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 .
This action is in response to the application filed 4 September 2025. Claims 1-20 are pending and have been examined.
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 to non-statutory subject matter. The claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) a combination of (1) certain methods of organizing human activity specifically, commercial interactions in the form of matching labor supply to labor demand, and managing personal behavior or interactions between people in the form of instructing and supervising a worker and (2) mental processes, namely the observations, evaluations, and judgments involved in generating task guidance, monitoring a worker's progress, validating task completion, and updating records based on assessed performance. This judicial exception is not integrated into a practical application because the additional elements a generic processor, a network interface configured to communicate with off-the-shelf augmented reality headsets and mobile devices, and a memory are recited at a high level of generality and merely link the abstract idea to a generic computing, networking, and AR hardware environment, without reciting any specific improvement to computer functionality, AR technology, machine-learning technology, or any other technical field. The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, considered individually and in combination, constitute well-understood, routine, conventional computer functions (e.g., receiving/transmitting data over a network, storing and retrieving data in memory, and applying an off-the-shelf machine-learning/vision-language model to compare data and generate an output) that amount to no more than instructions to “apply” the abstract idea using generic technology.
STEP 1
Regarding Step 1 of the Subject Matter Eligibility Test for Products and Processes, claims 11–20 are directed to a process/method, and claims 1–10 are directed to a system/machine (claim 1 recites a processor, a network interface, and a memory). No claim in this claim set is directed to a computer-readable medium. Therefore, the claims fall within the statutory categories of invention.
STEP 2A Prong One
The claim(s) recite(s) an abstract idea. Specifically, independent claims 1 and 11 recite the following limitations:
(a) receiving a labor task request from a user;
(b) providing a matching worker to the user;
(c) generating task guidance based on the task request;
(d) monitoring worker progress based on the generated guidance;
(e) validating task completion; and
(f) updating a task library based on worker performance.
Abstract Idea Grouping Analysis
Certain Methods of Organizing Human Activity:
Limitation (b) “provide a matching worker to the user” recites matching a worker (labor supply) to a task requester (labor demand), which is a commercial interaction and a fundamental economic principle or practice akin to a staffing or labor-brokering transaction that connects a service provider to a service requester based on task compatibility, comparable to the fundamental economic practices of hedging and price-setting recognized in Alice, and Bilski v. Kappos, and to the business-practice and matching analyses in Elec. Commc’n Techs., LLC v. ShoppersChoice.com, LLC, and Bozeman Fin. LLC v. Fed. Reserve Bank of Atlanta. Limitations (c)–(e) generating guidance for, monitoring, and validating the work of a human worker further constitute “managing personal behavior or relationships or interactions between people,” including “following rules or instructions,” which is expressly enumerated in MPEP 2106.04(a)(2), subsection II, because they describe the traditional interaction between a supervisor/trainer and a worker in which the supervisor instructs the worker how to perform a task, observes the worker’s performance, and confirms that the task was completed correctly. See MPEP 2106.04(a)(2), subsection II.
Mental Processes
Limitations (b)–(f), under their broadest reasonable interpretation, also and independently cover performance in the human mind, including observation, evaluation, judgment, and opinion. “Provide a matching worker to the user” encompasses a mental evaluation in which a person (e.g., a dispatcher) reviews the requirements of a task against the qualifications and availability of candidate workers and judges which worker is best suited the same type of comparison found to be a mental process in Trinity Info Media, LLC v. Covalent, Inc., (comparing answers to generate a “likelihood of match”). “Generate task guidance based on the task request” encompasses the mental formulation and articulation of instructions that a supervisor could give a worker describing how to perform a task, based on the supervisor’s own knowledge or a recollected or written reference procedure. “Monitor worker progress based on the generated guidance” and “validate task completion” encompass an observation and evaluation in which a person watches a worker perform a task and compares what he or she observes to the expected procedure to judge whether the worker is on track and has completed the task correctly, the same type of mental “observation, evaluation, judgment” found in In re Killian, and PersonalWeb Techs. LLC v. Google LLC, (a “medley of mental processes”). “Update a task library based on worker performance” encompasses the mental act of a supervisor revising his or her own notes or understanding of how to perform or teach a task based on an observed worker’s performance, which is again an evaluation and judgment. The mere nominal recitation of a “processor,” “network interface,” and “memory” in claim 1 does not take these limitations out of the mental-processes grouping. See MPEP 2106.04(a)(2), subsection III.
Note regarding AI limitations: Because independent claims 1 and 11 recite “generate task guidance” and “monitor worker progress” generically, without reciting any vision-language-model (VLM) component or any specific sensor data stream, the mental-processes grouping is not being expanded here to encompass claim limitations that cannot practically be performed in the human mind, consistent with the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence, and MPEP 2106.04(a)(2), subsection III.A. To the extent certain dependent claims (e.g., claims 7, 10, 17, and 20) recite use of a VLM to analyze real-time sensor data streams, the mental-processes grouping is not relied upon for those specific limitations. As explained in the Dependent Claims Analysis below, however, those limitations do not overcome this rejection because they merely implement the same certain-methods-of-organizing-human-activity abstract idea using a generic, off-the-shelf AI tool.
Because limitations (b)–(f) fall within both the certain-methods-of-organizing-human-activity and mental-processes groupings, they are considered together as a single abstract idea for purposes of further analysis.
STEP 2A Prong Two
Identification of Additional Elements
The claims recite the following additional elements beyond the identified abstract idea:
“receiving a labor task request from a user” (data gathering);
“a processor”;
“a network interface configured to communicate with augmented reality headsets and mobile devices”; and
“a memory storing instructions.”
Analysis of Additional Elements
Improvement to Technology or Technical Field (MPEP 2106.05(a)):
The claims do not recite an improvement to the functioning of a computer or to any other technology or technical field. The specification describes the system as using off-the-shelf “generative AI models such as Transformers or diffusion models” and conventional AR-headset sensors (cameras, time-of-flight sensors, LIDAR) to automate labor matching, guidance, and monitoring more efficiently (see par. [0053]–[0058]), which describes using existing computing, networking, and AR components as tools to perform the abstract idea, rather than improving the functioning of those components. Unlike Ex Parte Desjardins, Appeal No. 2024-000567, in which the specification and claims recited a specific technical mechanism for how a machine-learning model’s own training process was improved (protecting previously learned parameters against “catastrophic forgetting” while training on a new task), claim 1 does not recite any comparable technical mechanism by which the processor, network interface, or memory function differently or better as a result of the claimed steps. See MPEP 2106.05(a); Versata Dev. Group v. SAP Am.
Particular Machine (MPEP 2106.05(b)):
The claims do not recite use of a particular machine that imposes meaningful limits on the claim. The recited “processor,” “network interface,” and “memory” are generic computing components recited functionally and at a high level of generality. The “network interface configured to communicate with augmented reality headsets and mobile devices” does not recite any particular technical configuration of that interface (e.g., a specific protocol or hardware architecture); the AR headsets and mobile devices are referenced only as generic external endpoints of communication and are not claimed with any particular configuration.
Mere Instructions to Apply the Exception (MPEP 2106.05(f)):
The additional elements amount to no more than mere instructions to implement the abstract idea on a computer. The claims recite generic computing components (processor, network interface, memory) performing generic computing functions (receiving a request, transmitting and receiving guidance and monitoring data, storing and updating a data record) to carry out the abstract labor-matching and worker-supervision idea. This is tantamount to adding the words “apply it” or “apply it using a computer and a network” to the judicial exception. See Alice Corp.
Insignificant Extra-Solution Activity (MPEP 2106.05(g)):
The additional element of “receiving a labor task request from a user” constitutes insignificant extra-solution activity. This is mere data gathering that is necessary to any application of the abstract labor-matching idea and is recited at a high level of generality, similar to the “receiving” limitations found to be insignificant extra-solution activity in OIP Techs., Inc. v. Amazon.com, Inc., and in the 2024 AI-SME Update’s Example 47 (Anomaly Detection), Claim 2. See MPEP 2106.05(g).
Considering the additional elements individually and in combination, the claims as a whole do not integrate the judicial exception into a practical application. The additional elements do not impose any meaningful limits on practicing the abstract idea. Accordingly, the claims are directed to an abstract idea.
STEP 2B
As discussed with respect to Step 2A Prong Two, the additional elements in the claims amount to no more than mere instructions to apply the exception using generic computer components. The same analysis applies in Step 2B mere instructions to apply an exception using generic computer components cannot provide an inventive concept. See MPEP 2106.05(f).
Well-Understood, Routine, Conventional Activity Analysis
The additional elements, when considered individually and in combination, are well-understood, routine, and conventional activities in the field. Specifically:
“Receiving a labor task request from a user” and the “network interface configured to communicate with augmented reality headsets and mobile devices” the courts have recognized receiving or transmitting data over a network as well-understood, routine, conventional activity. See MPEP 2106.05(d)(II), citing Symantec; TLI Communications LLC v. AV Auto., LLC; OIP Techs.
“A memory storing instructions” and “update a task library” the courts have recognized storing and retrieving information in memory as well-understood, routine, conventional activity. See MPEP 2106.05(d)(II), citing Versata Dev. Group, Inc. v. SAP Am., Inc.; OIP Techs.,.
“A processor” executing generic instructions to perform the recited functions is a generic computer component performing well-understood, routine, generic computer functions. See Alice Corp.
Considering the additional elements individually and in combination, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claims are not patent eligible.
Dependent Claim Analysis
The dependent claims do not add limitations that integrate the judicial exception into a practical application or provide an inventive concept, whether considered individually or in combination:
Claims 2, 12: These claims further define the content-receiving step by specifying that content is received “from multiple sources including recordings of experts, descriptions from manuals, and instructional videos.” This further specifies insignificant extra-solution/mere data-gathering activity from additional generic sources; it does not integrate the abstract idea into a practical application and is well-understood, routine, conventional data-receiving activity. See MPEP 2106.05(d)(II), citing Symantec; TLI Communications.
Claims 3, 13: These claims recite “segmenting the task into subtasks by analyzing the received content to identify discrete operational phases, tool transitions, and material handling procedures.” This limitation further narrows the abstract idea itself rather than adding a technological element: a person reviewing a manual, video, or a recollected expert demonstration can mentally identify natural break points and sub-steps in a procedure, in the same way a person learning or teaching a task would an evaluation and judgment. The claim does not recite any particular algorithm, technique, or technical improvement by which the segmentation is accomplished. This limitation does not integrate the abstract idea into a practical application or provide an inventive concept.
Claims 4, 14: These claims recite “converting the segmented subtasks into an encoded representation comprising nodes representing individual procedural states and edges representing allowed transitions between different phases of task execution.” This is, at most, a generic graph/state-machine data-organization scheme and, in the alternative, an extension of the abstract idea of encoding instructions for a task, rather than a technical improvement. The claim does not recite any particular technical benefit flowing from this specific data structure (e.g., no recitation of reduced storage, reduced computational complexity, or any other benefit of the kind credited in Ex Parte Desjardins or Enfish, LLC v. Microsoft Corp.); the specification describes the encoded representation only as a means of enabling a generic vision-language model to be applied to the labor-matching/guidance idea (par. [0055], and par. [0088]), not as improving how the underlying computer, database, or networking technology functions. This limitation does not integrate the exception into a practical application and, in Step 2B, is not sufficient, alone or in combination with the other elements, to amount to significantly more.
Claims 5, 15: These claims recite adding the encoded representation to the task library “alongside metadata including task categories, complexity ratings, required tools and materials, and estimated completion times.” This is further insignificant extra-solution activity in the form of generic data storage and indexing, which is well-understood, routine, conventional activity. See MPEP 2106.05(d)(II), citing Versata Dev. Group; OIP Techs.
Claims 6, 16: These claims recite “retrieving an encoded representation from the task library based on the labor task request,” which is generic data retrieval well-understood, routine, conventional activity. See MPEP 2106.05(d)(II), citing Versata Dev. Group; Symantec.
Claims 7, 17: These claims recite “assess[ing] a current state against the encoded representation by utilizing vision language models that analyze real-time sensor data streams from augmented reality headsets.” The Examiner has carefully considered, consistent with the AI-SME Update and MPEP 2106.04(a)(2), subsection III.A, whether this limitation falls outside the mental-processes grouping because a human mind is not equipped to process continuous multi-sensor data streams from an AR headset the way a VLM does (cf. SRI Int’l, Inc. v. Cisco Sys., Inc. Out of an abundance of caution, this rejection does not rely on the mental-processes grouping for this specific limitation. That determination does not, however, render claims 7 and 17 eligible, because independent claims 1 and 11 remain directed to the certain-methods-of-organizing-human-activity abstract idea discussed above (matching and supervising labor), and the VLM-based assessment in claims 7 and 17 merely implements that same abstract idea comparing a worker’s real-time conduct to an expected task sequence using a generic, off-the-shelf machine-learning tool. The claims recite “vision language models” and “real-time sensor data streams” at a high level of generality, reciting only the outcome of “assessing” without any technical detail regarding the architecture, training, or specific algorithm of the VLM, or any explanation of how the claimed use of the VLM improves the functioning of the VLM, the AR headset, or any other technology. The specification confirms that off-the-shelf “generative AI models such as Transformers or diffusion models” are used generically “to understand and match environmental states with stored task data” (par. [0055]), without disclosing any improvement to those models or to computer or AR functionality. This is directly analogous to Example 47 (Anomaly Detection) of the 2024 AI-SME Update, in which limitations reciting “detecting” and “analyzing” using a “trained ANN” recited at a high level of generality, without details of how the ANN operates, were found to amount to no more than mere instructions to implement the abstract idea using a generic AI component (2024 AI-SME Update, Example 47, Claim 2. Accordingly, claims 7 and 17 do not integrate the abstract idea into a practical application, and the “vision language model” limitation, at Step 2B, is no more than the generic application of a well-known class of AI tool to perform data comparison and does not supply an inventive concept.
Claims 8, 18: These claims recite generating the task guidance “by creating visual overlays, audio prompts, and textual instructions that provide workers with specific guidance for completing current procedural steps.” This further specifies the output/display format of the “generate task guidance” limitation from claims 1 and 11, which is itself part of the abstract idea (instructing a worker). Producing visual overlays, audio prompts, and text is a generic output/display step, insignificant extra-solution activity consisting of outputting the results of the abstract idea that does not integrate the exception into a practical application. See MPEP 2106.05(g).
Claims 9, 19: These claims recite that the task guidance “is displayed through an augmented reality graphical user interface comprising multiple types of visual overlays including arrows, outlines, and ghosted overlays that highlight tool positions and material placements.” This is a generic display/output step using off-the-shelf AR display technology, reciting only the result (highlighting tool or material positions) without any technical detail as to how the overlay is generated, rendered, or spatially aligned that would reflect an improvement to AR display technology. This limitation constitutes insignificant extra-solution activity and generic computer (AR) implementation and does not integrate the exception into a practical application or add an inventive concept.
Claims 10, 20: These claims recite that monitoring worker progress “includes utilizing a vision language model to compare observed environmental conditions with stored procedural expectations and detect deviations from prescribed task sequences.” As with claims 7 and 17, and out of the same abundance of caution, this rejection does not rely on the mental-processes grouping for the VLM-based comparison itself. The limitation, however, is recited at a high level of generality a generic VLM performing a generic comparison and deviation-detection function and, per the specification, uses off-the-shelf generative AI models without disclosing any improvement to those models or to the underlying computer/AR technology. This is again analogous to the generic “detecting”/“analyzing” limitations found ineligible in Example 47 of the 2024 AI-SME Update. This limitation therefore does not integrate the abstract idea into a practical application and does not provide an inventive concept under Step 2B.
For the foregoing reasons, claims 1–20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. Because it is more likely than not that the claims are ineligible for the reasons set forth above, this rejection is maintained notwithstanding the presence of generative-AI and augmented-reality hardware limitations in certain dependent claims.
Claim Rejections - 35 USC 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent may not be obtained through the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 6, 9-11, 16, 19 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kempf et al. (U.S. Patent Publication 2021/0255693 A1) (hereafter Kempf) in view of Rogan et al. (U.S. Patent Publication 2020/0320302 A1) (hereafter Rogan) in further view of ENGEL et al. (U.S. Patent Publication 2023/0377283 A1) (hereafter Engel).
Referring to Claim 1, Kempf teaches an augmented reality (AR) guided labor services system:
a processor (see; par. [0060] of Kempf teaches a processor with memory).
a network interface configured to communicate with augmented reality headsets and mobile devices (see; par. [0055] and par. [0059] of Kempf teaches an AR device connected to a laptop computer, a tablet computer, a smartphone, a wearable computing device, AR glasses or goggles heads up displays and digital helmet (i.e. headset), par. [0062]: “The AR device 100 may be implemented as a hardware device with embedded software that can be connected securely to the cloud via wired or wireless connection, and par. [0099] bidirectional data communications network such as a local area network (LAN) or a wide area network (WAN), a wireless local area network (WLAN), wireless data network).
a memory storing instructions that, when executed by the processor, cause the system to (see; par. [0060] of Kempf teaches a processor with memory).
generate task guidance based on the task request (see; par. [0051] of Kempf teaches that the system generates instructional Messages containing task-contextual data (batch ID, step tagname, instruction text) from the currently active Recipe, Sequence, or Recipe Step, i.e., task guidance generated in direct response to, and based on, the assigned task (task request), par. [0083] confirms this generation mechanism operates in the broader SOR workflow, demonstrating it is not limited to a single task type and mirrors the claim’s requirement that guidance be based on the task request received).
validate task completion (see; par. [0066] of Kempf directly recites “an instruction to designate a task as complete” as a recognized user-input type this is, verbatim, task completion validation initiated by the operator, par. [0084] reinforces this by establishing that Messages (step-completion signals) must be affirmatively acknowledged and confirmed by the operator (including electronic signature or voice command) before the system advances the system thus validates that the task step is complete before proceeding and par. [0052] provides a parallel statement of the same confirmation requirement, cumulatively teaching the “validate task completion” limitation).
Kempf does not explicitly disclose the following limitations, however,
Rogan teaches receive a labor task request from a user (see; par. [0018] and Abstract of Rogan teaches a “service request” which is a labor task request submitted by a user (requester) through a client application to the network platform the same function recited in the limitation under BRI. The service requested is performed by a human provider (worker) dispatched to fulfill the request), and
provide a matching worker to the user (see; par. [0018] and Abstract of Rogan teaches a network system selects an available provider and matches that provider to the requesting user based on service-type and availability information directly teaching “provide a matching worker to the user” under BRI. The AR guidance element for the matched provider is also present: “the provider client device… may be associated with a heads-up display unit that displays AR elements in the provider’s line of sight.”)
The Examiner notes that Kempf teaches similar to the instant application teaches augmented reality interactive messages and instructions for batch manufacturing and procedural operations. Specifically, Kempf discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Rogan teaches mutual augmented reality experience for users in a network system and as it is comparable in certain respects to Kempf which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kempf discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation. However, Kempf fails to disclose receive a labor task request from a user, and provide a matching worker to the use.
Rogan discloses receive a labor task request from a user, and provide a matching worker to the use.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kempf the receive a labor task request from a user, and provide a matching worker to the use as taught by Rogan since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kempf, and Rogan teach the collecting and analysis of data in order utilize augmented reality to perform tasks in a business environment and they do not contradict or diminish the other alone or when combined.
Kempf in view of Rogan does not explicitly disclose the following limitation, however,
Engel teaches monitor worker progress based on the generated guidance (see; par. [0057], par. [0031] of Engel teaches procedural guidance logic continuously observes the operator via sensors and computer-vision input, determines the operator’s position in the procedure (guiding to the next step = tracking progress), and detects when the operator deviates from the prescribed sequence teaching monitoring worker progress based on the generated procedural guidance),and
update a task library based on worker performance (see; par. [0055] of Engel teaches a protocol library (knowledge base) is updated with machine-learning derived from operator performance data (error patterns captured during use) and reapplied to future protocol guidance directly teaching updating a task library based on worker performance).
The Examiner notes that Kempf teaches similar to the instant application teaches augmented reality interactive messages and instructions for batch manufacturing and procedural operations. Specifically, Kempf discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Rogan teaches mutual augmented reality experience for users in a network system and as it is comparable in certain respects to Kempf which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Engel teaches control structure for procedural guidance systems using augmented reality and as it is comparable in certain respects to Kempf and Rogan which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kempf and Rogan discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation. However, Kempf and Rogan fails to disclose monitor worker progress based on the generated guidance and update a task library based on worker performance.
Engel discloses monitor worker progress based on the generated guidance and update a task library based on worker performance.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kempf and Rogan monitor worker progress based on the generated guidance and update a task library based on worker performance as taught by Engel since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kempf, Rogan, and Engel teach the collecting and analysis of data in order utilize augmented reality to perform tasks in a business environment and they do not contradict or diminish the other alone or when combined.
Referring to Claim 6, see discussion of claim 1 above, while Kempf in view of Rogan in further view of Engel teaches the system above, Kempf in view of Rogan does not explicitly disclose a system having the limitations of, however,
Engel teaches the instructions further cause the system to retrieve an encoded representation from the task library based on the labor task request (see; par. [0056]-[0057] of Johnson teaches retrieving protocol content (i.e. encoded representation) from the knowledge base (i.e. task library) via queries triggered by the system’s procedural guidance logic in response to the running task teaching retrieval from a task library based on a task request).
The Examiner notes that Kempf teaches similar to the instant application teaches augmented reality interactive messages and instructions for batch manufacturing and procedural operations. Specifically, Kempf discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Rogan teaches mutual augmented reality experience for users in a network system and as it is comparable in certain respects to Kempf which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Engel teaches control structure for procedural guidance systems using augmented reality and as it is comparable in certain respects to Kempf and Rogan which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kempf and Rogan discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation. However, Kempf and Rogan fails to disclose the instructions further cause the system to retrieve an encoded representation from the task library based on the labor task request.
Johson discloses the instructions further cause the system to retrieve an encoded representation from the task library based on the labor task request.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kempf, Rogan, and Engel the instructions further cause the system to retrieve an encoded representation from the task library based on the labor task request as taught by Johson since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kempf, Rogan, Engel, and Johnson teach the collecting and analysis of data in order utilize augmented reality to perform tasks in a business environment and they do not contradict or diminish the other alone or when combined.
Referring to Claim 9, see discussion of claim 1 above, while Kempf in view of Rogan in further view of Engel teaches the system above, Kempf further discloses a method having the limitations of,
the task guidance is displayed through an augmented reality graphical user interface comprising multiple types of visual overlays including arrows, outlines, and ghosted overlays that highlight tool positions and material placements (see; par. [0067] of Kempf teaches “arrows” (i.e. pointing arrows and flashing indications of emphasis) and “outlines” (“schematics or diagrams associated with a target apparatus or surrounding structures” = outline drawings of the apparatus and environment), par. [0068] teaches “ghosted overlays” (i.e. the “translucent overlay” is a semi-transparent graphical layer superimposed on the real-world view, which is the broadest reasonable interpretation of “ghosted” as confirmed by the application’s, par. [0048] “transparent or semi-transparent images”). Par. [0085] confirms the overlay highlights “physical areas of equipment” (i.e. tool positions) and par. [0086] confirms highlighting of “correct physical controls needed to perform tasks” (i.e. material placements). All four overlay types and their referents are thus disclosed across these four paragraphs).
Referring to Claim 10, see discussion of claim 1 above, while Kempf in view of Rogan in further view of Engel teaches the system above, Kempf in view of Rogan does not explicitly disclose a method having the limitations of,
Engel teaches monitoring worker progress comprises utilizing a vision language model to compare observed environmental conditions with stored procedural expectations and detect deviations from prescribed task sequences (see; par. [0031] of Engel the system ontology encodes “permitted relationships among objects in the work environment, so that, using input from a computer vision component, the procedural guidance system may identify relationships among objects that corresponded to error conditions” (detecting deviations from prescribed task sequences), and par. [0057] the system uses its sensors to “understand what it is seeing” (observed environmental conditions) and compares that understanding against the ontology-encoded expected state (stored procedural expectations) to “detect when the operator… is about to make an error” (deviation detection) which is viewed to disclose functionally compares observed conditions (sensor/computer-vision input) to stored procedural expectations (the ontology/knowledge base) and flags deviations the claimed comparison and deviation-detection function.
The Examiner notes that Kempf teaches similar to the instant application teaches augmented reality interactive messages and instructions for batch manufacturing and procedural operations. Specifically, Kempf discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Rogan teaches mutual augmented reality experience for users in a network system and as it is comparable in certain respects to Kempf which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Engel teaches control structure for procedural guidance systems using augmented reality and as it is comparable in certain respects to Kempf and Rogan which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kempf and Rogan discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation. However, Kempf and Rogan fails to disclose monitoring worker progress comprises utilizing a vision language model to compare observed environmental conditions with stored procedural expectations and detect deviations from prescribed task sequences.
Engel discloses monitoring worker progress comprises utilizing a vision language model to compare observed environmental conditions with stored procedural expectations and detect deviations from prescribed task sequences.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kempf and Rogan monitoring worker progress comprises utilizing a vision language model to compare observed environmental conditions with stored procedural expectations and detect deviations from prescribed task sequences as taught by Engel since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kempf, Rogan, and Engel teach the collecting and analysis of data in order utilize augmented reality to perform tasks in a business environment and they do not contradict or diminish the other alone or when combined.
Referring to Claim 11, Kempf in view of Rogan in further view of Engel teaches a method for performing augmented reality (AR) guided labor services. Claim 11 recites the same or similar limitations as those addressed above in claim 1, Claim 11 is therefore rejected for the same reasons as set forth above in claim 1.
Referring to Claim 16, see discussion of claim 11 above, while Kempf in view of Rogan in further view of Engel teaches the method above Claim 16 recites the same or similar limitations as those addressed above in claim 6, Claim 16 is therefore rejected for the same or similar limitations as set forth above in claim 6.
Referring to Claim 19, see discussion of claim 11 above, while Kempf in view of Rogan in further view of Engel teaches the method above Claim 19 recites the same or similar limitations as those addressed above in claim 9, Claim 19 is therefore rejected for the same or similar limitations as set forth above in claim 9.
Referring to Claim 20, see discussion of claim 11 above, while Kempf in view of Rogan in further view of Engel teaches the method above Claim 20 recites the same or similar limitations as those addressed above in claim 10, Claim 20 is therefore rejected for the same or similar limitations as set forth above in claim 10.
Claims 2-5, and 12-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kempf et al. (U.S. Patent Publication 2021/0255693 A1) (hereafter Kempf) in view of Rogan et al. (U.S. Patent Publication 2020/0320302 A1) (hereafter Rogan) in further view of ENGEL et al. (U.S. Patent Publication 2023/0377283 A1) (hereafter Engel) in further view of Johnson et al. (U.S. Patent Publication 2021/0264810 A1) (hereafter Johnson).
Referring to Claim 2, see discussion of claim 1 above, while Kempf in view of Rogan in further view of Engel teaches the system above, Kempf in view of Rogan in further view of Engel does not explicitly disclose a system having the limitations of, however,
Johnson teaches instructions further cause the system to receive content related to a task from multiple sources including recordings of experts, descriptions from manuals, and instructional videos (see; par. [0057] of Johnson teaches the ingesting task content from (i) recorded expert demonstrations (recordings of experts), (ii) documentation data (descriptions from manuals), and (iii) photographs/videos of real procedures (instructional videos) the same three source categories recited in the claim, taught by a single reference).
The Examiner notes that Kempf teaches similar to the instant application teaches augmented reality interactive messages and instructions for batch manufacturing and procedural operations. Specifically, Kempf discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Rogan teaches mutual augmented reality experience for users in a network system and as it is comparable in certain respects to Kempf which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Engel teaches control structure for procedural guidance systems using augmented reality and as it is comparable in certain respects to Kempf and Rogan which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Johnson teaches generating a virtual reality training session and as it is comparable in certain respects to Kempf, Rogan, and Engel which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kempf, Rogan, and Engel discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation. However, Kempf, Rogan, and Engel fails to disclose instructions further cause the system to receive content related to a task from multiple sources including recordings of experts, descriptions from manuals, and instructional videos.
Johnson discloses instructions further cause the system to receive content related to a task from multiple sources including recordings of experts, descriptions from manuals, and instructional videos.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kempf, Rogan, and Engel instructions further cause the system to receive content related to a task from multiple sources including recordings of experts, descriptions from manuals, and instructional videos as taught by Johson since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kempf, Rogan, Engel, and Johnson teach the collecting and analysis of data in order utilize augmented reality to perform tasks in a business environment and they do not contradict or diminish the other alone or when combined.
Referring to Claim 3, see discussion of claim 2 above, while Kempf in view of Rogan in further view of Engel in further view of Johnson teaches the system above, Kempf in view of Rogan in further view of Engel does not explicitly disclose a system having the limitations of, however,
Johnson teaches the instructions further cause the system to segment the task into subtasks by analyzing the received content to identify discrete operational phases, tool transitions, and material handling procedures (see; par. [0059]-[0061] of Johnson teaches analyzing captured expert content and segments the procedure into atomic actions (discrete operational phases), where each action is tied to a specific tool (tool transition from one step’s tool to the next) and identifies the specific parts to be handled at each atomic step (material handling procedures). A single reference teaches all three enumerated sub-elements).
The Examiner notes that Kempf teaches similar to the instant application teaches augmented reality interactive messages and instructions for batch manufacturing and procedural operations. Specifically, Kempf discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Rogan teaches mutual augmented reality experience for users in a network system and as it is comparable in certain respects to Kempf which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Engel teaches control structure for procedural guidance systems using augmented reality and as it is comparable in certain respects to Kempf and Rogan which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Johnson teaches generating a virtual reality training session and as it is comparable in certain respects to Kempf, Rogan, and Engel which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kempf, Rogan, and Engel discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation. However, Kempf, Rogan, and Engel fails to disclose the instructions further cause the system to segment the task into subtasks by analyzing the received content to identify discrete operational phases, tool transitions, and material handling procedures.
Johnson discloses the instructions further cause the system to segment the task into subtasks by analyzing the received content to identify discrete operational phases, tool transitions, and material handling procedures.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kempf, Rogan, and Engel the instructions further cause the system to segment the task into subtasks by analyzing the received content to identify discrete operational phases, tool transitions, and material handling procedures as taught by Johnson since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kempf, Rogan, Engel, and Johnson teach the collecting and analysis of data in order utilize augmented reality to perform tasks in a business environment and they do not contradict or diminish the other alone or when combined.
Referring to Claim 4, see discussion of claim 3 above, while Kempf in view of Rogan in further view of Engel in further view of Johnson teaches the system above, Kempf in view of Rogan does not explicitly disclose a system having the limitations of, however,
Engel teaches the instructions further cause the system to convert the segmented subtasks into an encoded representation comprising nodes representing individual procedural states and edges representing allowed transitions between different phases of task execution (see; par. [0024] and par. [0033] of Johnson teaches the encoding of a procedure as a Directed Acyclic Graph whose nodes are the procedure’s steps/states and whose edges are the “permitted” / ordinality relationships governing which step may follow which nodes representing procedural states and edges representing allowed transitions (i.e. converting and generating subtasks that are allowed).
The Examiner notes that Kempf teaches similar to the instant application teaches augmented reality interactive messages and instructions for batch manufacturing and procedural operations. Specifically, Kempf discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Rogan teaches mutual augmented reality experience for users in a network system and as it is comparable in certain respects to Kempf which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Engel teaches control structure for procedural guidance systems using augmented reality and as it is comparable in certain respects to Kempf and Rogan which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kempf and Rogan discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation. However, Kempf and Rogan fails to disclose the instructions further cause the system to add the encoded representation of the task to th11e task library alongside metadata including task categories, complexity ratings, required tools and materials, and estimated completion time.
Engel discloses the instructions further cause the system to add the encoded representation of the task to the task library alongside metadata including task categories, complexity ratings, required tools and materials, and estimated completion time
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kempf and Rogan the instructions further cause the system to convert the segmented subtasks into an encoded representation comprising nodes representing individual procedural states and edges representing allowed transitions between different phases of task execution as taught by Engel since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kempf, Rogan, and Engel teach the collecting and analysis of data in order utilize augmented reality to perform tasks in a business environment and they do not contradict or diminish the other alone or when combined.
Referring to Claim 5, see discussion of claim 4 above, while Kempf in view of Rogan in further view of Engel in further view of Johnson teaches the system above, Kempf in view of Rogan does not explicitly disclose a system having the limitations of, however,
Engel teaches the instructions further cause the system to add the encoded representation of the task to the task library alongside metadata including task categories, complexity ratings, required tools and materials, and estimated completion times (see; par. [0048]–[0049] of Engel teaches the knowledge base is organized around a “protocol-centric relational database” that stores “distinct settings for various protocols and the steps therein, including context in which certain protocols are performed as well as their intended use, and required machinery, reagents, tools and supplies” (required tools and materials), par. [0024] the system “utilize[s] hierarchical classification and cross-classification” of protocol content (task categories) (i.e. complexity determination), par. [0045] “metadata tags such as SKUs, serial numbers, etc.” and par. [0067] timing properties “include elapsed time and time to finish” (estimated completion times) which is viewed to teach a protocol-centric library stores each encoded protocol with metadata covering (i) hierarchical categorization (task categories), (ii) required tools/supplies (required tools and materials), and (iii) timing properties (estimated completion times).
The Examiner notes that Kempf teaches similar to the instant application teaches augmented reality interactive messages and instructions for batch manufacturing and procedural operations. Specifically, Kempf discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Rogan teaches mutual augmented reality experience for users in a network system and as it is comparable in certain respects to Kempf which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Engel teaches control structure for procedural guidance systems using augmented reality and as it is comparable in certain respects to Kempf and Rogan which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kempf and Rogan discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation. However, Kempf and Rogan fails to disclose the instructions further cause the system to add the encoded representation of the task to th11e task library alongside metadata including task categories, complexity ratings, required tools and materials, and estimated completion time.
Engel discloses the instructions further cause the system to add the encoded representation of the task to the task library alongside metadata including task categories, complexity ratings, required tools and materials, and estimated completion time
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kempf and Rogan the instructions further cause the system to convert the segmented subtasks into an encoded representation comprising nodes representing individual procedural states and edges representing allowed transitions between different phases of task execution as taught by Engel since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kempf, Rogan, and Engel teach the collecting and analysis of data in order utilize augmented reality to perform tasks in a business environment and they do not contradict or diminish the other alone or when combined.
Referring to Claim 12, see discussion of claim 11 above, while Kempf in view of Rogan in further view of Engel teaches the method above Claim 12 recites the same or similar limitations as those addressed above in claim 2, Claim 12 is therefore rejected for the same or similar limitations as set forth above in claim 2.
Referring to Claim 13, see discussion of claim 12 above, while Kempf in view of Rogan in further view of Engel teaches the method above Claim 13 recites the same or similar limitations as those addressed above in claim 3, Claim 13 is therefore rejected for the same or similar limitations as set forth above in claim 3.
Referring to Claim 14, see discussion of claim 13 above, while Kempf in view of Rogan in further view of Engel in further view of Johnson teaches the method above Claim 13 recites the same or similar limitations as those addressed above in claim 3, Claim 13 is therefore rejected for the same or similar limitations as set forth above in claim 3.
Referring to Claim 15, see discussion of claim 14 above, while Kempf in view of Rogan in further view of Engel in further view of Johnson teaches the method above Claim 13 recites the same or similar limitations as those addressed above in claim 3, Claim 13 is therefore rejected for the same or similar limitations as set forth above in claim 3.
Claims 7, 8, 17, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kempf et al. (U.S. Patent Publication 2021/0255693 A1) (hereafter Kempf) in view of Rogan et al. (U.S. Patent Publication 2020/0320302 A1) (hereafter Rogan) in further view of ENGEL et al. (U.S. Patent Publication 2023/0377283 A1) (hereafter Engel) in further view of Uzkent et al. (U.S. Patent Publication 2023/0289590 A1) (hereafter Uzkent)..
Referring to Claim 7, see discussion of claim 6 above, while Kempf in view of Rogan in further view of Engel teaches the system above, Kempf in view of Rogan does not explicitly disclose a system having the limitations of, however,
Engel teaches the instructions further cause the system to assess a current state against the encoded representation by utilizing models that analyze real-time sensor data streams from augmented reality headsets (see; par. [0031] and par. [0057] of Engel teaches procedural guidance logic assesses the current observed state (via computer-vision sensor input from the AR device) against the ontology-encoded expected state to identify step completion or error conditions teaching the recited assessment function.
The Examiner notes that Kempf teaches similar to the instant application teaches augmented reality interactive messages and instructions for batch manufacturing and procedural operations. Specifically, Kempf discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Rogan teaches mutual augmented reality experience for users in a network system and as it is comparable in certain respects to Kempf which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Engel teaches control structure for procedural guidance systems using augmented reality and as it is comparable in certain respects to Kempf and Rogan which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kempf and Rogan discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation. However, Kempf and Rogan fails to disclose the instructions further cause the system to assess a current state against the encoded representation by utilizing models that analyze real-time sensor data streams from augmented reality headsets.
Engel discloses the instructions further cause the system to assess a current state against the encoded representation by utilizing models that analyze real-time sensor data streams from augmented reality headsets.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kempf and Rogan the instructions further cause the system to assess a current state against the encoded representation by utilizing models that analyze real-time sensor data streams from augmented reality headsets as taught by Engel since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kempf, Rogan, and Engel teach the collecting and analysis of data in order utilize augmented reality to perform tasks in a business environment and they do not contradict or diminish the other alone or when combined.
Kempf in view of Rogan in further view of Engel does not explicitly disclose the following limitation, however,
Uzkent teaches utilizing vision language models (see; par. [0032] of Uzkent teaches utilizing a language model to for training, par. [0069] along with augmented reality to manage tasks).
The Examiner notes that Kempf teaches similar to the instant application teaches augmented reality interactive messages and instructions for batch manufacturing and procedural operations. Specifically, Kempf discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Rogan teaches mutual augmented reality experience for users in a network system and as it is comparable in certain respects to Kempf which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Engel teaches control structure for procedural guidance systems using augmented reality and as it is comparable in certain respects to Kempf and Rogan which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Uzkent teaches learning to share weights across transformer backbones in vision and language tasks and as it is comparable in certain respects to Kempf, Rogan, and Engel which augmented reality interactive messages and instructions for batch manufacturing and procedural operations as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Kempf, Rogan, and Engel discloses the augmented reality device in a batch production or sequential operation to display a visualization of sequential operation. However, Kempf, Rogan, and Engel fails to disclose utilizing vision language models.
Uzkent discloses utilizing vision language models.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Kempf, Rogan, and Engel utilizing vision language models as taught by Uzkent since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Kempf, Rogan, Engel, and Uzkent teach the collecting and analysis of data in order utilize augmented reality to perform tasks in a business environment and they do not contradict or diminish the other alone or when combined.
Referring to Claim 8, see discussion of claim 7 above, while Kempf in view of Rogan in further view of Engel in further view of Uzkent teaches the system above, Kempf further discloses a system having the limitations of,
the instructions further cause the system to generate the task guidance by creating visual overlays, audio prompts, and textual instructions that provide workers with specific guidance for completing current procedural steps (see; [0067] of Kempf teaches the visual overlay modality (i.e. translucent overlay of graphical elements) and the textual instruction modality (icons, text, menus, messages), each keyed to the operator’s current procedural step and par. [0068] teaches the audio prompt modality (i.e. auditory instructions and audible alerts delivered via earpiece or headphones). Together these two paragraphs teach all three modalities visual overlays, audio prompts, and textual instructions directed to the worker’s current step, as recited in the claim.
Referring to Claim 17, see discussion of claim 16 above, while Kempf in view of Rogan in further view of Engel teaches the method above Claim 17 recites the same or similar limitations as those addressed above in claim 7, Claim 17 is therefore rejected for the same or similar limitations as set forth above in claim 7.
Referring to Claim 18, see discussion of claim 17 above, while Kempf in view of Rogan in further view of Engel in further view of Uzkent teaches the method above Claim 18 recites the same or similar limitations as those addressed above in claim 8, Claim 18 is therefore rejected for the same or similar limitations as set forth above in claim 8.
Conclusion
The prior art made of record and not relied upon considered pertinent to Applicant’s disclosure.
Lusthaus et al. (U.S. Patent 9,824,318 B1) discloses generating labor requirements.
Brent et al. (U.S. Patent Publication 2023/0068660 A1) discloses somatic and somatosensory guidance in virtual and augmented reality environments.
Ramani et al. (U.S. Patent Publication 2021/0134065 A1) discloses a system and method for generating asynchronous augmented reality instructions.
Lusthaus et al. (U.S. Patent 9,824,318 B1) discloses generating labor requirements.
Bailey et al. (U.S. Patent Publication 2005/0120111 A1) discloses reporting of abnormal computer resource utilization data.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to STEPHEN S SWARTZ whose telephone number is (571)270-7789. The examiner can normally be reached Mon-Fri 9:00 - 6:00.
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, Boswell Beth can be reached at 571 272-6737. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/S.S.S/Examiner, Art Unit 3625
/BETH V BOSWELL/Supervisory Patent Examiner, Art Unit 3625
Prosecution Insights