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 .
Response to Arguments
Applicant’s arguments, see Page 6, filed 12/01/2025, with respect to the rejection(s) of claim(s) 16 under 102 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Lawrence (GB 2490256 A) in view of Delmas (EP 0636341 A1)
Applicant’s arguments, see Page 6, filed 12/01/2025, with respect to the rejection(s) of claim(s) 1-15 under 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Lawrence (GB 2490256 A) in view of Delmas (EP 0636341 A1) and Brown (US 20140008087 A1).
Applicant's remaining arguments filed 12/01/2025 have been fully considered but they are not persuasive.
While Examiner concedes to Applicants assertion that Lawrence does not disclose filtering of sensor signals, Examiner does not rely on Lawrence to disclose this feature but instead relies on Brown.
Regarding applicants’ arguments with respect to Brown not curing Lawrence’s deficiencies,
applicant first argues that the claimed pre-processing step is part of a multi-sensor usage-classification pipeline that prepares sensor data for a subsequent classification step generating a plurality of control signals, and that brown is merely concerned with conditioning a single audio channel before digitization.
Applicant further argues that Brown only supplies generic analog to digital audio filtering. However, the claim does not require any specific methods of filtering the signals, other than that they are filtered as part of a pre-processing step, which Brown teaches.
In response to applicant's argument that Brown is nonanalogous art, it has been held that a prior art reference must either be in the field of the inventor’s endeavor or, if not, then be reasonably pertinent to the particular problem with which the inventor was concerned, in order to be relied upon as a basis for rejection of the claimed invention. See In re Oetiker, 977 F.2d 1443, 24 USPQ2d 1443 (Fed. Cir. 1992). In this case, Brown and Lawrence are both related to processing signals in relation to a vacuum cleaner.
Regarding Applicants’ arguments pointed towards Claim 3, Applicant argues that Claim 3, adds the pre-processing step comprises extracting features from time portions of the generated sensor signals and further comprises band-pass and low-pass filters. Examiner only relies on Usselman to further disclose band and low pass filters in signal processing.
In response to applicant's argument that Usselman is nonanalogous art, it has been held that a prior art reference must either be in the field of the inventor’s endeavor or, if not, then be reasonably pertinent to the particular problem with which the inventor was concerned, in order to be relied upon as a basis for rejection of the claimed invention. See In re Oetiker, 977 F.2d 1443, 24 USPQ2d 1443 (Fed. Cir. 1992). In this case, Both Usselman and Brown are related towards utilizing filters to eliminate noise from signals.
In response to applicants arguments regarding Claims 9, 10, 11, 13, and 14. Applicant argues that the goals and objectives of the additional references used in the rejection of these claims are pointed towards a different objective to the instant application, and one of ordinary skill in the art before the effective filling date of the invention would not be motivated to incorporate the teachings of these references with those of Lawrance and Brown. it has been held that a prior art reference must either be in the field of the inventor’s endeavor or, if not, then be reasonably pertinent to the particular problem with which the inventor was concerned, in order to be relied upon as a basis for rejection of the claimed invention. See In re Oetiker, 977 F.2d 1443, 24 USPQ2d 1443 (Fed. Cir. 1992).
In this case: Regarding, claim 9 Gangon is concerned with detecting and processing signals relating to if a tool is attached to the cleaner, which is reasonably pertinent to the subject matter of claim 9, and thus the particular problem the inventor was concerned with.
Regarding Claim 10, Hong is concerned with a robotic vacuum cleaner and teaches a type of sensor that can be used to determine contact and orientation of the cleaner, while the instant application is concerned with processing sensor signals.
Hird, used in the rejection of claim 13, is reasonably pertinent for the reasons as Hong used in the rejection of claim 10.
Tsuboi, used in the rejection of claim 14, discloses a cleaner controller implemented in software, and is not relied on to teach the claimed pre-processing/classification steps but to disclose the controls (such as the ones taught by Lawrence as modified) being implemented in software.
Regarding Applicants arguments with respect to claim 15, Applicant argues that Lawrence fails to disclose the claimed pipeline for the same as set forth with respect to claim 1, which is not found persuasive for the reasons outlined above.
Finally, in response to applicants arguments with respect to distinction on objective, the fact that the inventor has recognized another advantage which would flow naturally from following the suggestion of the prior art cannot be the basis for patentability when the differences would otherwise be obvious. See Ex parte Obiaya, 227 USPQ 58, 60 (Bd. Pat. App. & Inter. 1985).
In specific response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971).
In this case, the argued references disclose broad methods of processing, obtaining and analyzing data for a vacuum cleaner, as discussed above, and are cited to teach that such methods (detecting an attachment, machine learning, utilizing an IMU, applying filters to signals) are known in the art for controlling a vacuum cleaner to operate in a desired way.
Additionally, the test for obviousness is not whether the features of a secondary reference may be bodily incorporated into the structure of the primary reference; nor is it that the claimed invention must be expressly suggested in any one or all of the references. Rather, the test is what the combined teachings of the references would have suggested to those of ordinary skill in the art. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981). As such modifying Lawrence in view of Brown to filter input signals from the sensors of Lawrence does not require fully importing the objective of the base reference (the tool-sound triggered start) into Lawrence, but instead merely discloses that the use of filters in signal processing is known and advantageous.
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 (i.e., changing from AIA to pre-AIA ) 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.
Claim(s) 16 is rejected under 35 U.S.C. 103 as being unpatentable over Lawrence (GB 2490256 A) in view of Delmas (EP 0636341 A1)
Regarding Claim 16, Lawrence discloses
a non-transitory computer readable storage medium having stored thereon a computer program comprising a set of instructions, which, when executed by a computerized device, cause the computerized device to perform a method of operating a vacuum cleaner, the method comprising (See Page 7 Line 1-7 “The main body 3 further comprises a control PCB 25, for controlling at least some of the electric functions of the vacuum cleaner 1, a clock 26 and an indicator 29. The control PCB 25 comprises a processor/receiver 27 for receiving wireless signals transmitted by one or other, or both, of the first wireless transmitter 19 and the second wireless transmitter 23. in this embodiment, the processor/receiver 27 is shown as one device integral with the control PCB 25.”):
generating sensor signals by a plurality of sensors of the vacuum cleaner (See Page 4 Lines 4-8 “Preferably, the first sensor is a motion sensor and the second sensor is a touch sensor. Thus the signals output from the first and second sensors may indicate different states of the machine, i.e. whether it is in the first use state or the second non-use state. Both sensors may be touch sensors, or both sensors may be motion sensors.”); And suggests but does not explicitly disclose
at a first module of a controller, processing the sensor signals to generate a plurality of control signals (See Page 7 Line 9-13 “The processor/receiver 27 may be two devices: a receiving device for receiving the transmitted signals and a processing device for processing the received signals, both of which devices may be integral with the control PCB 25. The processor/receiver 27 and the receiving device and/or processing device may be separate from the control PCB 25.”)
at a second module of the controller, processing the plurality of control signals to generate an output signal indicating that the vacuum cleaner is currently being used (See Page. 10 “On detection of either the first signal (step 9) or the second signal (step 10), or both of the first and second signals (step 11), the power management system is powers up the motor, stops outputting the indicator signal such that the LED 29 turns off and resets the power management system, such that the stored value of the first time period is removed from the power management system (step 12). The automatic powering up of the motor avoids the user having to take any additional steps, such as pressing a button, before they begin to use the vacuum cleaner 1.”); and
activating or deactivating a vacuum motor of the vacuum cleaner in dependence on the output signal (Page 9-10,
“On entering the idle mode, the power management system outputs an indicator signal to the LED 29 (step 8) causing the LED 29 to flash I0 intermittently. The LED 29 may light continuously instead. The LED indicates to the user that the vacuum cleaner 1 is in the idle mode. When the vacuum cleaner us left unattended and has entered the idle mode, a user may pick up the wand 13 or may begin moving the vacuum cleaner I with or without holding the upper portion 14 of the wand 13. A user picking up the upper portion 14 of the wand 13 so as to touch the touch sensor 17 will cause the touch sensor I 7 to output the second signal indicating that the vacuum cleaner Us in use. Movement of the vacuum cleaner I will cause the motion sensor 21 to output the first signal indicating that the vacuum cleaner I is in use.
On detection of either the first signal (step 9) or the second signal (step 10), or both of the first and second signals (step 11), the power management system is powers up the motor, stops outputting the indicator signal such that the LED 29 turns off and resets the power management system, such that the stored value of the first time period is removed from the power management system (step 12). The automatic powering up of the motor avoids the user having to take any additional steps, such as pressing a button, before they begin to use the vacuum cleaner 1.”).
Examiner notes that while Lawrence does not explicitly disclose a separate first and second module, at a first module of a controller, processing the sensor signals to generate a plurality of control signals;
at a second module of the controller, processing the plurality of control signals to generate an output signal indicating that the vacuum cleaner is currently being used; and Lawrence does generally disclose the concept of a controller receiving generated sensor signals, processing them into an output signal, and the vacuum motor is configured to activate or deactivate in dependence on the output signal (Page 9-10,
“On entering the idle mode, the power management system outputs an indicator signal to the LED 29 (step 8) causing the LED 29 to flash intermittently. The LED 29 may light continuously instead. The LED indicates to the user that the vacuum cleaner 1 is in the idle mode. When the vacuum cleaner us left unattended and has entered the idle mode, a user may pick up the wand 13 or may begin moving the vacuum cleaner I with or without holding the upper portion 14 of the wand 13. A user picking up the upper portion 14 of the wand 13 so as to touch the touch sensor 17 will cause the touch sensor I 7 to output the second signal indicating that the vacuum cleaner is in use. Movement of the vacuum cleaner I will cause the motion sensor 21 to output the first signal indicating that the vacuum cleaner I is in use.
On detection of either the first signal (step 9) or the second signal (step 10), or both of the first and second signals (step 11), the power management system is powers up the motor, stops outputting the indicator signal such that the LED 29 turns off and resets the power management system, such that the stored value of the first time period is removed from the power management system (step 12). The automatic powering up of the motor avoids the user having to take any additional steps, such as pressing a button, before they begin to use the vacuum cleaner 1.”
Delmas discloses a controller for a cleaner arranged such
at a first module (pretreatment means 30 and classification means 40) of a controller (65), processing the sensor signals to generate a plurality of control signals (See Delmas Para [0064] – [0075] discussing the operation of the pre-processing and classifying block, taking info from sensors, and using them to determine the surface of the floor the cleaner is operating on);
at a second module of the controller, processing the plurality of control signals to generate an output signal indicating that the vacuum cleaner is currently being used (See Para [0078] - [0079] discussing 50 receiving the output of 40 for determining a suction motor pressure for the detected floor type, and Para [0085] Discussing 60 using comparing the determined suction motor pressure and the current pressure to provide an output signal 61 so that the appropriate motor pressure is applied);
It would be obvious to one of ordinary skill in the art before the effective filling date of the invention to modify the in-use detection of Lawrence to utilize the control architecture of Delmas, as Delmas discloses that the use of a neural network classification system over a comparison with pre-memorized tabulated values of the sensor avoids errors due to the difference in all components of the cleaner that may develop over time, See Para [0016] (“This vacuum cleaner also has the advantage that it is now the coefficients of the neural network that allow the classification of floors according to the signal of the floor sensor, and no longer, the comparison with pre-memorized tabulated values. The result is that one can thus avoid errors due to the dispersion of characteristics in all parts of the vacuum cleaner.”).
Examiner notes that Lawrance as modified would disclose
A non-transitory computer-readable storage medium having stored thereon a computer program comprising a set of instructions, which, when executed by a computerised device, cause the computerised device to perform a method of operating a vacuum cleaner, the method comprising (See Lawrance Page 7 Line 1-7 “The main body 3 further comprises a control PCB 25, for controlling at least some of the electric functions of the vacuum cleaner 1, a clock 26 and an indicator 29. The control PCB 25 comprises a processor/receiver 27 for receiving wireless signals transmitted by one or other, or both, of the first wireless transmitter 19 and the second wireless transmitter 23. in this embodiment, the processor/receiver 27 is shown as one device integral with the control PCB 25.”):
generating sensor signals by a plurality of sensors of the vacuum cleaner (See Page 4 Lines 4-8 “Preferably, the first sensor is a motion sensor and the second sensor is a touch sensor. Thus the signals output from the first and second sensors may indicate different states of the machine, i.e. whether it is in the first use state or the second non-use state. Both sensors may be touch sensors, or both sensors may be motion sensors.”);
at a first module of a controller, processing the sensor signals to generate a plurality of control signals (See Delmas Para [0078] - [0079] discussing 50 receiving the output of 40 for determining a suction motor pressure for the detected floor type, and Para [0085] Discussing 60 using comparing the determined suction motor pressure and the current pressure to provide an output signal 61 so that the appropriate motor pressure is applied);
at a second module of the controller, processing the plurality of control signals to generate an output signal indicating that the vacuum cleaner is currently being used (See Delmas Para [0078] - [0079] discussing 50 receiving the output of 40 for determining a suction motor pressure for the detected floor type, and Para [0085] Discussing 60 using comparing the determined suction motor pressure and the current pressure to provide an output signal 61 so that the appropriate motor pressure is applied); and
activating or deactivating a vacuum motor of the vacuum cleaner in dependence on the output signal the vacuum motor is configured to activate or deactivate in dependence on the output signal (See Lawrence Page 10 “On detection of either the first signal (step 9) or the second signal (step 10), or both of the first and second signals (step 11), the power management system is powers up the motor, stops outputting the indicator signal such that the LED 29 turns off and resets the power management system, such that the stored value of the first time period is removed from the power management system (step 12). The automatic powering up of the motor avoids the user having to take any additional steps, such as pressing a button, before they begin to use the vacuum cleaner 1.”).
Claim(s) 1, 7, 8, 12, 15, 17, and 18 is rejected under 35 U.S.C. 103 as being unpatentable over Lawrence (GB 2490256 A) in view of Delmas (EP 0636341 A1) and Brown (US 20140008087 A1).
Regarding Claim 1, Lawrence discloses:
A vacuum cleaner comprising:
a plurality of sensors configured to generate sensor signals (See Page 4 Lines 4-8 “Preferably, the first sensor is a motion sensor and the second sensor is a touch sensor. Thus the signals output from the first and second sensors may indicate different states of the machine, i.e. whether it is in the first use state or the second non-use state. Both sensors may be touch sensors, or both sensors may be motion sensors.”);
a vacuum motor (24); and suggests but does not explicitly disclose:
a controller (processor 27 and “power management system”) comprising first (processor and receiver portions described below in citation from page 7) and second modules (clock 26 and indicator 29), wherein (See Page 7 Line 9-13 “The processor/receiver 27 may be two devices: a receiving device for receiving the transmitted signals and a processing device for processing the received signals, both of which devices may be integral with the control PCB 25. The processor/receiver 27 and the receiving device and/or processing device may be separate from the control PCB 25.”):
the first module is configured to process the generated sensor signals to generate a plurality of control signals (receiving part of processor, See citation from page 7 above. And Page 7 Line 24 “The power management system is arranged to output an indicator signal”), wherein the first module is configured to process the generated sensor signals by performing a pre-processing step and a classification step (See Page 4, cited below, Showing the processor classifying the signals to first second third and fourth signal, and preprocessing by associating a time signal with each signal.
“The processor may be arranged to detect the first, the second, the third and the fourth signals, and the power management system may be arranged to control power to the motor in dependence on the detected signals.
The processor may be arranged to associate the time signal with the or each is detected signal, and the power management system may be arranged to power down the motor when a predetermined time period has elapsed after detection of the second signal and the fourth signal. Thus, the power management system may be arranged to power down the motor a certain time period after a user stops using the machine.
The power management system may be arranged such that, on detection of the first signal or the third signal, the power management system powers up the motor.”);
the second module is configured to process the plurality of control signals to generate an output signal indicating that the vacuum cleaner is currently being used (See Page 3 “The power management system may comprise a clock which outputs a time signal, and the processor may be arranged to detect the time signal and to associate the time signal with the signal from the sensor, the power management system being arranged to power down the motor after a predetermined time period has elapsed after detection that the machine goes from being in the first use state to being in the second non-use state.”); and
the vacuum motor is configured to activate or deactivate in dependence on the output signal (Page 9-10,
“On entering the idle mode, the power management system outputs an indicator signal to the LED 29 (step 8) causing the LED 29 to flash intermittently. The LED 29 may light continuously instead. The LED indicates to the user that the vacuum cleaner 1 is in the idle mode. When the vacuum cleaner us left unattended and has entered the idle mode, a user may pick up the wand 13 or may begin moving the vacuum cleaner I with or without holding the upper portion 14 of the wand 13. A user picking up the upper portion 14 of the wand 13 so as to touch the touch sensor 17 will cause the touch sensor I 7 to output the second signal indicating that the vacuum cleaner is in use. Movement of the vacuum cleaner I will cause the motion sensor 21 to output the first signal indicating that the vacuum cleaner I is in use.
On detection of either the first signal (step 9) or the second signal (step 10), or both of the first and second signals (step 11), the power management system is powers up the motor, stops outputting the indicator signal such that the LED 29 turns off and resets the power management system, such that the stored value of the first time period is removed from the power management system (step 12). The automatic powering up of the motor avoids the user having to take any additional steps, such as pressing a button, before they begin to use the vacuum cleaner 1.”).
but does not disclose wherein the pre-processing step comprises filtering the sensor signals.
Examiner notes that while Lawrence does not explicitly disclose a separate first and second module, wherein the first module is configured to process the generated sensor signals to generate a plurality of control signals, wherein the first module is configured to process the generated sensor signals by performing a pre-processing step and a classification step and wherein the pre-processing step comprises filtering the sensor signals;
the second module is configured to process the plurality of control signals to generate an output signal indicating that the vacuum cleaner is currently being used;
Lawrence does generally disclose the concept of a controller receiving generated sensor signals, processing them into an output signal, and the vacuum motor is configured to activate or deactivate in dependence on the output signal (Page 9-10,
“On entering the idle mode, the power management system outputs an indicator signal to the LED 29 (step 8) causing the LED 29 to flash intermittently. The LED 29 may light continuously instead. The LED indicates to the user that the vacuum cleaner 1 is in the idle mode. When the vacuum cleaner us left unattended and has entered the idle mode, a user may pick up the wand 13 or may begin moving the vacuum cleaner I with or without holding the upper portion 14 of the wand 13. A user picking up the upper portion 14 of the wand 13 so as to touch the touch sensor 17 will cause the touch sensor I 7 to output the second signal indicating that the vacuum cleaner is in use. Movement of the vacuum cleaner I will cause the motion sensor 21 to output the first signal indicating that the vacuum cleaner I is in use.
On detection of either the first signal (step 9) or the second signal (step 10), or both of the first and second signals (step 11), the power management system is powers up the motor, stops outputting the indicator signal such that the LED 29 turns off and resets the power management system, such that the stored value of the first time period is removed from the power management system (step 12). The automatic powering up of the motor avoids the user having to take any additional steps, such as pressing a button, before they begin to use the vacuum cleaner 1.”).
Delmas discloses a cleaner with a controller (65), the controller comprises a first (pretreatment and classification means 30 and 40 respectively) and second module (setpoint means 50 and control means 60)
the first module (30 and 40) is configured to process the generated sensor signals to generate a plurality of control signals (output control signals 41, See Para [0073] “The neural network block 40 therefore provides output 41 with two possible signals which correspond to two complementary classes, indicating the "carpet" state and the "hard floor" state.”), wherein the first module is configured to process the generated sensor signals by performing a pre-processing step (See Para [0064]
“This signal processing device for ground detection sensors includes: a pre-processing block 30 which receives as input the outputs 16 and 26 of the first and second pressure sensors and which performs a process called PRE-PROCESSING consisting of calculating: the average pressure amplitude PM of the oscillations of the output signal 16 of the first pressure sensor 14, relative to the pressure existing at the inlet 11 of the dust chamber 12; the difference in amplitude ΔP between maxima and minima of the oscillations of the output signal 16 of the pressure sensor 14 relating to that same pressure; the difference in average values (PM'-PM) of the pressures existing at the inlet 11 at the measurement point 15 and at the outlet 23a or 23b of the dust chamber, at the measurement point 25.”)
and a classification step (See Para [0070]-[0073]
“Outputs 31, 32, 33 from preprocessing block 30 are applied to a neural network block 40, called the classifier, which includes: with 3 entrances, outputs for the signals to be calculated. The three inputs of block 40 of the classifier neural network consist of the three output signals calculated by preprocessing block 30: a signal 31 of the maximum value of the difference in amplitude ΔP between the maxima and minima of the pressure oscillations, of the signal provided by the ground sensor 14. To this end, in order to eliminate the effect of noise on the maximum and minimum values, a signal smoothing step, for example by calculating the average over 0.3 second windows, can be provided; a signal 32 of the value of the average amplitude of PM pressure provided by the soil sensor 14, a signal 33 of the difference in average pressure amplitudes (PM' - PM) between the outlet and the inlet of the dust chamber. Possibly, the coefficients of the neural network relating to this input are low.” )
the second module is configured to process the plurality of control signals (See Para [0078] “The output 41 of the classifier neural network block 40 is carried to a setpoint block 50 which, by a direct conversion as a function of the ground, gives a setpoint 51 of the average pressure amplitude PM which must be imposed at the inlet of the dust chamber, for adequate cleaning of the detected ground.” ) to generate an output signal indicating how the vacuum motor should be adjusted (See Para [0085] “This average pressure amplitude setpoint 51 is reported to a controller 60 which compares the setpoint signal 51 with the average pressure amplitude PM 32 existing at that moment at the inlet of the dust chamber, and which provides a signal 61 to adjust the electrical power of the main motor so that the appropriate pressure setpoint is brought or maintained at the inlet of the dust chamber.”);
Additionally, Brown discloses a cleaner that with a controller that utilizes filters in a pre-processing step (See Para [0097] “To make the digital signal received by the processor 51 more in order, a filter circuit 53 can be arranged between the sound sensor 41 and the analog-digital conversion circuit 48. The filter circuit 53 can filter the analogue signal generated by the sound sensor 41 such that the analogue signal entering the analog-digital conversion circuit 48 is more in order and that the digital signal which is converted by the analog-digital conversion circuit 48 and enters the processor 51 is more in order. In this embodiment, the filter circuit 53 is electrically connected between the signal amplification circuit 42 and the analog-digital conversion circuit 48.”).
It would be obvious to one of ordinary skill in the art before the effective filling date of the invention to modify the in-use detection of Lawrence to utilize the control architecture of Delmas, as Delmas discloses that the use of a neural network classification system over a comparison with pre-memorized tabulated values of the sensor avoids errors due to the difference in all components of the cleaner that may develop over time, See Para [0016] (“This vacuum cleaner also has the advantage that it is now the coefficients of the neural network that allow the classification of floors according to the signal of the floor sensor, and no longer, the comparison with pre-memorized tabulated values. The result is that one can thus avoid errors due to the dispersion of characteristics in all parts of the vacuum cleaner.”).
It would be further obvious to one of ordinary skill in the art to apply filters to the signals during the pre-processing step to cut out noise from the sensor and to prevent accidental activation/deactivations of the motor.
Examiner notes that Lawrence as modified would disclose
A vacuum cleaner comprising:
a plurality of sensors configured to generate sensor signals (See Lawrence Page 4 Lines 4-8 “Preferably, the first sensor is a motion sensor and the second sensor is a touch sensor. Thus the signals output from the first and second sensors may indicate different states of the machine, i.e. whether it is in the first use state or the second non-use state. Both sensors may be touch sensors, or both sensors may be motion sensors.”);
a vacuum motor (Lawrence 24); and
a controller (Lawrence processor 27 and “power management system”) comprising first (30 and 40 of Delmas) and second modules (50 and 60 of Delmas), wherein:
the first module (30 and 40) is configured to process the generated sensor signals to generate a plurality of control signals (output control signals 41, See Para [0073] “The neural network block 40 therefore provides output 41 with two possible signals which correspond to two complementary classes, indicating the "carpet" state and the "hard floor" state.”), wherein the first module is configured to process the generated sensor signals by performing a pre-processing step (See Para [0064]
“This signal processing device for ground detection sensors includes: a pre-processing block 30 which receives as input the outputs 16 and 26 of the first and second pressure sensors and which performs a process called PRE-PROCESSING consisting of calculating: the average pressure amplitude PM of the oscillations of the output signal 16 of the first pressure sensor 14, relative to the pressure existing at the inlet 11 of the dust chamber 12; the difference in amplitude ΔP between maxima and minima of the oscillations of the output signal 16 of the pressure sensor 14 relating to that same pressure; the difference in average values (PM'-PM) of the pressures existing at the inlet 11 at the measurement point 15 and at the outlet 23a or 23b of the dust chamber, at the measurement point 25.”)
and a classification step (See Para [0070]-[0073]
“Outputs 31, 32, 33 from preprocessing block 30 are applied to a neural network block 40, called the classifier, which includes: with 3 entrances, outputs for the signals to be calculated. The three inputs of block 40 of the classifier neural network consist of the three output signals calculated by preprocessing block 30: a signal 31 of the maximum value of the difference in amplitude ΔP between the maxima and minima of the pressure oscillations, of the signal provided by the ground sensor 14. To this end, in order to eliminate the effect of noise on the maximum and minimum values, a signal smoothing step, for example by calculating the average over 0.3 second windows, can be provided; a signal 32 of the value of the average amplitude of PM pressure provided by the soil sensor 14, a signal 33 of the difference in average pressure amplitudes (PM' - PM) between the outlet and the inlet of the dust chamber. Possibly, the coefficients of the neural network relating to this input are low.” )
wherein the pre-processing step comprises filtering the sensor signals (as taught by Brown);
the second module is configured to process the plurality of control signals (See Para [0078] “The output 41 of the classifier neural network block 40 is carried to a setpoint block 50 which, by a direct conversion as a function of the ground, gives a setpoint 51 of the average pressure amplitude PM which must be imposed at the inlet of the dust chamber, for adequate cleaning of the detected ground.” ) to generate an output signal indicating how the vacuum motor should be adjusted (See Para [0085] “This average pressure amplitude setpoint 51 is reported to a controller 60 which compares the setpoint signal 51 with the average pressure amplitude PM 32 existing at that moment at the inlet of the dust chamber, and which provides a signal 61 to adjust the electrical power of the main motor so that the appropriate pressure setpoint is brought or maintained at the inlet of the dust chamber.”);
the vacuum motor is configured to activate or deactivate in dependence on the output signal (See Lawrence Page 10 “On detection of either the first signal (step 9) or the second signal (step 10), or both of the first and second signals (step 11), the power management system is powers up the motor, stops outputting the indicator signal such that the LED 29 turns off and resets the power management system, such that the stored value of the first time period is removed from the power management system (step 12). The automatic powering up of the motor avoids the user having to take any additional steps, such as pressing a button, before they begin to use the vacuum cleaner 1.”).
Regarding Claim 7, Lawrence discloses all the limitations of claim 1 and in addition discloses wherein the second module comprises a finite state machine (See Para [0018] of Delmas “According to the invention, these problems are solved by means of a vacuum cleaner further characterized in that the sequential control system is a FINITE STATE machine which includes at least the STATES of:”).
Regarding Claim 8, Lawrence discloses all the limitations of claim 1 and in addition Suggests but does not explicitly discloses wherein the output signal is a binary signal (Delmas discloses the first module outputting a binary signal, See Para [0075] “The output levels of block 40 of the classifier neural network can be carried to a conversion stage which provides a binary output 41, such that for example the level of this signal 41 is +1 for the detected CARPET state, and is φ for the detected HARD FLOOR state.”).
It would be obvious to one of ordinary skill in the art before the effective filling date of the invention to modify Lawrence as modified such that the output signal of the secondary module is a binary signal, as doing the output of the controller of Lawrence as modified is only meant to change the motor between two states: on and off, and doing so would simplify the operation of the cleaner for the user, and would protect against unintentional firings of the motor.
Regarding Claim 12, Lawrence discloses all the limitations of claim 1 and in addition discloses wherein the plurality of sensors comprises a capacitive sensor located in proximity to a handle of the vacuum cleaner and configured to generate sensor signals dependent on whether a user is gripping the handle (see Page 5 Line 32- Page Line 5 “The sensor may be a touch sensor. The touch sensor may be one of a capacitance sensor and a pressure sensor.”).
Regarding Claim 15, Lawrence discloses A method of operating a vacuum cleaner comprising:
generating sensor signals by a plurality of sensors of the vacuum cleaner (See Page 4 Lines 4-8 “Preferably, the first sensor is a motion sensor and the second sensor is a touch sensor. Thus the signals output from the first and second sensors may indicate different states of the machine, i.e. whether it is in the first use state or the second non-use state. Both sensors may be touch sensors, or both sensors may be motion sensors.”); and suggests but does not explicitly disclose
at a first module of a controller, processing the sensor signals to generate a plurality of control signals (receiving part of processor, See citation from page 7 above. And Page 7 Line 24 “The power management system is arranged to output an indicator signal”), wherein processing the sensor signals comprises performing a pre-processing step and a classification step, and (See Page 4, cited below, Showing the processor classifying the signals to first second third and fourth signal, and preprocessing by associating a time signal with each signal.
“The processor may be arranged to detect the first, the second, the third and the fourth signals, and the power management system may be arranged to control power to the motor in dependence on the detected signals.
The processor may be arranged to associate the time signal with the or each is detected signal, and the power management system may be arranged to power down the motor when a predetermined time period has elapsed after detection of the second signal and the fourth signal. Thus, the power management system may be arranged to power down the motor a certain time period after a user stops using the machine.
The power management system may be arranged such that, on detection of the first signal or the third signal, the power management system powers up the motor.”);
at a second module of the controller, processing the plurality of control signals to generate an output signal indicating that the vacuum cleaner is currently being used (See Page 3 “The power management system may comprise a clock which outputs a time signal, and the processor may be arranged to detect the time signal and to associate the time signal with the signal from the sensor, the power management system being arranged to power down the motor after a predetermined time period has elapsed after detection that the machine goes from being in the first use state to being in the second non-use state.”); and
activating or deactivating a vacuum motor of the vacuum cleaner in dependence on the output signal (See Lawrence Page 10 “On detection of either the first signal (step 9) or the second signal (step 10), or both of the first and second signals (step 11), the power management system is powers up the motor, stops outputting the indicator signal such that the LED 29 turns off and resets the power management system, such that the stored value of the first time period is removed from the power management system (step 12). The automatic powering up of the motor avoids the user having to take any additional steps, such as pressing a button, before they begin to use the vacuum cleaner 1.”).
the first module is configured to process the generated sensor signals to generate a plurality of control signals (receiving part of processor, See citation from page 7 above. And Page 7 Line 24 “The power management system is arranged to output an indicator signal”), wherein the first module is configured to process the generated sensor signals by performing a pre-processing step and a classification step (See Page 4, cited below, Showing the processor classifying the signals to first second third and fourth signal, and preprocessing by associating a time signal with each signal.
“The processor may be arranged to detect the first, the second, the third and the fourth signals, and the power management system may be arranged to control power to the motor in dependence on the detected signals.
The processor may be arranged to associate the time signal with the or each is detected signal, and the power management system may be arranged to power down the motor when a predetermined time period has elapsed after detection of the second signal and the fourth signal. Thus, the power management system may be arranged to power down the motor a certain time period after a user stops using the machine.
The power management system may be arranged such that, on detection of the first signal or the third signal, the power management system powers up the motor.”);
the second module is configured to process the plurality of control signals to generate an output signal indicating that the vacuum cleaner is currently being used (See Page 3 “The power management system may comprise a clock which outputs a time signal, and the processor may be arranged to detect the time signal and to associate the time signal with the signal from the sensor, the power management system being arranged to power down the motor after a predetermined time period has elapsed after detection that the machine goes from being in the first use state to being in the second non-use state.”); and
the vacuum motor is configured to activate or deactivate in dependence on the output signal (Page 9-10,
“On entering the idle mode, the power management system outputs an indicator signal to the LED 29 (step 8) causing the LED 29 to flash intermittently. The LED 29 may light continuously instead. The LED indicates to the user that the vacuum cleaner 1 is in the idle mode. When the vacuum cleaner us left unattended and has entered the idle mode, a user may pick up the wand 13 or may begin moving the vacuum cleaner I with or without holding the upper portion 14 of the wand 13. A user picking up the upper portion 14 of the wand 13 so as to touch the touch sensor 17 will cause the touch sensor I 7 to output the second signal indicating that the vacuum cleaner is in use. Movement of the vacuum cleaner I will cause the motion sensor 21 to output the first signal indicating that the vacuum cleaner I is in use.
On detection of either the first signal (step 9) or the second signal (step 10), or both of the first and second signals (step 11), the power management system is powers up the motor, stops outputting the indicator signal such that the LED 29 turns off and resets the power management system, such that the stored value of the first time period is removed from the power management system (step 12). The automatic powering up of the motor avoids the user having to take any additional steps, such as pressing a button, before they begin to use the vacuum cleaner 1.”).
but does not disclose wherein the pre-processing step comprises filtering the sensor signals.
Examiner notes that while Lawrence does not explicitly disclose a separate first and second module, wherein the first module is configured to process the generated sensor signals to generate a plurality of control signals, wherein the first module is configured to process the generated sensor signals by performing a pre-processing step and a classification step and wherein the pre-processing step comprises filtering the sensor signals;
the second module is configured to process the plurality of control signals to generate an output signal indicating that the vacuum cleaner is currently being used;
Lawrence does generally disclose the concept of a controller receiving generated sensor signals, processing them into an output signal, and the vacuum motor is configured to activate or deactivate in dependence on the output signal (Page 9-10,
“On entering the idle mode, the power management system outputs an indicator signal to the LED 29 (step 8) causing the LED 29 to flash intermittently. The LED 29 may light continuously instead. The LED indicates to the user that the vacuum cleaner 1 is in the idle mode. When the vacuum cleaner us left unattended and has entered the idle mode, a user may pick up the wand 13 or may begin moving the vacuum cleaner I with or without holding the upper portion 14 of the wand 13. A user picking up the upper portion 14 of the wand 13 so as to touch the touch sensor 17 will cause the touch sensor I 7 to output the second signal indicating that the vacuum cleaner is in use. Movement of the vacuum cleaner I will cause the motion sensor 21 to output the first signal indicating that the vacuum cleaner I is in use.
On detection of either the first signal (step 9) or the second signal (step 10), or both of the first and second signals (step 11), the power management system is powers up the motor, stops outputting the indicator signal such that the LED 29 turns off and resets the power management system, such that the stored value of the first time period is removed from the power management system (step 12). The automatic powering up of the motor avoids the user having to take any additional steps, such as pressing a button, before they begin to use the vacuum cleaner 1.”).
Delmas discloses a cleaner with a controller (65), the controller comprises a first (pretreatment and classification means 30 and 40 respectively) and second module (setpoint means 50 and control means 60)
the first module (30 and 40) is configured to process the generated sensor signals to generate a plurality of control signals (output control signals 41, See Para [0073] “The neural network block 40 therefore provides output 41 with two possible signals which correspond to two complementary classes, indicating the "carpet" state and the "hard floor" state.”), wherein the first module is configured to process the generated sensor signals by performing a pre-processing step (See Para [0064]
“This signal processing device for ground detection sensors includes: a pre-processing block 30 which receives as input the outputs 16 and 26 of the first and second pressure sensors and which performs a process called PRE-PROCESSING consisting of calculating: the average pressure amplitude PM of the oscillations of the output signal 16 of the first pressure sensor 14, relative to the pressure existing at the inlet 11 of the dust chamber 12; the difference in amplitude ΔP between maxima and minima of the oscillations of the output signal 16 of the pressure sensor 14 relating to that same pressure; the difference in average values (PM'-PM) of the pressures existing at the inlet 11 at the measurement point 15 and at the outlet 23a or 23b of the dust chamber, at the measurement point 25.”)
and a classification step (See Para [0070]-[0073]
“Outputs 31, 32, 33 from preprocessing block 30 are applied to a neural network block 40, called the classifier, which includes: with 3 entrances, outputs for the signals to be calculated. The three inputs of block 40 of the classifier neural network consist of the three output signals calculated by preprocessing block 30: a signal 31 of the maximum value of the difference in amplitude ΔP between the maxima and minima of the pressure oscillations, of the signal provided by the ground sensor 14. To this end, in order to eliminate the effect of noise on the maximum and minimum values, a signal smoothing step, for example by calculating the average over 0.3 second windows, can be provided; a signal 32 of the value of the average amplitude of PM pressure provided by the soil sensor 14, a signal 33 of the difference in average pressure amplitudes (PM' - PM) between the outlet and the inlet of the dust chamber. Possibly, the coefficients of the neural network relating to this input are low.” )
the second module is configured to process the plurality of control signals (See Para [0078] “The output 41 of the classifier neural network block 40 is carried to a setpoint block 50 which, by a direct conversion as a function of the ground, gives a setpoint 51 of the average pressure amplitude PM which must be imposed at the inlet of the dust chamber, for adequate cleaning of the detected ground.” ) to generate an output signal indicating how the vacuum motor should be adjusted (See Para [0085] “This average pressure amplitude setpoint 51 is reported to a controller 60 which compares the setpoint signal 51 with the average pressure amplitude PM 32 existing at that moment at the inlet of the dust chamber, and which provides a signal 61 to adjust the electrical power of the main motor so that the appropriate pressure setpoint is brought or maintained at the inlet of the dust chamber.”);
Additionally, Brown discloses a cleaner that with a controller that utilizes filters in a pre-processing step (See Para [0097] “To make the digital signal received by the processor 51 more in order, a filter circuit 53 can be arranged between the sound sensor 41 and the analog-digital conversion circuit 48. The filter circuit 53 can filter the analogue signal generated by the sound sensor 41 such that the analogue signal entering the analog-digital conversion circuit 48 is more in order and that the digital signal which is converted by the analog-digital conversion circuit 48 and enters the processor 51 is more in order. In this embodiment, the filter circuit 53 is electrically connected between the signal amplification circuit 42 and the analog-digital conversion circuit 48.”).
It would be obvious to one of ordinary skill in the art before the effective filling date of the invention to modify the in-use detection of Lawrence to utilize the control architecture of Delmas, as Delmas discloses that the use of a neural network classification system over a comparison with pre-memorized tabulated values of the sensor avoids errors due to the difference in all components of the cleaner that may develop over time, See Para [0016] (“This vacuum cleaner also has the advantage that it is now the coefficients of the neural network that allow the classification of floors according to the signal of the floor sensor, and no longer, the comparison with pre-memorized tabulated values. The result is that one can thus avoid errors due to the dispersion of characteristics in all parts of the vacuum cleaner.”).
It would be further obvious to one of ordinary skill in the art to apply filters to the signals during the pre-processing step to cut out noise from the sensor and to prevent accidental activation/deactivations of the motor.
Examiner notes Lawrence as modified above discloses
A method of operating a vacuum cleaner comprising:
generating sensor signals by a plurality of sensors of the vacuum cleaner (See Lawrence Page 4 Lines 4-8 “Preferably, the first sensor is a motion sensor and the second sensor is a touch sensor. Thus the signals output from the first and second sensors may indicate different states of the machine, i.e. whether it is in the first use state or the second non-use state. Both sensors may be touch sensors, or both sensors may be motion sensors.”);
at a first module of a controller, processing the sensor signals to generate a plurality of control signals(output control signals 41, See Para [0073] “The neural network block 40 therefore provides output 41 with two possible signals which correspond to two complementary classes, indicating the "carpet" state and the "hard floor" state.”), wherein processing the sensor signals comprises performing a pre-processing step (See Para [0064]
“This signal processing device for ground detection sensors includes: a pre-processing block 30 which receives as input the outputs 16 and 26 of the first and second pressure sensors and which performs a process called PRE-PROCESSING consisting of calculating: the average pressure amplitude PM of the oscillations of the output signal 16 of the first pressure sensor 14, relative to the pressure existing at the inlet 11 of the dust chamber 12; the difference in amplitude ΔP between maxima and minima of the oscillations of the output signal 16 of the pressure sensor 14 relating to that same pressure; the difference in average values (PM'-PM) of the pressures existing at the inlet 11 at the measurement point 15 and at the outlet 23a or 23b of the dust chamber, at the measurement point 25.”)
and a classification step (See Para [0070]-[0073]
“Outputs 31, 32, 33 from preprocessing block 30 are applied to a neural network block 40, called the classifier, which includes: with 3 entrances, outputs for the signals to be calculated. The three inputs of block 40 of the classifier neural network consist of the three output signals calculated by preprocessing block 30: a signal 31 of the maximum value of the difference in amplitude ΔP between the maxima and minima of the pressure oscillations, of the signal provided by the ground sensor 14. To this end, in order to eliminate the effect of noise on the maximum and minimum values, a signal smoothing step, for example by calculating the average over 0.3 second windows, can be provided; a signal 32 of the value of the average amplitude of PM pressure provided by the soil sensor 14, a signal 33 of the difference in average pressure amplitudes (PM' - PM) between the outlet and the inlet of the dust chamber. Possibly, the coefficients of the neural network relating to this input are low.” )
wherein the pre-processing step comprises filtering the sensor signals (as taught by Brown);
at a second module of the controller, processing the plurality of control signals (See Para [0078] “The output 41 of the classifier neural network block 40 is carried to a setpoint block 50 which, by a direct conversion as a function of the ground, gives a setpoint 51 of the average pressure amplitude PM which must be imposed at the inlet of the dust chamber, for adequate cleaning of the detected ground.” ) to generate an output signal indicating how the vacuum motor should be adjusted (See Para [0085] “This average pressure amplitude setpoint 51 is reported to a controller 60 which compares the setpoint signal 51 with the average pressure amplitude PM 32 existing at that moment at the inlet of the dust chamber, and which provides a signal 61 to adjust the electrical power of the main motor so that the appropriate pressure setpoint is brought or maintained at the inlet of the dust chamber.”);
the vacuum motor is configured to activate or deactivate in dependence on the output signal (See Lawrence Page 10 “On detection of either the first signal (step 9) or the second signal (step 10), or both of the first and second signals (step 11), the power management system is powers up the motor, stops outputting the indicator signal such that the LED 29 turns off and resets the power management system, such that the stored value of the first time period is removed from the power management system (step 12). The automatic powering up of the motor avoids the user having to take any additional steps, such as pressing a button, before they begin to use the vacuum cleaner 1.”).
Regarding Claim 17, Lawrence as modified discloses all the limitations of claim 1 and in addition discloses wherein the first module is configured to periodically generate the plurality of control signals based on the processing of the generated sensor signals (See Para [0025]-[0030] discussing the periodic back and forth motion of the cleaner, then see Para [0065] discussing the pre processing step (30) be carried out over time period/time windows over corresponding to the time the average use takes to change the direction of the cleaner).
It would be obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the first module of Lawrance as modifies such that the control signals are periodically generated based on the processing of the generated sensor signals as doing so would allow for the cleaner to continually ping the sensors to detect if the cleaner is in use, See Para [0091] “This sequential control system 65 activates the pretreatment means 30, classification means 40, setpoint means 50 and control means 60, in an appropriate order, over appropriate time windows T, or durations, and this automatically.”
Regarding Claim 18, Lawrance as modified discloses all the limitations of claim 1 but does not explicitly disclose wherein the vacuum cleaner is a handheld vacuum cleaner.
However, Brown discloses system in which a handheld vacuum cleaner (See Para [0027] “The present invention also discloses a vacuum cleaner which is used in combination with electric tools. The vacuum cleaner includes: a body capable of vacuuming, a handle installed on the body for being held by a user, a hose installed on the body, and a function selection switch arranged on the body.”) is activated automatically in response to detected signals (See Abstract of Brown).
It would be obvious to one of ordinary skill in the art before the effective to modify the cleaner of Lawrence to be a handheld cleaner as doing so would allow for the operator to easily transport the vacuum and easily perform spot cleaning.
Claim(s) 3, 5 and 6 is rejected under 35 U.S.C. 103 as being unpatentable over Lawrence (GB 2490256 A) in view of Delmas (EP 0636341 A1) and Brown (US 20140008087 A1) as modified in claim 1 and in further view of USSELMAN (US 20140261551 A1).
Regarding Claim 3, Lawrence discloses all the limitations of claim 2 and in addition discloses wherein the pre-processing step comprises extracting features from time portions of the generated sensor signals (See Delmas [0104] “The preprocessing block 30 is ACTIVE to record data over a duration or "window" T3 = 2 seconds. The T3 duration of 2 seconds is intended to encompass at least one change of direction of the nozzle between a back-and-forth movement on the floor to be detected, during the cleaning operation by an average user;”).
But does not disclose the pre-processing step further comprises band-pass and low-pass filters.
However, USSELMAN discloses a system utilizing a sensor utilizing conditioning circuits for a pre-processing step comprising band-pass and low-pass filters (See Para [0036] “The sensors 200 provide the sensor signals to conditioning circuits 204-1, 204-2, 204-3, and 204-4 (collectively, conditioning circuits 204), respectively. The conditioning circuits 204 create conditioned signals by amplifying the respective sensor signals from the sensors 200. In various implementations, the conditioning circuits 204 also apply various analog processing, such as low-pass, high-pass, or band-pass filtering.”)
It would be obvious to one of ordinary skill in the art before the effective filling date of the invention to modify controller module to include band-pass and low-pass filtering during the preprocessing step as one of ordinary skill in the art would understand that doing so would allow for the removal of undesirable signals, such as an accidental impact of the cleaner triggering the motion sensor, or electrical interference, increasing the accuracy of the following classification and additional processing.
Regarding Claim 5, Lawrence discloses all the limitations of claim 3 and in addition discloses, wherein the classification step comprises processing the extracted features (See Para [0071]-[0073] of Delmas
“The three inputs of block 40 of the classifier neural network consist of the three output signals calculated by preprocessing block 30: a signal 31 of the maximum value of the difference in amplitude ΔP between the maxima and minima of the pressure oscillations, of the signal provided by the ground sensor 14. To this end, in order to eliminate the effect of noise on the maximum and minimum values, a signal smoothing step, for example by calculating the average over 0.3 second windows, can be provided; a signal 32 of the value of the average amplitude of PM pressure provided by the soil sensor 14, a signal 33 of the difference in average pressure amplitudes (PM' - PM) between the outlet and the inlet of the dust chamber. Possibly, the coefficients of the neural network relating to this input are low.
Block 40 of the classifier neural network has only two complementary outputs: carpet, hard and smooth floor.
In this case, all examples of carpet are counter-examples of hard flooring, and vice versa. Furthermore, it may be possible to control, in addition to the main fan motor 22, an auxiliary brush motor (not shown).
The neural network block 40 therefore provides output 41 with two possible signals which correspond to two complementary classes, indicating the "carpet" state and the "hard floor" state.”)
using a machine learning classifier to provide the plurality of control signals. (See above citation of Delmas discussing the use of a neural network).
Regarding Claim 6, Lawrence discloses all the limitations of claim 5 and in addition discloses wherein the machine learning classifier comprises one or more of: an artificial neural network, a random forest and a support- vector machine (Para [0071]-[0073] of Delmas as cited above, discussing the use of a neural network).
Claim(s) 9 is rejected under 35 U.S.C. 103 as being unpatentable over Lawrence (GB 2490256 A) in view of Delmas (EP 0636341 A1) and Brown (US 20140008087 A1) as modified in claim 1 and in further view of Gangon (US 20180078107 A1).
Regarding Claim 9, Lawrence discloses all the limitations of claim 1 but does not explicitly disclose wherein the plurality of sensors comprises a tool switch sensor configured to generate a sensor signal dependent on the installation of a removable tool on the vacuum cleaner.
However, Gangon does discloses a cleaning system that utilizes a sensor to detect if a cleaning attachment or tool is installed (See Para [0033] “In this configuration, the contact sensor can also detect attachment of the central vacuum tools and accessories to the remote intake port 54 and signal the central vacuum 52 to create the central airflow. In certain examples, the contact sensor can determine if the autonomous vacuum system 20 is coupled to the remote intake port 54 or other tools and accessories are coupled to the remote intake port 54.”).
It would be obvious to one of ordinary skill in the art to modify the cleaner of Lawrence to have a sensor that generates a signal based on the attachment of a tool, as doing so would allow for the cleaner to power down the motor if the tool isn’t attached or power up when it is as suggested by Gangon in para [0033].
Claim(s) 10 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Lawrence (GB 2490256 A) in view of Delmas (EP 0636341 A1) and Brown (US 20140008087 A1) as modified in claim 1 and in further view of Hong (US 20190343354 A1).
Regarding Claim 10, Lawrence discloses all the limitation of the claim 1 and suggests but does not explicitly disclose the plurality of sensors comprises an inertial measurement unit, IMU, configured to generate sensor signals based on sensed motion and orientation of the vacuum cleaner (See Page 3 Line 11-12 “The or another sensor may be a motion sensor. The motion sensor may be one of a force sensor and an acceleration sensor.”).
However, Hong explicitly discloses a cleaner with a with an IMU, configured to generate sensor signals based on sensed motion and orientation of the vacuum cleaner (See Para [0160] “The IMU 216 may be a combination of sensors for detecting changes in locations and/or orientations of the cleaning apparatus 1000 based on inertial acceleration. For example, a combination of sensors may include accelerometers and gyroscopes.”).
It would be obvious to one of ordinary skill in the art before the effective filling date of the invention to modify the sensor of Lawrence to be an IMU, as Lawrence states the motion sensor may be one of a force sensor and an acceleration sensor (See page 3 Line 11-12 “The or another sensor may be a motion sensor. The motion sensor may be one of a force sensor and an acceleration sensor.”), and Hong discloses that an IMU is a known equivalent for to a force or acceleration sensor, and includes a plurality of sensors for detecting information and includes and IMU for detecting a location and orientation of the cleaner. And is has been held to substituting equivalents known for the same purpose would be obvious to one of ordinary skill in the art, See MPEP 2144.06 II.
Regarding Claim 11, Lawrence discloses all the limitations of claim 10 and in addition discloses wherein the sensor signals generated by the IMU are based only on sensed motion of the vacuum cleaner or only on sensed orientation of the vacuum cleaner. (See Hong Para [0160] “The IMU 216 may be a combination of sensors for detecting changes in locations and/or orientations of the cleaning apparatus 1000 based on inertial acceleration. For example, a combination of sensors may include accelerometers and gyroscopes.” Hong states that the IMU is capable of detecting changes in location (sense motion) and/or (orientation), the “and/or” indicating that the IMU may be configured to sense only sensed motion, only sense orientation or both).
It would be obvious to one of ordinary skill in the art before the effective filling date of the invention to modify the IMU of Lawrence as modified to generate sensor signals based on a single modality (motion or orientation) as doing so would minimize undesirable noise and would prevent unintentional starts of the cleaner if the undesired parameter changes.
Claim(s) 13 is rejected under 35 U.S.C. 103 as being unpatentable over Lawrence (GB 2490256 A) in view of Delmas (EP 0636341 A1) and Brown (US 20140008087 A1) as modified in claim 1 and in further view of Hird (US 20190099051 A1).
Regarding Claim 13, Lawrence discloses all the limitations of claim 1 but does not explicitly disclose wherein the plurality of sensors comprises a proximity sensor configured to generate sensor signals dependent on the proximity of an object to the proximity sensor.
However, Hird discloses a vacuum cleaner utilizing a proximity sensor in order to detect a surface and modulate the suction power of the cleaner in dependence on the signal from the proximity sensor (See Para [0005] “a proximity sensor for detecting a surface; and a controller configured to change the suction power of the suction device in dependence on a signal from the proximity sensor and in dependence on the position of the extendable inlet nozzle.”). It would be obvious to one of ordinary skill in the art before the effective filling date of the invention to modify the sensors of Lawrence to include a proximity sensor as they are both art recognized equivalents for the same purpose of generating a signal to control the output of a motor. (See MPEP 2144.06 II).
Claim(s) 14 is rejected under 35 U.S.C. 103 as being unpatentable over Lawrence (GB 2490256 A) in view of Delmas (EP 0636341 A1) and Brown (US 20140008087 A1) as modified in claim 1 and in further view of Tsuboi (US 20150000068 A1).
Regarding claim 14, Lawrence discloses all the limitations of claim 1 but does not explicitly disclose wherein the first and second modules comprise first and second software modules.
However, Tsuboi discloses a cleaner utilizing a controller that utilizes software (See Para [0314] “Lastly, the control section 52 of the self-propelled cleaner 1 can be configured by hardware with the use of a logic circuit formed on an integrated circuit (IC chip) or by software with the use of CPU.”)
It would be obvious to one of ordinary skill in the art before the effective filling date of the invention to modify the controller of Lawrence to be a CPU running software as it is well known in the art that a CPU running software is an equivalent for the same purpose of controlling a cleaner and its functions as a controller is. (See MPEP 2144.06 II).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Tyler James McFarland whose telephone number is (571)272-7270. The examiner can normally be reached M-F 7:30AM-5PM (E.S.T), Flex First Friday.
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/T.J.M./Examiner, Art Unit 3723
/DAVID S POSIGIAN/Supervisory Patent Examiner, Art Unit 3723
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