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
Claims 9-21 are pending. Claims 9-21 are rejected.
Amendments to the claims have been recorded.
Response to Amendment
Applicant’s arguments with respect to claims have been considered but are moot because the arguments do not apply to the new references being used in the current rejection.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
means for determining learning error values.
means for filtering the determined learning error values
means filtering the determined learning error values
means for operating the machine
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 9-21 are rejected under 35 U.S.C. 103 as being unpatentable over Cella US 20210157312 as applied to claim above, and further in view of Yajima US 20220378525.
Claims 9-21 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by
The claims are incredibly broad and do not convey the inventive idea.
1-8. (CANCELLED)
9. Cella teaches a method for operating a, the method comprising:
on the basis of reference values of the machine, wherein the model values are determined using a first model and a second model on the basis of machine state values; 2154; the machine learning circuit is seeded with a model that enables it to learn data patterns.
b) filtering the determined learning error values using a first filter, and 3063; the edge device 28704 may dedupe any reporting packets that are duplicative and/or may filter out sensor data that is clearly erroneous (e.g., outside of a tolerance range). Also 3020
calibrating the first model on the basis of the learning error values filtered by the first filter; 3022; encoding module 522 may represent sensor data in an original integer or “counts format” and with relevant calibration coefficients and offsets at the time of collection.
c) filtering the determined learning error values using a second filter and calibrating the second model on the basis of the learning error values filtered by the second filter; and 3023; may normalize [filter spicks] the sensor data into values that fall within a range and format of a media frame.
Cella teaches all of the limitations of the claim but does not teach
robotic manipulator:
a) determining learning error values resulting from nonlinearities on the basis of model values, and
d) controlling operation of the robotic manipulator with a robot controller using model values output from the calibrated first model and the calibrated second model and based on state values of the robotic manipulator.
However, Yajima teaches:
robotic manipulator: 57; device 20 is a manipulator
a) determining learning error values resulting from nonlinearities on the basis of model values, and 65; when the frictional force acts on the joint portion J1 of the arm portion, the joint portion J1 does not rotate smoothly [nonlinearities] as compared with the case of an ideal joint portion which neglects the influence of the frictional force. Furthermore, when the joint portion J1 does not rotate smoothly, the movement of the arm portion is hindered in conjunction therewith.
d) controlling operation of the robotic manipulator with a robot controller using model values output from the calibrated first model and the calibrated second model and based on state values of the robotic manipulator. 129; the object to be driven [controlling] (slave device 20 [manipulator]) includes one or value by inputting the torque estimation value and the external torque response value to the machine learning model.
Therefore, it was well known at the time the invention was filed and would have been obvious to one of ordinary skill in the art to combine the teachings for the purpose of high precision model and apparatus calibrating data used for salve devices such as minipulators such that the claimed invention as a whole would have been obvious. The combination is also considered obvious to try as stated in KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007).
10. The method of claim 9, wherein at least one of:
operating the machine comprises operating a multi-axis robot;
or
operating the machine comprises at least one of controlling
or
monitoring the machine.430; methods and systems for using collected data to provide improved monitoring,
11. The method of claim 9, wherein the step sequence a) - d) is repeated cyclically such that, in a current cycle, in step a) the model values are determined using the first and second models calibrated in steps 2431; current and previous data
b) and c) of a preceding cycle. 2431; The maintained data may characterize forward error correction parameters [learning] associated with the one or more current or previous data communication connections.
12. The method of claim 9, wherein at least one of:
the first model has a function approximator based on parameter-weighted basis functions; 954; Machine learning may be used to improve the foregoing, such as by adjusting one or more weights, structures, rules, or the like (such as changing a function within a model) based on feedback (such as regarding the success of a model in a given situation) or based on iteration (such as in a recursive process).
or
the second model has a function approximator based on parameter-weighted basis functions.
13. The method of claim 12, wherein at least one of:
the first model function approximator is a
radial basis function network 1660; radial basis function neural networks,
or
a general regression neural network;
or
the second model function approximator is based on parameter-weighted periodic basis functions;
the second model function approximator is a harmonic activated neural network.
14. The method of claim 9, wherein one of the first
or
second filters has a notch filter
or
band-stop filter, and the other of the first
or
second filters has a band-pass filter. 437; band-pass tracking filter
15. The method of claim 9, wherein at least one of the first or the second filter is a machine-state-value-adaptive filter, the behavior of which varies with the machine state values.963; using filtered peak-hold circuits or functionally or other means, this capability to alarm with adaptive scheduling techniques for continuous monitoring and the continuous monitoring system's software adapting and adjusting the data collection sequence based on statistics, analytics, data alarms and dynamic analysis.
16. The method of claim 9, wherein at least one of:
the model values and reference values depend on
at least one of
forces 993; torsional vibration detection and analysis is provided utilizing transitory signal analysis to provide an advanced torsional vibration analysis for a more comprehensive way to diagnose machinery where torsional forces are relevant (such as machinery with rotating components).
or
torques of the machine;
or
the machine state values depend on speeds of the machine.
17. The method of claim 16, wherein the machine state values depend on rotational speeds of the machine. 993; smaller speed changes associated with torsion relative to the shaft's rotational speed which suggest that monitoring phase behavior would show the quick or transient speed bursts in contrast to the slow phase changes historically associated with ramping a machine's speed up or down (as typified with Bode or Nyquist plots).
18. is rejected using the same rejections as made to claim 9.
19. is rejected using the same rejections as made to claim 10.
20. is rejected using the same rejections as made to claim 9.
21. is rejected using the same rejections as made to claim 10.
Conclusion
THIS ACTION IS MADE FINAL. 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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SIHAR A KARWAN whose telephone number is (571)272-2747. The examiner can normally be reached on M-F 11am.-7pm.
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/SIHAR A KARWAN/Examiner, Art Unit 3664