goes beyond a mere abstract idea and instead recites a technical improvement that enhances the accuracy and efficiency of computer-based geolocation identification, thereby satisfying Step 2B under MPEP §2106.05(a).
The limitations referenced in the claims do not actually include the detection element of the motion data. Instead they disclose “detecting, for at least one determined geolocation, whether each of set of motion data associated with the data points of the cluster of the geolocation is indicative of a type of movement of the respective client device, wherein a first type of movement is associated with vertical movement.” As the limitation is written, it is merely directed to analyzing collected data, NOT the process of collecting the data. The Applicant’s Specification does include details about collecting the sensor information for performing the detection in [0044] for example. Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Amending the claims to include details collecting or sensing the motion data could help to make the claims eligible under 35 USC 101. MPEP 2106.05(a)(II) provides examples that the courts have indicated may be sufficient to show an improvement in existing technology, including: “Particular configuration of inertial sensors and a particular method of using the raw data from the sensors, Thales Visionix, Inc. v. United States, 850 F.3d 1343, 1348-49, 121 USPQ2d 1898, 1902 (Fed. Cir. 2017).” This case might provide further idea and/or guidance for ways to amend the claims to be considered eligible.
35 USC 103
Applicant argues that the cited portion of Gupta merely describes determining whether or not a mobile device is in motion, which is different from claim 1’s “types” of movement that motion data may be associated with, including “ a first type of movement is associated with vertical motion.” However, Gupta teaches in [0099] “a mobile device may include certain motion sensors to detect motion of the mobile device… examples of zero motion sensors used by a mobile device may include an accelerator, gyroscope, magnetometer, and/or a gravitometer. An accelerometer may detect acceleration of a mobile device and a gyroscope may detect a change in an orientation of the mobile device, for example. A magnetometer may measure a strength and/or direction of a magnetic field in the vicinity of the magnetometer, and a gravitometer may measure a local gravitational field of the Earth as observed by the gravitometer, for example. In some implementations, for example, images from a video camera on a mobile device may be processed to detect motion of the mobile device.” Gupta does teach in [0038] “movement of a user between a first location estimate and a second location estimate may be identified and a direction of the movement may be determined with respect to a Cartesian coordinate system. If an individual vector is determined, the individual vector may be associated with one or more points on a Cartesian coordinate system,” and in [0039] “first location estimate 10 and second location estimate 15 may be associated with horizontal and vertical coordinates within a 2-dimensional space, such as x,y coordinates. If magnitude and direction of individual vector 5 have been determined, a location of individual vector 5 with respect to a Cartesian coordinate system may subsequently be determined In one particular implementation, an individual vector 5 may be represented by a point located at a midpoint of line segment 20, together with an indication of its magnitude and direction.” As such, Gupta does teach the limitation of “a first type of movement is associated with vertical direction.”
Conclusion
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/REVA R MOORE/Examiner, Art Unit 3627
/FAHD A OBEID/Supervisory Patent Examiner, Art Unit 3627