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 .
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1,8-13, 15-20,22-24 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Murai et al. (US 20180224810 A1.).
As per claim 1, Murai et al. teach
An information processing method for optimizing a plurality of control parameters in a device that performs a plurality of operations based on the plurality of control parameters (Fig.1, Fig.9), the method comprising: by an information processing device,
in control parameter optimization processing, selecting a representative operation including at least one operation among all of the plurality of operations capable of being performed by the device (para 49, control parameter optimization and setting for operation of a specific purpose and situation. That is a representative operation from many operations for many purposes and situations), causing the device to perform the selected representative operation, acquiring measurement data regarding an operation of the device, the measurement data being measured by performing the representative operation (para 39, Operation data acquisition unit 133 of Fig. 1 acquire actual operation data of the servo. Operation data is measured {para 75, #920 of Fig.1}), calculating an evaluation value of a predetermined evaluation index based on the acquired measurement data (para 40, evaluation value for normative data/evaluation index is determined; para 34-35, normative data is stored in advance therefore predetermined), and updating the plurality of control parameters based on the calculated evaluation value (S106 Fig.4): and executing the control parameter optimization processing a plurality of times while changing an evaluation criterion of the control parameter optimization processing (paras 34-35,para 40, normative data setting unit #112 set the normative data plurality of times ).
As per claim 8, Murai et al. teach
The information processing method according to claim 1, wherein the changing the evaluation criterion includes changing the evaluation index (para 32, measuring the position, measuring the speed require the measured data, therefore there is a change in the evaluation data, also see para 40, evaluation value for normative data/evaluation index is determined).
As per claim 9, Murai et al. teach
The information processing method according to claim 8, wherein each of the plurality of operations is an operation for causing the device to transfer an object to a target position, and the evaluation index includes a settling time until a positional deviation between a position of the object and the target position converges within an allowable range. (paras 32 and 4; position of a target device is measured {para 32} and parameter adjustment is based on position reaching settling {para 4} within allowable value).
As per claim 10, Murai et al. teach
The information processing method according to claim 8, wherein each of the plurality of operations is an operation for causing the device to transfer an object to a target position, and the evaluation index includes an integrated value of a deviation time at which a positional deviation between a position of the object and the target position deviates from an allowable range or of a positional deviation amount ( para 4, the control parameter device is determining an adjustment settling feature by measuring the actual position data and normative position data and evaluating them against an allowable range. Therefore, it is evaluating a deviation amount. Also see, para 43, the parameter determination unit comparing the evaluation value with allowable value and control parameters to be determined are related to position and speed data measured).
As per claim 11, Murai et al. teach
The information processing method according to claim 1, further comprising setting a search range of the control parameters that are update candidates in the control parameter optimization processing at a next time, based on a plurality of the evaluation values calculated in the control parameter optimization processing at a current time (paras 63-64, Fig. 8A-8B, region/range or search range for parameter).
As per claim 12, Murai et al. teach
The information processing method according to claim 1, further comprising: causing the device to perform a predetermined evaluation operation for comprehensively evaluating an operation of the device in comprehensive evaluation processing (paras 31-32, target device 910 is executing a predetermined tact according to the operation of the servo motor. Measuring instrument 920 directly measuring the predetermined speed, vibration and position. Also see para 40, an evaluation value for normative data/evaluation index is determined; para 34-35, normative data is stored in advance therefore predetermined): acquiring measurement data regarding the operation of the device measured in the performing of the evaluation operation (para 39, Operation data acquisition unit 133 of Fig. 1 acquire actual operation data of the servo. Operation data is measured {para 75, #920 of Fig.1}). Also see, para 40, evaluation value for normative data/evaluation index is determined based on the acquired data)
calculating an evaluation value of the evaluation index based on the acquired measurement data (para 40, calculating an evaluation value): and making the comprehensive evaluation based on the calculated evaluation value (para 45-46, an evaluation value has been outputted to the parameter determination unit 132 by the data evaluation unit 131.Using the evaluation value the evaluation unit 131 calculates a norm using a current data. This process also repeated for the normative data in para 47).
As per claim 13, Murai et al. teach
The information processing method according to claim 12, wherein the evaluation operation is all the operations (abstract, an evaluation value is calculated and reapplied to calculate the control parameter, also Fig. 4, Fig 5, and Fig. 10A -10B for evaluation value calculation. Also see paras 34-35, and 40 for evaluation value calculation).
As per claim 15, Murai et al. teach
The information processing method according to claim 12, wherein the evaluation operation is a prescribed operation defined in advance from all the operations (para 34-35, the normative data is stored in advance for the evaluation purpose; therefore, the data is predetermined. para 31-32, target device 910 is executing a predetermined tact according to the operation of the servo motor. Measuring instrument 920 directly measuring the predetermined speed, vibration and position. Also see para 40, an evaluation value for normative data/evaluation index is determined. The predetermined or advanced steps/data collection teach the prescribed operation).
As per claim 16, Murai et al. teach
The information processing method according to claim 12, further comprising: determining whether the evaluation result of the comprehensive evaluation satisfies a predetermined end condition (Fig. 4, Fig. 7, Step S104 determines whether the evaluation value is within an allowable value, also see para 54, based on the evaluation value determination step S104, as Yes or No, the control parameter has been changed).
As per claim 17, Murai et al. teach
The information processing method according to claim 1, wherein each of the plurality of operations is an operation for causing the device to transfer an object to a target position, the method further comprising outputting, to a user for a notification, status information regarding at least one of: an elapsed time from start of the control parameter optimization processing ( Fig. 2, para 40, the data evaluation unit 131 performs discrete sampling on the operation data and the normative data at time tm (m=1 to n) the total time at n teach the elapsed time) : a remaining time until a maximum time for continuing the control parameter optimization processing: an operation condition including at least one of identification information, a transfer amount, a transfer speed, an acceleration time, and a deceleration time regarding an operation being currently performed among the at least one operation included in the representative operation: a number of operations included in the representative operation (para 70, Fig. 10B, number of times the evaluation value has been changed depending on number of updates): a number of update times of the control parameters (para 70, “FIG. 10A is a diagram (the number of times the setting of the control parameter is changed by using the optimization algorithm)” :
and a remaining number of times up to a maximum number of times of updating the control parameters.
As per claim 18, Murai et al. teach
The information processing method according to claim 17, further comprising updating the status information every time the evaluation criterion is changed (para 54, processing device changes the control parameter as the evaluation value changes).
As per claim 19, Murai et al. teach
The information processing method according to claim 17, further comprising setting the maximum time (para 41, a settling time has been adjusted according to the norm L1 and L2 of the operation condition, para 42, a norm of the operation data and the normative data has been calculated within a time of the determination interval. It implies that the interval refers a range with maximum value) the operation condition (para 4, the control parameter adjustment device extracts a settling feature from normative position data and the actual position data within an allowable range, the settling feature teaches operation condition), and the maximum number of times based on condition setting information input by a user(para 70, Fig. 10B, number of times the evaluation value has been changed depending on number of updates, “FIG. 10A is a diagram (the number of times the setting of the control parameter is changed by using the optimization algorithm, Also see ,Fig. 2, para 40, the data evaluation unit 131 performs discrete sampling on the operation data and the normative data at time tm (m=1 to n) the total time at n teach the elapsed time).
As per claim 20, Murai et al. teach
The information processing method according to claim 17, wherein the operation condition is preset for each device, the method further including setting the operation condition in accordance with the selected device based on device selection information input by a user (para 31-32, target device 910 is executing a predetermined tact according to the operation of the servo motor. Measuring instrument 920 directly measuring the predetermined speed, vibration and position. Also see para 40, an evaluation value for normative data/evaluation index is determined; para 34-35, normative data is stored in advance therefore predetermined).
As per claim 22, Murai et al. teach
An information optimization method comprising
by an information processing device(para 29), executing first optimization processing on information using a first evaluation criterion ( para 33 , “The manipulation receiving unit 100 instructs the target setting unit 11 and the control parameter setting unit 13 to execute a control parameter optimization process”, Also see para 40, normative data setting unit #112 set the normative data plurality of times): setting a search range of the information based on a plurality of evaluation values calculated in the first optimization processing (para 32 and 4; position of a target device is measured {para 32} and parameter adjustment is based on position reaching settling {para 4} within allowable value, para 54, settling value within allowable range according to the allowable value): and executing second optimization processing on the information regarding the set search range using a second evaluation criterion ( para 40, the process is executing plurality of times. Para 47, the process repeated here after).
As per claim 23, Murai et al. teach
An information processing device (para 29, CPU) that optimizes a plurality of control parameters in a device that performs a plurality of operations based on the plurality of control parameters, comprising a processor (para 29), wherein the processor in control parameter optimization processing,
selects a representative operation including at least one operation among all of the plurality of operations capable of being performed by the device (para 49, control parameter optimization and setting for operation of a specific purpose and situation. That is a representative operation from many operations for many purposes and situations),
causes the device to perform the representative operation, acquires measurement data regarding an operation of the device measured in performing the representative operation (para 39, Operation data acquisition unit 133 of Fig. 1 acquire actual operation data of the servo. Operation data is measured {para 75, #920 of Fig.1}),
calculates an evaluation value of a predetermined evaluation index based on the measurement data (para 40, evaluation value for normative data/evaluation index is determined; paras 34-35, normative data is stored in advance therefore predetermined),
updates the plurality of control parameters based on the evaluation value (S106 Fig.4), and the control parameter optimization processing is executed a plurality of times while an evaluation criterion of the control parameter optimization processing is being changed (paras 34-35, para 40, normative data setting unit #112 set the normative data plurality of times).
As per claim 24, Murai et al. teach
A computer-readable non-transitory recording medium (para 29) recording a program for causing an information processing device to perform a process, the information processing device optimizing a plurality of control parameters in a device that performs a plurality of operations based on the plurality of control parameters, wherein the information processing device, by executing the program, in the control parameter optimization processing,
selects a representative operation including at least one operation among all of the plurality of operations capable of being performed by the device (para 49, control parameter optimization and setting for operation of a specific purpose and situation. That is a representative operation from many operations for many purposes and situations),
causes the device to perform the representative operation, acquires measurement data regarding an operation of the device measured in performing the representative operation (para 39, Operation data acquisition unit 133 of Fig. 1 acquire actual operation data of the servo. Para 75, Operation data is measured {para 75, #920 of Fig.1}),
calculates an evaluation value of a predetermined evaluation index based on the measurement data (para 40, evaluation value for normative data/evaluation index is determined; paras 34-35, normative data is stored in advance therefore predetermined),
updates the plurality of control parameters based on the evaluation value, and the control parameter optimization processing is executed a plurality of times while an evaluation criterion of the control parameter optimization processing is being changed (para 40, normative data setting unit #112 set the normative data plurality of times).
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 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or no obviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 2-6, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Murai et al. (US 20180224810 A1.), and in view of Mizobe et al. (US 20230001578 A1.).
As per claim 2, Murai et al. teach
The information processing method according to claim 1, wherein the changing the evaluation (para 36, setting an allowable value depending on operation accuracy)
Although Murai et al. teach evaluation criterion/allowable value is based on operation accuracy (para 36) it is not explicitly teaching the changing the evaluation criterion includes changing the representative operation.
Therefore, Murai et al. do not teach
wherein the changing the evaluation criterion includes changing the representative operation.
In the same field of endeavor, Mizobe et al. teach
wherein the changing the evaluation criterion includes changing the representative operation (para 33-38; operations/motions M1-M5 are used and evaluated. See Fig.4 s230 and para 53).
It would have been obvious to a person ordinary skilled in the art, before the effective filing date of the claimed invention to modify the changing evaluation criterion operation taught by Murai et al. and to include the changing representative operation taught by Mizobe et al. into the system. This would have been obvious because both Murai et al. and Mizobe et al. teach an evaluation criterion by acquiring actual position data. By adding optimization processing step in S230, the actual position data acquisition will be more accurate (Mizobe et al., para 33-38, Fig. 4, Step S230, para 53).
As per claim 3, Murai et al. do not teach
The information processing method according to claim 2, wherein the changing the representative operation includes changing a number of operations in the representative operation.
In the same field of endeavor, Mizobe et al. teach
The information processing method according to claim 2, wherein the changing the representative operation includes changing a number of operations in the representative operation (more motions/operations for M3 are used, para 39).
It would have been obvious to a person ordinary skilled in the art, before the effective filing date of the claimed invention to modify the changing evaluation criterion operation taught by Murai et al. and to include the method for changing a number of operations taught by Mizobe et al. This would have been obvious because both Murai et al. and Mizobe et al. teach a method for evaluation criterion change by acquiring actual position data. By adding method for motions evaluation taught by Mizobe et al., the operations method can add more trials such as M1, M2, M3 towards upward, horizontal, and downward directions and plurality of motion evaluations will acquire more position data for evaluation. Therefore, performance index values and characteristic values in the respective motions can be respectively evaluated (Mizobe et al., more motions/operations for M3 are used, para 39).
As per claim 4, Murai et al. do not teach
The information processing method according to claim 3, wherein the changing the number of operations includes increasing the number of operations.
In the same field of endeavor, Mizobe et al. teach
The information processing method according to claim 3, wherein the changing the number of operations includes increasing the number of operations (more motions/operations for M3 are used, para 39).
It would have been obvious to a person ordinary skilled in the art, before the effective filing date of the claimed invention to modify the changing evaluation criterion operation taught by Murai et al. and to include the method for changing a number of operations taught by Mizobe et al. This would have been obvious because both Murai et al. and Mizobe et al. teach a method for evaluation criterion change by acquiring actual position data. By adding method for motions evaluation taught by Mizobe et al., the operations method can add more trials such as M1, M2, M3 towards upward, horizontal, and downward directions and plurality of motion evaluations will acquire more position data for evaluation. Therefore, more position data will be evaluated by the increasing number of operations. The performance of the index values and characterization values can be evaluated more precisely. (Mizobe et al., more motions/operations for M3 are used, para 39).
As per claim 5, Murai et al. do not teach
The information processing method according to claim 2, wherein the changing the representative operation includes changing contents of an operation included in the representative operation.
In the same field of endeavor, Mizobe et al. teach
The information processing method according to claim 2, wherein the changing the representative operation includes changing contents of an operation included in the representative operation (Para 36 and para 39, The Motion M3 is divided into three pieces and three different directions, therefore the contents of the operation of M3 has been changed).
It would have been obvious to a person ordinary skilled in the art, before the effective filing date of the claimed invention to modify the changing evaluation criterion operation taught by Murai et al. and to include the changing the content of operations taught by Mizobe et al. into the system. This would have been obvious because both Murai et al. and Mizobe et al. teach an evaluation criterion change by acquiring actual position data. By adding motions for evaluation method taught by Mizobe et al., the operations method can add more trials such as M1, M2, M3 towards upward, horizontal, and downward directions and plurality of motion evaluations will acquire more position data for evaluation. Therefore, performance index values and characteristic values in the respective motions can be respectively evaluated (Mizobe et al., more motions/operations for M3 are used, para 36, 39).
As per claim 6, Murai et al. do not teach
The information processing method according to claim 5, wherein the changing the contents of the operation includes making the contents of the operation complicated.
In the same field of endeavor, Mizobe et al. teach
The information processing method according to claim 5, wherein the changing the contents of the operation includes making the contents of the operation complicated (Paras 36-39, M3 is more complicated than other, Such as M3 has two different workpiece WK1 and WK2 moving in horizontal, upward and downward directions. Where M4 and M5 have less directions.).
It would have been obvious to a person ordinary skilled in the art, before the effective filing date of the claimed invention to modify the changing evaluation criterion operation taught by Murai et al. and to include the changing the content of operations taught by Mizobe et al. into the system. This would have been obvious because both Murai et al. and Mizobe et al. teach an evaluation criterion change by acquiring actual position data. By adding the complex method for content addition taught by Mizobe et al., the operations method can add more trials such as M1, M2, M3 towards upward, horizontal, and downward directions and plurality of motion evaluations will acquire more position data for evaluation through different workpiece. Therefore, performance index values and characteristic values in the respective motions can be respectively evaluated (Mizobe et al., more motions/operations for M3 are used, para 36, 39).
As per claim 21, Murai et al. teach
The information processing method according to claim 1, further comprising recording a performing time (Fig. 2, para 40, the data evaluation unit 131 performs discrete sampling on the operation data and the normative data at time tm (m=1 to n) the total time at n teach the elapsed time)
Murai et al. do not teach
The information processing method according to claim 1, further comprising recording operation history information including an operation condition for each operation performed by the device in the control parameter optimization processing.
In the same field of endeavor, Mizobe et al. teach
The information processing method according to claim 1, further comprising recording operation history information including an operation condition for each operation performed by the device in the control parameter optimization processing (Fig. 6, para 64, History of the objective function displaying the optimal solution, para 68, “The worker can use the history diagram of the objective function as a criterion for determination as to whether or not a satisfactory solution is obtained.” Also see para 78, the SC graph showing history of the constraints evaluation and worker may perform the operation to change the limit value with respect to the constraint evaluation value).
It would have been obvious to a person ordinary skilled in the art, before the effective filing date of the claimed invention to modify the recording the operation history method taught by Murai et al. and to include the recording history of operation condition method taught by Mizobe et al. into the system. This would have been obvious because both Murai et al. and Mizobe et al. teach an information processing method by obtaining data. By adding the obtaining history of portions condition data through SC graph, the user can change the limit value and obtain a satisfactory solution (Mizobe et al., paras 78,64,68)
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Murai et al. (US 20180224810 A1.), and in view of Mizobe et al. (US 20230001578 A1.), and further in view of Takano et al. (US 20220308531 A1.).
As per claim 14, the combination of Murai et al. and Mizobe et al. do not teach
The information processing method according to claim 12, wherein the evaluation operation is a differential operation between all the operations and a most recent representative operation with respect to the evaluation operation.
In the same field of endeavor, Takano et al. each
The information processing method according to claim 12, wherein the evaluation operation is a differential operation between all the operations and a most recent representative operation with respect to the evaluation operation (para 48, “First, of the command parameters 104 used in the evaluation operations in all the learning cycles”, “The command parameters 104 used in these evaluation operations are set as candidates for the optimum command parameter 104. Then, of the candidates of the command parameters 104, the command parameter 104 that has allowed the evaluation operation in which the deviation has fallen within the allowable range in the shortest time period from the start of the evaluation operation may be further selected and set as the optimum command parameter 104.”; That is first optimization parameter for all the evaluation operation for all cycles are used then out of those the {this teaches differential operation with respect to all operation} one that reach the allowable range in shortest time is used).
It would have been obvious to a person ordinary skilled in the art, before the effective filing date of the claimed invention, to modify evaluation operation taught by Murai et al. and Mizobe et al. and to include the differential evaluation method taught by Takano et al. This would have been obvious because the combination of Murai et al., Mizobe et al., and Takano et al. teach an information evaluation process by utilizing a control/command parameter. By adding the differential operation, the command parameter can set the candidates for the optimum command parameter and evaluate the deviation within the allowable range in a shortest time period. These candidates can be set for further evaluation to get the optimum solution (Takano et al. para 48).
Allowable Subject Matter
Claim 7 is objected to as being dependent upon a rejected base claim, but would be
allowable if rewritten in independent form including all of the limitations of the base claim and any
intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Please refer to the form 892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Rokeya Alam whose telephone number is (571)272-0083. The examiner can normally be reached on 7:30am - 4:30pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mr. Scott Baderman can be reached at telephone number (571-272-3644). The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/ROKEYA SHAWALI ALAM/Examiner, Art Unit 2118
/HOWARD CORTES/Primary Examiner, Art Unit 2118
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