DETAILED ACTION
Status of Claims
Claims 15, 17-19, and 21-22 are currently pending and have been examined in this application. This Final Rejection is in response to the amendment submitted on 08/21/2026.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Response to Arguments and Amendments
Applicant’s arguments, filed on 08/21/2026, with respect to the rejection of Claims 15, 17-19, and 21-22 under 35 USC 101 have been fully considered but they are not persuasive. The rejection has been maintained.
Regarding 35 USC 101:
Applicant Remarks:
Argument A :
“Applicant submits that the claim as a whole is not reasonably characterized as a mental process. … not practically performable in the human mind or with pen and paper, given the volume, structure, and continuously-updating nature of the operational data generated by an operating collaborative robot.”
Argument B:
“… Even if the claims were considered to recite an abstract idea, the additional elements integrate that idea into a practical application under Step 2A, Prong Two.”
Examiner Reply:
Claims 15, 17, 19, and 21 were amended to further limit and explain the invention. While the amendments succeed in further limiting and explaining the invention, they do not, in the Examiner’s opinion, prompt the withdrawal of the 35 USC 101 rejection.
Applicant’s argument above categorized as argument A, asserts that the invention is not reasonably characterized as a mental process based on the volume of data that is being processed. However this data volume is not reflected in the claims. Applicant for example refers to a “plurality of operational data”. This “plurality” under BRI could constitute as few as two data points. As a counter example if a claim were to mention the processing of point cloud data or a specific and well understood data collection technique which indicates a large number of data points, then the volume argument would be persuasive. Additionally the newly amended claim language introduces actions such as “receiving”, “assigning”, and “confirming” which are tasks that can be performed in the human mind.
The argument above categorized as argument B, asserts that the inventive ideas are integrated into a practical application. However the practical application of the processed data is not reflected in the claim language of claim 1. Claim 18 approaches the concept of a practical application, but falls short by simply displaying the fault. As a counter example if the processed fault data was applied to a specific purpose such creating a specific alert for the operator or halting the operation of the robot or some similar practical application then the argument would be persuasive.
Applicant’s arguments, filed on 08/21/2026, with respect to the rejection of claims 15-22 under 35 USC 103 have been fully considered and they are persuasive. The rejection has been withdrawn.
Regarding 35 USC 103:
Applicant Remarks:
“Because none of Inagaki, Ghose, or Lee, whether alone or in combination, discloses or suggests the specific hierarchical index generation scheme recited in claim 15 (i.e., the analysis ID, first analysis index, and second analysis index, each defined by a specific combination of the program ID, motion ID, program execution index, and motion execution index) or the specific fault-tracing methodology of confirming operational data sharing a common index, confirming a plurality of data values for that confirmed operational data, and confirming a data value that deviates from the other confirmed data values by a threshold or more, there would have been no reason or motivation for one of ordinary skill in the art to combine the cited references to arrive at the combination of features of claim 15.”
Examiner Reply:
The newly modified independent claims 15 and 19 have sufficiently narrowed the limitations to the point that Inagaki modified by Ghose and Lee no longer reads on the independent claims as currently written. No sufficient replacement art was found that would fully read on the newly amended claims and therefore the USC 103 rejection was withdrawn for the claims as currently written.
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 15, 17-19, and 21-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The claims are directed to a system or method, which is one of the statutory categories of invention. (Step 1: YES)
The examiner has identified system Claim 15 as the claim that represents the claimed invention for analysis and is similar to apparatus Claim 19. Claim 15 recites the limitations of (additional elements emphasized in bold are considered to be parsed from the remaining abstract idea):
A method for tracing a fault of a collaborative robot in a system for fault tracing, the system comprising the collaborative robot and an electronic device including a controller and a memory configured to store an operational data of the collaborative robot, the method comprising: setting, by the controller, a basic index which serves as an analysis criterion of operational data generated by the collaborative robot, the basic index including a program ID indicating a type of program performed by the collaborative robot, a motion ID indicating a motion constituting the program, a program execution index indicating a number of times the program has been executed, and a motion execution index indicating a number of times the motion has been executed setting, by the controller, an analysis index for analyzing the operational data, the analysis index including an analysis ID that combines the program ID and the motion ID, a first analysis index that combines the program execution index; and the motion ID, and a second analysis index that combines the first analysis index and the motion execution index; receiving, by the controller, a plurality of operational data from the collaborative robot; assigning, by the controller, the basic index and the analysis index to each of the plurality of operational data, and storing, in the memory, the plurality of operational data to which the basic index and the analysis index are respectively assigned; confirming, by the controller, a second analysis index having a same analysis ID or a same first analysis index, from among the analysis indexes assigned to each of the plurality of operational data stored in the memory; confirming, by the controller, each of a plurality of data values for each of the plurality of operational data corresponding to the confirmed second analysis index; confirming, by the controller, a data value which is different by a threshold or more from among the plurality of confirmed data values; and tracing a fault generated in the collaborative robot by confirming program and a motion associated with the confirmed data value.
which under its broadest reasonable interpretation, covers performance of the limitation(s) as a mental process (concept performed in the human mind) of setting a basic index of data, receiving a plurality of operational data, assigning a basic index and analysis index to data sets, storing a plurality of operational data, confirming data a plurality of data values, and tracing a fault of the collaborative robot. One of ordinary skill in the art could set a basic index of robot data, receive a set of operational data, assign data values to basic and analysis indexes, store the assigned values, confirm the collected data and then determine which program was being used when the fault occurred through observations and available data.
Similarly, if a claim limitation under its BRI, covers performance of the limitation in the human mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. (Claims can recite a mental process even if they are claimed as being performed on a computer Gottschalk v. Benson, 409 U.S. 63; “Courts 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.))
Accordingly, the claim recites an abstract idea (Step 2A- Prong 1: YES. The claims are abstract).
This judicial exception is not integrated into a practical application. Limitations that are not indicative of integration into a practical application include: (1) Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05.f), (2) Adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05.g), (3) Generally linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05.h).
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
A method for tracing a fault of a collaborative robot in a system for fault tracing, the system comprising the collaborative robot and an electronic device including a controller and a memory configured to store an operational data of the collaborative robot, the method comprising: setting, by the controller, a basic index which serves as an analysis criterion of operational data generated by the collaborative robot, the basic index including a program ID indicating a type of program performed by the collaborative robot, a motion ID indicating a motion constituting the program, a program execution index indicating a number of times the program has been executed, and a motion execution index indicating a number of times the motion has been executed setting, by the controller, an analysis index for analyzing the operational data, the analysis index including an analysis ID that combines the program ID and the motion ID, a first analysis index that combines the program execution index; and the motion ID, and a second analysis index that combines the first analysis index and the motion execution index; receiving, by the controller, a plurality of operational data from the collaborative robot; assigning, by the controller, the basic index and the analysis index to each of the plurality of operational data, and storing, in the memory, the plurality of operational data to which the basic index and the analysis index are respectively assigned; confirming, by the controller, a second analysis index having a same analysis ID or a same first analysis index, from among the analysis indexes assigned to each of the plurality of operational data stored in the memory; confirming, by the controller, each of a plurality of data values for each of the plurality of operational data corresponding to the confirmed second analysis index; confirming, by the controller, a data value which is different by a threshold or more from among the plurality of confirmed data values; and tracing a fault generated in the collaborative robot by confirming program and a motion associated with the confirmed data value.
The controller and collaborative robot in Claim 15 are just using generic computer components. The computer hardware is recited at a high level of generality such that it amounts to no more than mere instructions to implement an abstract idea by adding the words “apply it” (or an equivalent) with the judicial exception. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore claim 15 is directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using computer hardware amounts to no more than mere instructions to implement an abstract idea by adding the words “apply it” (or an equivalent) with the judicial exception. Mere instructions to implement an abstract idea on or with the use of generic computer components, cannot provide an inventive concept - rendering the claim patent ineligible. Thus claim 1 is not patent eligible. (Step 2B: NO. The claims do not provide significantly more).
The dependent claims further define the abstract idea that is present in their respective independent claims and hence are abstract for at least the reasons presented above. The dependent claims do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Therefore, the dependent claims are directed to an abstract idea. Thus, the aforementioned claims are not patent-eligible.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure or directed to the state of the art is listed on the enclosed PTO-892.
The following is a brief description for relevant prior art that was cited but not applied:
Inagaki (US 20170031329 A1) describes a fault prediction system includes a machine learning device that learns conditions associated with a fault of an industrial machine. The machine learning device includes a state observation unit that, while the industrial machine is in operation or at rest, observes a state variable including, e.g., data output from a sensor, internal data of control software, or computational data obtained based on these data, a determination data obtaining unit that obtains determination data used to determine whether a fault has occurred in the industrial machine or the degree of fault, and a learning unit that learns the conditions associated with the fault of the industrial machine in accordance with a training data set generated based on a combination of the state variable and the determination data.
Ghose (US 20190283254 A1) describes a data driven approach for fault detection in robotic actuation is disclosed. Here, a set of robotic tasks are received and analyzed by a Deep Learning (DL) analytics. The DL analytics includes a stateful (Long Short Term Memory) LSTM. Initially, the stateful LSTM is trained to match a set of activities associated with the robots based on a set of tasks gathered from the robots in a multi robot environment. Here, the stateful LSTM utilizes a master slave framework based load distribution technique and a probabilistic trellis approach to predict a next activity associated with the robot with minimum latency and increased accuracy. Further, the predicted next activity is compared with an actual activity of the robot to identify any faults associated robotic actuation.
Lee (US 20190196893 A1) describes a method performed by an appliance includes receiving, from a managing server, information about a data pattern detection routine to detect abnormal data among operation data of the appliance, determining whether the operation data of the appliance matches a normal data pattern defined by the data pattern detection routine, determining the operation data as the abnormal data when the operation data does not match the normal data pattern, and transmitting the abnormal data to the managing server.
Hosek (US 20140201571 A1) describes a system for condition monitoring and fault diagnosis which includes a data collection function that acquires time histories of selected variables for one or more of the components, a pre-processing function that calculates specified characteristics of the time histories, an analysis function for evaluating the characteristics to produce one or more hypotheses of a condition of the one or more components, and a reasoning function for determining the condition of the one or more components from the one or more hypotheses.
Kuno (US 20180147735 A1) describes a failure diagnosis device applicable to a mechanical device provided with motors independent of One another as sources to drive motion axes, respectively, and configured to acquire a moving position of each motion axis and a disturbance torque value applied to the motion axis during a predetermined period to diagnose a failure of the mechanical device. The device includes a failure diagnosis unit configured to diagnose the motion axis as a failure when the disturbance torque value is larger than a predetermined failure determination threshold.
Gawlik (US 20190143521 A1) describes a method for assessing the health of a device system by registering predetermined operating data of dynamic performance variables output by the device and determining a base value characterized by a probability density function of each dynamic performance variable output. Comparing base values for each of the dynamic performance variable output by the device respectively corresponding to the predetermined motion base set and the other predetermined motion sets.
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 ALAN LINDSAY OSTROW whose telephone number is (703)756-1854. The examiner can normally be reached M-F 8 - 5.
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, Adam Mott can be reached on (571) 270 5376. 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.
/ALAN LINDSAY OSTROW/
Examiner, Art Unit 3657
/ADAM R MOTT/Supervisory Patent Examiner, Art Unit 3657
Prosecution Insights