DETAILED ACTION
This action is responsive to the following communications: the application filed on March 28, 2024.
Claims 1-20 are presented for Examination. Claims 1, 10 and 19 are independent.
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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
In claims 1, 10 and 19 recite the limitations of “a magnitude of a characteristic associated with the first amount of activation of the trigger” renders the claim indefinite because one of ordinary skill in the art would not be able to determine with reasonable certainty what "characteristic" is being measured. The specification may describe rate of change, acceleration, or other parameters, but the claim language is broad enough to encompass any measurable attribute, making the claim scope unclear. For the examination purpose these limitations will be treated as rate of change, acceleration, or other parameters.
In claim 1 recites the limitations of “first amount of activation" and "second amount of activation” which are indefinite because it is unclear whether these refer to physical trigger positions, electrical signal levels, or virtual/interpreted activation values. The claim requires the second amount to be "different than the first amount," but the basis for comparison is undefined.
In claim 2 recites "detect a change in the magnitude of the characteristic associated with the first amount of activation." It is unclear what baseline or reference is used to detect a "change" and over what time period. The claim does not specify whether this is a rate of change, a comparison to a previous value, or some other metric.
In claim 3 recites " modify a parameter that is used to adjust the modified trigger signal." which is indefinite because the "modified trigger signal" has already been generated according to parent Claim 1. It is unclear whether this limitation refers to adjusting the already-modified signal or to parameters that will affect future trigger signal modifications.
In claims 5 and 14 recite "apply one or more constraints to the modified trigger signal to limit an amount of modification" is indefinite because neither the nature of the constraints nor the metric for measuring "amount of modification" is specified. One of ordinary skill would not be able to determine what constraints fall within the claim scope.
In claims 6 and 15, recite "the sensor is related to a position of the trigger" is indefinite because the required relationship between the sensor and trigger position is unclear. This could encompass a sensor that directly measures position, a sensor that measures a parameter affected by position, or virtually any sensor that has some connection to trigger operation.
In claims 7 and 16, recite "smoothness" and "amount of advancement" in the Markush group are indefinite. "Smoothness" could refer to motor operation, trigger response, output shaft movement, or other parameters. "Amount of advancement" does not clearly indicate what is being advanced (fastener, motor rotation, trigger position, etc.).
In claims 9 and 18, recite "modify the trained machine learning model based on the feedback" is indefinite because it is unclear what type of modification is required. Modifying a machine learning model could mean retraining, updating weights, changing hyperparameters, or other operations. One of ordinary skill would not know the scope of "modify" in this context.
In claims 19 recites that the controller "modify the trigger signal" and also "modify a parameter that is used to adjust the modified trigger signal." The distinction between "modify" and "adjust" is unclear, and it is uncertain whether these are the same operation, sequential operations, or independent operations.
Appropriate correction is requested.
Since the independent claims 1, 10 and 19 are rejected under 35 U.S.C. 112(b) and hence the dependent claims of 1, 10 and 19 are also rejected under 35 U.S.C. 112(b).
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 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Mergener et al (US 2016/0311094).
Regarding independent claim 1, Mergener et al disclose that a power tool (Fig.2) comprising:
a housing (Fig.2);
a motor (Fig.3:214) located within the housing and coupled to an output member;
a motor drive circuit (Fig.3:216) configured to drive the motor;
a trigger (Fig.3:212) configured to generate a trigger signal related to an activation of the trigger; and
an electronic controller (Fig.3:226) connected to the motor drive circuit, the electronic controller configured to:
receive the trigger signal from the trigger, the trigger signal corresponding to a first amount of activation(([0051]; “CLOSED”)) of the trigger([0043];” The trigger 212 is moveably coupled to the handle 204 such that the trigger 212 moves with respect to the tool housing “),
determine a magnitude of a characteristic associated with the first amount of activation of the trigger ([0043]; “The trigger 212 is coupled to a push rod, which is engageable with a trigger switch”),
modify the trigger signal based on the magnitude of the characteristic, the modified trigger signal corresponding to a second amount of activation(([0051]; “OPEN”)) of the trigger, the second amount of activation of the trigger being different than the first amount of activation of the trigger, and
control the motor drive circuit to drive the motor based on the modified trigger signal ([0043];” The trigger 212 is moveably coupled to the handle 204 such that the trigger 212 moves with respect to the tool housing “).
Regarding claim 2, Mergener et al disclose that wherein, to modify the trigger signal based on the magnitude of the characteristic, the electronic controller is configured to:
detect a change in the magnitude of the characteristic associated with the first amount of activation of the trigger; and
adjust the trigger signal based on the change that is detected, the adjusted trigger signal corresponding to the second amount of activation of the trigger ([0043] “ the electrical trigger switch 213 may be activated by, for example, a position sensor (e.g., a Hall-Effect sensor) that relays information about the relative position of the trigger 212 to the electrical trigger switch” and [0058]).
Regarding claim 3, Mergener et al disclose that further comprising a communication interface connected to the electronic controller, the communication interface configured to communicate with an external device,
wherein, to modify the trigger signal based on the magnitude of the characteristic, the electronic controller is further configured to:
receive, via the communication interface, a configuration setting of the power tool, a value for the configuration setting being selected via a user input on the external device, and
modify a parameter that is used to adjust the modified trigger signal based on the configuration setting([0043] “ the electrical trigger switch 213 may be activated by, for example, a position sensor (e.g., a Hall-Effect sensor) that relays information about the relative position of the trigger 212 to the electrical trigger switch”).
Regarding claims 4 and 13, Mergener et al disclose that wherein the parameter is a kick parameter or a filter parameter ([0074]; “filters”).
Regarding claims 5 and 14 , Mergener et al disclose that wherein, to modify the trigger signal based on the magnitude of the characteristic, the electronic controller is further configured to apply one or more constraints to the modified trigger signal to limit an amount of modification to the trigger signal ([0051]; “When the push button is activated, such as by the push rod discussed above, the electrical contacts are in a CLOSED position”).
Regarding claim 6, Mergener et al disclose that further comprising a sensor coupled to the electronic controller, the sensor configured to provide a sensor signal,
wherein the electronic controller is configured to:
receive the sensor signal, and
adjust the modified trigger signal based on the sensor signal,
wherein the sensor is related to a position of the trigger ([0043]; “a position sensor (e.g., a Hall-Effect sensor) that relays information about the relative position of the trigger 212 to the electrical trigger switch”).
Regarding claim 7, Mergener et al disclose that wherein the electronic controller is further configured to:
receive feedback information related to the modified trigger signal, the feedback information is selected from a group consisting of: overshoot, undershoot, smoothness, motor efficiency, and amount of advancement, and
modify a parameter that is used to adjust the modified trigger signal based on the received feedback information (Fig.18).
Regarding claim 8, Mergener et al disclose that wherein the electronic controller includes memory that includes a trained machine learning model,
wherein the electronic controller is further configured to:
process, with the trained machine learning model, the trigger signal from the trigger, and
generate a target output that includes the modified trigger signal ([0055]; a memory 232).
Regarding claim 9, Mergener et al disclose that further comprising a communication interface connected to the electronic controller, the communication interface configured to communicate with an external device,
wherein the electronic controller is further configured to:
receive feedback regarding a performance of the trained machine learning model from at least one selected from a group consisting of: users via the communication interface, one or more sensors included in the power tool, or both, and
modify the trained machine learning model based on the feedback (Fig.18 and [0060]).
Regarding independent claim 10, Mergener et al disclose that a method for implementing a dynamic trigger response to control a power tool(Fig.2), the method comprising:
receiving a trigger signal from a trigger of the power tool, the trigger signal corresponding to a first amount of activation ([0051]; “OPEN”) of the trigger ([0043];” The trigger 212 is moveably coupled to the handle 204 such that the trigger 212 moves with respect to the tool housing “);
determining a magnitude of a characteristic associated with the first amount of activation of the trigger([0043]; “The trigger 212 is coupled to a push rod, which is engageable with a trigger switch”);
modifying the trigger signal based on the magnitude of the characteristic, the modified trigger signal corresponding to a second amount of activation(([0051]; “OPEN”)) of the trigger, the second amount of activation of the trigger being different than the first amount of activation of the trigger; and
driving a motor of the power tool based on the modified trigger signal ([0043] “ the electrical trigger switch 213 may be activated by, for example, a position sensor (e.g., a Hall-Effect sensor) that relays information about the relative position of the trigger 212 to the electrical trigger switch” and [0058]).
Regarding claim 11, Mergener et al disclose that wherein modifying the trigger signal based on the magnitude of the characteristic includes:
detecting a change in the magnitude of the characteristic associated with the first amount of activation of the trigger; and
adjusting the trigger signal based on the change, the adjusted trigger signal corresponding to the second amount of activation of the trigger ([0043] “ the electrical trigger switch 213 may be activated by, for example, a position sensor (e.g., a Hall-Effect sensor) that relays information about the relative position of the trigger 212 to the electrical trigger switch” and [0058]).
Regarding claim 12, Mergener et al disclose that wherein modifying the trigger signal based on the magnitude of the characteristic includes:
receiving a selection of a value for a configuration setting of the power tool; and
modifying a parameter that is used to adjust the modified trigger signal based on the configuration setting. ([0043] “ the electrical trigger switch 213 may be activated by, for example, a position sensor (e.g., a Hall-Effect sensor) that relays information about the relative position of the trigger 212 to the electrical trigger switch”).
Regarding claim 15, Mergener et al disclose that receiving a sensor signal from a sensor; and
adjusting the modified trigger signal based on the sensor signal;
wherein the sensor signal is related to a position of the trigger ([0053]).
Regarding claim 16, Mergener et al disclose that receiving feedback information related to the modified trigger signal, the feedback information is selected from a group consisting of: overshoot, undershoot, signal smoothness, motor efficiency, and amount of advancement; and
modifying a parameter that is used to adjust the modified trigger signal(Fig. 18).
Regarding claim 17, Mergener et al disclose that processing, with a trained machine learning model, the trigger signal from the trigger; and
generating a target output that includes the modified trigger signal ([0055]).
Regarding claim 18, Mergener et al disclose that further comprising:
receiving feedback regarding a performance of the trained machine learning model from one or more users of the power tool, one or more sensors included in the power tool, or both; and
modifying the trained machine learning model based on the feedback. (Fig.18).
Regarding independent claim 19, Mergener et al disclose that 19. A power tool comprising:
a housing(Fig.2);
a motor (Fig.3:214) located within the housing and coupled to an output member;
a motor drive circuit (Fig.3:216) configured to drive the motor;
a trigger (Fig.3:212) configured to generate a trigger signal related to an activation of the trigger; and
an electronic controller (Fig.3:226) coupled to the motor drive circuit, the electronic controller configured to:
receive the trigger signal from the trigger, the trigger signal corresponding to a first amount of activation (([0051]; “CLOSED”)) of the trigger([0043];” The trigger 212 is moveably coupled to the handle 204 such that the trigger 212 moves with respect to the tool housing “),
determine a magnitude of a characteristic associated with the first amount of activation of the trigger ([0043]; “The trigger 212 is coupled to a push rod, which is engageable with a trigger switch”),
detect a change in the magnitude of the characteristic associated with the first amount of activation of the trigger([0051]),
modify the trigger signal based on the detected change in the magnitude of the characteristic, the modified trigger signal corresponding to a second amount of activation of the trigger ([0051]; “OPEN”), the second amount of activation of the trigger being different than the first amount of activation of the trigger,
control the motor drive circuit to drive the motor based on the modified trigger signal,
receive feedback information related to the modified trigger signal, and
modify a parameter that is used to adjust the modified trigger signal based on the received feedback information ([0043];” The trigger 212 is moveably coupled to the handle 204 such that the trigger 212 moves with respect to the tool housing “).
Regarding claim 20, Mergener et al disclose that wherein the feedback information is selected from a group consisting of: an overshoot value, an undershoot value, a smoothness value, motor efficiency, and an amount of advancement (Fig.18 and [0060]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MUHAMMAD S ISLAM whose telephone number is (571)272-8439. The examiner can normally be reached on 9:30am to 6:00pm.
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/MUHAMMAD S ISLAM/Primary Examiner, Art Unit 2846