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 .
DETAILED ACTION
Status of the Application
The following is a Final Office Action.
In response to Examiner's communication of 4/20/2026, Applicant responded on 7/20/2026. Amended claim 1, 8, 15.
Claims 1-20 are pending in this application and have been examined.
Response to Amendment
Applicant's amendments to claims 1, 8, 15 are not sufficient to overcome the 35 USC 101 rejections set forth in the previous action.
Applicant's amendments to claims 1, 8, 15 are not sufficient to overcome the prior art rejections set forth in the previous action.
Response to Arguments – 35 USC § 101
Applicant’s arguments with respect to the rejections have been fully considered, but they are not persuasive.
Applicant submits, “…Applicants respectfully submit that these characterizations are internally inconsistent with the very claim language they purport to describe and are not tethered to what Claim I actually recites…The recited real-time monitoring via devices and the real-time transmission of tasks to a mobile device are, by their express terms, incapable of being performed in the human mind or with pen and paper... the Examiner's own analysis is logically inconsistent. The Examiner concedes that Claim I recites "one or more devices" and a "mobile device" as additional elements (April 20, 2026, Office Action, page 4), yet simultaneously alleges that the identical limitations reciting these devices "can include a human using their mind and using pen and paper" (April 20, 2026, Office Action, page 3). A limitation cannot be both a device-based operation and a purely mental step performed with pen and paper. The presence of the real-time device-based monitoring and mobile-device transmission removes Claim I from both the "mental process" and "certain methods of organizing human activities" groupings, because these operations are neither practically performable in the human mind nor reducible to interpersonal interactions…Viewed as a whole, Claim I is directed to a specific technical system that, among other things, detects errors during real-time execution monitoring and transmits corrective tasks to a mobile device in real time - a concrete implementation, not an abstract idea. As Applicants' specification describes, among other things, the system may detect an error in real time and transmit in real time one or more tasks to a mobile device of the user to account for the error (see for example, paragraphs [0006], [0029] and [0070] of Applicants' specification)…Claim I addresses this technical problem by, among other things, "monitor[ing], in real time, execution of the one or more generated tasks via one or more devices associated with the retailer," "detect[ing] at least one error in the execution of the one or more generated tasks," and "transmit/ting], in real time, one or more tasks to a mobile device to account for the at least one error."…These limitations are not merely applying an abstract idea using generic computer components. Rather, they reflect a specific, ordered process in which real-time monitoring of task execution via devices enables real-time error detection, which in turn triggers real-time transmission of corrective tasks to a mobile device. This closed-loop, real-time technical mechanism achieves, among other things, a concrete, real-world result - the efficient and nondisruptive execution of planogram changes - that improves upon the deficiencies of prior retail systems described in the specification (see for example, paragraphs [0003], [0007] and [0070] of Applicants' specification). The claims therefore reflect a specific technical improvement to the field of planogram execution and are integrated into a practical application…The Examiner’s dismissal of the “identifying…” and “…transmitting…” limitations as mere "extra-solution activity, pre and post solution activity - i.e. data gathering. .. data output" (April 20, 2026, Office Action, page 5) is misplaced. Applicants respectfully note that the "transmit, in real time, one or more tasks to a mobile device to account for the at least one error" limitation is not post-solution "data output"; it is an integral step of the claimed closed-loop mechanism that acts upon the detected error to enable corrective execution. The transmission is the very mechanism by which the claimed system, among other things, achieves its improved result, not incidental output appended to an abstract idea….Applicants respectfully note that the cited paragraphs describe computing hardware but do not establish that the specific ordered combination recited in Claim 1 of, among other things, real-time monitoring of task execution via devices, real-time detection of at least one error in that execution, and real time transmission of corrective tasks to a mobile device - was well-understood, routine, and conventional…Viewed as an ordered combination, the claim elements of Claim 1 provide an unconventional arrangement that achieves an improvement going beyond routine and conventional use. The Examiner has not identified any disclosure - in Applicants' specification or otherwise - establishing that the recited real-time, closed-loop error-detection-and-correction mechanism was conventional. Reciting hardware in the specification does not establish that the specific combination of real-time monitoring, error detection, and corrective transmission recited in Claim 1 was routine….” The Examiner respectfully disagrees.
While Applicant’s amendments further prosecution, by Applicant’s own admission, the claims and the argued elements, as a whole, indeed recite and direct to, …detects errors during real-time execution monitoring and transmits corrective tasks…monitor[ing], in real time, execution of the one or more generated tasks associated with the retailer," "detect[ing] at least one error in the execution of the one or more generated tasks," and "transmit/ting], in real time, one or more tasks to account for the at least one error… [0003] In retail planning and execution (i.e. organizing human activities, fundamental economic practice, commercial interactions), planograms are generated for sections of retail stores (i.e. organizing) periodically, such as seasonally, and thereafter executed by team members (i.e. human) by moving, replacing, removing or adding items to shelves (i.e. activities) of the retail stores. However, in some situations a planogram may be updated between generation periods, such as a new planogram being generated in-season, for a variety of reasons, such as in response to unexpectedly high or low sales of certain items or to promote sales of other items (i.e. organizing human activities, fundamental economic practice, commercial interactions). Using existing retail systems, when a planogram is updated between set generation periods, such as in-season, retail stores typically struggle to implement the updated planogram. For example, in-season planogram changes or updates may be difficult for team members (i.e. human) to understand (i.e. mental process), it may be a complex problem to determine how to implement a planogram change and any changes that are implemented may be performed ad-hoc and in an inefficient manner that disrupts the operation of the retail store (i.e. organizing human activities, fundamental economic practice, commercial interactions). For these reasons and more, existing retail systems implement planogram changes lack an ability to efficiently and competently implement updates or changes to existing planograms and may disrupt retail operations when implementing planogram changes, all of which is undesirable (i.e. organizing human activities, fundamental economic practice, commercial interactions)…[0007] Embodiments provide ensembled techniques that combine multiple algorithms to generate tasks, determine tasks priority and dynamically sequence tasks to be performed to implement planogram changes (i.e. mental process to organize human activities). Use of embodiments may increase accuracy of planogram task execution (i.e. mental process to organize human activities). Embodiments provide tools to view, analyze and execute planogram tasks at several different scopes (i.e. mental process to organize human activities). Use of embodiment may reduce time spent on analyzing or identifying planogram tasks as well as the time spent taking correct measure during execution of such tasks (i.e. mental process to organize human activities). Use of embodiment provide effective and efficient handling of planogram tasking by providing enhanced planogram task understanding as well as provide shortest paths possible perform planogram tasks (i.e. mental process to organize human activities). Use of embodiments may enable improved compliance with planograms at both a retail level and a supply chain or supply chain network level (i.e. organizing human activities, fundamental economic practice, commercial interactions)…., which is a problem directed to organizing human activity (i.e. human accounting for errors in task executed by human retail workers and correcting human retail workers with corrected task lists when errors are detected, i.e. fundamental economic practice, commercial interactions) and a mental process (i.e. human observing human retail workers, human accounting for errors in task executed by human retail workers and correcting human retail workers with corrected task lists when errors are detected), as established in Step 2A Prong 1. This problem does not specifically arise in the realm of computer technology, but rather, this problem existed and was addressed long before the advent of computers. Thus, the claims do not recite a technical improvement to a technical problem or necessarily roots in computing technologies. Additionally, pursuant to the broadest reasonable interpretation, as an ordered combination as a whole, each of the additional elements are computing elements recited at high level of generality implementing the abstract idea, and thus, are no more than applying the abstract idea with generic computer components, i.e. computer, mobile device. Further, as an ordered combination as a whole, these additional elements generally link the abstract idea to a technical environment, namely the environment of a computer, mobile device, performing extra solution activities. Therefore, as an ordered combination as a whole, the additional elements do not integrate the abstract ideas into a practical application in Step 2A Prong 2 (apply it and general link) or amount to significantly more in Step 2B (apply it and wurc).
Even novel and newly discovered judicial exceptions are still exceptions, despite their novelty. July 2015 Update, p. 3; see SAP America Inc. v. Investpic, LLC, No. 2017-2081, slip op. at 2 (Fed Cir. May 15, 2018).
Simply reciting specific limitations that narrow the abstract idea does not make an abstract idea non-abstract. 79 Fed. Reg. 74631; buySAFE Inc. v. Google, Inc., 765 F.3d 1350, 1355 (2014); see SAP America at p. 12. As discussed in SAP America, no matter how much of an advance the claims recite, when “the advance lies entirely in the realm of abstract ideas, with no plausibly alleged innovation in the non-abstract application realm,” “[a]n advance of that nature is ineligible for patenting.” Id. at p. 3.
As stated in the MPEP, "an improvement in the abstract idea itself ... is not an improvement in technology." MPEP 2106.05(a). Mere automation of a manual process or a business method being applied on a general purpose computer is not sufficient to show an improvement in computers or other technology, and the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology. MPEP 2106.05(a). Thus, Applicant’s claims do not recite an improvement in technology or integrate into a practical application, but rather mental processes and certain methods of organizing human activities implemented using or applying generic computer components.
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. See, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674 (noting that the claimed “conversion of [binary-coded decimal] numerals to pure binary numerals can be done mentally,” i.e., “as a person would do it by head and hand.”); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1139, 120 USPQ2d 1473, 1474 (Fed. Cir. 2016) (holding that claims to a mental process of “translating a functional description of a logic circuit into a hardware component description of the logic circuit” are directed to an abstract idea, because the claims “read on an individual performing the claimed steps mentally or with pencil and paper”).
Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, “[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind.” Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer").
Claims can recite a mental process even if they are claimed as being performed on a computer. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures “can be carried out in existing computers long in use, no new machinery being necessary.” 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of “anonymous loan shopping” recited in a computer system claim is an abstract idea because it could be “performed by humans without a computer”).
Performing a mental process on a generic computer. An example of a case identifying a mental process performed on a generic computer as an abstract idea is Voter Verified, Inc. v. Election Systems & Software, LLC, 887 F.3d 1376, 1385, 126 USPQ2d 1498, 1504 (Fed. Cir. 2018). In this case, the Federal Circuit relied upon the specification in explaining that the claimed steps of voting, verifying the vote, and submitting the vote for tabulation are “human cognitive actions” that humans have performed for hundreds of years. The claims therefore recited an abstract idea, despite the fact that the claimed voting steps were performed on a computer. 887 F.3d at 1385, 126 USPQ2d at 1504. Another example is Versata, in which the patentee claimed a system and method for determining a price of a product offered to a purchasing organization that was implemented using general purpose computer hardware. 793 F.3d at 1312-13, 1331, 115 USPQ2d at 1685, 1699. The Federal Circuit acknowledged that the claims were performed on a generic computer, but still described the claims as “directed to the abstract idea of determining a price, using organizational and product group hierarchies, in the same way that the claims in Alice were directed to the abstract idea of intermediated settlement, and the claims in Bilski were directed to the abstract idea of risk hedging.” 793 F.3d at 1333; 115 USPQ2d at 1700-01.
Performing a mental process in a computer environment. An example of a case identifying a mental process performed in a computer environment as an abstract idea is Symantec Corp., 838 F.3d at 1316-18, 120 USPQ2d at 1360. In this case, the Federal Circuit relied upon the specification when explaining that the claimed electronic post office, which recited limitations describing how the system would receive, screen and distribute email on a computer network, was analogous to how a person decides whether to read or dispose of a particular piece of mail and that “with the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper”. 838 F.3d at 1318, 120 USPQ2d at 1360. Another example is FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 120 USPQ2d 1293 (Fed. Cir. 2016). The patentee in FairWarning claimed a system and method of detecting fraud and/or misuse in a computer environment, in which information regarding accesses of a patient’s personal health information was analyzed according to one of several rules (i.e., related to accesses in excess of a specific volume, accesses during a pre-determined time interval, or accesses by a specific user) to determine if the activity indicates improper access. 839 F.3d. at 1092, 120 USPQ2d at 1294. The court determined that these claims were directed to a mental process of detecting misuse, and that the claimed rules here were “the same questions (though perhaps phrased with different words) that humans in analogous situations detecting fraud have asked for decades, if not centuries.” 839 F.3d. at 1094-95, 120 USPQ2d at 1296.
Using a computer as a tool to perform a mental process. An example of a case in which a computer was used as a tool to perform a mental process is Mortgage Grader, 811 F.3d. at 1324, 117 USPQ2d at 1699. The patentee in Mortgage Grader claimed a computer-implemented system for enabling borrowers to anonymously shop for loan packages offered by a plurality of lenders, comprising a database that stores loan package data from the lenders, and a computer system providing an interface and a grading module. The interface prompts a borrower to enter personal information, which the grading module uses to calculate the borrower’s credit grading, and allows the borrower to identify and compare loan packages in the database using the credit grading. 811 F.3d. at 1318, 117 USPQ2d at 1695. The Federal Circuit determined that these claims were directed to the concept of “anonymous loan shopping”, which was a concept that could be “performed by humans without a computer.” 811 F.3d. at 1324, 117 USPQ2d at 1699. Another example is Berkheimer v. HP, Inc., 881 F.3d 1360, 125 USPQ2d 1649 (Fed. Cir. 2018), in which the patentee claimed methods for parsing and evaluating data using a computer processing system. The Federal Circuit determined that these claims were directed to mental processes of parsing and comparing data, because the steps were recited at a high level of generality and merely used computers as a tool to perform the processes. 881 F.3d at 1366, 125 USPQ2d at 1652-53. See MPEP 2106.04(a)(2).
Further, the courts have indicated may not be sufficient to show an improvement in computer-functionality:
i. Generating restaurant menus with functionally claimed features, Ameranth, 842 F.3d at 1245, 120 USPQ2d at 1857;
ii. Accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer, FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016);
iii. Mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017) or speeding up a loan-application process by enabling borrowers to avoid physically going to or calling each lender and filling out a loan application, LendingTree, LLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2016) (non-precedential);
iv. Recording, transmitting, and archiving digital images by use of conventional or generic technology in a nascent but well-known environment, without any assertion that the invention reflects an inventive solution to any problem presented by combining a camera and a cellular telephone, TLI Communications, 823 F.3d at 611-12, 118 USPQ2d at 1747;
v. Affixing a barcode to a mail object in order to more reliably identify the sender and speed up mail processing, without any limitations specifying the technical details of the barcode or how it is generated or processed, Secured Mail Solutions, LLC v. Universal Wilde, Inc., 873 F.3d 905, 910-11, 124 USPQ2d 1502, 1505-06 (Fed. Cir. 2017);
vi. Instructions to display two sets of information on a computer display in a non-interfering manner, without any limitations specifying how to achieve the desired result, Interval Licensing LLC v. AOL, Inc., 896 F.3d 1335, 1344-45, 127 USPQ2d 1553, 1559-60 (Fed. Cir. 2018);
vii. Providing historical usage information to users while they are inputting data, in order to improve the quality and organization of information added to a database, because “an improvement to the information stored by a database is not equivalent to an improvement in the database’s functionality,” BSG Tech LLC v. Buyseasons, Inc., 899 F.3d 1281, 1287-88, 127 USPQ2d 1688, 1693-94 (Fed. Cir. 2018); and
viii. Arranging transactional information on a graphical user interface in a manner that assists traders in processing information more quickly, Trading Technologies v. IBG LLC, 921 F.3d 1084, 1093-94, 2019 USPQ2d 138290 (Fed. Cir. 2019).
And, the courts have indicated may not be sufficient to show an improvement to technology include:
i. A commonplace business method being applied on a general purpose computer, Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1976; Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015);
ii. Using well-known standard laboratory techniques to detect enzyme levels in a bodily sample such as blood or plasma, Cleveland Clinic Foundation v. True Health Diagnostics, LLC, 859 F.3d 1352, 1355, 1362, 123 USPQ2d 1081, 1082-83, 1088 (Fed. Cir. 2017);
iii. Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48;
iv. Delivering broadcast content to a portable electronic device such as a cellular telephone, when claimed at a high level of generality, Affinity Labs of Tex. v. Amazon.com, 838 F.3d 1266, 1270, 120 USPQ2d 1210, 1213 (Fed. Cir. 2016); Affinity Labs of Tex. v. DirecTV, LLC, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016);
v. A general method of screening emails on a generic computer, Symantec, 838 F.3d at 1315-16, 120 USPQ2d at 1358-59;
vi. An advance in the informational content of a download for streaming, Affinity Labs of Tex. v. DirecTV, LLC, 838 F.3d 1253, 1263, 120 USPQ2d 1201, 1208 (Fed. Cir. 2016); and
vii. Selecting one type of content (e.g., FM radio content) from within a range of existing broadcast content types, or selecting a particular generic function for computer hardware to perform (e.g., buffering content) from within a range of well-known, routine, conventional functions performed by the hardware, Affinity Labs of Tex. v. DirecTV, LLC, 838 F.3d 1253, 1264, 120 USPQ2d 1201, 1208 (Fed. Cir. 2016).
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 (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or 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). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
TLI Communications provides an example of a claim invoking computers and other machinery merely as a tool to perform an existing process. The court stated that the claims describe steps of recording, administration and archiving of digital images, and found them to be directed to the abstract idea of classifying and storing digital images in an organized manner. 823 F.3d at 612, 118 USPQ2d at 1747. The court then turned to the additional elements of performing these functions using a telephone unit and a server and noted that these elements were being used in their ordinary capacity (i.e., the telephone unit is used to make calls and operate as a digital camera including compressing images and transmitting those images, and the server simply receives data, extracts classification information from the received data, and stores the digital images based on the extracted information). 823 F.3d at 612-13, 118 USPQ2d at 1747-48. In other words, the claims invoked the telephone unit and server merely as tools to execute the abstract idea. Thus, the court found that the additional elements did not add significantly more to the abstract idea because they were simply applying the abstract idea on a telephone network without any recitation of details of how to carry out the abstract idea.
Other examples where the courts have found the additional elements to be mere instructions to apply an exception, because they do no more than merely invoke computers or machinery as a tool to perform an existing process include:
i. A commonplace business method or mathematical algorithm being applied on a general purpose computer, Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 573 U.S. 208, 223, 110 USPQ2d 1976, 1983 (2014); Gottschalk v. Benson, 409 U.S. 63, 64, 175 USPQ 673, 674 (1972); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015);
ii. Generating a second menu from a first menu and sending the second menu to another location as performed by generic computer components, Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1243-44, 120 USPQ2d 1844, 1855-57 (Fed. Cir. 2016);
iii. A process for monitoring audit log data that is executed on a general-purpose computer where the increased speed in the process comes solely from the capabilities of the general-purpose computer, FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016);
iv. A method of using advertising as an exchange or currency being applied or implemented on the Internet, Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 715, 112 USPQ2d 1750, 1754 (Fed. Cir. 2014);
v. Requiring the use of software to tailor information and provide it to the user on a generic computer, Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1370-71, 115 USPQ2d 1636, 1642 (Fed. Cir. 2015);
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. An example of post-solution activity is an element that is not integrated into the claim as a whole, e.g., a printer that is used to output a report of fraudulent transactions, which is recited in a claim to a computer programmed to analyze and manipulate information about credit card transactions in order to detect whether the transactions were fraudulent.
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). In Flook, the Court reasoned that “[t]he notion that post-solution activity, no matter how conventional or obvious in itself, can transform an unpatentable principle into a patentable process exalts form over substance. A competent draftsman could attach some form of post-solution activity to almost any mathematical formula”. 437 U.S. at 590; 198 USPQ at 197; Id. (holding that step of adjusting an alarm limit variable to a figure computed according to a mathematical formula was “post-solution activity”). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 79, 101 USPQ2d 1961, 1968 (2012) (additional element of measuring metabolites of a drug administered to a patient was insignificant extra-solution activity).
Below are examples of activities that the courts have found to be insignificant extra-solution activity:
Mere Data Gathering:
i. Performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989);
ii. Testing a system for a response, the response being used to determine system malfunction, In re Meyers, 688 F.2d 789, 794; 215 USPQ 193, 196-97 (CCPA 1982);
iii. Presenting offers to potential customers and gathering statistics generated based on the testing about how potential customers responded to the offers; the statistics are then used to calculate an optimized price, OIP Technologies, 788 F.3d at 1363, 115 USPQ2d at 1092-93;
iv. Obtaining information about transactions using the Internet to verify credit card transactions, CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011);
v. Consulting and updating an activity log, Ultramercial, 772 F.3d at 715, 112 USPQ2d at 1754; and
vi. Determining the level of a biomarker in blood, Mayo, 566 U.S. at 79, 101 USPQ2d at 1968. See also PerkinElmer, Inc. v. Intema Ltd., 496 Fed. App'x 65, 73, 105 USPQ2d 1960, 1966 (Fed. Cir. 2012) (assessing or measuring data derived from an ultrasound scan, to be used in a diagnosis).
Selecting a particular data source or type of data to be manipulated:
i. Limiting a database index to XML tags, Intellectual Ventures I LLC v. Erie Indem. Co., 850 F.3d at 1328-29, 121 USPQ2d at 1937;
ii. Taking food orders from only table-based customers or drive-through customers, Ameranth, 842 F.3d at 1241-43, 120 USPQ2d at 1854-55;
iii. Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016); and
iv. Requiring a request from a user to view an advertisement and restricting public access, Ultramercial, 772 F.3d at 715-16, 112 USPQ2d at 1754.
Insignificant application:
i. Cutting hair after first determining the hair style, In re Brown, 645 Fed. App'x 1014, 1016-1017 (Fed. Cir. 2016) (non-precedential); and
ii. Printing or downloading generated menus, Ameranth, 842 F.3d at 1241-42, 120 USPQ2d at 1854-55.
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network);
ii. Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) (“The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.”);
iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining “shadow accounts”); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log);
iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93;
v. Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank, 776 F.3d 1343, 1348, 113 USPQ2d 1354, 1358 (Fed. Cir. 2014) (optical character recognition); and
vi. A Web browser’s back and forward button functionality, Internet Patent Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015).
Response to Arguments – Prior Art
Applicant’s arguments with respect to the rejections have been fully considered, but they are not persuasive.
Applicant submits, “…Applicants respectfully submit that Tiwari does not teach or suggest "dynamically re-sequence, in real time and in response to the detected at least one error, the one or more generated tasks to generate an updated task sequence, and transmit the updated task sequence to the mobile device to enable continued execution of the one or more generated tasks in accordance with the updated task sequence." The Examiner relies on portions of Tiwari directed to a robotic system that adjusts its own RFID scan parameters and repeats scan routines (see, e.g., Tiwari at [0052], [0065], [0082]). Rather, Tiwari merely discusses a robotic system rescanning inventory structures with modified wireless scan parameters to improve the accuracy of collected RFID data; Tiwari does not disclose Applicants' claimed limitations…Further, Tiwari does not teach or suggest "detect at least one error in the execution of the one or more generated tasks." The Examiner cites Tiwari at [0098], [0107], [0110], [0112], and [0120] for this limitation (April 20, 2026, Office Action, pages 11-13). However, these portions of Tiwari describe detecting mis-stocked slots, incorrect products, and price discrepancies as a result of the robotic system's own scanning of inventory structures - that is, Tiwari detects the state of the store's inventory, not errors "in the execution of the one or more generated tasks." Tiwari is silent as to detecting an error in the execution of previously generated tasks…Tiwari simply does not teach or suggest the limitation "in the execution of the one or more generated tasks."…” The Examiner respectfully disagrees.
Under the broadest reasonable interpretation, Tiwari
detect at least one error in the execution of the one or more generated tasks; (in at least [0098] By then implementing this set of template images to identify products in images of the inventory structure, the computer system may more rapidly identify both products assigned to the inventory structure and RFID-tagged products mistakenly placed on the inventory structure, such as by a patron of the store. [0107] The computer system can also: implement machine vision techniques to identify slots stocked with incorrect products; identify products occupying these slots based on RFID values collected by the robotic system while navigating along the inventory structure (i.e. in the execution of the one or more generated tasks) but not contained in a list of SKUs assigned to the inventory structure by the planogram; and write a hotspot—indicating SKUs and/or other relevant data—to slots stocked with incorrect products represented in the 2D elevation image of the inventory structure. [0110] Therefore, in this implementation, the computer system can: detect price tags in an optical image of an inventory structure recorded by the robotic system; project locations of these price tags onto locations of product units calculated from corresponding RFID data collected substantially concurrently (i.e. in the execution of the one or more generated tasks) by the computer system (or vice versa); and link an optically-detected price tag to a product unit (or a cluster of product units) identified in RFID data collected by the robotic system based on physical proximity of the price tag and product unit(s). The computer system can then confirm whether a price value indicated in a price tag equals a price assigned to the corresponding product unit(s) (e.g., in the planogram or price database managed by the store) and then selectively prompt a store associated to correct the price tag if a difference is detected. For example, the computer system can transmit a location of the incorrect price tag and a correct price value for the price tag (or printable image for the correct price tag) to a mobile computing device associated with the store associate. [0112] system can generate a stocking status graph, table, or list of improperly-stocked slots throughout the store, such as including a mis-stocking mode (e.g., too many facings, too few facings, misoriented packaging, damaged packaging, outdated packaging, under quantity, over quantity, incorrect product location, etc.) for each improperly-stocked slot in this list based on stock values extracted from RFID and/or optical data collected by the robotic system, as shown in FIGS. 1, 2, 4, and 6. In this implementation, the system can serve this graph, table, or list to the manager of the store via a manager portal, such as executing on a desktop computer, a laptop computer, a tablet, or a smartphone, etc. [0114] the computer system: detects omission of a first product entirely from a first slot on a first inventory structure in the store based on failure of the robotic system to read an RFID value corresponding to this first product while scanning the first inventory structure and failure to detect a unit of the first product in an optical image of the inventory structure; retrieves a first number of units of the first product assigned to the first slot by the planogram; generates a notification specifying an identifier (e.g., a SKU) of the first product, the number of units of the first product assigned to the first slot, a location of the first slot on the first inventory structure, and a location of the first inventory structure within the store; and then transmits the notification to a mobile computing device assigned to an associate of the store substantially in Block S110. In this example, the system can transmit the notification to the associate in real-time, such as if the first product is a high-value product determined to be empty during a high-traffic period at the store (i.e. detect at least one error in the execution of the one or more generated tasks). Alternatively, the system can delay transmission of the notification to the associate until the robotic system completes a scan of the store, a full stock state of the store is determined from these scan data, and a list of restocking prompts is ordered according to values of these under- or mis-stocked products. [0120] By comparing this list of SKUs and their actual quantities to the planogram (or textual or numerical representation of the planogram), the system can also populate the digital report with indicators of slots or other inventory structures that are empty, under-stocked, over-stocked, or improperly-stocked with the incorrect product, etc. For example, the system can generate a textual list of the stock state of each slot in the store, such as ordered with empty slots followed by under-stocked slots followed by improperly-stocked slots, etc. and ordered by highest-value SKU to lowest-value SKU. Alternatively, the system can generate a 2D heat map of the stock states of slots throughout the store, such as indicating regions in which highest-value slots are empty in red, lower-value empty slots and overstocked-slots in a cooler color, and properly-stocked slots in even cooler colors.)
…
dynamically re-sequence, in real time and in response to the detected at least one error, the one or more generated tasks to generate an updated task sequence, and transmit the updated task sequence to the mobile device to enable continued execution of the one or more generated tasks in accordance with the updated task sequence. (in at least [0112] computer system generates an electronic restocking list containing a filtered list of slots at inventory structures throughout the store in need of correction, such as addition of product, exchange of product, or straightening of product. For example, the system can generate a stocking status graph, table, or list of improperly-stocked slots throughout the store, such as including a mis-stocking mode (e.g., too many facings, too few facings, misoriented packaging, damaged packaging, outdated packaging, under quantity, over quantity, incorrect product location, etc.) for each improperly-stocked slot in this list based on stock values extracted from RFID and/or optical data collected by the robotic system, as shown in FIGS. 1, 2, 4, and 6. In this implementation, the system can serve this graph, table, or list to the manager of the store via a manager portal, such as executing on a desktop computer, a laptop computer, a tablet, or a smartphone, etc. [0113] The computer system can also generate a stock correction task list to correct improperly-stocked slots. In this implementation, the system can generate a prioritized list of tasks to move misplaced products, to restock empty or improperly-stocked slots, etc. and then serve this task list to an associate (e.g., employee) of the store via a native stocking application executing on a mobile computing device (e.g., a tablet, a smartphone) carried by the associate. In this implementation, the computer system can implement methods and techniques described in U.S. patent application Ser. No. 15/347,689 to prioritize this list of tasks to correct improperly-stocked slots throughout the store. [0114] the computer system: detects omission of a first product entirely from a first slot on a first inventory structure in the store based on failure of the robotic system to read an RFID value corresponding to this first product while scanning the first inventory structure and failure to detect a unit of the first product in an optical image of the inventory structure; retrieves a first number of units of the first product assigned to the first slot by the planogram; generates a notification specifying an identifier (e.g., a SKU) of the first product, the number of units of the first product assigned to the first slot, a location of the first slot on the first inventory structure, and a location of the first inventory structure within the store; and then transmits the notification to a mobile computing device assigned to an associate of the store substantially in Block S110. In this example, the system can transmit the notification to the associate in real-time, such as if the first product is a high-value product determined to be empty during a high-traffic period at the store (i.e. detect at least one error in the execution of the one or more generated tasks, update task sequence, re-sequence). Alternatively, the system can delay transmission of the notification to the associate until the robotic system completes a scan of the store, a full stock state of the store is determined from these scan data, and a list of restocking prompts is ordered according to values of these under- or mis-stocked products.)
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 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claim 1 (similarly 8, 15) recites, “A … for detecting and executing one or more changes in a planogram, comprising: …, and configured to:
identify one or more changes in a planogram for a retailer;
generate one or more tasks based on the one or more identified changes;
determine a task priority for each of the one or more generated tasks;
monitor, in real time, execution of the one or more generated tasks via … associated with the retailer, wherein the execution is specified by the task priority for each of the one or more generated tasks;
detect at least one error in the execution of the one or more generated tasks;
transmit, in real time, one or more tasks to a … to account for the at least one error; and
dynamically re-sequence, in real time and in response to the detected at least one error, the one or more generated tasks to generate an updated task sequence, and transmit the updated task sequence to the … to enable continued execution of the one or more generated tasks in accordance with the updated task sequence.
Analyzing under Step 2A, Prong 1:
The limitations regarding, …detecting and executing one or more changes in a planogram… identify one or more changes in a planogram for a retailer; generate one or more tasks based on the one or more identified changes; determine a task priority for each of the one or more generated tasks; monitor, in real time, execution of the one or more generated tasks via … associated with the retailer, wherein the execution is specified by the task priority for each of the one or more generated tasks; detect at least one error in the execution of the one or more generated tasks; transmit, in real time, one or more tasks to a … to account for the at least one error; and dynamically re-sequence, in real time and in response to the detected at least one error, the one or more generated tasks to generate an updated task sequence, and transmit the updated task sequence to the … to enable continued execution of the one or more generated tasks in accordance with the updated task sequence.…, under the broadest reasonable interpretation, can include a human using their mind and using pen and paper to perform the above identified limitations, therefore, the claims are directed to a mental process.
Further, …detecting and executing one or more changes in a planogram… identify one or more changes in a planogram for a retailer; generate one or more tasks based on the one or more identified changes; determine a task priority for each of the one or more generated tasks; monitor, in real time, execution of the one or more generated tasks via … associated with the retailer, wherein the execution is specified by the task priority for each of the one or more generated tasks; detect at least one error in the execution of the one or more generated tasks; transmit, in real time, one or more tasks to a … to account for the at least one error; and dynamically re-sequence, in real time and in response to the detected at least one error, the one or more generated tasks to generate an updated task sequence, and transmit the updated task sequence to the … to enable continued execution of the one or more generated tasks in accordance with the updated task sequence…, are human observing changes in retail stores, human generating tasks and task priorities based on changes in retail stores, human accounting for errors in task executed by human retail workers and correcting human retail workers with corrected task lists when errors are detected, which are fundamental economic principles or practices, managing personal behavior or relationships or interactions between people, therefore the claims, are directed to certain methods of organizing human activities.
Accordingly, the claims are directed to a mental process, certain methods of organizing human activities, and thus, the claims are directed to an abstract idea under the first prong of Step 2A.
Analyzing under Step 2A, Prong 2:
This judicial exception is not integrated into a practical application under the second prong of Step 2A.
In particular, the claims recite the additional elements beyond the recited abstract idea identified under Step 2A, Prong 1, such as:
Claim 1, 8, 15: system, a computer, comprising a processor and memory, one or more devices, mobile device, computer-implemented, A non-transitory computer-readable storage medium embodied with software
Claim 5, 12, 19: one or more cameras, one or more sensors and one or more devices capable of transmitting location data
, and pursuant to the broadest reasonable interpretation, as an ordered combination, each of the additional elements are computing elements recited at high level of generality implementing the abstract idea, and thus, are no more than applying the abstract idea with generic computer components.
Further, these additional elements generally link the abstract idea to a technical environment, namely the environment of a computer.
Additionally, with respect to, “…identify…”, “…transmit…”, “…in response to the detected at least one error…”, “…transmit the updated task sequence…”, these elements do not add a meaningful limitations to integrate the abstract idea into a practical application because they are extra-solution activity, pre and post solution activity - i.e. data gathering – “…identify…”, “…in response to the detected at least one error…”, data output – “…transmit…”, “…transmit the updated task sequence…”
Analyzing under Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under Step 2B.
As noted above, the aforementioned additional elements beyond the recited abstract idea are not sufficient to amount to significantly more than the recited abstract idea because, as an order combination, the additional elements are no more than mere instructions to implement the idea using generic computer components (i.e. apply it).
Additionally, as an order combination, the additional elements append the recited abstract idea to well-understood, routine, and conventional activities in the field as individually evinced by the applicant’s own disclosure, as required by the Berkheimer Memo, in at least:
[0017] As shown in FIGURE 1, supply chain network 100 comprising planogram update system 110,archiving system 120, and planning and execution system 130 may operate on one or more computers 150 that are integral to or separate from the hardware and/or software that support planogram update system 110,archiving system 120 and planning and execution system 130. One or more computers 150 may include any suitable input device 152, such as a keypad, mouse, touch screen, microphone, or other device to input information. Output device 154 may convey information associated with the operation of supply chain network 100, including digital or analog data, visual information, or audio information. One or more computers may include fixed or removable computer-readable storage media, including a non-transitory computer- readable medium, magnetic computer disks, flash drives, CD-ROM, in-memory device, or other suitable media to receive output from and provide input to supply chain network 100.
[0018] One or more computers 150 may include one or more processors 150 and associated memory to execute instructions and manipulate information according to the operation of supply chain network 100 and any of the methods described herein. In addition, or as an alternative, embodiments contemplate executing the instructions on one or more computers 150 that cause one or more computers to perform functions of the methods. An apparatus implementing special purpose logic circuitry, for example, one or more field-programmable gatearrays (FPGA) or application-specific integrated circuits (ASIC), may perform functions of the methods described herein. Further examples may also include articles of manufacture including tangible non-transitory computer-readable media that have computer-readable instructions encoded thereon, and the instructions may comprise instructions to perform functions of the methods described herein.
[0019] In addition, or as an alternative, supply chain network 100 may comprise a cloud- based computing system having processing and storage devices at one or more locations, local to, or remote from planogram update system 110,archiving system 120 and planning and execution system 130. In addition, each of one or more computers 150 may be a workstation, personal computer (PC), network computer, notebook computer, tablet, personal digital assistant (PDA), cell phone, telephone, smartphone, wireless data port, augmented or virtual reality headset, or any other suitable computing device.
[0029] In an embodiment user interface module 216 generates and displays a user interface (UI), such as, for example, a graphical user interface (GUI), that displays planograms or any other data of planogram update system 110 in charts or graphs, or any other visual representations of data of planogram update system 110. According to embodiments, user interface module 216 displays a GUI comprising interactive graphical elements for selecting one or more planograms and/or data of any kind stored in the database of planogram update system 110, and, in response to the selection, displaying the selected data on one or more display devices. User interface module 216 may generate interfaces for planograms or planogram tasks to be performed and transmit the interfaces to devices associated with users, such as smartphones or tablets of employees within a physical retail store. The users may then use the interfaces to perform planogram tasks in a task sequence, such as in sequence determined by the task priority determined by task priority module 214. In embodiments, user interface module 216 may generate non-visual interfaces, such as voice-based personal assistants or email messages or other text-based messages, and present planogram data to customers over such voice-based or text-based interfaces.
[0062] At seventh activity 314planogram update system 110 outputs a dynamic task sequence consisting of tasks associated with a particular user and a planogram associated with the tasks. In embodiments, the dynamic task sequence may be transmitted to a device associated with an associate or employer of the retailer, such as a tablet or smartphone.
[0070] At fourth activity 440planogram update system 110 monitors execution of the tasks generated at second activity 420 in sequence of the task priority determined at third activity 430.Planogram update system 110 may monitor execution in real time via devices associated with a physical store, including cameras or other sensors installed in the physical store, as well as devices associated with users or employees, including smartphones, tablets or other devices, such as IoT devices, that can transmit location data. In embodiments, if a task is performed out of sequence, or a task that was not in the set of tasks was performed, or the user has otherwise deviated from the task sequence, planogram update system 110 may perform dynamic re- sequencing to account for the deviated sequence. Planogram update system 110 may then transmit an updated task sequence to the user. In embodiments, the planogram update system 110 may perform dynamic resequencing in real time to account for a deviated sequence and transmit in real time an updated task sequence. For example, if an error occurs by a user executing a task, the Planogram update system 110 may detect the error in real time and transmit in real time one or more tasks to a mobile device of the user to account for the error. Planogram update system 110 may monitor execution of the tasks and send new task sequences as needed, until all tasks of the task sequence have been performed.
[0071] Reference in the foregoing specification to "one embodiment", "an embodiment", or "some embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment.
[0072] While the exemplary embodiments have been illustrated and described, it will be understood that various changes and modifications to the foregoing embodiments may become apparent to those skilled in the art without departing from the spirit and scope of the present invention.
Furthermore, as an ordered combination, these elements amount to generic computer components receiving or transmitting data over a network, performing repetitive calculations, electronic record keeping, and storing and retrieving information in memory, which, as held by the courts, are well-understood, routine, and conventional. See MPEP 2106.05(d).
Moreover, the remaining elements of dependent claims do not transform the recited abstract idea into a patent eligible invention because these remaining elements merely recite further abstract limitations that provide nothing more than simply a narrowing of the abstract idea recited in the independent claims.
Looking at these limitations as an ordered combination adds nothing additional that is sufficient to amount to significantly more than the recited abstract idea because they simply provide instructions to use a generic arrangement of generic computer components to “apply” the recited abstract idea, perform insignificant extra-solution activity, and generally link the abstract idea to a technical environment. Thus, the elements of the claims, considered both individually and as an ordered combination, are not sufficient to ensure that the claim as a whole amounts to significantly more than the abstract idea itself. Since there are no limitations in these claims that transform the exception into a patent eligible application such that these claims amount to significantly more than the exception itself, claims 1-20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 102
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 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(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) 1-20 is/are rejected under 35 U.S.C. 102 as being unpatentable by US Patent Publication to US20180293543A1 to Tiwari et al., (hereinafter referred to as “Tiwari”).
As per Claim 1, Tiwari teaches: (Currently Amended) A system for detecting and executing one or more changes in a planogram, comprising: a computer, comprising a processor and memory, and configured to: ([0122])
identify one or more changes in a planogram for a retailer; (in at least [0019] execute Blocks of the method S100 to implement perpetual inventory techniques to account for changing inventory in the store by recording (near) real-time changes in product stock on shelves throughout the store, such as to account for product units that are lost, damaged, stolen, misplaced, or not shelved.) [0026] the computer system can (re)construct a planogram of shelves throughout the store based on these RFID data and product data linked to these RFID data; the system can then implement this “constructed” planogram to detect changes in stock level throughout the store over time.)
generate one or more tasks based on the one or more identified changes; (in at least [0074] The system can also: implement methods and techniques described above to approximate the 2D or 3D location of a particular RFID tag that broadcast an RF signal that was interpreted as a particular SKU in the first list of unique SKUs; access product information of this particular SKU, as described above; generate a task specifying the approximate location of the particular RFID tag, product information of the particular SKU, and a prompt to remove a unit of the particular SKU from the inventory structure of interest; and then transmit this task to an associate of the store, thereby guiding the associate to correct misplaced products throughout the store. [0112] generates an electronic restocking list containing a filtered list of slots at inventory structures throughout the store in need of correction, such as addition of product, exchange of product, or straightening of product.)
determine a task priority for each of the one or more generated tasks; (in at least [0113] The computer system can also generate a stock correction task list to correct improperly-stocked slots. In this implementation, the system can generate a prioritized list of tasks to move misplaced products, to restock empty or improperly-stocked slots, etc. and then serve this task list to an associate (e.g., employee) of the store via a native stocking application executing on a mobile computing device (e.g., a tablet, a smartphone) carried by the associate. In this implementation, the computer system can implement methods and techniques described in U.S. patent application Ser. No. 15/347,689 to prioritize this list of tasks to correct improperly-stocked slots throughout the store.)
monitor, in real time, execution of the one or more generated tasks via one or more devices associated with the retailer, wherein the execution is specified by the task priority for each of the one or more generated tasks; (in at least [0105] in FIG. 3, the system: generates a 2D elevation image of an inventory structure, such as by stitching multiple discrete images recorded by the robotic system when occupying waypoints along the inventory structure into a single panoramic image of the inventory structure; implements methods and techniques described above to transform RFID values and related metadata collected by the robotic system when occupying the same waypoints into 2D plan or 3D locations of corresponding RFID tags within the store; and projects the 2D plan or 3D locations of these RFID tags onto the 2D elevation image of the inventory structure. The system can then: retrieve product data (e.g., SKU, serial number, data of manufacture, etc.) associated with each of these RFID values; and populate discrete regions of the 2D elevation image with corresponding product data in order to generate a visual representation of the inventory structure and unit-level product inventory in a single 2D visual document in Block S194.)
detect at least one error in the execution of the one or more generated tasks; (in at least [0098] By then implementing this set of template images to identify products in images of the inventory structure, the computer system may more rapidly identify both products assigned to the inventory structure and RFID-tagged products mistakenly placed on the inventory structure, such as by a patron of the store. [0107] The computer system can also: implement machine vision techniques to identify slots stocked with incorrect products; identify products occupying these slots based on RFID values collected by the robotic system while navigating along the inventory structure (i.e. in the execution of the one or more generated tasks) but not contained in a list of SKUs assigned to the inventory structure by the planogram; and write a hotspot—indicating SKUs and/or other relevant data—to slots stocked with incorrect products represented in the 2D elevation image of the inventory structure. [0110] Therefore, in this implementation, the computer system can: detect price tags in an optical image of an inventory structure recorded by the robotic system; project locations of these price tags onto locations of product units calculated from corresponding RFID data collected substantially concurrently (i.e. in the execution of the one or more generated tasks) by the computer system (or vice versa); and link an optically-detected price tag to a product unit (or a cluster of product units) identified in RFID data collected by the robotic system based on physical proximity of the price tag and product unit(s). The computer system can then confirm whether a price value indicated in a price tag equals a price assigned to the corresponding product unit(s) (e.g., in the planogram or price database managed by the store) and then selectively prompt a store associated to correct the price tag if a difference is detected. For example, the computer system can transmit a location of the incorrect price tag and a correct price value for the price tag (or printable image for the correct price tag) to a mobile computing device associated with the store associate. [0112] system can generate a stocking status graph, table, or list of improperly-stocked slots throughout the store, such as including a mis-stocking mode (e.g., too many facings, too few facings, misoriented packaging, damaged packaging, outdated packaging, under quantity, over quantity, incorrect product location, etc.) for each improperly-stocked slot in this list based on stock values extracted from RFID and/or optical data collected by the robotic system, as shown in FIGS. 1, 2, 4, and 6. In this implementation, the system can serve this graph, table, or list to the manager of the store via a manager portal, such as executing on a desktop computer, a laptop computer, a tablet, or a smartphone, etc. [0114] the computer system: detects omission of a first product entirely from a first slot on a first inventory structure in the store based on failure of the robotic system to read an RFID value corresponding to this first product while scanning the first inventory structure and failure to detect a unit of the first product in an optical image of the inventory structure; retrieves a first number of units of the first product assigned to the first slot by the planogram; generates a notification specifying an identifier (e.g., a SKU) of the first product, the number of units of the first product assigned to the first slot, a location of the first slot on the first inventory structure, and a location of the first inventory structure within the store; and then transmits the notification to a mobile computing device assigned to an associate of the store substantially in Block S110. In this example, the system can transmit the notification to the associate in real-time, such as if the first product is a high-value product determined to be empty during a high-traffic period at the store (i.e. detect at least one error in the execution of the one or more generated tasks). Alternatively, the system can delay transmission of the notification to the associate until the robotic system completes a scan of the store, a full stock state of the store is determined from these scan data, and a list of restocking prompts is ordered according to values of these under- or mis-stocked products. [0120] By comparing this list of SKUs and their actual quantities to the planogram (or textual or numerical representation of the planogram), the system can also populate the digital report with indicators of slots or other inventory structures that are empty, under-stocked, over-stocked, or improperly-stocked with the incorrect product, etc. For example, the system can generate a textual list of the stock state of each slot in the store, such as ordered with empty slots followed by under-stocked slots followed by improperly-stocked slots, etc. and ordered by highest-value SKU to lowest-value SKU. Alternatively, the system can generate a 2D heat map of the stock states of slots throughout the store, such as indicating regions in which highest-value slots are empty in red, lower-value empty slots and overstocked-slots in a cooler color, and properly-stocked slots in even cooler colors.)
transmit, in real time, one or more tasks to a mobile device to account for the at least one error; and (in at least [0110] The computer system can then confirm whether a price value indicated in a price tag equals a price assigned to the corresponding product unit(s) (e.g., in the planogram or price database managed by the store) and then selectively prompt a store associated to correct the price tag if a difference is detected. For example, the computer system can transmit a location of the incorrect price tag and a correct price value for the price tag (or printable image for the correct price tag) to a mobile computing device associated with the store associate. [0112] system can generate a stocking status graph, table, or list of improperly-stocked slots throughout the store, such as including a mis-stocking mode (e.g., too many facings, too few facings, misoriented packaging, damaged packaging, outdated packaging, under quantity, over quantity, incorrect product location, etc.) for each improperly-stocked slot in this list based on stock values extracted from RFID and/or optical data collected by the robotic system, as shown in FIGS. 1, 2, 4, and 6. In this implementation, the system can serve this graph, table, or list to the manager of the store via a manager portal, such as executing on a desktop computer, a laptop computer, a tablet, or a smartphone, etc.)
dynamically re-sequence, in real time and in response to the detected at least one error, the one or more generated tasks to generate an updated task sequence, and transmit the updated task sequence to the mobile device to enable continued execution of the one or more generated tasks in accordance with the updated task sequence. (in at least [0112] computer system generates an electronic restocking list containing a filtered list of slots at inventory structures throughout the store in need of correction, such as addition of product, exchange of product, or straightening of product. For example, the system can generate a stocking status graph, table, or list of improperly-stocked slots throughout the store, such as including a mis-stocking mode (e.g., too many facings, too few facings, misoriented packaging, damaged packaging, outdated packaging, under quantity, over quantity, incorrect product location, etc.) for each improperly-stocked slot in this list based on stock values extracted from RFID and/or optical data collected by the robotic system, as shown in FIGS. 1, 2, 4, and 6. In this implementation, the system can serve this graph, table, or list to the manager of the store via a manager portal, such as executing on a desktop computer, a laptop computer, a tablet, or a smartphone, etc. [0113] The computer system can also generate a stock correction task list to correct improperly-stocked slots. In this implementation, the system can generate a prioritized list of tasks to move misplaced products, to restock empty or improperly-stocked slots, etc. and then serve this task list to an associate (e.g., employee) of the store via a native stocking application executing on a mobile computing device (e.g., a tablet, a smartphone) carried by the associate. In this implementation, the computer system can implement methods and techniques described in U.S. patent application Ser. No. 15/347,689 to prioritize this list of tasks to correct improperly-stocked slots throughout the store. [0114] the computer system: detects omission of a first product entirely from a first slot on a first inventory structure in the store based on failure of the robotic system to read an RFID value corresponding to this first product while scanning the first inventory structure and failure to detect a unit of the first product in an optical image of the inventory structure; retrieves a first number of units of the first product assigned to the first slot by the planogram; generates a notification specifying an identifier (e.g., a SKU) of the first product, the number of units of the first product assigned to the first slot, a location of the first slot on the first inventory structure, and a location of the first inventory structure within the store; and then transmits the notification to a mobile computing device assigned to an associate of the store substantially in Block S110. In this example, the system can transmit the notification to the associate in real-time, such as if the first product is a high-value product determined to be empty during a high-traffic period at the store (i.e. detect at least one error in the execution of the one or more generated tasks, update task sequence, re-sequence). Alternatively, the system can delay transmission of the notification to the associate until the robotic system completes a scan of the store, a full stock state of the store is determined from these scan data, and a list of restocking prompts is ordered according to values of these under- or mis-stocked products.)
As per Claim 2, Tiwari teaches: The system of Claim 1,
wherein the one or more generated tasks comprise a task sequence. (in at least [0021] sequentially navigating to these waypoints and executing RFID interrogation parameters and imaging parameters defined by these waypoints. However, the computer system can alternatively define a continuous scan path along a shelving segment, a shelving structure, an aisle, a set of inventory structures, or throughout the entire store with fixed or varying (e.g., parametric or non-parametric) RFID interrogation and imaging parameters; and the robotic system can navigate along this continuous scan path while broadcasting an RFID interrogation signal, recording RFID values returned by RFID tags nearby, and/or recording optical (e.g., digital photographic) images substantially continuously along this path. [0044] determine that an inventory structure represents a hanging clothing rack stocked with hanging shirts based on data contained in the planogram of the store; then define a sequence of waypoints encircling the inventory structure; and specify a lower output power level for interrogation signals broadcast at each of these waypoints given lower density of materials between product stocked on the inventory structure and the robotic system at each of these waypoints. In yet another example, the computer system can: identify an inventory structure stocked with canned goods based on the planogram of the store; label the inventory structure as unsuitable for an RFID scan; and label waypoints defined along this inventory structure with triggers for optical scans only.)
As per Claim 3, Tiwari teaches: The system of Claim 1,
wherein the one or more transmitted tasks comprise an updated task sequence. (in at least [0052] Once the robotic system completes one or more scan routines at a waypoint, the robotic system can navigate to a next waypoint and repeat this process for each other waypoint defined for the store. [0082] interfaces with a restocking scheduler and with a point of sale system integrated into the store to track ingress of new products loaded onto the inventory structure throughout the store and to track egress or products from the store through sales; and updates quantities and/or types (e.g., SKUs) of products expected to be on the inventory structure throughout the store based on such product flux data. The robotic system can then implement these updated product quantity and/or type data when determining whether to repeat RFID scan routines at waypoints throughout the store in Block S140. [0065] the robotic system (or the remote computer system) can modify RFID interrogation parameters (e.g., interrogation power, inventory structure offset distance, robotic system speed, interrogation frequency, robotic system yaw orientation, etc.) based on data collected by the robotic system during a scan routine along an inventory structure in order to: ensure that RFID values are read from all RFID-tagged product units on the inventory structure; and/or improve accuracy of localization of these RFID tags. For example, the robotic system (or the remote computer system) can execute these closed-loop controls in real-time as the robotic system completes a scan routine at a single waypoint adjacent an inventory structure or as the robotic system traverses a short, continuous path along the inventory structure. Alternatively, the robotic system (or the remote computer system) can execute these processes asynchronously, such as once a scan of the inventory structure is completed or once the current scan cycle for the entire store is completed.)
As per Claim 4, Tiwari teaches: The system of Claim 1, wherein the computer is further configured to:
identify the one or more changes in the planogram by comparing an initial planogram with an updated planogram. (in at least [0061] in FIG. 4, inventory structures throughout the store are labeled with RFID tags or include integrated RFID tags loaded with substantially unique identifiers. In this variation, the system can track types, configurations, and locations, etc. of these inventory structures based on RFID values received by the robotic system during a scan cycle throughout the store. [0083] the system identifies RF signals as originating from RFID tags arranged on or in product units carried in shopping carts, carried in shopping baskets, or discarded onto the floor. For example, the system can extract—from the planogram—2D plan areas or 3D volumes of inventory structures throughout the store. In this example, during execution of a scan routine along an inventory structure of interest, the robotic system can: collect RFID values from nearby RFID tags in Block S120; implement methods and techniques described above to determine 2D or 3D locations of RFID tags within the store based on these RFID values and related metadata; and flag RFID values located outside of known plan areas or volumes of inventory structures in the store. The system can then remove unique product units corresponding to these flagged RFID values from a list of product units stocked on an adjacent inventory structure such that this list of product units represents a substantially authentic summary of the stock state of the inventory structure and excludes product units currently occupying shoppers' carts or baskets or product units discarded onto a floor of the store.)
As per Claim 5, Tiwari teaches: The system of Claim 1,
wherein the one or more devices associated with the retailer comprise one or more of: one or more cameras, one or more sensors and one or more devices capable of transmitting location data. (in at least [0024] The robotic system can also include cameras mounted statically to the mast, such as two vertically offset cameras on a left side of the mast and two vertically offset cameras on the right side of the mast, as shown in FIG. 3. The robotic system can additionally or alternatively include articulable cameras, such as: one camera on the left side of the mast and supported by a first vertical scanning actuator; and one camera on the right side of the mast and supported by a second vertical scanning actuator. Furthermore, each camera can include a zoom lens or a wide-angle lens, etc.)
As per Claim 6, Tiwari teaches: The system of Claim 1, wherein the computer is further configured to:
update the determined task priority for each task in real time based on one or more changing conditions at the retailer. (in at least [0113] generate a stock correction task list to correct improperly-stocked slots. In this implementation, the system can generate a prioritized list of tasks to move misplaced products, to restock empty or improperly-stocked slots, etc. and then serve this task list to an associate (e.g., employee) of the store via a native stocking application executing on a mobile computing device (e.g., a tablet, a smartphone) carried by the associate. In this implementation, the computer system can implement methods and techniques described in U.S. patent application Ser. No. 15/347,689 to prioritize this list of tasks to correct improperly-stocked slots throughout the store.)
As per Claim 7, Tiwari teaches: The system of Claim 1,
wherein the determined task priority is based, at least in part, on a lowest-cost task sequence for the tasks. (in at least [0067] the robotic system can flag the set of waypoints for a second set of scan routines if the target quantity of products assigned to the inventory structure by the planogram exceeds the actual quantity of unique RFID values collected along the set of waypoints by more than a preset threshold, such as: by a static difference of 5% for all inventory structures in the store; by 5% during low-traffic hours and by 15% during high-traffic hours; by a difference threshold proportional to a value (e.g., composite of margin and sale rate) of products assigned to the inventory structure (e.g., between 2% for high-value products and up to 15% for low-value products); etc. For example, the computer system can repeat a scan cycle at each waypoint in the set at an increased interrogation signal output power level in Block S150. In another example, the robotic system can: adjust a target orientation of the robotic system at each waypoint (e.g., by 15° to shift the plane of propagation of the interrogation signal out of the plane of RFID tags not previously detected); increase the density of waypoints along (or around) the inventory structure (e.g., to achieve greater overlap of interrogation signals at the inventory structure); and/or shift these waypoints further away from the inventory structure (e.g., to enable the interrogation signal to reach product units on shelves at the top and/or bottom of inventory structure). By thus implementing different power, distance, and/or orientation parameters when executing additional scan routines at waypoints along this inventory structure, the system can increase likelihood that any RFID tags—on product units stocked on the inventory structure—that were obscured from interrogation signals broadcast by the robotic system during the previous scan routine are excited during this next scan routine and thus return RFID values back to the robotic system, thereby increasing accuracy of inventory data collected by the robotic system for this inventory structure during the current scan cycle. [0109] For a particular product unit—in this first list of product units—the computer system can detect a price difference between a price assigned to the particular product unit and a price value indicated by an adjacent price tag in the set of price tags; and then generate a stock correction prompt to correct the adjacent price tag on the first inventory structure in response to detecting this price difference. [0104] the system can transmit the notification to the associate in real-time, such as if the first product is a high-value product determined to be empty during a high-traffic period at the store. Alternatively, the system can delay transmission of the notification to the associate until the robotic system completes a scan of the store, a full stock state of the store is determined from these scan data, and a list of restocking prompts is ordered according to values of these under- or mis-stocked products. [0120] By comparing this list of SKUs and their actual quantities to the planogram (or textual or numerical representation of the planogram), the system can also populate the digital report with indicators of slots or other inventory structures that are empty, under-stocked, over-stocked, or improperly-stocked with the incorrect product, etc. For example, the system can generate a textual list of the stock state of each slot in the store, such as ordered with empty slots followed by under-stocked slots followed by improperly-stocked slots, etc. and ordered by highest-value SKU to lowest-value SKU. Alternatively, the system can generate a 2D heat map of the stock states of slots throughout the store, such as indicating regions in which highest-value slots are empty in red, lower-value empty slots and overstocked-slots in a cooler color, and properly-stocked slots in even cooler colors.)
As per Claim 8-14 for a computer-implemented method (see at least Tiwari [0122]), respectively, substantially recite the subject matter of Claim 1-7 and are rejected based on the same reasoning and rationale.
As per Claim 15-20 for a non-transitory computer-readable storage medium (see at least Tiwari [0122]), respectively, substantially recite the subject matter of Claim 1-6 and are rejected based on the same reasoning and rationale.
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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PO HAN MAX LEE whose telephone number is (571)272-3821. The examiner can normally be reached on Mon-Thurs 8:00 am - 7:00 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rutao Wu can be reached on (571) 272-6045. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/PO HAN LEE/Primary Examiner, Art Unit 3623
Prosecution Insights