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 .
Claims 12-13 are cancelled.
Claims 1, 3-7, 9-11, and 14-20 are amended.
Claims 22 and 23 are new.
Claims 1-11 and 14-22 are pending.
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.
Claim 17 is 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 17 recites “analyzing the audio signal with the noise cancellation system” is not clear.
Claim Objections
Claim 14 is objected to because of the following informalities: Claim 14 recites “wherein the cancellation system generates an analyzed audio signal that is free of the audible noise from, from the audio signal comprising noise associated with the noise generating components”. “from” has been duplicated. Appropriate correction is required.
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.
Claim(s) 1-3, 6-10, 14-15, 17-19, and 21-22 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Xu et al. (US #2016/0063987).
Regarding Claim 1, Xu discloses a system (title, abstract, figs. 1-11), comprising:
noise generating components (Xu ¶0004 discloses one or more background noise-producing components, such as propellers or rotors of the UAV. ¶0055 discloses the target audio, however, can be competing with interfering background noise which can be produced by a background noise-generating component of the UAV. For example, propellers, rotors, cameras and/or carriers of the UAV can be the background noise-generating components. ¶0082 discloses a UAV 210 is equipped with an audio source collecting microphone 250 and plurality of background microphones 260. The UAV 210 may have a central body 230 [not shown in fig. 2] from which one or more arms 220 can extend. Any number of arms can be provided, such as one, two, three, four, five, six, seven, eight, nine, ten, or more arms. Each arm may have a propulsion unit on the arm. In one example, the UAV 210 can comprise four rotors 240 [a.k.a. propellers] which can be disposed at distal ends of the four arms 220. In addition, the UAV 210 can carry various payloads including but not limited to carriers, cameras, and sensors. The payloads may be carried on the central body of the UAV, the arms of the UAV, a landing stand of the UAV, or any other portion of the UAV. All these components can generate noise in operation. ¶0084 discloses examples of noise-producing components can include, but are not limited to, propulsion unit [e.g., rotors], motors, payload carriers, payloads, sensors, communication units, emitters [e.g., speakers], landing gear, or any other component on board the UAV. Noise-producing components can be an on external surface of the UAV housing, within a UAV housing, integrated into a UAV housing, or provided on an extension extending away from the housing. In some instances, vibrations of the UAV can generate noise. Vibrations can occur due to actuation of one or more motors, or other components of the UAV. ¶0088 discloses in some instances, cameras may include shutters that may provide noise. Other types of payloads may be supported by a UAV. Other payloads may be capable of generating noise);
a noise cancellation system configured to capture an audio signal comprising audible noise from the noise generating components (Xu ¶0055 discloses the UAV can be provided with at least one audio source collecting microphone to detect a target audio signal, and at least one background microphone to collect background noise produced by, for example, the propellers of UAV or other background noise-generating components. ¶0056 discloses reducing the noise generated by the UAV itself using an ANC [Active Noise Cancellation] technique), wherein the noise cancellation system is configured to remove the audible noise from the captured audio signal so that clean audio is created that is free of the audible noise from the noise generating components (Xu ¶0055 discloses the collected background noise can be cancelled from the audio signal detected by the audio source collecting microphone using a Multi-Channel RLS adaptive filter, thus only the desired target audio signal remains for recording); and
a memory to store the clean audio (Xu ¶0055 discloses thus only the desired target audio signal remains for recording).
Regarding Claim 2, Xu discloses the system of claim 1,
wherein the system comprises an unmanned aerial vehicle (Xu fig. 1: 110; ¶0057).
Regarding Claim 3, Xu discloses the system of claim 1,
wherein the audible noise from the noise generating components (Xu ¶0107 discloses the background noise can be different from the target audio in frequency and/or amplitude. The background noise may be produced by the UAV itself, e.g., by a propulsion unit comprising a propeller and a rotor. Optionally, the background noise may be produced by payloads carried by UAV, e.g., a camera, or a carrier configured to support a camera carried by the UAV and permit variation in orientation of the camera relative to the UAV [e.g., a gimbal]. ¶0109 discloses various background noise-producing components may be distributed anywhere on the UAV. In some instances, the background noise-producing components may be on an arm or extension of the UAV or a central body of the UA V. The background noise-producing components may be supported above a UAV on a side of a UAV, or beneath the UAV. The background noise-producing components may be external to a housing of the UAV, or within a housing of the UAV. Any combination of locations for various background components may be provided. ¶0110-¶0113 discloses at least one processor can be provided to cancel the background noise from the audio data collected by the audio source collecting microphone, and generate a processed signal [e.g., an audio signal in which background noise is removed or reduced from the collected audio signal]) include baseline noise parameters that comprise noise frequencies associated with a noise generating component of the system (Xu ¶0114 discloses fig. 4 shows a generic Multi-Channel RLS adaptive filter which is particularly suitable to reduce the effects of the background noise in UAVs. The Multi-Channel RLS adaptive filter of fig. 4 can be applied in a UAV with X rotors, which is provided with X background microphones and one audio source collecting microphone. In fig. 4, the noise produced by the propellers can be considered as the background noise. ¶0115 discloses the processor may adopt an adaptive filtering method to cancel the background noise. The filter parameters at current timing can be automatically adjusted according to an estimation error, by using the filter parameters at previous timing).
Regarding Claim 6, Xu discloses the system of claim 1,
wherein the captured audio signal is filtered to remove noise from the audio signal, the noise comprising any of air noise and vibrational noise from the noise generating components (Xu ¶0055 discloses the collected background noise can be cancelled from the audio signal detected by the audio source collecting microphone using a Multi-Channel RLS adaptive filter. ¶0056 discloses the noise generated by the propeller of the UAV itself can be reduced using an ANC. ¶0080 discloses the sound of wind can be dominant noise source when the UAV is in flight. The noise from UAV can be generated from the UAV itself or any onboard instrument like propulsion unit, gimbal motors, or cameras. To collect and record the interested target audio received from the audio source collecting microphone, the background noise has to be cancelled. ¶0083 discloses a noise producing component can interact with an environment to produce wind noise. ¶0107 discloses the background noise can be generated by ambience such as wind. ¶0084 discloses vibration of the UAV can generate noise. Vibrations can occur due to actuation of one or more motors, or other components of the UAV).
Regarding Claim 7, Xu discloses the system of claim 3,
wherein the baseline noise parameters includes an operational condition of a noise generating component at a time of capture of the capture audio signal (Xu ¶0113 discloses the processed signal can be generated in real-time while the UAV is in flight. ¶0115 discloses the processor can adopt an adaptive filtering method to cancel the background noise. The filter parameters at current timing can be automatically adjusted according to an estimation error, by using the filter parameters at previous timing. The optimal filtering can be achieved by keeping a specific "cost function" minimum).
Regarding Claim 8, Xu discloses the system of claim 7,
wherein the baseline noise parameters further include operational conditions of other noise generating components of the system at the time of capture of the audio signal (Xu ¶0080 discloses in collecting the target audio, the audio signal arriving at the audio collecting microphone can be noise [interference audio], in addition to the target audio. The interfering noise can be the noise produced by UAV itself or ambient noise. For example, the rotors of a multi-rotor UAV can generate remarkable noise when the UAV is in operation. Optionally, the sound of wind can be a dominant noise source when the UAV is in flight. The noise from UAV can be generated from the UAV itself or any onboard instrument, including but not limited to, propulsion units, gimbal motors, or cameras).
Regarding Claim 9, Xu discloses the system of claim 8,
wherein the operational condition comprises any of a velocity and an acceleration of the system (Xu ¶0080 discloses the interfering noise can be the noise produced by UAV itself or ambient noise. For example, the rotors of a multi-rotor UAV can generate remarkable noise when the UAV is in operation. ¶0200 discloses the rotation rate of each of the horizontally oriented rotors can be varied independently in order to control the lift and/or thrust produced by each rotor, and thereby adjust the spatial disposition, velocity, and/or acceleration of the movable object 1000. ¶0201 discloses the rotation rate of each of the horizontally oriented rotors can be varied independently in order to control the lift and/or thrust produced by each rotor, and thereby adjust the spatial disposition, velocity, and/or acceleration of the movable object 1000).
Regarding Claim 10, Xu discloses the system of claim 8,
wherein the operational condition comprises wind speed captured from a thermal anemometer of the system (Xu ¶0080 discloses the sound of wind can be a dominant noise source when the UAV is in flight. ¶0144 discloses the background noise can be provided by one or more noise-producing components on-board the UAV. This can include how the noise-producing components may actuate and/or interact with environmental conditions, such as wind).
Regarding Claim 14, Xu discloses an unmanned aerial vehicle, comprising:
components on the unmanned aerial vehicle (Xu ¶0082 discloses a UAV 210 is equipped with an audio source collecting microphone 250 and plural of background microphones 260. The UAV 210 may have a central body 230 [not shown in fig. 2] from which one or more arms 220 can extend. Any number of arms can be provided, such as one, two, three, four, five, six, seven, eight, nine, ten, or more arms. Each arm may have a propulsion unit on the arm. In one example, the UAV 210 can comprise four rotors 240 [a.k.a. propellers] which can be disposed at distal ends of the four arms 220. In addition, the UAV 210 can carry various payloads including but not limited to carriers, cameras, and sensors. The payloads may be carried on the central body of the UAV, the arms of the UAV, a landing stand of the UAV, or any other portion of the UAV. All these components can generate noise in operation), some of the components are noise generating components (Xu ¶0004 discloses one or more background noise-producing components, such as propellers or rotors of the UAV. ¶0055 discloses the target audio, however, can be competing with interfering background noise which can be produced by a background noise-generating component of the UAV. For example, propellers, rotors, cameras and/or carriers of the UAV can be the background noise-generating components. ¶0083 discloses in some instances, a noise-producing component may interact with an environment in order to produce the noise [e.g., wind]. A noise producing component may move to produce the noise. A noise producing component may be actuated or driven by an actuator to produce noise. The noise-producing component may include one or more electrically powered component that may generate the noise, ¶0084 discloses examples of noise-producing components can include, but are not limited to, propulsion unit [e.g., rotors], motors, payload carriers, payloads, sensors, communication units, emitters [e.g., speakers], landing gear, or any other component on board the UAV. Noise-producing components can be an on external surface of the UAV housing, within a UAV housing, integrated into a UAV housing, or provided on an extension extending away from the housing. In some instances, vibrations of the UAV can generate noise. Vibrations can occur due to actuation of one or more motors, or other components of the UAV. ¶0088 discloses in some instances, cameras may include shutters that may provide noise. Other types of payloads may be supported by a UAV. Other payloads may be capable of generating noise);
a cancellation system configured to capture an audio signal comprising audible noise from the noise generating components (Xu ¶0055 discloses the UAV can be provided with at least one audio source collecting microphone to detect a target audio signal, and at least one background microphone to collect background noise produced by, for example, the propellers of UAV or other background noise-generating components. ¶0056 discloses reducing the noise generated by the UAV itself using an ANC [Active Noise Cancellation] technique) and wherein the cancellation system generates an analyzed audio signal that is free of the audible noise from, from the audio signal comprising noise associated with the noise generating components (Xu ¶0055 discloses the collected background noise can be cancelled from the audio signal detected by the audio source collecting microphone using a Multi-Channel RLS adaptive filter, thus only the desired target audio signal remains for recording); and
memory configured to store the analyzed audio signal (Xu ¶0055 discloses thus only the desired target audio signal remains for recording).
Regarding Claim 15, Xu discloses the unmanned aerial vehicle of claim 14, wherein the cancellation system comprises:
a noise analyzer (Xu ¶0167 discloses a noise canceller can emit a sound to reduce or cancel the sound of a background noise-producing component to which it is dedicated. Alternatively, the noise canceller can emit a sound to reduce or cancel the sound of multiple background noise-components. The sounds from the multiple background noise-producing components can be analyzed to determine a sound for the noise canceller to produce, Figs. 4-5) that is configured to identify the noise of the noise generating components of the unmanned aerial vehicle and to determine noise information for each of the noise generating components (Xu ¶0016 disclose identifying at least one background noise-producing component of the UAV, wherein said background noise-producing component is configured to produce background noise that is different from the target audio signal; attaching at least one background microphone on the UAV within a proximity sufficiently close to collect interfering noise from the at least one background noise-producing component; and providing at least one processor configured to (a) receive signals indicative of (1) audio data collected by the at least one audio source collecting microphone and (2) audio data collected by the at least one background microphone, and (b) generate a processed signal based on the received signals).
Regarding Claim 17, Xu discloses a method, comprising:
receiving an audio signal (Xu ¶0082 discloses a UAV 210 is equipped with an audio source collecting microphone 250 and plural of background microphones 260) comprising audible noise from noise generating components, of an unmanned aerial vehicle (Xu ¶0004 discloses one or more background noise-producing components, such as propellers or rotors of the UAV. ¶0055 discloses the target audio, however, can be competing with interfering background noise which can be produced by a background noise-generating component of the UAV. For example, propellers, rotors, cameras and/or carriers of the UAV can be the background noise-generating components, ¶0082 discloses the UAV 210 may have a central body 230 [not shown in fig. 2] from which one or more arms 220 can extend. Any number of arms can be provided, such as one, two, three, four, five, six, seven, eight, nine, ten, or more arms. Each arm may have a propulsion unit on the arm. In one example, the UAV 210 can comprise four rotors 240 [a.k.a. propellers] which can be disposed at distal ends of the four arms 220. In addition, the UAV 210 can carry various payloads including but not limited to carriers, cameras, and sensors. The payloads may be carried on the central body of the UAV, the arms of the UAV, a landing stand of the UAV, or any other portion of the UAV. All these components can generate noise in operation. ¶0083 discloses in some instances, a noise-producing component may interact with an environment in order to produce the noise [e.g., wind]. A noise producing component may move to produce the noise. A noise producing component may be actuated or driven by an actuator to produce noise. The noise-producing component may include one or more electrically powered component that may generate the noise, ¶0084 discloses examples of noise-producing components can include, but are not limited to, propulsion unit [e.g., rotors], motors, payload carriers, payloads, sensors, communication units, emitters [e.g., speakers], landing gear, or any other component on board the UAV. Noise-producing components can be an on external surface of the UAV housing, within a UAV housing, integrated into a UAV housing, or provided on an extension extending away from the housing. In some instances, vibrations of the UAV can generate noise. Vibrations can occur due to actuation of one or more motors, or other components of the UAV. ¶0088 discloses in some instances, cameras may include shutters that may provide noise. Other types of payloads may be supported by a UAV. Other payloads may be capable of generating noise), with a noise cancellation system (Xu ¶0055 discloses the UAV can be provided with at least one audio source collecting microphone to detect a target audio signal, and at least one background microphone to collect background noise produced by, for example, the propellers of UAV or other background noise-generating components. ¶0056 discloses reducing the noise generated by the UAV itself using an ANC [Active Noise Cancellation] technique);
analyzing the audio signal (Xu ¶0167 discloses the noise canceller can emit a sound to reduce or cancel the sound of multiple background noise-components. The sounds from the multiple background noise-producing components can be combined and/or analyzed to determine a sound for the noise canceller to produce. ¶0207 discloses the processing unit 1104 can be configured to execute instructions causing one or more processors of the processing unit 1104 to analyze sensing data produced by the sensing module) with the noise cancellation system, wherein the noise cancellation system removes the audible noise from the received audio signal to create clean audio that is free of the audible noise from the noise generating components (Xu ¶0055 discloses the collected background noise can be cancelled from the audio signal detected by the audio source collecting microphone using a Multi-Channel RLS adaptive filter, thus only the desired target audio signal remains for recording. ¶0167 discloses a noise canceller may emit a sound to reduce or cancel the sound of a background noise-producing component to which it is dedicated); and
storing the clean audio in memory (Xu ¶0055 discloses thus only the desired target audio signal remains for recording).
Claims 18-19 are rejected for the same reasons as set forth in Claims 4 and 15.
Regarding Claim 21, Xu discloses the method of claim 17, wherein the noise cancellation system comprises:
a spectral noise cancellation filter (Xu ¶0113 discloses the processor can generate the processed signal using a variety of algorithms, like a Multi-Channel RLS algorithm or a Multi-Channel RLS adaptive filter to reduce the effects of the background noise. Other kinds of adaptive filters having similar configuration but less computation and less estimation can be used).
Regarding Claim 22, Xu discloses the method of claim 17,
wherein baseline noise parameters further include operational conditions of other noise generating components of the system at a time of capture of the audio signal (Xu ¶0080 discloses in collecting the target audio, the audio signal arriving at the audio collecting microphone can be noise [interference audio], in addition to the target audio. The interfering noise can be the noise produced by UAV itself or ambient noise. For example, the rotors of a multi-rotor UAV can generate remarkable noise when the UAV is in operation. Optionally, the sound of wind can be a dominant noise source when the UAV is in flight. The noise from UAV can be generated from the UAV itself or any onboard instrument, including but not limited to, propulsion units, gimbal motors, or cameras. ¶0107 discloses the background noise can be different from the target audio in frequency and/or amplitude. The background noise may be produced by the UAV itself, e.g., by a propulsion unit comprising a propeller and a rotor. Optionally, the background noise may be produced by payloads carried by UAV, e.g., a camera, or a carrier configured to support a camera carried by the UAV and permit variation in orientation of the camera relative to the UAV [e.g., a gimbal]. ¶0109 discloses various background noise-producing components may be distributed anywhere on the UAV. In some instances, the background noise-producing components may be on an arm or extension of the UAV or a central body of the UA V. The background noise-producing components may be supported above a UAV on a side of a UAV, or beneath the UAV. The background noise-producing components may be external to a housing of the UAV, or within a housing of the UAV. Any combination of locations for various background components may be provided. ¶0110-¶0113 discloses at least one processor can be provided to cancel the background noise from the audio data collected by the audio source collecting microphone, and generate a processed signal [e.g., an audio signal in which background noise is removed or reduced from the collected audio signal]. ¶0114 discloses fig. 4 shows a generic Multi-Channel RLS adaptive filter which is particularly suitable to reduce the effects of the background noise in UAVs. The Multi-Channel RLS adaptive filter of fig. 4 can be applied in a UAV with X rotors, which is provided with X background microphones and one audio source collecting microphone. In fig. 4, the noise produced by the propellers can be considered as the background noise. ¶0115 discloses the processor may adopt an adaptive filtering method to cancel the background noise. The filter parameters at current timing can be automatically adjusted according to an estimation error, by using the filter parameters at previous timing), and
wherein the operational condition comprises any of a velocity and an acceleration of the system (Xu ¶0080 discloses the interfering noise can be the noise produced by UAV itself or ambient noise. For example, the rotors of a multi-rotor UAV can generate remarkable noise when the UAV is in operation. ¶0200 discloses the rotation rate of each of the horizontally oriented rotors can be varied independently in order to control the lift and/or thrust produced by each rotor, and thereby adjust the spatial disposition, velocity, and/or acceleration of the movable object 1000. ¶0201 discloses the rotation rate of each of the horizontally oriented rotors can be varied independently in order to control the lift and/or thrust produced by each rotor, and thereby adjust the spatial disposition, velocity, and/or acceleration of the movable object 1000).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 4-5, 11, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Xu et al. (US #2016/0063987) in view of Beard et al. (US Patent #9489937).
Regarding Claim 4, Xu discloses the system of claim 1, but may not explicitly disclose wherein the noise cancellation system includes a filter that comprises a look up table.
However, Beard (title, abstract, figs. 1-4) teaches wherein the noise cancellation system includes a filter that comprises a look up table (Beard col. 4 lines 34-42 discloses predetermined frequency ranges 234a associated with the velocity of each motor or rotor 102, as well as attitude-dependent frequency ranges, can be stored in lookup tables 232. col. 5 lines 22-26 discloses the sensor 218 is operably connected to a lookup table 232 and a digital signal processor 230 to receive, recognize and/or calculate, and immediately subtract one or more noise-associated frequencies 122 from one or more incoming audio signals 120. col. 5 lines 35-48 discloses the sensor 218 can look up or find one or more frequencies 234a in the lookup table 232 that previously were determined to be associated with noise 122 generated by the motors M1 through Mn (106) and/or the rotors R1 through Rn (102) at one or more attitudes of the UAV 100. The sensor 218 can further determine the current attitude of the UAV 100 and subtract any frequency of the captured incoming audio signals [e.g., signal 120 and/or signal 122] that corresponds to the frequency found in the lookup table 232 [e.g., frequency 234a] at the current attitude of the UAC to generate one or more corrected audio signals 240 by subtracting [immediately] undesired frequencies 122, Fig. 3).
Xu and Beard are analogous art as they pertain to Unmanned Aerial Vehicle. Therefore it would have been obvious to someone of ordinary skill in the art before the effective filing date of the invention was made to modify the UAV system utilizing a filter (as taught by Xu) to eliminate a broader range of frequencies 122 by the combined process than the subtraction or cancellation process alone can initially capture (as taught by Beard, col. 5 lines 26-29) to generate and transmit a correlated audio signal after the frequencies, amplitudes, and harmonics are acquired (Beard, col. 2 lines 64-66).
Regarding Claim 5, Xu in view of Beard discloses the system of claim 4,
wherein the filter comprises a spectral noise cancellation filter (Xu ¶0113 discloses the processor can generate the processed signal using a variety of algorithms, like a Multi-Channel RLS algorithm or a Multi-Channel RLS adaptive filter to reduce the effects of the background noise. Other kinds of adaptive filters having similar configuration but less computation and less estimation can be used).
Regarding Claim 11, Xu discloses the system of claim 3, but may not explicitly disclose wherein the noise generating components comprise: a motor, wherein an audio signal frequency generated from the motor is based on a speed of the motor and the audio signal frequency is one part the baseline noise parameters.
However, Beard (title, abstract, figs. 1-4) teaches wherein the noise generating components comprise: a motor (Beard col. 3 lines 1-5 discloses one or more motors 106), wherein an audio signal frequency generated from the motor is based on a speed of the motor and the audio signal frequency is one part the baseline noise parameters (Beard col. 3 line 54 - col. 4 line 6 discloses referring to Fig. 3, the UAV 100 and noise-reducing system 200 further comprises one or more sensors 218 fixed to the airframe 108 and configured to measure/detect one or more variables [e.g., a rotor speed, motor speed, motor power input, etc.]. The sensors 218 are configured to track the attitude of the UAV 100, as well as the rotational velocity of each motor 102 or rotor 106. For example, each rotor 102 can include multiple blades. During operation, each motor 106 and each blade of each of rotor 102 produces a dynamic noise on a set frequency spectrum [e.g., audio signal 122]. Dependent on at least a determined speed and a determined orientation or angle of the UAV 100 [e.g., determined by sensors 218], the noise created from each rotor 102 and/or motor 106 varies on a constant basis. For example, a rotor 102 or motor 106 can spin at a determined rate [e.g., revolve at x RPM), while the UAV may have a determined attitude [e.g., orientation] y. The combination of x and y yields a determined noise z [e.g., the audio feed will include operating noise 122 having frequency/frequencies z]).
Xu and Beard are analogous art as they pertain to Unmanned Aerial Vehicle. Therefore it would have been obvious to someone of ordinary skill in the art before the effective filing date of the invention was made to modify the UAV system utilizing a filter (as taught by Xu) to eliminate a broader range of frequencies 122 by the combined process than the subtraction or cancellation process alone can initially capture (as taught by Beard, col. 5 lines 26-29) to generate and transmit a correlated audio signal after the frequencies, amplitudes, and harmonics are acquired (Beard, col. 2 lines 64-66).
Regarding Claim 16, Xu discloses the unmanned aerial vehicle of claim 15, but may not explicitly disclose wherein a filter is further configured to alter the audio signal based on a baseline profile.
However, Beard (title, abstract, figs. 1-4) teaches wherein a filter is further configured to alter the audio signal based on a baseline profile (Beard col. 5 lines 49-53 discloses the digital signal processor 230 and sensor 218 are configured to receive and recognize/calculate one or more frequencies 234a associated with an undesired audio signal 122 and utilize noise-cancellation techniques to produce a corrected audio signal 240. The correction signal 236 can be generated in the form of an anti-noise or anti-wave to reduce and/or eliminate the undesired audio signal 122).
Xu and Beard are analogous art as they pertain to Unmanned Aerial Vehicle. Therefore it would have been obvious to someone of ordinary skill in the art before the effective filing date of the invention was made to modify the UAV system utilizing a filter (as taught by Xu) to eliminate a broader range of frequencies 122 by the combined process than the subtraction or cancellation process alone can initially capture (as taught by Beard, col. 5 lines 26-29) to generate and transmit a correlated audio signal after the frequencies, amplitudes, and harmonics are acquired (Beard, col. 2 lines 64-66).
Claim 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Xu et al. (US #2016/0063987) in view of Beckman et al. (US Patent #10118692).
Regarding Claim 20, Xu discloses the method of claim 19, but may not explicitly disclose wherein the baseline noise parameters are noise with a known decibel and/or frequency, and wherein the filter includes removing the audible noise with a known decibel and/or frequency from the audio.
However, Beckman (title, abstract, figs. 1-12) teaches wherein the baseline noise parameters are noise with a known decibel and/or frequency, and wherein the filter includes removing the audible noise with a known decibel and/or frequency from the audio (Beckman col. 3 lines 25-39 discloses the measured sounds can be utilized to generate a sound profile that identifies a particular decibel level and other metrics associated with the sounds generated by or around the UAV. For example, a sound profile may be generated for each set of different sized propellers that identifies a decibel level, loudness, sharpness, roughness, fluctuation strength, and tonal prominence. Each metric included in the sound profile may be compared to one or more thresholds that correspond to the portion of the flight for delivery of an item to determine if the sound generated by the UAV should be reduced or altered).
Xu and Beckman are analogous art as they pertain to Unmanned Aerial Vehicle. Therefore it would have been obvious to someone of ordinary skill in the art before the effective filing date of the invention was made to modify the UAV system utilizing a filter (as taught by Xu) to generate a sound profile that identifies a particular decibel level and other metrics associated with the sounds generated by or around the UAV (as taught by Beckman, col. 3 lines 25-39) to reduce and/or alter the sound generated by a UAV during delivery of a payload, such as one containing an item ordered from a network-based resource, particularly, a UAV can be configured to utilize one or more sets of different sized propellers, during a transit portion of the flight and during a flight to a delivery location, and to release the payload upon arrival to the delivery location to reduce the overall decibel level of sound generated by the UAV and to generate a more pleasurable sound for nearby users (Beckman col. 2 lines 32-61).
Conclusion
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/YOGESHKUMAR PATEL/Primary Examiner, Art Unit 2691
