Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 3 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 3 recites the limitation "as a control input to the extended Kalman filter" at the end of the clauses beginning with “computing the frequency…” There is insufficient antecedent basis for the control input in the claim. Specifically, the phrase is grammatically and technically ambiguous as it is unclear which of the following elements in intended to be the “control input”:
The computed frequency of the sinusoidal signal
The sinusoidal signal itself
The measured angular velocity data
Because an extended Kalman filter treats “control inputs” (u) and “measurements” (z) as mathematically distinct entities, one skilled in the art would not be able to determine the metes and bounds of the claim without knowing which specific physical or mathematical quantity is being utilized as the control input.
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.
Claims 1, 16 and 31 are rejected under 35 U.S.C. 103 as being unpatentable over Xie (US 2019/0257923 A1) in view of Bosukonda et al. (US 2021/0262448 A1), Murarka et al. (US 2021/0055107 A1), and Fan et al. (CN204117440U).
Regarding Claim 1, Xie teaches a method of controlling laser scanning by a rotorcraft ([Abstract] LIDAR modules… the UAV can carry a motion mechanism operable to rotate the scanning module relative to the airframe about a spin axis, so that the scanning module can perform 360 degree horizontal scans), the rotorcraft comprising a rotatable body frame configured to rotate during flight ([0038] The rotors can include one or more rotor blades coupled to a shaft. The rotor blades and shaft can be rotated by a suitable drive mechanism, such as a motor. Although the propulsion units 130 of the moveable object 110 are depicted as propeller-based); a laser rangefinder configured to perform laser scanning ([0008] The scanning element includes a scanner, which can be a light detection and ranging (LIDAR) system).
Xie is not relied upon as teaching that the method of controlling a rotorcraft comprises a laser rangefinder that is mounted on the rotatable body frame; and a magnetometer configured to measure the magnetic field, the method comprising: obtaining magnetic field measurement data from the magnetometer while the rotatable body frame is rotating during flight, the magnetic field measurement data comprising a sinusoidal signal; estimating a frequency of the sinusoidal signal; and controlling the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal.
However, Bosukonda teaches that the method of controlling a rotorcraft comprises a laser rangefinder that is mounted on the rotatable body frame ([0007] a wind turbine blade comprising a main blade portion and a light detection and ranging (LIDAR) element, the main blade portion having a shell defining an outer aerodynamic surface of the blade, and the LIDAR element being disposed within a volume bounded by the outer aerodynamic surface and comprising at least one LIDAR system configured to transmit light beams away from the blade and to detect reflected light beams incident upon the blade).
Xie and Bosukonda are considered to be analogous to the claimed invention because they are both in the same field of remote sensing and laser scanning using rotatable aerodynamic structures. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the rotatable body frame of Xie to include the LIDAR element mounted directly on a rotatable frame (the blade) of Bosukonda with a reasonable expectation of success. This modification would have been motivated by the desire to simplify the mechanical scanning assembly by utilizing the inherent rotation of the vehicle’s own structural components (e.g., the rotor/blade) to provide the necessary scanning motion, rather than relying on a separate dedicated motion mechanism. By integrating Bokusanda’s teaching of mounting a LIDAR system within the volume of a rotatable aerodynamic surface into Xie’s rotorcraft system, the system can achieve wide-area scanning coverage while reducing the overall payload weight and mechanical complexity of the UAV. A person of ordinary skill in the art would recognize that using the rotation of the body frame to drive the scanning sweep would yield the predictable result of a synchronized laser scan that correlates directly with the rotational frequency of the rotorcraft’s propulsion or body components.
Bosukonda is not relied upon as teaching that the method of controlling a rotorcraft comprises a magnetometer configured to measure the magnetic field, the method comprising: obtaining magnetic field measurement data from the magnetometer while the rotatable body frame is rotating during flight, the magnetic field measurement data comprising a sinusoidal signal; estimating a frequency of the sinusoidal signal; and controlling the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal.
However, Murarka teaches that the method of controlling a rotorcraft comprises a magnetometer configured to measure the magnetic field ([0107] a magnetic field sensor or a magnetic intensity sensor (also called a magnetometer) may be used, communicably coupled to the object, in order to sense or detect or measure (and record) magnetic field intensity and its changes as the object's orientation or attitude changes with time), the method comprising:
obtaining magnetic field measurement data from the magnetometer while the rotatable body frame is rotating during flight ([0052] there is disclosed a system for measuring the rate of angular displacement, of an object, traveling along a trajectory, using magnetic field sensing), the magnetic field measurement data comprising a sinusoidal signal ([0148] FIGS. 3 and 4 illustrate magnetic field intensity plotted over time for different trajectories. The Y-axis delineates various magnetic field intensity values, the X-axis delineates time-stamp values, time instances, or data point numbers, or data point indexing numbers Examiner Note: Both Fig. 3 and 4 show sinusoidal signals);
estimating a frequency of the sinusoidal signal ([0129] where a measurement is the act of deducing the number of peaks in the magnetometer signal or the frequency to thereby calculate the rate of rotation).
Xie in view of Bosukonda, and Murarka are considered to be analogous to the claimed invention because they are both in the same field of sensor-based navigation and rotation sensing for moving objects. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the rotorcraft system of Xie as modified by Bosukonda to include magnetometer and frequency estimation method of Murarka with a reasonable expectation of success. This modification would have been motivated by the desire to accurately determine the rotational rate and orientation of the rotatable body frame without requiring complex mechanical encoders or optical sensors, which may be prone to failure in flight environments. By integrating Murarka’s teaching of obtaining magnetic field measurement data to deduce a rotation rate from a sinusoidal signal into Xie’s rotorcraft system (as modified by Bosukonda), the system can dynamically adjust and control the timing of the laser rangefinder scans based on the real-time angular displacement of the rotating blade. A person of ordinary skill in the art would recognize that using ambient magnetic field fluctuations to estimate frequency would yield the predictable result of a synchronized scanning system that maintains consistent spatial resolution regardless of fluctuations in the rotor’s rotational speed.
Murarka is not relied upon as teaching controlling the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal.
However, Fan teaches controlling the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal ([Abstract] the signal generation module outputs a sinusoidal oscillation signal to the coil of the electromagnet, and drives the vibration mechanism in the X direction through the electromagnet to drive the small laser to vibrate, and the laser beam scans along the X direction on the mirror; the motor drives the vibration mechanism in the Y direction to drive the mirror along the Vibration in the Y direction makes the laser beam reflected by the mirror scan along the Y direction).
Xie in view of Bosukonda and Murarka, and Fan are considered to be analogous to the claimed invention because they are both in the same field of controlling laser scanning modules based on oscillatory or periodic signal feedback. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the rotorcraft scanning system of Xie (as modified by Bosukonda and Murarka) to include controlling the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal as taught by Fan with a reasonable expectation of success. This modification would have been motivated by the desire to synchronize the firing and movement of the laser scanner with the physical oscillation or rotation of the scanning platform to ensure uniform data point distribution. By integrating Fan’s teaching of utilizing a sinusoidal signal to drive and control the vibration or scanning path of a laser into the rotorcraft system already utilizing Murarka’s magnetic frequency estimation, the system can dynamically time the laser pulses to occur at specific angular positions of the rotatable body frame. A person of ordinary skill in the art would recognize that using the frequency derived from the magnetometer to drive the scanning trigger logic would yield the predictable result of a stabilized laser scan where the scanning frequency is automatically slaved into the rotational frequency of the rotor blades, preventing smearing or gaps in the resulting point cloud.
Regarding Claim 16, Xie teaches a controller for controlling laser scanning by a rotorcraft ([0010] the light sensing module includes an array of light sensors. The vehicle can further include a controller configured to estimate a first distance between the vehicle and a detected obstacle based on output from a select one (e.g., the centermost) light sensor among the array of light sensors), the rotorcraft comprising a rotatable body frame configured to rotate during flight ([0038] The rotors can include one or more rotor blades coupled to a shaft. The rotor blades and shaft can be rotated by a suitable drive mechanism, such as a motor. Although the propulsion units 130 of the moveable object 110 are depicted as propeller-based); a laser rangefinder configured to perform laser scanning ([0008] The scanning element includes a scanner, which can be a light detection and ranging (LIDAR) system);
the controller comprising:
a memory ([0032] instructions can be contained in any suitable memory device); and
at least one processor communicatively coupled to the memory ([0032] a special-purpose computer or data processor that is specifically programmed, configured or constructed to perform one or more of the computer-executable instructions…. instructions can be contained in any suitable memory device).
Xie is not relied upon as teaching that the rotorcraft comprises a laser rangefinder that is mounted on the rotatable body frame; and a magnetometer configured to measure the magnetic field, the at least one processor configured to: obtain magnetic field measurement data from the magnetometer while the rotatable body frame is rotating during flight, the magnetic field measurement data comprising a sinusoidal signal; estimate a frequency of the sinusoidal signal; and control the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal.
However, Bosukonda teaches that the rotorcraft comprises a laser rangefinder that is mounted on the rotatable body frame ([0007] a wind turbine blade comprising a main blade portion and a light detection and ranging (LIDAR) element, the main blade portion having a shell defining an outer aerodynamic surface of the blade, and the LIDAR element being disposed within a volume bounded by the outer aerodynamic surface and comprising at least one LIDAR system configured to transmit light beams away from the blade and to detect reflected light beams incident upon the blade).
Xie and Bosukonda are considered to be analogous to the claimed invention because they are both in the same field of remote sensing and laser scanning using rotatable aerodynamic structures. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the rotatable body frame of Xie to include the LIDAR element mounted directly on a rotatable frame (the blade) of Bosukonda with a reasonable expectation of success. This modification would have been motivated by the desire to simplify the mechanical scanning assembly by utilizing the inherent rotation of the vehicle’s own structural components (e.g., the rotor/blade) to provide the necessary scanning motion, rather than relying on a separate dedicated motion mechanism. By integrating Bokusanda’s teaching of mounting a LIDAE system within the volume of a rotatable aerodynamic surface into Xie’s rotorcraft system, the system can achieve wide-area scanning coverage while reducing the overall payload weight and mechanical complexity of the UAV. A person of ordinary skill in the art would recognize that using the rotation of the body frame to drive the scanning sweep would yield the predictable result of a synchronized laser scan that correlates directly with the rotational frequency of the rotorcraft’s propulsion or body components.
Bosukonda is not relied upon as teaching that the rotorcraft comprises a magnetometer configured to measure the magnetic field, the at least one processor configured to: obtain magnetic field measurement data from the magnetometer while the rotatable body frame is rotating during flight, the magnetic field measurement data comprising a sinusoidal signal; estimate a frequency of the sinusoidal signal; and control the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal.
However, Murarka teaches that the rotorcraft comprises a magnetometer configured to measure the magnetic field ([0107] a magnetic field sensor or a magnetic intensity sensor (also called a magnetometer) may be used, communicably coupled to the object, in order to sense or detect or measure (and record) magnetic field intensity and its changes as the object's orientation or attitude changes with time), the at least one processor configured to:
obtain magnetic field measurement data from the magnetometer while the rotatable body frame is rotating during flight ([0052] there is disclosed a system for measuring the rate of angular displacement, of an object, traveling along a trajectory, using magnetic field sensing), the magnetic field measurement data comprising a sinusoidal signal ([0148] FIGS. 3 and 4 illustrate magnetic field intensity plotted over time for different trajectories. The Y-axis delineates various magnetic field intensity values, the X-axis delineates time-stamp values, time instances, or data point numbers, or data point indexing numbers Examiner Note: Both Fig. 3 and 4 show sinusoidal signals); and
estimate a frequency of the sinusoidal signal ([0129] where a measurement is the act of deducing the number of peaks in the magnetometer signal or the frequency to thereby calculate the rate of rotation).
Xie in view of Bosukonda, and Murarka are considered to be analogous to the claimed invention because they are both in the same field of sensor-based navigation and rotation sensing for moving objects. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the rotorcraft system of Xie as modified by Bosukonda to include magnetometer and frequency estimation method of Murarka with a reasonable expectation of success. This modification would have been motivated by the desire to accurately determine the rotational rate and orientation of the rotatable body frame without requiring complex mechanical encoders or optical sensors, which may be prone to failure in flight environments. By integrating Murarka’s teaching of obtaining magnetic field measurement data to deduce a rotation rate from a sinusoidal signal into Xie’s rotorcraft system (as modified by Bosukonda), the system can dynamically adjust and control the timing of the laser rangefinder scans based on the real-time angular displacement of the rotating blade. A person of ordinary skill in the art would recognize that using ambient magnetic field fluctuations to estimate frequency would yield the predictable result of a synchronized scanning system that maintains consistent spatial resolution regardless of fluctuations in the rotor’s rotational speed.
Murarka is not relied upon as teaching the at least one processor configured to: control the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal.
However, Fan teaches at least one processor configured to: control the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal ([Abstract] the signal generation module outputs a sinusoidal oscillation signal to the coil of the electromagnet, and drives the vibration mechanism in the X direction through the electromagnet to drive the small laser to vibrate, and the laser beam scans along the X direction on the mirror; the motor drives the vibration mechanism in the Y direction to drive the mirror along the Vibration in the Y direction makes the laser beam reflected by the mirror scan along the Y direction).
Xie in view of Bosukonda and Murarka, and Fan are considered to be analogous to the claimed invention because they are both in the same field of controlling laser scanning modules based on oscillatory or periodic signal feedback. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the rotorcraft scanning system of Xie (as modified by Bosukonda and Murarka) to include controlling the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal as taught by Fan with a reasonable expectation of success. This modification would have been motivated by the desire to synchronize the firing and movement of the laser scanner with the physical oscillation or rotation of the scanning platform to ensure uniform data point distribution. By integrating Fan’s teaching of utilizing a sinusoidal signal to drive and control the vibration or scanning path of a laser into the rotorcraft system already utilizing Murarka’s magnetic frequency estimation, the system can dynamically time the laser pulses to occur at specific angular positions of the rotatable body frame. A person of ordinary skill in the art would recognize that using the frequency derived from the magnetometer to drive the scanning trigger logic would yield the predictable result of a stabilized laser scan where the scanning frequency is automatically slaved into the rotational frequency of the rotor blades, preventing smearing or gaps in the resulting point cloud.
Regarding Claim 31, Xie teaches a rotorcraft configured to perform laser scanning ([Abstract] LIDAR modules…the UAV can carry a motion mechanism operable to rotate the scanning module relative to the airframe about a spin axis, so that the scanning module can perform 360-degree horizontal scans), the rotorcraft comprising:
a rotatable body frame configured to rotate during flight ([0038] The rotors can include one or more rotor blades coupled to a shaft. The rotor blades and shaft can be rotated by a suitable drive mechanism, such as a motor. Although the propulsion units 130 of the moveable object 110 are depicted as propeller-based);
a laser rangefinder configured to perform laser scanning ([0008] The scanning element includes a scanner, which can be a light detection and ranging (LIDAR) system);
the controller for controlling the laser rangefinder to perform laser scanning ([0010] the light sensing module includes an array of light sensors. The vehicle can further include a controller configured to estimate a first distance between the vehicle and a detected obstacle based on output from a select one (e.g., the centermost) light sensor among the array of light sensors),
the controller comprising:
a memory ([0032] instructions can be contained in any suitable memory device); and
at least one processor communicatively coupled to the memory ([0032] a special-purpose computer or data processor that is specifically programmed, configured or constructed to perform one or more of the computer-executable instructions…. instructions can be contained in any suitable memory device).
Xie is not relied upon as teaching that rotorcraft comprises a laser rangefinder that is mounted on the rotatable body frame; and a magnetometer configured to measure magnetic field; the processor configured to: obtain magnetic field measurement data from the magnetometer while the rotatable body frame is rotating during flight, the magnetic field measurement data comprising a sinusoidal signal; estimate a frequency of the sinusoidal signal; and control the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal.
However, Bosukonda teaches that the rotorcraft comprises a laser rangefinder that is mounted on the rotatable body frame ([0007] a wind turbine blade comprising a main blade portion and a light detection and ranging (LIDAR) element, the main blade portion having a shell defining an outer aerodynamic surface of the blade, and the LIDAR element being disposed within a volume bounded by the outer aerodynamic surface and comprising at least one LIDAR system configured to transmit light beams away from the blade and to detect reflected light beams incident upon the blade).
Xie and Bosukonda are considered to be analogous to the claimed invention because they are both in the same field of remote sensing and laser scanning using rotatable aerodynamic structures. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the rotatable body frame of Xie to include the LIDAR element mounted directly on a rotatable frame (the blade) of Bosukonda with a reasonable expectation of success. This modification would have been motivated by the desire to simplify the mechanical scanning assembly by utilizing the inherent rotation of the vehicle’s own structural components (e.g., the rotor/blade) to provide the necessary scanning motion, rather than relying on a separate dedicated motion mechanism. By integrating Bokusanda’s teaching of mounting a LIDAE system within the volume of a rotatable aerodynamic surface into Xie’s rotorcraft system, the system can achieve wide-area scanning coverage while reducing the overall payload weight and mechanical complexity of the UAV. A person of ordinary skill in the art would recognize that using the rotation of the body frame to drive the scanning sweep would yield the predictable result of a synchronized laser scan that correlates directly with the rotational frequency of the rotorcraft’s propulsion or body components.
Bosukonda is not relied upon as teaching that the rotorcraft comprises a magnetometer configured to measure the magnetic field, the processor configured to: obtain magnetic field measurement data from the magnetometer while the rotatable body frame is rotating during flight, the magnetic field measurement data comprising a sinusoidal signal; estimate a frequency of the sinusoidal signal; and control the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal.
However, Murarka teaches that the rotorcraft comprises a magnetometer configured to measure the magnetic field ([0107] a magnetic field sensor or a magnetic intensity sensor (also called a magnetometer) may be used, communicably coupled to the object, in order to sense or detect or measure (and record) magnetic field intensity and its changes as the object's orientation or attitude changes with time), the processor configured to:
obtain magnetic field measurement data from the magnetometer while the rotatable body frame is rotating during flight ([0052] there is disclosed a system for measuring the rate of angular displacement, of an object, traveling along a trajectory, using magnetic field sensing), the magnetic field measurement data comprising a sinusoidal signal ([0148] FIGS. 3 and 4 illustrate magnetic field intensity plotted over time for different trajectories. The Y-axis delineates various magnetic field intensity values, the X-axis delineates time-stamp values, time instances, or data point numbers, or data point indexing numbers Examiner Note: Both Fig. 3 and 4 show sinusoidal signals);
estimate a frequency of the sinusoidal signal ([0129] where a measurement is the act of deducing the number of peaks in the magnetometer signal or the frequency to thereby calculate the rate of rotation).
Xie in view of Bosukonda, and Murarka are considered to be analogous to the claimed invention because they are both in the same field of sensor-based navigation and rotation sensing for moving objects. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the rotorcraft system of Xie as modified by Bosukonda to include magnetometer and frequency estimation method of Murarka with a reasonable expectation of success. This modification would have been motivated by the desire to accurately determine the rotational rate and orientation of the rotatable body frame without requiring complex mechanical encoders or optical sensors, which may be prone to failure in flight environments. By integrating Murarka’s teaching of obtaining magnetic field measurement data to deduce a rotation rate from a sinusoidal signal into Xie’s rotorcraft system (as modified by Bosukonda), the system can dynamically adjust and control the timing of the laser rangefinder scans based on the real-time angular displacement of the rotating blade. A person of ordinary skill in the art would recognize that using ambient magnetic field fluctuations to estimate frequency would yield the predictable result of a synchronized scanning system that maintains consistent spatial resolution regardless of fluctuations in the rotor’s rotational speed.
Murarka is not relied upon as teaching the processor configured to control the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal.
However, Fan teaches the processor configured to control the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal ([Abstract] the signal generation module outputs a sinusoidal oscillation signal to the coil of the electromagnet, and drives the vibration mechanism in the X direction through the electromagnet to drive the small laser to vibrate, and the laser beam scans along the X direction on the mirror; the motor drives the vibration mechanism in the Y direction to drive the mirror along the Vibration in the Y direction makes the laser beam reflected by the mirror scan along the Y direction).
Xie in view of Bosukonda and Murarka, and Fan are considered to be analogous to the claimed invention because they are both in the same field of controlling laser scanning modules based on oscillatory or periodic signal feedback. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the rotorcraft scanning system of Xie (as modified by Bosukonda and Murarka) to include controlling the laser rangefinder to perform laser scanning based on the estimated frequency of the sinusoidal signal as taught by Fan with a reasonable expectation of success. This modification would have been motivated by the desire to synchronize the firing and movement of the laser scanner with the physical oscillation or rotation of the scanning platform to ensure uniform data point distribution. By integrating Fan’s teaching of utilizing a sinusoidal signal to drive and control the vibration or scanning path of a laser into the rotorcraft system already utilizing Murarka’s magnetic frequency estimation, the system can dynamically time the laser pulses to occur at specific angular positions of the rotatable body frame. A person of ordinary skill in the art would recognize that using the frequency derived from the magnetometer to drive the scanning trigger logic would yield the predictable result of a stabilized laser scan where the scanning frequency is automatically slaved into the rotational frequency of the rotor blades, preventing smearing or gaps in the resulting point cloud.
Claims 2 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Xie (US 2019/0257923 A1), Bosukonda et al. (US 2021/0262448 A1), Murarka et al. (US 2021/0055107 A1), and Fan et al. (CN204117440U) in further view of Madgwick et al. (“Estimation of IMU and MARG orientation using a gradient descent algorithm” 2011 IEEE International Conference on Rehabilitation Robotics Rehab Week Zurich, ETH Zurich Science City, Switzerland, June 29 - July 1, 2011).
Regarding Claims 2 and 17, Xie, Bosukonda, Murarka, and Fan are not relied upon as teaching that the frequency of the sinusoidal signal is estimated based on an extended Kalman filter.
However, Madgwick teaches that the frequency of the sinusoidal signal is estimated based on an extended Kalman filter ([Col. 2, ll. 40-43] The state relationships describing rotational kinematics in three dimensions typically require large state vectors and an extended Kalman filter implementation).
Xie in view of Bosukonda, Murarka, and Fan, and Madgwick are considered to be analogous to the claimed invention because they are both in the same field of state estimation and signal processing for rotating bodies. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the signal processing method of Xie (as modified by Bosukonda, Murarka, and Fan) to include estimating the frequency based on an extended Kalman filter as taught by Madgwick with a reasonable expectation of success. This modification would have been motivated by the desire to improve the accuracy and robustness of the rotation frequency estimation in the presence of noise or non-linearities. By integrating Madgwick’s teaching of using an extended Kalman filter for rotational kinematics into the rotorcraft scanning system, the system can more effectively filter magnetic field measurement data to provide a smoothed, real time frequency estimate. A person of ordinary skill in the art would recognize that utilizing a Kalman filter to process the sinusoidal signal would yield the predictable result of reduced estimation error and more stable control of the laser rangefinder.
Claims 3, 4, 6, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Xie (US 2019/0257923 A1), Bosukonda et al. (US 2021/0262448 A1), Murarka et al. (US 2021/0055107 A1), Fan et al. (CN204117440U), and Madgwick et al. (2011 IEEE International Conference on Rehabilitation Robotics Rehab Week Zurich, ETH Zurich Science City, Switzerland, June 29 - July 1, 2011) in further view of Morgan (US 2012/0265440 A1).
Regarding Claims 3 and 18, Xie (as previously modified by Bosukonda, Murarka, Fan, and Madgwick) is not relied upon as teaching that the rotorcraft further comprises a gyroscope mounted on the rotatable body frame and configured to measure an angular velocity thereof about a rotational axis of the rotatable body frame, and said estimating the frequency of the sinusoidal signal comprises: obtaining gyroscope measurement data from the gyroscope, the gyroscope measurement data comprising measured angular velocity data measured by the gyroscope about the rotational axis of the rotatable body frame; and computing the frequency of the sinusoidal signal based on the measured angular velocity data as a control input to the extended Kalman filter.
However, Bosukonda teaches that the rotorcraft further comprises a gyroscope mounted on the rotatable body frame ([Abstract] the LIDAR element being disposed within a volume bounded by the outer aerodynamic surface and comprising at least one LIDAR system configured to transmit light beams away from the blade and to detect reflected light beams incident upon the blade, wherein the shell comprises at least one aperture extending at least partly through a thickness of the shell and containing optically transparent material, wherein the at least one LIDAR system is disposed within a volume bounded by an inner surface of the shell… comprising a gyroscope mechanism coupled to the at least one LIDAR system such that an orientation of the at least one LIDAR system is substantially unaffected by movement of the blade so as to vary an angle at which light beams are transmitted through the optically transparent material as the blade moves).
Xie (as modified by Bosukonda, Murarka, Fan, and Madgwick) and Bosukonda are considered to be analogous to the claimed invention because they are both in the same field of integrating sensor payloads into aerodynamic structures. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the system of Xie (as already modified) to include the gyroscope mounted on the rotatable body frame as taught by Bosukonda with a reasonable expectation of success. This modification would have been motivated by the desire to provide a localized measurement of the rotor’s motion directly at eh point of the LIDAR’s mounting, ensuring that the sensor’s orientation data is not skewed. By further integrating Bosukonda’s teaching of a gyroscope mechanism coupled to the LIDAR system within the rotor blade volume into the combined rotorcraft system, the system can achieve higher precision into mapping the spatial coordinates of the laser returns. A person of ordinary skill in the art would recognize that placing the gyroscope in the same rotatable housing as the laser rangefinder would yield the predictable result of providing a direct correlation between the sensor’s rotation velocity and the scanner’s spatial output.
Bosukonda is not relied upon as teaching that the gyroscope is configured to measure an angular velocity thereof about a rotational axis of the rotatable body frame, and said estimating the frequency of the sinusoidal signal comprises: obtaining gyroscope measurement data from the gyroscope, the gyroscope measurement data comprising measured angular velocity data measured by the gyroscope about the rotational axis of the rotatable body frame; and computing the frequency of the sinusoidal signal based on the measured angular velocity data as a control input to the extended Kalman filter.
However, Murarka teaches that the gyroscope is configured to measure an angular velocity thereof about a rotational axis of the rotatable body frame ([0003] electronic gyroscopes or angular rate sensors detect the rate of angular displacement of an object or a body to which they are attached or integrated), and
said estimating the frequency of the sinusoidal signal comprises:
obtaining gyroscope measurement data from the gyroscope, the gyroscope measurement data comprising measured angular velocity data measured by the gyroscope about the rotational axis of the rotatable body frame ([0145] the system comprises an inertial measurement unit (IMU) further comprising one or more of a single-axis gyroscope or a multi-axis gyroscope providing gyroscope data; and at least one processor which causes the system to use said gyroscope data to verify the fidelity of computed orientation of said traveling object); and
computing the frequency of the sinusoidal signal based on the measured angular velocity data ([0067] causes the system to use said gyroscope data to verify the fidelity of computed orientation of said traveling object).
Xie (as modified by Bosukonda, Murarka, Fan, and Madgwick) and Murarka are considered to be analogous to the claimed invention because they are both in the same field of motion estimation and signal processing for traveling objects. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the system of Xie (as already modified) to include the gyroscope measurement data used to verify the fidelity of computed orientation as taught by Murarka with a reasonable expectation of success. This modification would have been motivated by the desire to enhance the reliability of the system’s spatial awareness by providing a secondary, independent data source to cross-reference the magnetometer derived frequency. By further integrating Murarka’s teaching of utilizing an inertial measurement unit comprising a multi-axis gyroscope into the combined rotorcraft system, the system can validate that the sinusoidal signal frequency correctly corresponds to the physical rotation of the body frame. A person of ordinary skill in the art would recognize that using gyroscope data to verify the fidelity of computed orientation would yield the predictable result of identifying and correcting for estimation drift or magnetic interference, ensuring the laser scanning remains aligned with the intended coordinates.
Murarka is not relied upon as teaching a control input to the extended Kalman filter.
However, Morgan teaches a control input to the extended Kalman filter ([0038]-[0039] Extended Kalman Filter (EKF) 310 receives inputs from a high rate INS navigation propagation unit 320… The navigation propagation unit 320 receives INS data 322, which includes integrated acceleration data and gyroscope data, such as from an IMU).
Xie in view of Bosukonda, Murarka, Fan, and Madgwick, and Morgan are considered to be analogous to the claimed invention because they are both in the same field of navigation state estimation and sensor data processing. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the signal processing method of the combined system to include computing the frequency based on measured angular velocity data as a control input to the extended Kalman filter as taught by Morgan with a reasonable expectation of success. This modification would have been motivated by the desire to utilize inertial data to provide the state estimator with information regarding changes in rotational velocity. By integrating Morgan’s teaching of an Extended Kalman Filter (EKF) that receives inputs from a navigation propagation unit utilizing gyroscope data into the rotorcraft system, the system can treat the angular velocity as a known control input to drive the state transition model. A person of ordinary skill in the art would recognize that using the measured angular velocity as a control input to the extended Kalman filter would yield the predictable result of enabling the filter to maintain an accurate frequency estimate even during rapid accelerations of the rotatable body frame, ensuring the laser scanning remains synchronized with the actual physical movement.
Regarding Claim 4, Xie (as previously modified by Bosukonda, Murarka, Fan, Madgwick, and Morgan) is not relied upon as teaching that said estimating the frequency of the sinusoidal signal further comprises estimating a gyro bias associated with the gyroscope in relation to the measured angular velocity data based on an estimated state in the extended Kalman filter, and said computing the frequency of the sinusoidal signal is further based on the estimated gyro bias, wherein the extended Kalman filter is based on a state transition function, the measured angular velocity data is a control input to the state transition function, and the estimated gyro bias is an estimated state in the state transition function.
However, Morgan teaches that said estimating the frequency of the sinusoidal signal further comprises estimating a gyro bias associated with the gyroscope in relation to the measured angular velocity data based on an estimated state in the extended Kalman filter ([0037] or navigation quality inertial measurement units 108, the states can include gyroscope bias (3), gyroscope scale factor (3), gyroscope non-orthogonality (3), accelerometer bias (3), accelerometer scale factor (3), and accelerometer misalignment (6). Note that another possible implementation could use three accelerometer non-orthogonality and six gyroscope misalignment states. A combination of pre- and post-measurement processing, along with cross comparing change in phase with change in inertial data, can be used to detect accumulated phase cycle slips and ensure the accuracy of the navigation solution), and
said computing the frequency of the sinusoidal signal is further based on the estimated gyro bias ([0039] navigation propagation unit 320 receives INS data 322, which includes integrated acceleration data and gyroscope data, such as from an IMU. The navigation propagation unit 320 also receives initial navigation state conditions 324, which contain initial estimates of position, velocity, and attitude. Since EKF 310 aligns the INS and uses GPS data, it is not necessary for the initial conditions to be very accurate. The navigation propagation unit 320 outputs navigation state data to EKF 310. The navigation state data includes current position, velocity, and attitude data),
wherein
the extended Kalman filter is based on a state transition function ([0039] The state transition matrix is discussed in further detail hereafter),
the measured angular velocity data is a control input to the state transition function ([0044] A state transition matrix integration module 450 receives navigation state data 446, accelerometer data 404, and gyroscope data 402), and
the estimated gyro bias is an estimated state in the state transition function ([0039] The navigation propagation unit 320 also outputs an INS state transition matrix to EKF 310. The state transition matrix is discussed in further detail hereafter).
Xie (as previously modified by Bosukonda, Murarka, Fan, Madgwick, and Morgan) and Morgan are considered to be analogous to the claimed invention because they are both in the same field of state estimation and inertial navigation processing. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Extended Kalman Filter of the combined system to include estimating a gyro bias associated with the gyroscope in relation to the measured angular velocity data based on an estimated state in the extended Kalman filter as taught by Morgan with a reasonable expectation of success. This modification would have been motivated by the desire to improve the long-term accuracy and stability for the rotational frequency estimation by compensating for inherent sensor errors. By further integrating Morgan’s teaching of including gyroscope bias as an estimated state within an EKF into the rotorcraft scanning system, the filter can dynamically distinguish between actual changes in the rotor’s rotation rate and the drifting errors typical of MEMS gyroscopes. A person of ordinary skill in the art would recognize that accounting for gyro bias in the state transition function would yield the predictable result of preventing cumulative error in the sinusoidal frequency estimation.
Regarding Claim 6, Xie (as previously modified by Bosukonda, Murarka, Fan, Madgwick, and Morgan) is not relied upon as teaching that said computing the frequency of the sinusoidal signal is further based on a difference between the measured angular velocity data and the estimated gyro bias.
However, Murarka teaches computing the frequency of the sinusoidal signal ([0129] where a measurement is the act of deducing the number of peaks in the magnetometer signal or the frequency to thereby calculate the rate of rotation).
Xie (as previously modified by Bosukonda, Murarka, Fan, Madgwick, and Morgan) and Murarka are considered to be analogous to the claimed invention because they are both in the same field of signal processing for rotating objects. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the signal processing method for the combined system to include computing the frequency of the sinusoidal signal as taught by Murarka with a reasonable expectation of success. This modification would have been motivated by the desire to accurately determine the physical rate of rotation of the body frame by analyzing the periodic peaks of the sensed magnetic field. By further integrating Murarka’s teaching of deducing the frequency from the number of peaks in a magnetometer signal into the rotorcraft scanning system, the system can establish a reliable baseline for the scanning rate. A person of ordinary skill in the art would recognize that using a peak-to-peak frequency calculation would yield the predictable result of a direct mathematical representation of the rotor’s angular velocity based on environmental magnetic flux.
Murarka is not relied upon as teaching a difference between the measured angular velocity data and the estimated gyro bias
However, Morgan teaches a difference ([0042] The INS data 322 received by navigation propagation unit 320 includes gyroscope data 402 and accelerometer data 404… one Hz navigation state corrections module 410 receives navigation state data… The navigation state corrections module 410 outputs updated navigation state data, including attitude, velocity, and position measurements, to an integrator 418 that includes a quaternion integration module 420, a velocity integration module 430, and a position integration module 440 Examiner Note: the corrections module is implementing the difference) between the measured angular velocity data ([0044] A state transition matrix integration module 450 receives navigation state data 446, accelerometer data 404, and gyroscope data 402) and the estimated gyro bias ([0039] The navigation propagation unit 320 also outputs an INS state transition matrix to EKF 310. The state transition matrix is discussed in further detail hereafter).
Xie (as previously modified by Bosukonda, Murarka, Fan, Madgwick, and Morgan) and Morgan are considered to be analogous to the claimed invention because they are both in the same field of processing inertial sensor data for navigation systems. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the signal processing method of the combined system to include computing the frequency of the sinusoidal signal based on a difference between the measured angular velocity data and the estimated gyro bias as taught by morgan with a reasonable expectation of success. This modification would have been motivated by the desire to calculate a corrected angular velocity by removing known sensor errors before the data is used for high-level control logic. By further integrating Morgan’s teaching of using a corrections module to implement the difference between the measured data and estimated bias states into the rotorcraft scanning system, the system can ensure that the frequency used to control the laser rangefinder reflects the actual physical rotation of the rotor rather than a biased sensor reading. A person of ordinary skill in the art would recognize that subtracting the estimated gyro bias from the raw measured angular velocity would yield the predictable result of increased accuracy in the synchronization of the laser pulses.
Claims 7, 11, 22, and 26 are rejected under 35 U.S.C. 103 as being unpatentable over Xie (US 2019/0257923 A1), Bosukonda et al. (US 2021/0262448 A1), Murarka et al. (US 2021/0055107 A1), and Fan et al. (CN204117440U) in view of Hseih et al. (“Phase-Locked Loop Techniques-A Survey” IEEE Transactions of Industrial electronics, Vol. 43, No. 6, December 1996) and Furtney, Jr. (US 3878473).
Regarding Claims 7 and 22, Xie (as previously modified by Bosukonda, Murarka, and Fan) is not relied upon as teaching that the frequency of the sinusoidal signal is estimated based on a phase-locked loop, wherein the phase-locked loop comprises a phase detector, a loop filter and a numerically- controlled oscillator, the phase detector being configured to compare a phase of an output signal of the phase-locked loop with a phase of a reference input signal of the phase-locked loop to produce an error signal, and the reference input signal is based on the sinusoidal signal of the magnetic field measurement data.
However, Hseih teaches that the frequency of the sinusoidal signal is estimated based on a phase-locked loop ([Col. 2, ll. 34-35 & Col. 3, ll. 2-3] The VCO is a frequency-modulated oscillator, whose instantaneous angular frequency winst is a linear function of the controlled signal vc(t), around the central angular frequency)
wherein the phase-locked loop comprises a phase detector and a loop filter ([Col. 2, ll. 7-9] PLL is shown in Fig. 1, which consists of a phase detector (PD), a loop filter (LF), and a voltage-controlled oscillator (VCO)), the phase detector being configured to compare a phase of an output signal of the phase-locked loop with a phase of a reference input signal of the phase-locked loop to produce an error signal ([Col. 2, ll. 4-6] the PLL is simply a servo system, which controls the phase of its output signal in such a way that the phase error between output phase and reference phase reduces to a minimum), and
the reference input signal is based on the sinusoidal signal ([Col. 2, ll. 10-15] Let xi and xo be, respectively, the input and the VCO signals, which can be expressed as… Examiner Noter: See Equations 1 and 2 reproduced below:).
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Xie (as previously modified by Bosukonda, Murarka, and Fan) and Hseih are considered to be analogous to the claimed invention because they are both in the same field of signal frequency estimation and phase synchronization. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the signal processing method of the combined system to include estimating the frequency of the sinusoidal signal based on a phase-locked loop as taught by Hseih with a reasonable expectation of success. This modification would have been motivated by the desire to provide a continuous and high-precision estimate of the rotation frequency that can stay “locked” to the input signal even in the presence of noise. By integrating Hseih’s teaching of a phase-locked loop (PLL) comprising a phase detector, loop filter, and oscillator into the rotorcraft scanning system, the system can produce an output signal that tracks the phase of the magnetometer-derived sinusoidal signal to minimize error. A person of ordinary skill in the art would recognize that using a PLL for frequency estimation would yield the predictable result of a stable control signal for the laser rangefinder, ensuring consistent timing for each scan.
Hseih is not relied upon as teaching that the phase-locked loop comprises a numerically- controlled oscillator, and that the reference input signal is based on the magnetic field measurement data.
However, Furtney, Jr. teaches teaching that the phase-locked loop comprises a numerically- controlled oscillator, and that the reference input signal is based on the magnetic field measurement data ([Abstract] digital phase-locked loop (PLL). The PLL of the present invention is advantageously employed in a readback circuit for a digital signal magnetic recorder… a PLL digital filter wherein the successive values are averaged and scaled for controlling a digital VFO, also referred to as an NCO (numerically controlled oscillator)).
Xie as previously modified by Bosukonda, Murarka, Fan, and Hseih, and Furtney, Jr. are considered to be analogous to the claimed invention because they are both in the same field of digital signal processing and frequency control circuits. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the phase-locked loop of the combined system to include a numerically-controlled oscillator as taught by Furtney, Jr. with a reasonable expectation of success. This modification would have been motivated by the desire to implement the frequency estimation in a purely digital domain to improve thermal stability and allow for easier integration with microprocessor-based control systems. By integrating Furtney, Jr.’s teaching of utilizing a digital NCO within a PLL into the rotorcraft scanning system, the system can more precisely regulate the laser trigger pulses using digital logic rather than sensitive analog components. A person of ordinary skill in the art would recognize that the use of an NCO in place of a standard oscillator represents a simple substitution of one known type of oscillator for another to yield the predictable result of a more robust and drift-free PLL for synchronizing laser scans based on magnetic field measurement data.
Regarding Claims 11 and 26, Xie as previously modified by Bosukonda, Murarka, Fan, Hseih, and Furtney, Jr. teaches the numerically controlled oscillator ([Furtney, Jr.: Abstract] a PLL digital filter wherein the successive values are averaged and scaled for controlling a digital VFO, also referred to as an NCO (numerically controlled oscillator).
Xie as previously modified by Bosukonda, Murarka, Fan, Hseih, and Furtney, Jr. is not relied upon as teaching that the frequency of the sinusoidal signal is estimated based on an instantaneous frequency of the oscillator.
However, Hseih teaches that the frequency of the sinusoidal signal is estimated based on an instantaneous frequency of the oscillator ([Col. 2 ll. 36-37 & Col. 3 ll. 2-3] The VCO is a frequency-modulated oscillator, whose instantaneous angular frequency winst is a linear function of the controlled signal vc(t), around the central angular frequency w).
Xie (as previously modified by Bosukonda, Murarka, Fan, Hseih, and Furtney, Jr., and Hseih are considered to be analogous to the claimed invention because they are both in the same field of frequency estimation and phase synchronization circuits. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the combined system to include estimating the frequency of the sinusoidal signal based on an instantaneous frequency of the oscillator as taught by Hseih with a reasonable expectation of success. This modification would have been motivated by the desire to utilize the most responsive output of the PLL to ensure the laser scanning system reacts immediately to any rotational fluctuations. By further integrating Hseih’s teaching of the oscillator’s instantaneous angular frequency being a function of the control signal into the rotorcraft scanning system, the system can derive a real-time frequency value directly from the NCO (as taught by Furtney, Jr.). A person of ordinary skill in the art would recognize that using the instantaneous frequency of the oscillator would yield the predictable result of minimizing the phase lag between the actual rotation of the body frame and the laser trigger timing, resulting in higher scanning accuracy.
Claims 9, and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Xie (US 2019/0257923 A1), Bosukonda et al. (US 2021/0262448 A1), Murarka et al. (US 2021/0055107 A1), Fan et al. (CN204117440U), Hseih et al. (“Phase-Locked Loop Techniques-A Survey” IEEE Transactions of Industrial electronics, Vol. 43, No. 6, December 1996), and Furtney, Jr. (US 3878473) in view of Marins et al. (“An Extended Kalman Filter for Quaternion-Based Orientation Estimation Using MARG Sensors” Proceedings of the 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems Maui, Hawaii, USA, Oct. 29 - Nov. 03, 2001).
Regarding Claim 9, Xie as previously modified by Bosukonda, Murarka, Fan, Hseih, and Furtney, Jr. is not relied upon as teaching each of the reference input signal and the output reference signal is a complex sinusoidal signal.
However, Marins teaches that the reference input signal and the output reference signal is a complex sinusoidal signal ([Col. 2 ll. 27-30 & Col. 1 ll. 6-8 & Col. 4 ll. 2-3] Phase-coherence trackers determine distance by measuring the difference in phase of a reference signal and an emitted signal detected by sensors… The filter represents rotations using quaternions rather than Euler angles… Quaternions are a four-dimensional extension to complex numbers).
Xie as previously modified by Bosukonda, Murarka, Fan, Hseih, and Furtney, Jr., and Marins are considered to be analogous to the claimed invention because they are both in the same field of signal processing and orientation estimation for the rotating systems. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the signal processing method of the combined system to include representing reference input signal and the output reference signal as a complex sinusoidal signal as taught by Marins with a reasonable expectation of success. This modification would have been motivated by the desire to simplify the mathematical representation of and reduce computation load on the system’s processor. By integrating Marins’s teaching of representing rotations using quaternions, a four-dimensional extension to complex numbers, into the rotorcraft’s PLL-based frequency estimation logic, the system can more efficiently process orientation data in real-time. A person of ordinary skill in the art would recognize that using complex sinusoidal signals would yield the predictable result of linearizing the measurement equations of the Kalman filter and significantly reducing computational requirements, making it possible to estimate orientation in real-time with higher precision and lower latency.
Regarding Claim 10, Xie as previously modified by Bosukonda, Murarka, Fan, Hseih, and Furtney, Jr., and Marins teaches the rotorcraft ([Xie: Abstract] the UAV) and that the sinusoidal signal of the reference signal is complex ([Marins: Col. 2 ll. 27-30 & Col. 1 ll. 6-8 & Col. 4 ll. 2-3] Phase-coherence trackers determine distance by measuring the difference in phase of a reference signal and an emitted signal detected by sensors… The filter represents rotations using quaternions rather than Euler angles… Quaternions are a four-dimensional extension to complex numbers).
Xie as previously modified by Bosukonda, Murarka, Fan, Hseih, and Furtney, Jr., and Marins is not relied upon as teaching the complex sinusoidal signal of the reference input signal is produced based on a first component and a second component of the sinusoidal signal, the first component corresponding to a front direction of the rotorcraft and the second component corresponding to a starboard direction of the rotorcraft.
However, Murarka teaches that the sinusoidal signal of the reference input signal is produced based on a first component and a second component of the sinusoidal signal, the first component corresponding to a front direction of the rotorcraft and the second component corresponding to a starboard direction of the rotorcraft ([0102] if a magnetometer has 3 orthogonal sense axes (x, y, and z), the aforementioned method can be used with the magnetic field measurements about each of those axes to calculate the rates of rotation about each of those orthogonal axes).
Xie as previously modified by Bosukonda, Murarka, Fan, Hseih, and Furtney, Jr., and Marins, and Murarka are considered to be analogous to the claimed invention because they are both in the same field of multi-axis sensing and rotational measurement. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the combined system to include producing the complex sinusoidal signal of the reference input signal based on a first component and a second component of the sinusoidal signal, corresponding to different directions of the rotorcraft, as taught by Murarka with a reasonable expectation of success. This modification would have been motivated by the desire to leverage the full spatial data available from a 3-axis magnetometer to more accurately track the rotorcraft’s orientation in three-dimensional space. By further integrating Murarka’s teaching of utilizing orthogonal sense axes (x, y, and z) to calculate rates of rotation about each axis into the rotorcraft scanning system, the system can provide the multi-dimensional inputs required for the complex signal processing. A person of ordinary skill in the art would recognize that using orthogonal components from a magnetometer to form the complex input signal would yield the predictable result of allowing the orientation filter to resolve the direction of rotation with greater clarity, specifically by correlating magnetic field changes directly to the front and starboard directions of the aircraft frame.
Claims 12 and 27 are rejected under 35 U.S.C. 103 as being unpatentable over Xie (US 2019/0257923 A1), Bosukonda et al. (US 2021/0262448 A1), Murarka et al. (US 2021/0055107 A1), and Fan et al. (CN204117440U), Hseih et al. (“Phase-Locked Loop Techniques-A Survey” IEEE Transactions of Industrial electronics, Vol. 43, No. 6, December 1996) and Furtney, Jr. (US 3878473) in view of Johansen et al. (US 2007/0163349 A1).
Regarding Claims 12 and 27, Xie as previously modified by Bosukonda, Murarka, Fan, Hseih, and Furtney, Jr. teaches that the rotorcraft further comprises a gyroscope mounted on the rotatable body frame ([Bosukonda: Abstract] the LIDAR element being disposed within a volume bounded by the outer aerodynamic surface and comprising at least one LIDAR system configured to transmit light beams away from the blade and to detect reflected light beams incident upon the blade, wherein the shell comprises at least one aperture extending at least partly through a thickness of the shell and containing optically transparent material, wherein the at least one LIDAR system is disposed within a volume bounded by an inner surface of the shell… comprising a gyroscope mechanism coupled to the at least one LIDAR system such that an orientation of the at least one LIDAR system is substantially unaffected by movement of the blade so as to vary an angle at which light beams are transmitted through the optically transparent material as the blade moves), and the gyroscope is configured to measure an angular velocity thereof about a rotational axis of the rotatable body frame ([Murarka: 0003] electronic gyroscopes or angular rate sensors detect the rate of angular displacement of an object or a body to which they are attached or integrated), and
said estimating the frequency of the sinusoidal signal comprises:
obtaining gyroscope measurement data from the gyroscope, the gyroscope measurement data comprising measured angular velocity data measured by the gyroscope about the rotational axis of the rotatable body frame ([Murarka: 0145] the system comprises an inertial measurement unit (IMU) further comprising one or more of a single-axis gyroscope or a multi-axis gyroscope providing gyroscope data; and at least one processor which causes the system to use said gyroscope data to verify the fidelity of computed orientation of said traveling object) and measured angular velocity data ([0003] electronic gyroscopes or angular rate sensors detect the rate of angular displacement of an object or a body to which they are attached or integrated).
Xie as previously modified by Bosukonda, Murarka, Fan, Hseih, and Furtney, Jr. is not relied upon as teaching setting a free-running frequency of the numerically-controlled oscillator.
However, Johansen teaches setting a free-running frequency of the numerically-controlled oscillator ([0057] The improved PLL design adds an additional control register that sets the starting, or free running frequency. When ultrasound is deactivated and the zero-crossing reference signal disappears, the NCO will run at the free run frequency set point).
Xie as previously modified by Bosukonda, Murarka, Fan, Hseih, Furtney, Jr., and Marins, and Johansen are considered to be analogous to the claimed invention because they are both in the same field of frequency acquisition and control systems. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the combined system to include estimating the frequency of the sinusoidal signal further based on a free-running frequency of the oscillator as taught by Johansen with a reasonable expectation of success. This modification would have been motivated by the desire to provide the PLL with a stable starting point (initial condition) to accelerate the lock-in time of the frequency estimation. By further integrating Johansen’s teaching of utilizing an initial frequency estimate (free-running frequency) for the integrator within the loop structure into the rotorcraft scanning system, the system can begin generating valid scan timing immediately upon startup, even before the magnetic field signal has been fully characterized. A person of ordinary skill in the art would recognize that incorporating a free-running frequency as a baseline for the oscillator would yield the predictable result of preventing the frequency estimator from wandering during initialization.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Xie (US 2019/0257923 A1), Bosukonda et al. (US 2021/0262448 A1), Murarka et al. (US 2021/0055107 A1), and Fan et al. (CN204117440U) in view of Duan (US 10852431 B1).
Regarding Claim 13, Xie as previously modified by Bosukonda, Murarka, and Fan is not relied upon as teaching that said controlling the laser rangefinder comprises: determining an angular velocity of the rotorcraft based on the estimated frequency of the sinusoidal signal; and sending the determined angular velocity of the rotorcraft to the laser rangefinder, the laser rangefinder being configured to perform laser scanning based on the determined angular velocity of the rotorcraft.
However, Murarka teaches that said controlling the laser rangefinder comprises:
determining an angular velocity of the rotorcraft based on the estimated frequency of the sinusoidal signal ([Abstract] determining, number of peaks, present in a measurement sample comprising a set of said measurements, of time duration; and computing said rate of angular displacement, for said traveling object, as a function of said determined number of peaks and said time duration).
Xie as previously modified by Bosukonda, Murarka, and Fan, and Murarka are considered to be analogous to the claimed invention because they are both in the same field of motion estimation and sensor data interpretation. Therefore, t would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the combined system to include determining an angular velocity of the rotorcraft based on the estimated frequency of the sinusoidal signal as taught by Murarka with a reasonable expectation of success. This modification would have been motivated by the desire to derive a meaningful physical measurement of the rotor’s motion from the raw periodic data generated by the magnetic field sensors. By further integrating Murarka’s teaching of computing the rate of angular displacement as a function of the determined number of signal peaks and time duration into the rotorcraft system, the system can translate frequency counts into a kinematic value representing the rotation rate of the body frame. A person of ordinary skill in the art would recognize that using the frequency to determine angular velocity would yield the predictable result of providing a standardized rotational metric.
Murarka is not relied upon as teaching sending the determined angular velocity of the rotorcraft to the laser rangefinder, the laser rangefinder being configured to perform laser scanning based on the determined angular velocity of the rotorcraft.
However, Duan teaches sending the determined angular velocity of the rotorcraft to the laser rangefinder, the laser rangefinder being configured to perform laser scanning based on the determined angular velocity of the rotorcraft ([Col 28 ll. 3-17] An ADC (Analog to Digital Converter) 483 converts the signal output by the magnetic sensor 482 into a digital value in real time, and provides the digital value to a scanning speed calculation circuitry 484. The scanning speed calculation circuitry 484 converts the signal input by the ADC 483 into an orientation angle of the magnet for detection 481 based on the pre-restored corresponding relationship between the signal level of the magnetic sensor 482 and the orientation angle of the magnet for detection 481, then calculates, based on the temporal rate of change of the orientation angle, the rotation angular velocity of the magnet for detection 481, that is, the rotation angular velocity (scanning speed) of the mirror 401″, and provides the rotation angular velocity to the control circuitry 471).
Xie as previously modified by Bosukonda, Murarka, and Fan, and Duan are considered to be analogous to the claimed invention because they are both in the same field of controlling optical scanning systems based on rotational feedback. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combined system to include sending the determined angular velocity of the rotorcraft to the laser rangefinder, the laser rangefinder being configured to perform laser scanning based on the determined angular velocity as taught by Duan with a reasonable expectation of success. This modification would have been motivated by the desire to synchronize the laser’s firing rate with the actual physical rotation of the mounting platform, thereby preventing distortion in the captured image or point cloud. By integrating Duan’s teaching of providing the rotation angular velocity to control circuitry into the rotorcraft system, the system can ensure that the laser rangefinder knows exactly how fast it is moving relative to the ground. A person of ordinary skill in the art would recognize that using a calculated angular velocity to drive the laser scanning process would yield the predictable result of uniform spatial sampling, where the distance between laser pulses on the target remains consistent regardless of changes in the rotorcraft’s rotation speed.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Xie (US 2019/0257923 A1), Bosukonda et al. (US 2021/0262448 A1), Murarka et al. (US 2021/0055107 A1), Fan et al. (CN204117440U) and Duan (US 10852431 B1) in view of Taquet et al. (US 2025/0252611 A1).
Regarding Claim 14, Xie as previously modified by Bosukonda, Murarka, Fan, and Duan teaches that the laser rangefinder is configured to scan based on the determined angular velocity of the rotorcraft ([Duan: Col 28 ll. 3-17] An ADC (Analog to Digital Converter) 483 converts the signal output by the magnetic sensor 482 into a digital value in real time, and provides the digital value to a scanning speed calculation circuitry 484. The scanning speed calculation circuitry 484 converts the signal input by the ADC 483 into an orientation angle of the magnet for detection 481 based on the pre-restored corresponding relationship between the signal level of the magnetic sensor 482 and the orientation angle of the magnet for detection 481, then calculates, based on the temporal rate of change of the orientation angle, the rotation angular velocity of the magnet for detection 481, that is, the rotation angular velocity (scanning speed) of the mirror 401″, and provides the rotation angular velocity to the control circuitry 471).
Xie as previously modified by Bosukonda, Murarka, Fan, and Duan is not relied upon as teaching, the laser rangefinder is a single unidirectional laser and is configured to generate planar pointcloud data for a complete planar lidar scan, and the complete planar lidar scan is a planar lidar scan having completed a full revolution as determined based on the determined angular velocity of the rotorcraft.
However, Murarka teaches completing a full revolution as determined based on the determined angular velocity of the rotorcraft ([0112] Consecutive peaks in magnetometer measurements for any of its particular sense axes indicate the completion of one complete rotation of 360 degrees or 2*π radians… about that particular axis).
Xie as previously modified by Bosukonda, Murarka, Fan, and Duan, and Murarka are considered to be analogous to the claimed invention because they are both in the same field of rotational sensing and motion tracking. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the combined system to include a planar lidar scan having completed a full revolution as determined based on the determined angular velocity of the rotorcraft as taught by Murarka with a reasonable expectation of success. This modification would have been motivated by the desire to accurately identify the boundaries of a single scan line to ensure that 3D point cloud data is organized into complete, non-overlapping sets. By further integrating Murarka’s teaching of identifying consecutive peaks in magnetometer measurements to indicate the completion of one complete rotation of 360 degrees into the rotorcraft scanning system, the system can determine precisely when a scan cycle should terminate. A person of ordinary skill in the art would recognize that using peak-to-peak magnetic data to mark a full revolution would yield the predictable result of allowing the lidar system to automatically reset its scanning buffer or trigger a new planar scan at the exact moment the rotor returns to its starting orientation, thereby maintaining perfect spatial alignment in the generated environment map.
Murarka is not relied upon as teaching that the laser rangefinder is a single unidirectional laser and is configured to generate planar pointcloud data for a complete planar lidar scan, and the complete planar lidar scan is a planar lidar scan.
However, Taquet teaches that the laser rangefinder is a single unidirectional laser and is configured to generate planar pointcloud data for a complete planar lidar scan, and the complete planar lidar scan is a planar lidar scan ([0097]-[0099] LiDAR-acquired point clouds are acquired by a set of spinning lasers…
a single laser 704 rotating around a head axis 702 and having an angle θ with respect to the plane 708. Plane 708 is perpendicular to the head axis 702).
Xie as previously modified by Bosukonda, Murarka, Fan, and Duan, and Taquet are considered to be analogous to the claimed invention because they are both in the same field of LIDAR scanning systems and point cloud generation. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the laser rangefinder of the combined system to be a single unidirectional laser configured to generate planar point cloud data for a complete planar lidar scan as taught by Taquet with a reasonable expectation of success. This modification would have been motivated by the desire to minimize hardware complexity and payload weight while maintaining the ability to capture high0-resolution environmental data. By integrating Taquet’s teaching of a single laser rotating around a head axis to generate a point cloud in a specific plane into the rotorcraft system, the designer can achieve a wide-angle field of view without the cost or power requirements of a wide-angle array. A person of ordinary skill in the art would recognize that configuring a single laser to perform a planar scan would yield the predictable result of producing a geometrically consistent slice of the surrounding environment that, when combined with the rotorcraft’s rotation, enables the efficient construction of a full 3D map.
Claim 30 is under 35 U.S.C. 103 as being unpatentable over Xie (US 2019/0257923 A1), Bosukonda et al. (US 2021/0262448 A1), Murarka et al. (US 2021/0055107 A1), and Fan et al. (CN204117440U) in view of Calvert (US 9062948 B1).
Regarding Claim 30, Xie as modified by Bosukonda, Murarka, and Fan is not relied upon as teaching that the rotorcraft is configured to entirely rotate during flight.
However, Calvert teaches that the rotorcraft is configured to entirely rotate during flight ([Col 6 ll. 28-38] The aircraft is a helicopter with a single rotor, the body of the helicopter will tend to spin in an opposite direction to the main rotor once aircraft lifts off the ground. The usual countervailing force to prevent such rotation in a helicopter is a tail rotor. Asymmetrical torque can also be experienced when using multiple rotors spinning in opposite directions, but do not fully offset each other. However, in any event, if the compensating rotor does not fully counter rotate the aircraft, it creates an asymmetrical torque that can be used to spin the aircraft).
Xie in view of Bosukonda, Murarka, and Fan, and Calvert are considered to be analogous to the claimed invention because they are both in the same field of rotorcraft design and aerial scanning platforms. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the rotorcraft configuration of the combined system to ensure the rotorcraft is configured to entirely rotate during flight as taught by Calvert with a reasonable expectation of success. This modification would have been motivated by the desire to enable a panoramic field of view for the onboard sensors without requiring complex external gimbals or multiple sensor arrays. By integrating Calvert’s teaching of utilizing asymmetrical torque to intentionally spin the aircraft body into the rotorcraft scanning system, the system can leverage the natural physics of a single rotor aircraft to achieve the rotation. A person of ordinary skill in the art would recognize that allowing the entire aircraft to rotate would yield the predictable result of enabling the aircraft to change orientation without changing position.
Conclusion
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/E.H.H./Patent Examiner, Art Unit 3645
/HELAL A ALGAHAIM/SPE , Art Unit 3645