DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Summary
This communication is a First Office Action Non-Final Rejection on the merits.
Claims 1 – 14 are currently pending and considered below.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
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Claims 1 – 14 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 – 4 and 6 of U.S. Patent No. 12,270,654 B2. Although the claims at issue are not identical, they are not patentably distinct from each other because The claims 1 – 14 recites substantially similar claim limitations and inventions as claims 1 – 4 and 6 of US 12,270,654 as shown below:
Current Application
U.S. Patent No. 12,270,654 B2
1. An inertial navigation method of a vehicle, the method comprising: receiving, at a controller of the vehicle, at each of a plurality of iterations, a plurality of first outputs from a corresponding plurality of sensors; and a plurality of second outputs from the corresponding plurality of sensors; at each of the plurality of iterations: applying a first Gaussian curve to the plurality first outputs; and a second Gaussian curve to the plurality of second outputs; weighting each of the plurality of first outputs based on a position on the first Gaussian curve of each of the plurality of first outputs; and each of the plurality of second outputs based on a position on the second Gaussian curve of each of the plurality of second outputs; determining a combined first output based on the weighting of the plurality of first outputs and determining a combined second output based on the weighting of the plurality of second outputs; and calculating a roll of the vehicle based on the combined first output, and a pitch of the vehicle based on the combined second output; and at each of the plurality of iterations: controlling at least one of an engine and a control surface of the vehicle based on the roll of the vehicle and the pitch of the vehicle.
4. The inertial navigation method according to claim 1, wherein: the receiving further comprises, at each of the plurality of iterations: a plurality of third outputs from the corresponding plurality of sensors; at each of the plurality of iterations: the applying further comprises applying a third Gaussian curve to the plurality of third outputs; the weighting further comprises weighting each of the plurality of third outputs based on a position on the third Gaussian curve of each of the plurality of third outputs; the determining further comprises determining a combined third output based on the weighting of the plurality of third outputs; and the calculating further comprises calculating a heading of the vehicle based on the combined third output; and at each of the plurality of iterations, the controlling further comprises controlling the at least one of the engine and the control surface of the vehicle based on the heading of the vehicle.
1. An inertial navigation method of a vehicle, the method comprising: receiving, at an integrated circuit of the vehicle, at each of a plurality of iterations, data comprising one or more physical quantities from a first three-axis sensor and a second three-axis sensor; at each of the plurality of iterations: determining a plurality of solutions of a roll of the vehicle, based on the data, determining a plurality of solutions of a pitch of the vehicle, based on the data, and determining a plurality of solutions of a heading of the vehicle based on the data; at each of the plurality of iterations: determining a first Gaussian curve based on the plurality of solutions of the roll of the vehicle, determining a second Gaussian curve based on the plurality of solutions of the pitch of the vehicle, and determining a third a Gaussian curve based on the plurality of solutions of the heading of the vehicle; at each of the plurality of iterations: applying the first Gaussian curve to the plurality of solutions of the roll of the vehicle and weighting the plurality of solutions of the roll of the vehicle based on a position of the first Gaussian curve, thereby determining a plurality of weighted solutions of the roll of the vehicle, applying the second Gaussian curve to the plurality of solutions of the pitch of the vehicle and weighting the plurality of solutions of the pitch of the vehicle based on a position of the second Gaussian curve, thereby determining a plurality of weighted solutions of the pitch of the vehicle, applying third Gaussian curve to the plurality of solutions of the heading of the vehicle and weighting the plurality of solutions of the heading of the vehicle based on a position of the third Gaussian curve, thereby determining a plurality of weighted solutions of the heading of the vehicle; at each of the plurality of iterations: calculating a combined roll of the vehicle based on the plurality of weighted solutions of the roll of the vehicle, calculating a combined pitch of the vehicle based on the plurality of weighted solutions of the pitch of the vehicle, and calculating a combined heading of the vehicle based on the plurality of weighted solutions of the heading of the vehicle; and at each of the plurality of iterations: controlling an engine of the vehicle based on the combined roll of the vehicle, the combined pitch of the vehicle, and the combined heading of the vehicle.
2. The inertial navigation method according to claim 1, further comprising: at each of the plurality of iterations: outputting the roll of the vehicle and the pitch of the vehicle to a navigation system of the vehicle; wherein the controlling comprises the navigation system of the vehicle controlling the at least one of the engine and a control surface of the vehicle.
2. The inertial navigation method of the vehicle according to claim 1, wherein, at each of the plurality of iterations, the controlling the engine of the vehicle comprises outputting the combined roll of the vehicle, the combined pitch of the vehicle, and the combined heading of the vehicle to a navigation system of the vehicle and the navigation system of the vehicle controlling the engine of the vehicle.
3. The inertial navigation method according to claim 1, wherein the first Gaussian curve is one of a first Probability Distribution Function, a first Cauchy Distribution, and a first Logistic Distribution, and the second Gaussian curve is one of a second Probability Distribution Function, a second Cauchy Distribution, and a second Logistic Distribution.
3. The inertial navigation method according to claim 1, wherein the first Gaussian curve is a first Probability Distribution Function, the second Gaussian curve is a second Probability Distribution Function, and the third Gaussian curve is a third Probability Distribution Function.
5. A vehicle comprising: an engine; and an inertial navigation system comprising: a plurality of sensors, each configured to measure a first physical quantity from which can be computed a roll of the vehicle, and a second physical quantity from which can be computed a pitch of the vehicle; a memory storing instructions therein; and a controller, operatively coupled to each of the plurality of sensors, the controller configured to execute the instructions and thereby: receive a plurality of first outputs, corresponding to the first physical quantity, from the plurality of sensors, and receive a plurality of second outputs, corresponding to the second physical quantity, from the plurality of sensors; apply a first Gaussian curve to the plurality of first outputs and apply a second Gaussian curve to the plurality of second outputs; weight each of the plurality of first outputs based on a position on the first Gaussian curve of each of the plurality of first outputs and weight each of the plurality of second outputs based on a position on the second Gaussian curve of each of the plurality of second outputs; determine a combined first output based on the weighting of the plurality of first outputs and determine a combined second output based on the weighting of the plurality of second outputs; calculate a roll of the vehicle based on the combined first output, and calculate a pitch of the vehicle based on the combined second output; and control at least one of the engine and a control surface of the vehicle based on the roll of the vehicle and the pitch of the vehicle.
7. The vehicle according to claim 5, wherein each of the plurality of sensors is further configured to measure a third physical quantity from which can be computed a heading of the vehicle; and the controller is further configured to: receive a plurality of third outputs, corresponding to the third physical quantity, from the plurality of sensors, apply a third Gaussian curve to the plurality of third outputs, weight each of the plurality of third outputs based on a position on the third Gaussian curve of each of the plurality of third outputs, determine a combined third output based on the weighting of the plurality of third outputs, calculate a heading of the vehicle based on the combined third output, and control the at least one of the engine and the control surface of the vehicle based on the heading of the vehicle.
4. A vehicle comprising: an engine; and as inertial navigation system comprising: a first three-axis sensor and a second three-axis sensor configured to measure one or more physical quantities; a memory storing instructions thereon; a controller, operatively coupled to the first three-axis sensor and the second three-axis sensor, the controller configured to execute the instructions and thereby: receive, at each of a plurality of iterations, data comprising the one or more physical quantities from the first three-axis sensor and the second three-axis sensor; at each of the plurality of iterations, determine a plurality of solutions of a roll of the vehicle, determine a plurality of solutions of a pitch of the vehicle, and determine a plurality of solutions of a heading of a vehicle, based on the data; at each of the plurality of iterations, determine a first Gaussian curve based on the plurality of solutions of the roll of the vehicle, determine a second Gaussian curve based on the plurality of solutions of the pitch of the vehicle, and determine a third Gaussian curve based on the plurality of solutions of the heading of the vehicle; at each of the plurality of iterations, apply the first Gaussian curve to the plurality of solutions of the roll of the vehicle, apply the second Gaussian curve to the plurality of solutions of the pitch of the vehicle, and apply the third Gaussian curve to the plurality of solutions of the heading of the vehicle; at each of the plurality of iterations: weigh the plurality of solutions of the roll of the vehicle based on a position on the first Gaussian curve, thereby determining a plurality of weighted solutions of the roll of the vehicle, weigh the plurality of solutions of the pitch of the vehicle based on a position on the second Gaussian curve, thereby determining a plurality of weighted solutions of the pitch of the vehicle, and weigh the plurality of solutions of the heading of the vehicle based on a position on the third Gaussian curve, thereby determining a plurality of weighted solutions of the heading of the vehicle; at each of the plurality of iterations calculate a combined roll of the vehicle, a combined pitch of the vehicle, and a combined heading of the vehicle based on the plurality of weighted solutions of the roll of the vehicle, the pitch of the vehicle, and the heading of the vehicle; and at each of the plurality of iterations, control the engine based on the combined roll of the vehicle, the combined pitch of the vehicle, and the combined heading of the vehicle.
6. The vehicle according to claim 5, wherein the first Gaussian curve is one of a first Probability Distribution Function, a first Cauchy Distribution, and a first Logistic Distribution, and the second Gaussian curve is one of a second Probability Distribution Function, a second Cauchy Distribution, and a second Logistic Distribution.
8. The vehicle according to claim 7, wherein the first Gaussian curve is one of a first Probability Distribution Function, a first Cauchy Distribution, and a first Logistic Distribution; the second Gaussian curve is one of a second Probability Distribution Function, a second Cauchy Distribution, and a second Logistic Distribution; and the third Gaussian curve is one of a third Probability Distribution Function, a third Cauchy Distribution, and a third Logistic Distribution.
6. The inertial navigation system according to claim 4, wherein the first Gaussian curve is a first Probability Distribution Function, the second Gaussian curve is a second Probability Distribution Function, and the third Gaussian curve is a third Probability Distribution Function.
Claims 9 – 14 recites substantially similar claim limitations as claims 1 – 8, and rejected in view of U.S. Patent No. 12,270,654 B2 as how claims 1 – 8 are rejected.
Allowable Subject Matter
Claims 1 – 14 are allowed over the record of prior arts.
The following is an examiner’s statement of reasons for allowance:
The independent claim 1 recites limitations of:
An inertial navigation method of a vehicle, the method comprising:
receiving, at a controller of the vehicle, at each of a plurality of iterations, a plurality of first outputs from a corresponding plurality of sensors; and a plurality of second outputs from the corresponding plurality of sensors;
at each of the plurality of iterations:
applying a first Gaussian curve to the plurality first outputs; and a second Gaussian curve to the plurality of second outputs;
weighting each of the plurality of first outputs based on a position on the first Gaussian curve of each of the plurality of first outputs; and each of the plurality of second outputs based on a position on the second Gaussian curve of each of the plurality of second outputs;
determining a combined first output based on the weighting of the plurality of first outputs and determining a combined second output based on the weighting of the plurality of second outputs; and
calculating a roll of the vehicle based on the combined first output, and a pitch of the vehicle based on the combined second output; and
at each of the plurality of iterations:
controlling at least one of an engine and a control surface of the vehicle based on the roll of the vehicle and the pitch of the vehicle.
Other independent claims 5 and 9 recites substantially similar claim limitations as claim 1.
The most remarkable prior arts are Tanenhaus et al. (US 2016/0047675 A1), Bosse et al. (US 11113873 B1), Shibata (US 2020/0293066 A1), and Belenkii et al. (US 9217643 B1).
Tanenhaus et al is directed to a n inertial measurement unit includes physically distinct sectors positioned in groups of orthogonally oriented angle rate sensors on a different sector of a base having orthogonally oriented accelerometers positioned thereon. A processor receiving signals from the sensors and accelerometers calculates a change in attitude, position, angular rate, velocity, acceleration of the unit over a plurality of finite time increments, or a combination thereof. The gyros and accelerometers have low-drift measurement accuracy for operation in a GPS-denied environment by preselecting pairs of gyros for physical assignment to achieve low-drift accuracy, determining weights for the gyros to be combined in tiered pairs, preselecting the accelerometers for physical assignment in low-drift pairs, determining weights for accelerometer optimal low-drift pair combining in tiers, or a combination thereof.
Bosse et al. is directed to navigation systems can identify objects in an environment and generate representations of those objects. A representation of an articulated vehicle can include two segments rotated relative to each other about a pivot, with a first segment corresponding to a first portion of the articulated vehicle and the second segment corresponding to a second portion of the articulated vehicle. The representation can be based on a model fit to points that are derived from sensor data and are associated with the object. In some examples, the model can be fit to the points using an expectation maximization algorithm and can be parameterized using attributes of the first and second segments.
Shibata is directed to a n aircraft includes at least one sensor, an altitude actuator, a memory device, and an electronic controller. The at least one sensor is configured to detect altitude of the aircraft, current position of the aircraft and speed of the aircraft. The altitude actuator is configured to change the altitude of the aircraft. The memory device is configured to store predetermined terrain data of an area. The electronic controller is configured to estimate a future position of the aircraft based on a detected current position of the aircraft and a detected speed of the aircraft. The electronic controller is further configured to control the altitude actuator based on the future position, a detected altitude of the aircraft and the predetermined terrain data.
Belenkii et al. is directed to an angles only navigation system. The system includes an IMU coupled with a passive optical sensor. The optical sensor provides periodic updates to the IMU in order to correct for accelerometer and gyro drifts. The IMU computes the air vehicle's instantaneous position, velocity, and attitude using gyro and accelerometer measurements. The optical sensor images stars and satellites. The navigation filter combines optical sensor measurements with IMU inputs, and determines those corrections needed to compensate for the IMU drifts. By applying periodic corrections to the IMU using satellite angular measurements, the navigation filter maintains an accurate position estimate during an entire flight.
None of the prior arts, individually or in combination, teaches all the elements of the claim limitations, particularly in regard to the limitations of:
“at each of the plurality of iterations:
weighting each of the plurality of first outputs based on a position on the first Gaussian curve of each of the plurality of first outputs; and each of the plurality of second outputs based on a position on the second Gaussian curve of each of the plurality of second outputs;
determining a combined first output based on the weighting of the plurality of first outputs and determining a combined second output based on the weighting of the plurality of second outputs; and
calculating a roll of the vehicle based on the combined first output, and a pitch of the vehicle based on the combined second output.”
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Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to IG T AN whose telephone number is (571)270-5110. The examiner can normally be reached M - F: 10:00AM- 4:00PM.
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IG T AN
Primary Examiner
Art Unit 3662
/IG T AN/Primary Examiner, Art Unit 3662
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