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 .
Information Disclosure Statement
The references listed in the Information Disclosure Statements filed on 09/05/2024, 01/17/2025, 01/31/2025 and 06/10/2025 have been considered by the examiner (see attached PTO-1449 forms).
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 1-18, 20 and 21 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.
Claim 1 recites a calibration method, wherein the method comprises: obtaining an observation signal of a to-be-tested system; calculating a corresponding performance index based on the observation signal of the to-be- tested system; obtaining an updated calibration parameter by using an optimization algorithm based on the performance index, a constraint condition, and at least one objective function, wherein the objective function indicates a function relationship between performance indexes; and sending the updated calibration parameter to a controller…
Claim 12 recites a calibration apparatus, wherein the apparatus a transceiver; at least one processor; and one or more memories coupled to the at least one processor and storing programming instructions for execution by the at least one processor to cause the apparatus to: obtain, by using the transceiver, an observation signal of a to-be-tested system; calculate a corresponding performance index based on the observation signal of the to-be-tested system; obtain an updated calibration parameter by using an optimization algorithm based on the performance index, a constraint condition, and at least one objective function, wherein the objective function indicates a function relationship between performance indexes; and send, by using the transceiver, the updated calibration parameter to a controller…
Claim 20 recites a calibration system, wherein the calibration system comprises a controller and a calibration apparatus, and the controller is coupled to the calibration apparatus, and wherein the calibration apparatus comprises: a transceiver; at least one processor; and one or more memories coupled to the at least one processor and storing programming instructions for execution by the at least one processor to cause the apparatus to: obtain, by using the transceiver, an observation signal of a to-be-tested system; calculate a corresponding performance index based on the observation signal of the to-be- tested system; obtain an updated calibration parameter by using an optimization algorithm based on the performance index, a constraint condition, and at least one objective function, wherein the objective function indicates a function relationship between performance indexes; and send, by using the transceiver, the updated calibration parameter to a controller…
and thus grouped as Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations.
These judicial exceptions are not integrated into a practical application because the additional elements, the data gathering step, (claim 1) “obtaining an observation signal of a to-be-tested system” (claim 12) “obtain, by using the transceiver, an observation signal of a to-be-tested system” (claim 20) “obtain, by using the transceiver, an observation signal of a to-be-tested system” are mere data gathering that do not add a meaningful limitation to the method as they are insignificant extra-solution activity. Furthermore, the additional elements (claims 12 and 20) the “at least one processor; and one or more memories coupled to the at least one processor and a controller and a calibration apparatus, and the controller is coupled to the calibration apparatus” are recited as performing generic computer functions routinely used in computer applications. Generic computer components recited as performing generic computer functions amount to no more than using a computer as a tool to perform an abstract idea. Regarding claims 1, 12 and 20, the recitation, “sending the updated calibration parameter to a controller, send, by using the transceiver, the updated calibration parameter to a controller and send, by using the transceiver, the updated calibration parameter to a controller,” the elements are considered insignificant extra-solution activity to the judicial exception – see MPEP 2106.05(g). All of which are considered not indicative of integration into a practical application (see MPEP 2106.04(d)).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are considered extra-solution activity of pre-solution and post-solution activity which fall under insignificant extra solution activity and deemed insufficient to qualify as “significantly more” - see MPEP 2106.05(g). The additional elements of the processor are mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and deemed insufficient to qualify as “significantly more” see MPEP 2106.05(f).
Dependent claims 2-11, 13-18, and 20-21 when analyzed as a whole are patent ineligible under 35 U.S.C. §101 because the dependent claims fail to establish that the claims are not directed to an abstract idea as they are directed mathematical concepts and/or mental processes and do not add significantly more to the abstract idea.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-18, 20 and 21 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Storfer Gerhard et al. [WO 2020/102842 A1 (Machine Translation)].
Regarding claim 1, Storfer Gerhard teaches a calibration method, wherein the method comprises:
obtaining an observation signal of a to-be-tested system (a number of data elements Dei – page 3);
calculating a corresponding performance index based on the observation signal of the to-be- tested system (first calibration data set DS1 is integrated with a plurality of data elements DEi to be calibrated. Each data element DEi in turn has a certain number of data attributes Dai – page 3) (Matching two data elements DEi of the two data sets DS1, DS2 – page 7);
obtaining an updated calibration parameter by using an optimization algorithm (Similarity model is, for example, a so-called binary decision, which can be used – page 6) based on the performance index, a constraint condition, and at least one objective function, wherein the objective function indicates a function relationship between performance indexes (suitable similarity model 10, and a similarity value AWi between meaningful data attributes DAri of the second calibration data set DS2 and meaningful data attributes DAri of the first Calibration data set DS1 – page 6); and
sending the updated calibration parameter (control parameters) to a controller (control unit) (interface for transmitting the calibration values is preferably provided as the vehicle component, wherein the calibration values are transmitted from the input unit to the control unit via the interface – page 2).
Regarding claim 2, Storfer Gerhard teaches the performance index comprises an objective-type performance index and a subjective-feeling-type performance index, the at least one objective function comprises at least one of an objective-type objective function or a subjective-type objective function, the objective-type objective function is a weighted sum of a plurality of objective-type performance indexes, a sum of weighting coefficients of the plurality of objective-type performance indexes is 1, the subjective-type objective function is a weighted sum of a plurality of subjective-feeling-type performance indexes, and a sum of weighting coefficients of the plurality of subjective-feeling-type performance indexes is 1 (Weighting unit E by means of a suitable weighting model 1 in order to increase the probability of also assigning the data element DEi of the second calibration data set DS2 – page 7).
Regarding claim 3, Storfer Gerhard teaches the method further comprises: determining a type of the calibration parameter, wherein the type of the calibration parameter comprises a map type (for example, numerical value, characteristic curve, characteristic map page 5) (self-organizing map, characteristic map – page 6) and a table type (end of page 6 - table below, some data attributes DAi are listed by way of example (first column), with the respective values in the two datasets DS1 (second column) and DS2 (third column) and page 7, see table); and determining an initial coupling factor between calibration parameters based on the type of the calibration parameter and an initial value of the calibration parameter.
Regarding claim 4, Storfer Gerhard teaches a quantity of initial coupling factors is less than a quantity of calibration parameters (weighting factors - page 8).
Regarding claim 5, Storfer Gerhard teaches the obtaining an updated calibration parameter by using an optimization algorithm based on the performance index, a constraint condition, and at least one objective function comprises: obtaining an updated coupling factor by using the optimization algorithm based on the performance index, the constraint condition, the at least one objective function, and a coupling factor used before updating, wherein the coupling factor used before updating comprises an initial coupling factor (At the end of the method, the data elements DEi of the second are assigned calibration data set DS2 – page 7).
Regarding claim 6, Storfer Gerhard teaches the calculating a corresponding performance index based on the observation signal of the to-be-tested system comprises: when the observation signal meets a first preset condition, performing data processing on the observation signal, and calculating the corresponding performance index based on a processed observation signal (Matching two data elements DEi of the two data sets DS1, DS2 – page 7).
Regarding claim 7, Storfer Gerhard teaches the method further comprises: generating exception alarm information when an exception occurs in a calibration process of the to-be-tested system, wherein the exception alarm information is used to prompt a user with a calibration exception (the calibration values are transmitted from the input unit to the control unit via the interface…. to the correct user responsible … – page 2).
Regarding claim 8, Storfer Gerhard teaches the method further comprises: generating a calibration report when a value of the at least one objective function meets a second preset condition, wherein the calibration report comprises at least one of the performance index, objective function value distribution, an optimal calibration parameter, or an important observation pattern (the calibration values are transmitted from the input unit to the control unit via the interface…. to the correct user responsible … – page 2).
Regarding claim 9, Storfer Gerhard teaches the optimization algorithm comprises at least one of the following: a Bayesian optimization algorithm, a particle swarm optimization algorithm, a genetic algorithm, and a machine learning algorithm (a neural network is preferably used as weighting model 1, particularly preferably a recurrent or feedback neural network (RNN) – page 7, last paragraph).
Regarding claim 10, Storfer Gerhard teaches the constraint condition comprises at least one of a constraint condition of the observation signal, a constraint condition of the performance index, a constraint condition of an objective function value, or a constraint condition of a coupling factor between the calibration parameters (suitable similarity model 10, and a similarity value AWi between meaningful data attributes DAri of the second calibration data set DS2 and meaningful data attributes DAri of the first Calibration data set DS1 – page 6).
Regarding claim 11, Storfer Gerhard teaches the method further comprises: sending prompt information to the controller, wherein the prompt information is used to prompt a user with at least one of a calibration start or a calibration end (control unit) (interface for transmitting the calibration values is preferably provided as the vehicle component, wherein the calibration values are transmitted from the input unit to the control unit via the interface – page 2).
Regarding claim 12, Storfer Gerhard teaches a calibration apparatus, wherein the apparatus a transceiver; at least one processor; and one or more memories coupled to the at least one processor and storing programming instructions for execution by the at least one processor to cause the apparatus to (implemented in at least one computing unit in the form of software – page 2):
obtain, by using the transceiver (an interface for transmitting – page 2), an observation signal of a to-be-tested system (a number of data elements Dei – page 3);
calculate a corresponding performance index based on the observation signal of the to-be-tested system (first calibration data set DS1 is integrated with a plurality of data elements DEi to be calibrated. Each data element DEi in turn has a certain number of data attributes Dai – page 3) (Matching two data elements DEi of the two data sets DS1, DS2 – page 7);
obtain an updated calibration parameter by using an optimization algorithm (Similarity model is, for example, a so-called binary decision, which can be used – page 6) based on the performance index, a constraint condition, and at least one objective function, wherein the objective function indicates a function relationship between performance indexes (suitable similarity model 10, and a similarity value AWi between meaningful data attributes DAri of the second calibration data set DS2 and meaningful data attributes DAri of the first Calibration data set DS1 – page 6); and
send, by using the transceiver, the updated calibration parameter (control parameters) to a controller (control unit) (interface for transmitting the calibration values is preferably provided as the vehicle component, wherein the calibration values are transmitted from the input unit to the control unit via the interface – page 2).
Regarding claim 13, Storfer Gerhard teaches the performance index comprises an objective-type performance index and a subjective-feeling-type performance index, the at least one objective function comprises at least one of an objective-type objective function or a subjective-type objective function, the objective-type objective function is a weighted sum of a plurality of objective-type performance indexes, a sum of weighting coefficients of the plurality of objective-type performance indexes is 1, the subjective-type objective function is a weighted sum of a plurality of subjective-feeling-type performance indexes, and a sum of weighting coefficients of the plurality of subjective-feeling-type performance indexes is 1 (Weighting unit E by means of a suitable weighting model 1 in order to increase the probability of also assigning the data element DEi of the second calibration data set DS2 – page 7).
Regarding claim 14, Storfer Gerhard teaches the programming instructions, when executed by the at least one processor, cause the apparatus to: determine a type of the calibration parameter, wherein the type of the calibration parameter comprises a map type (for example, numerical value, characteristic curve, characteristic map page 5) (self-organizing map, characteristic map – page 6) and a table type (end of page 6 - table below, some data attributes DAi are listed by way of example (first column), with the respective values in the two datasets DS1 (second column) and DS2 (third column) and page 7, see table); and determine an initial coupling factor between calibration parameters based on the type of the calibration parameter and an initial value of the calibration parameter.
Regarding claim 15, Storfer Gerhard teaches a quantity of initial coupling factors is less than a quantity of calibration parameters (weighting factors - page 8).
Regarding claim 16, Storfer Gerhard teaches the programming instructions, when executed by the at least one processor, cause the apparatus to obtain an updated coupling factor by using the optimization algorithm based on the performance index, the constraint condition, the at least one objective function, and a coupling factor used before updating, wherein the coupling factor used before updating comprises an initial coupling factor (At the end of the method, the data elements DEi of the second are assigned calibration data set DS2 – page 7).
Regarding claim 17, Storfer Gerhard teaches the programming instructions, when executed by the at least one processor, cause the apparatus to: when the observation signal meets a first preset condition, perform data processing on the observation signal, and calculate the corresponding performance index based on a processed observation signal (Matching two data elements DEi of the two data sets DS1, DS2 – page 7).
Regarding claim 18, Storfer Gerhard teaches the programming instructions, when executed by the at least one processor, cause the apparatus to generate exception alarm information when an exception occurs in a calibration process of the to-be-tested system, wherein the exception alarm information is used to prompt a user with a calibration exception (the calibration values are transmitted from the input unit to the control unit via the interface…. to the correct user responsible … – page 2).
Regarding claim 20, Storfer Gerhard teaches a calibration system, wherein the calibration system comprises a controller and a calibration apparatus (e method according to the invention is in particular a computer-assisted method which is carried out on at least one computing unit – page 3), and the controller is coupled to the calibration apparatus (control unit – page 2), and wherein the calibration apparatus comprises: a transceiver (an interface for transmitting – page 2); at least one processor; and one or more memories coupled to the at least one processor and storing programming instructions for execution by the at least one processor to cause the apparatus to (implemented in at least one computing unit in the form of software – page 2):
obtain, by using the transceiver (an interface for transmitting – page 2), an observation signal of a to-be-tested system (a number of data elements Dei – page 3);
calculate a corresponding performance index based on the observation signal of the to-be- tested system (first calibration data set DS1 is integrated with a plurality of data elements DEi to be calibrated. Each data element DEi in turn has a certain number of data attributes Dai – page 3) (Matching two data elements DEi of the two data sets DS1, DS2 – page 7);
obtain an updated calibration parameter by using an optimization algorithm (Similarity model is, for example, a so-called binary decision, which can be used – page 6) based on the performance index, a constraint condition, and at least one objective function, wherein the objective function indicates a function relationship between performance indexes (suitable similarity model 10, and a similarity value AWi between meaningful data attributes DAri of the second calibration data set DS2 and meaningful data attributes DAri of the first Calibration data set DS1 – page 6); and
send, by using the transceiver, the updated calibration parameter (control parameters) to a controller (control unit) (interface for transmitting the calibration values is preferably provided as the vehicle component, wherein the calibration values are transmitted from the input unit to the control unit via the interface – page 2).
Regarding claim 21, Storfer Gerhard teaches the performance index comprises an objective-type performance index and a subjective-feeling-type performance index, the at least one objective function comprises at least one of an objective-type objective function or a subjective-type objective function, the objective-type objective function is a weighted sum of a plurality of objective-type performance indexes, a sum of weighting coefficients of the plurality of objective-type performance indexes is 1, the subjective-type objective function is a weighted sum of a plurality of subjective-feeling-type performance indexes, and a sum of weighting coefficients of the plurality of subjective-feeling-type performance indexes is 1 (Weighting unit E by means of a suitable weighting model 1 in order to increase the probability of also assigning the data element DEi of the second calibration data set DS2 – page 7).
Relevant Prior Art / Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Zhao et al. (US Patent Application Publication 2023/0150518 A1) discloses calibration of sensors in autonomous vehicle applications;
Castorena Martinez et al. (US Patent Application Publication 2021/0215505 A1) discloses a vehicle sensor calibration system for correcting errors in sensor data;
Anderson et al. (US Patent Application Publication 2016/0377650 A1) discloses a system and method for correcting calibration estimates of acceleration data in a vehicle.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RICKY GO whose telephone number is (571)270-3340. The examiner can normally be reached on Monday through Friday from 9:00 a.m. to 5:30 p.m.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Arleen M. Vazquez can be reached on (571) 272-2619. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RICKY GO/Primary Examiner, Art Unit 2857
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