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 .
DETAILED ACTION
This office action is in regards to application # 18/749,822 that was filed on 06/21/2024. Claims 1-20 are currently pending and are under examination.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Axelsson (US 2017/0371029) in view of Mnerie et al. (doc. “Mathematical model of a galvanometer-based scanner: Simulations and experiments”).
Regarding Claim 1, Axelsson discloses a beam scanning system (abstract, para. [0002]-[0004]) comprising:
a two-dimensional scanner comprising a first galvanometer scanner configured to rotate about a first scanning axis based on a first driving signal, and a second galvanometer scanner configured to rotate about a second scanning axis based on a second driving signal (discloses a moveable deflection unit comprising one or more sweeping mirrors (including a Galvano-scanner) that directs laser pulses according to a given scan patter, enabling two dimensional scanning, para. [0008]; Fig. 5(e), claim 1);
a time-of-flight sensor configured to receive a reflected light beam and generate a distance measurement based on the reflected light beam (abstract, 13, Fig. 3, para. [0049]);
a driver system configured to receive a first angle setpoint for the first galvanometer scanner and a second angle setpoint for the second galvanometer scanner, drive the first galvanometer scanner with the first driving signal based on the first angle setpoint, and drive the second galvanometer scanner with the second driving signal based on the second angle setpoint (Axelsson’s control and processing unit uses scan pattern and drives the deflection unit (galvanometer mirror); col. 2, lines 38-45; col. 4, lines 8-38).
Axelsson discloses that the controlling processing unit calculate a predicted angle difference(i.e., estimated angular positions) between the outgoing and incoming beams bathed on the known scan pattern(command setpoints/ trajectory) and the predicted time of flight(distance measurement). The predicted angles are used to associate/compensate they received ToF distance measurement with the angular direction of this contradictory, thereby enabling accurate three dimensional positioning of the measured (para. [0012]-[0021]) . Generation of three dimensional point cloud from and two angular coordinates is inherent and expressly contemplated the result of Axelsson’s long range LIDAR surface scanning system.
Axelsson does not explicitly recite a formal” dynamic mode” of the scanner dynamics (inertia, lag etc.) that generates continuous estimated angle measurement signals that track the actual angular trajectory from the setpoints.
However, Mnerie expressly teaches exactly such a dynamic model. Mnerie derives and experimentally validates a multi parameter mathematical/dynamic model of a galvanometer scanner (motor and controller) that relates command/setpoint inputs to the actual angular output trajectory. The model is used to generate predicted/ estimated angular responses that the scanner’s actual trajectory under various input signals (triangular, sinusoidal, sawtooth). Simulations in Matlab/ Simulink confirm that the model accurately reproduces the Angular trajectory (abstract, sections 2-5, Figs. 1-6, conclusions).
It would have been obvious to a person of ordinary skill in art before the effective filing date of the invention to incorporate Mnerie’s dynamic model of the galvanometer scanner into Axelsson’s control processing unit. Both references are directed to high precision laser beam scanning systems. Axelsson already predicts angular positions from the scan pattern and time-of-flight data in order to correctly associate distance measurements with scan angles. Mnerie provides a well-known, experimentally validated dynamic model that improves the accuracy of such angle predictions by accounting for the actual electromechanical trajectory (lag, dynamics) of the galvanometer relative to the commanded setpoints. A person of ordinary skill in the art would have been motivated to do so to improve pointing accuracy association precision during the finite time-of-flight, especially at the highest scan rate-the precise problem Axelsson addresses. The combination yields a predictable result with reasonable expectation of success.
Regarding Claim 2, modified Axelsson discloses a beam scanning system (abstract, para. [0002]-[0004]) as recited in claim 1, wherein Mnerie teachers the input output relationship of claim 2. The dynamic model of the galvanometer scanner is driven by the command/ signal as its input; The model then produces the estimated/ predicted angular trajectory(output) that follows the actual motion of the scanner (abstract, sections 2-4, Figs. 1-4; MATLAB/Simulink simulations). Axelsson already supplies the angle setpoints and uses predicted angle association with ToF data. It would have been obvious to one of ordinary skin in art to implement Axelsson’s angle prediction using Mnerie’s dynamic model by feeding each axis setpoint into the corresponding dynamic model to obtain the estimated angle value as the modal output. The combination yield the claimed input output configuration with no unexpected results.
Regarding Claim 3, modified Axelsson discloses a beam scanning system (abstract, para. [0002]-[0004]) as recited in claim 1, wherein Mnerie’s dynamic model inherently filters or reject high frequency noise and disturbance because it is a physics based model of the dominant electromechanical dynamics of the galvanometer. By generating the estimated angle from the clean setpoint through the model rather than relying fully on a noisy sensor measurement, the model effectively removes measurement noise from the angle signal use downstream (section 5, discussions model fidelity versus real measured responses; use of the model for improved control precision). A person of ordinary skill in the art would have recognized that substituting or augmenting a noisy angle measurement with the model based estimate as taught by Mnerie removes noise, and would have been motivated to do so in Axelsson’s system to obtain cleaner angular values for association with the time of flight distance measurements, thereby improving point cloud accuracy. This is a predictable application of model based estimation.
Regarding Claim 4, modified Axelsson discloses a beam scanning system (abstract, para. [0002]-[0004]) as recited in claim 1. The limitation In claim 4 is essentially the same as claim 3 as stated in Result oriented language “ Substantially free of angle measurement noise”. Mnerie’s Model based estimation produces angle signals that closely the true trajectory while rejecting sensor noise and high frequency disturbances(the estimated signal are substantially free of the measurement noise that would be present in the direct encoder or sensor reading (abstract, section 2-6, simulation and experimental results showing clean model predicted trajectories). The same motivation in combination rationale applied to claim 3 apply equally to claim 4. Generating model based estimates that are substantially noise free is the ordinary and expected result of using Mnerie’s dynamic model in place of raw angle measurements with Axelsson’s control architecture.
Regarding Claim 5, modified Axelsson discloses a beam scanning system (abstract, para. [0002]-[0004]) as recited in claim 1. Axelsson discloses a control and processing unit that operates scan pattern(setpoints) and the actual motion of the deflection unit(galvanometer mirrors). Conventional galvanometer scanners used in Lidar systems (including used by Axelsson) are almost invariably close-loop devices that incorporate angle position detectors(optical encoders, capacitive sensors or Hall sensors) To generate real time angle measurement signals (para. [0009]-[0015] and inherent characteristics of close-loop galvanometers)).
Mnerie teaches the use of a dynamic model of the galvanometer that is driven by both the command/setpoint and measured angular position feedback. The model is identified and validated against actual measured angular responses. The estimated trajectory is generated by combining the setpoint input with the measured behavior of the scanner (abstract, section 2-5; Experimental identification using measured angle data ;Fig. 1-6 showing model vs. measured responses).
It would have been obvious to one of ordinary skill the art before the effective filing date of the invention to equip Axelsson’s galvanometer scanners with conventional angle position detectors (as is standard in closed loop galvos) and to fit both the setpoints and the resulting angle measurement signal into Mnerie’s dynamic model. Doing so produces the claimed estimated angle measurement signal and improves the accuracy of the angle prediction already performed by Axelsson for time-of-flight association. The combination is an ordinary closed loop model based estimation architecture.
Regarding Claim 6, modified Axelsson discloses a beam scanning system (abstract, para. [0002]-[0004]) as recited in claim 5. Claim 6 is the classic model-based filtering/observer/ noise-rejection function of the dynamic model. Mnerie’s model is identified from measure data and is used to produce clean estimated trajectories that reject high frequency sensor noise and disturbances present in the raw angle measurement signals. By taking both the clean setpoint and the noisy measurement as inputs, the model outputs an estimated angle that has the noise component substantially removed (section 3-6; Discussion of model fidelity vs. Noisy measured responses; use of model for improved precision and disturbance rejection).
A person ordinary skill in the art before the effective filing date of the invention would have been motivated to apply Mnerie’s Model in exactly this manner inside Axelsson’s controller. The setpoint provides the ideal command; the angle measurement provides the actual(noisy) feedback, and the dynamic model fuses them to produce a noise-reduced estimated angle for more accurate association with time-of-flight distance measurement and generation of 3D point cloud. This is a predictable and well-known use of dynamic model in closed loop galvanometric control.
Regarding Claim 7, modified Axelsson discloses a beam scanning system (abstract, para. [0002]-[0004]) as recited Claim 5. Claim 7 is a restatement of the model based noise attenuation already addressed in claims 3, 4, and 6. Mnerie’s dynamic model takes the setpoint as an input and produces an estimated angle trajectory that attenuates (rejects) high frequency measurement noise present in the raw angle sensor signal (section 3-6; experimental comparison of modal output vs. noisy measured responses; use of the model for improved precision). A person of ordinary skill in the art before the effective filing date of the invention would have obviously applied the model exactly as claimed- feeding the setpoint into the dynamic model to attenuate noise in the corresponding angle measurement signal- because that is the ordinary and intended operation of the model based estimator. The motivation remains the same cleaner estimated angle improves the accuracy of Axelsson’s time-of-flight to angle association and the resulting 3D point cloud.
Regarding Claim 8, modified Axelsson discloses a beam scanning system (abstract, para. [0002]-[0004]) as recited Claim 5. Implementing a dynamic model as a noise attenuating filter is conventional. Mnerie’s Mathematical model of the galvanometer dynamics can be and commonly is realized as a digital filter whose coefficients or structure are determined by the identified dynamic model. The filter then outputs the noise reduced estimated angle signals. (sections 4-5 and MATLAB/Simulink implementation of the model as real-time estimator). It would have been obvious a person of ordinary skill in the art before the effective filing date of the invention to realize Mnerie’s dynamic model inside Axelsson’s controller as a noise attenuating filter that outputs the estimated angle measurement signals. Doing so is a standard digital signal processing implementation of the model based estimator and yields the claimed structure with predictable results.
Regarding Claim 9, modified Axelsson discloses a beam scanning system (abstract, para. [0002]-[0004]) as recited in claim 1. This is a classic feedback control using the estimated angle as a feedback signal. Mnerie Discusses and implements control structures(including extend/ model based control) in which the driving signal is generated from/ the air between a setpoint command and the (Model estimated or measured) angular position (abstract, sections 5-6; Discussion of control are creatures that use the model for improved tracking, Figs. Showing closed-loop responses). Axelsson’s driver/control unit already generates driving signals have galvanometers based on the desired scan pattern. Substituting or augmenting the feedback with Mnerie’s Estimated angle signal(instead of a raw noisy measurement) is the ordinary way to close the loop with model-based estimator. A person of ordinary skill in the art before the effective filing date of the invention would have been obviously motivated to do so to obtain more accurate and noise robust tracking of the commanded trajectories, which in turn improves the quality of the time-of-flight associated point cloud.
Regarding Claim 10, claim 10 is a system claim that is essentially identical in scope to claim 1, with two substantive difference: first: the claim recites “a galvanometer scanner” configured to rotate about both a first and a second scanning axis (rather that two separate galvanometer scanner); and second: the claim also uses an “angle vector setpoint corresponding to a two-dimension scanning coordinates” instead of separate first and second angle setpoints.
Axelsson already teach a deflection unit that may comprise one or more galvanometer scanners driven according to two dimensional scan pattern. A single galvanometer scanner capable of dual-axis motion, or a dual axis galvo head treated as a single unit, is a conventional alternative implementation of the same two-dimensional scanner. Mnerie teaches dynamic modeling of galvanometer scanners that is equally applicable to a single or dual access devices. The “angle vector setpoint” is simply the mathematical packaging of two commanded angles into a single vector; Axelsson’s scan pattern is precisely such a two dimensional command. The remainder of claim 10 is disclosed and rendered obvious by the same combination and motivation already applied to claim 1.
Regarding Claims 11-13, claims 11-13 mirror claims 2-4 and are obvious for identical reasons. Applying the angle vector setpoint as input to the dynamic model to obtain the estimated angle value as outputs (claim 11), Removing angle measurement noise with dynamic model (claim 12), and generating estimated signals substantially free of noise (claim 13) are the ordinary input-output and noise rejection operations of Mnerie’s model when used inside Axelsson’s controller.
Regarding Claim 14, Claim 14 odds first and second angle position detectors and requires that the estimated angle signals be generated from the single vector setpoint, the measured angle signals, and the dynamic model. This is a closed-loop model-based estimation architecture already held obvious for claim 5. Conventional galvo systems include pollution detectors; Mnerie validates its model against measured angle data and uses both command and measurement information. This combination remains obvious.
Regarding Claims 15-17, claims 15-17 parallel claims 6-8. All conventional and predictable uses of Mnerie’s dynamic model as a model-based estimator/filter and are obvious for the same reason previously stated for claims 6-8.
Regarding Claim 18, claim 18 requires that the driver system compensate the driving signals based on the difference between the estimated angle measurement signals and setpoint control signals. This is ordinary closed-loop feedback control using the model-based estimate as feedback-the same architecture held obvious for claim 9.
Regarding Claim 19, claim 19 merely states that the angle vector setpoint includes a first angle setpoint for the first axis and a second angle setpoint for the second axis. This is the inherent and conventional content of any two dimensional angle vector setpoint and adds no patentable weight.
Regarding Claim 20, Claim 20 Is the method counterpart of claim 10 (claim 1). It the same steps of generating driving signals from setpoints, driving the two dimensional scanner, generating a TOF distance measurement, generating estimated angle measurement signals from the setpoints and the dynamic model that follows the angular trajectories, associating the distance measurement with the estimated angle values, and generating a 3D point cloud. The method is obvious for the same reason as the corresponding system claims. Axelsson and Mnerie together teach every step, and a person of ordinary skill in the art before ethe effective filing date of the invention would have combined them for the same motivation (accurate association of TOF data with true scanner angles via dynamic model).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Wang (US 11,555,895) discloses Galvanometer movement profiles/trajectories in Lidar; real time position feedback; compensation of driving signal based on position data and models/ profiles; association of scan angles with ranging data for point-cloud generation. Directly supports dynamic trajectory estimation and closed-loop compensation (claims 1,5-9, 10, and 14-18).
Wang et al. (US 12,013,261) discloses Angle pollution detect(Hall Sensors) on Galvanometer in LiDAR; determination of angular position; and use of measured angles in controller for scanning and ranging. Supports claims 5,14 and closed loop aspect.
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Assres H. Woldemaryam
Primary Examiner (Aeronautics and Astronautics)
Art Unit 3642
/ASSRES H WOLDEMARYAM/Primary Examiner, Art Unit 3642
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