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 .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 6/24/2026 has been entered.
Status of Claims
This Office Action is in response to the amendments filed on 6/24/2026. Claims 1-10 are presently pending and are presented for examination.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. All pending claims therefore have an effective filing date of 5/31/2023.
Response to Amendment
Applicant’s amendments, see page 8 of 13, filed 6/24/2026, with respect to claim objections and 112(b) rejections have been fully considered and are persuasive. The claim objections and 112(b) rejections have been withdrawn.
Response to Arguments
Applicant's first argument, see pages 9-11 of 13, filed 6/24/2026, has been fully considered but is not persuasive. The Applicant has argued that neither primary reference Billhartz nor secondary reference Dame teach two separate models which only determine a single pose estimate, however the Examiner respectfully disagrees. Paragraph [0057] states “…As discussed and otherwise disclosed herein, a sequence of images, such as the sequence of images 204 captured by camera(s) 202, are applied to one or more trained machine learning models (such as first machine learning model 208 and second machine learning model 210, for example) and processed to generate the information that can be used to support the guidance and/or control of an aircraft 100 during landing operations...” which the Examiner notes addresses the concept of two separate algorithms determining two positions.
Applicant's second argument, see page 12 of 13, filed 6/24/2026, has been fully considered but is not persuasive. The Applicant has argued that primary reference Billhartz does not disclose determining a translation and a rotation, however the Examiner respectfully disagrees. Paragraph [0070] of Billhartz states "As expressed in Equation 4, the scaling factors, the values of the rotation matrix R, and the translation vector T are unknown. However, example implementations of the subject disclosure involve solving for the unknowns in equations..." and is additionally detailed in the rejection below.
Claim Interpretations
Claim 2 as currently presented states “…recording information, for each of the plurality of predefined landing runways, representative of a second difference between the third position and the fourth position...the second difference being one of a plurality of second differences…” which the Examiner believes is redundant since the “second difference” has been established as being representative of each of the plurality of predefined runways. While acceptable as written, the Examiner notes this interpretation is necessary so as to avoid potential misinterpretation.
Claim Objections
Claims 1-6 are objected to because of the following informalities:
Claim 1 as currently presented states “…determining a position of the aircraft…determining a position of the aircraft…” which the Examiner recommends updating to differentiate between the two positions so as to avoid potential misinterpretation.
Claim 4 is objected to for similar reasons.
Claim 2 as currently presented states “…a second difference…a plurality of second differences…two smallest second differences…the second differences…” which the Examiner recommends updating to elaborate on which “the second differences” is being referred to so as to avoid potential misinterpretation.
Claim 2 as currently presented states “…the flight procedure…” which the Examiner recommends updating to instead state “… a flight procedure…” so as to avoid potential misinterpretation.
Claim 1 as currently presented states “…a position…a position…” as noted above; claim 3 is dependent on claim 1 and states “…a current position…the position…” which the Examiner recommends updating to elaborate on which “the position” is being referred to so as to avoid potential misinterpretation.
Claim 4 as currently presented states multiple instances of “…a predefined landing runway…the predefined landing runway…the runway…” which the Examiner recommends updating to instead state “…a predefined landing runway…the predefined landing runway…the predefined landing runway…” so as to avoid potential misinterpretation.
Claim 5 as currently presented states multiple instances of “…the landing runway…the runway…” which the Examiner recommends updating to instead state “…the predefined landing runway…the predefined landing runway…” if that is in fact the Applicant’s intention, so as to avoid potential misinterpretation.
Claim 5 as currently presented states “…the third position and fourth position…” which the Examiner recommends updating to instead state “…the third position and the fourth position…” so as to avoid potential misinterpretation.
Claim 4 as currently presented states “…a current position…”; claim 6 is dependent on claim 4 and also states “…a current position…the current position…” which the Examiner recommends updating to differentiate between the “a/the current position” so as to avoid potential misinterpretation.
Appropriate correction is required.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3-4, 6-9 are rejected under 35 U.S.C. 103 as being unpatentable over Billhartz et al. (US-2022/0067369; hereinafter Billhartz; already of record) in view of Dame et al. (US-2020/0027362; hereinafter Dame; already of record).
Regarding claim 1, Billhartz discloses a method for assisting landing of an aircraft on a predefined landing runway of a destination airport (see Billhartz at least Abs), the method comprising:
determining a first position of the aircraft with respect to the predefined landing runway, based on a photographic image taken from the aircraft, on coordinates of the predefined landing runway in a database, and on a first algorithm for determining a position of the aircraft with respect to the predefined landing runway using the photographic image (see Billhartz at least Fig 2, [0037] "In some example implementations, while the aircraft 100 is approaching a runway at an airfield, the system 200 is configured to receive a sequence of images 204 of the airfield. In some such example implementations, the sequence of images is captured by the camera 202, which is onboard the aircraft 100 approaching the runway." [0039] "In some example implementations, for at least one image 204A of the sequence of images 204, the system 200 is configured to apply the image to a machine learning model, such as the first machine learning model 208 or the second machine learning model 210, for example, that is trained to perform an object detection and segmentation in which the runway on the airfield, or a runway marking on the runway, is detected in the image..." [0047] "In example implementations where the runway-framed local coordinates are known, those known, runway-framed local coordinates can be matched by the image processing system 206 or another component of system 200 to corresponding points in the image... In some example implementations, the runway-framed local coordinates are stored in a local data store, and/or are accessed from a remote data store by the system 200 in advance of attempting to land on the given runway. In some example implementations, information from one or more additional information sources 226 can be used in connection with the machine learning models 208, 210 and/or the corner detector 214 to identify and/or match interest points in the image to corresponding points on the runway..." [0049] "...In some such example implementations, the system 200, such as through the operation of the perspective-n-point system 216, is configured to use the interest points and the known runway-framed local coordinates to determine a current pose estimate 218 of the camera 202 and thereby the aircraft 100 relative to the runway or the runway marking." and [0056] "In another example implementation where the system 200 uses and generates additional information, a given machine learning model, such as the first machine learning model 208 or the second machine learning model 210, for example, is further configured to determine a confidence interval 232 associated with the detection of the relevant runway or the relevant runway marking..."), wherein determining the first position includes determining a translation and a rotation between the predefined landing runway and a current position of the aircraft (see Billhartz at least [0070] "As expressed in Equation 4, the scaling factors, the values of the rotation matrix R, and the translation vector T are unknown. However, example implementations of the subject disclosure involve solving for the unknowns in equations. For example, the perspective-n-point system 216 can use an interative algorithmic or programmatic approach. One such approach involving receives four or more mappings of pixel-to-real world coordinates and solving for the unknowns. In some such approaches, the values returned from a given algorithm or program are the rotation and translation vectors to move from global coordinates to camera coordinates. In example implementations that are directed to estimating the camera 202 position (or the aircraft 100 position) relative to a desired real world landing position (which is expressed with a global coordinate system origin), the camera's coordinate system origin must be transformed into global coordinate points...");
determining a second position of the aircraft with respect to the predefined landing runway, based on the photographic image taken from the aircraft, on the coordinates of the predefined landing runway in the database, and on a second algorithm for determining a position of the aircraft with respect to the predefined landing runway using the photographic image, different from the first algorithm (see Billhartz at least Fig 2, [0037] "In some example implementations, while the aircraft 100 is approaching a runway at an airfield, the system 200 is configured to receive a sequence of images 204 of the airfield. In some such example implementations, the sequence of images is captured by the camera 202, which is onboard the aircraft 100 approaching the runway." [0039] "In some example implementations, for at least one image 204A of the sequence of images 204, the system 200 is configured to apply the image to a machine learning model, such as the first machine learning model 208 or the second machine learning model 210, for example, that is trained to perform an object detection and segmentation in which the runway on the airfield, or a runway marking on the runway, is detected in the image..." [0047] "In example implementations where the runway-framed local coordinates are known, those known, runway-framed local coordinates can be matched by the image processing system 206 or another component of system 200 to corresponding points in the image... In some example implementations, the runway-framed local coordinates are stored in a local data store, and/or are accessed from a remote data store by the system 200 in advance of attempting to land on the given runway. In some example implementations, information from one or more additional information sources 226 can be used in connection with the machine learning models 208, 210 and/or the corner detector 214 to identify and/or match interest points in the image to corresponding points on the runway..." [0049] "...In some such example implementations, the system 200, such as through the operation of the perspective-n-point system 216, is configured to use the interest points and the known runway-framed local coordinates to determine a current pose estimate 218 of the camera 202 and thereby the aircraft 100 relative to the runway or the runway marking." and [0056] "In another example implementation where the system 200 uses and generates additional information, a given machine learning model, such as the first machine learning model 208 or the second machine learning model 210, for example, is further configured to determine a confidence interval 232 associated with the detection of the relevant runway or the relevant runway marking..."); and
…a flight assistance controller of the aircraft (see Billhartz at least [0036] "...In some such example implementations, the pose estimate system 205, which is configured to incorporate the image processing system 206 and/or the perspective-n-point system 216 (both of which can also be incorporated into the aircraft 100), provide information to the guidance system 220 on the aircraft 100 and/or the control system 222 of the aircraft 100 to assist in the landing of the aircraft 100.") configured to, based on the information representative of the difference between the first position and the second position, proceed with a landing procedure of the aircraft to the predefined landing runway or to trigger an interruption of the landing procedure (see Billhartz at least [0057] "FIG. 3 is a block diagram of a system pipeline 300 that can be used in conjunction with a system, such as system 200, for supporting an aircraft approaching a runway on an airfield, according to example implementations of the subject disclosure. As discussed and otherwise disclosed herein, a sequence of images, such as the sequence of images 204 captured by camera(s) 202, are applied to one or more trained machine learning models (such as first machine learning model 208 and second machine learning model 210, for example) and processed to generate the information that can be used to support the guidance and/or control of an aircraft 100 during landing operations. The system pipeline 300 illustrated in FIG. 3 presents an example approach to acquiring and processing information used to train the machine learning models and to provide the information used in the guidance and control of the aircraft.").
However, while Billhartz additionally discloses that both algorithms determine a score for their respective images (see Billhartz at least [0056]), it is not clear that these score are compared, such as the limitation below:
…supplying information representative of a difference between the first position and the second position…
Dame, in the same field of endeavor, teaches the following:
…supplying information representative of a difference between the first position and the second position (see Dame at least [0074] "The computing system 102 can also use sensor data from one or both of the first sensor 112 and the second sensor 114 to determine a lateral displacement that represents a distance between a reference point of the aircraft and the target path (e.g., a centerline of the runway). For example, the computing system 102 could compare a first position of a reference point of the aircraft relative to a centerline of the runway (or other desired path) as represented in sensor data from the first sensor with a second position of the same reference point relative to the centerline of the runway as represented in sensor data from the second sensor with the second position...").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the individualized positional determinations as disclosed by Billhartz with a difference amongst positions such as taught by Dame with a reasonable expectation of success so as to hone in on accuracy by way of utilizing multiple reference points (see Dame at least [0069]-[0070] and [0096]).
Regarding claim 3, Billhartz in view of Dame teach the method for assisting landing of an aircraft on a runway of a destination airport according to claim 1, wherein:
the first algorithm is an algorithm of a “Perspective-n-Point” type comprising a first method for determining a translation between a landing runway and a current position of the aircraft, together with a method for determining the rotation between the landing runway and the current position of the aircraft (see Billhartz at least [0070] "...For example, the perspective-n-point system 216 can use an interative algorithmic or programmatic approach. One such approach involving receives four or more mappings of pixel-to-real world coordinates and solving for the unknowns. In some such approaches, the values returned from a given algorithm or program are the rotation and translation vectors to move from global coordinates to camera coordinates. In example implementations that are directed to estimating the camera 202 position (or the aircraft 100 position) relative to a desired real world landing position (which is expressed with a global coordinate system origin), the camera's coordinate system origin must be transformed into global coordinate points..."); and,
the second algorithm comprises a second method for determining a translation between a landing runway and the current position of the aircraft, together with an acquisition of the position of the aircraft (see Billhartz at least [0070] "...For example, the perspective-n-point system 216 can use an interative algorithmic or programmatic approach. One such approach involving receives four or more mappings of pixel-to-real world coordinates and solving for the unknowns. In some such approaches, the values returned from a given algorithm or program are the rotation and translation vectors to move from global coordinates to camera coordinates. In example implementations that are directed to estimating the camera 202 position (or the aircraft 100 position) relative to a desired real world landing position (which is expressed with a global coordinate system origin), the camera's coordinate system origin must be transformed into global coordinate points...") using information supplied by an inertial navigation system of the aircraft (see Dame at least [0076] "...The computing system 102 can also receive trend information regarding recent movements and orientations of the aircraft from other types of sensors, such as an inertial measurement unit (IMU) or standalone accelerometers, gyroscopes, or magnetometers.").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the aircraft as taught by Billhartz in view of Dame by substituting the generically recited camera with a specific inertial navigation system such as taught by Dame with a reasonable expectation of success since one of ordinary skill in the art would recognize that the simple substitution of one known element for another produces a predictable result (object detection).
Regarding claim 4, Billhartz in view of Dame teach the analogous material of that in claim 1 as recited in the instant claim and is rejected for similar reasons. Additionally, Billhartz discloses a device … comprising electronic circuitry (see Billhartz at least [0016]) …
Regarding claim 6, Billhartz in view of Dame teach the analogous material of that in claim 3 as recited in the instant claim and is rejected for similar reasons.
Regarding claim 7, Billhartz in view of Dame teach an aircraft comprising the device according to claim 4 (see Billhartz at least Abs and [0102] "FIG. 6 illustrates an apparatus 600 according to some example implementations of the subject disclosure. Generally, an apparatus of exemplary implementations of the subject disclosure can comprise, include or be embodied in one or more fixed or portable electronic devices. Examples of suitable electronic devices include a smartphone, tablet computer, laptop computer, desktop computer, workstation computer, server computer or the like. The apparatus can include one or more of each of a number of components such as, for example, processing circuitry 602 (e.g., processor unit) connected to a memory 604 (e.g., storage device).").
Regarding claim 8, Billhartz in view of Dame teach a computer program product comprising program code instructions for executing the method according to claim 1 when the instructions are executed by a processor of a landing assistance device of an aircraft (see Billhartz at least [0017] "Some example implementations provide a computer-readable storage medium for supporting an aircraft approaching a runway on an airfield, the computer-readable storage medium being non-transitory and having computer-readable program code stored therein that, in response to execution by processing circuitry, causes an apparatus to at least perform the method of any preceding example implementation, or any combination of any preceding example implementations." [0104] "The processing circuitry 602 can be a number of processors, a multi-core processor or some other type of processor, depending on the particular implementation. Further, the processing circuitry can be implemented using a number of heterogeneous processor systems in which a main processor is present with one or more secondary processors on a single chip. As another illustrative example, the processing circuitry can be a symmetric multi-processor system containing multiple processors of the same type. In yet another example, the processing circuitry can be embodied as or otherwise include one or more ASICs, FPGAs or the like. Thus, although the processing circuitry can be capable of executing a computer program to perform one or more functions, the processing circuitry of various examples can be capable of performing one or more functions without the aid of a computer program. In either instance, the processing circuitry can be appropriately programmed to perform functions or operations according to example implementations of the subject disclosure." and [0108] "As indicated above, program code instructions can be stored in memory, and executed by processing circuitry that is thereby programmed, to implement functions of the systems, subsystems, tools and their respective elements described herein. As will be appreciated, any suitable program code instructions can be loaded onto a computer or other programmable apparatus from a computer-readable storage medium to produce a particular machine, such that the particular machine becomes a means for implementing the functions specified herein. These program code instructions can also be stored in a computer-readable storage medium that can direct a computer, a processing circuitry or other programmable apparatus to function in a particular manner to thereby generate a particular machine or particular article of manufacture. The instructions stored in the computer-readable storage medium can produce an article of manufacture, where the article of manufacture becomes a means for implementing functions described herein. The program code instructions can be retrieved from a computer-readable storage medium and loaded into a computer, processing circuitry or other programmable apparatus to configure the computer, processing circuitry or other programmable apparatus to execute operations to be performed on or by the computer, processing circuitry or other programmable apparatus.").
Regarding claim 9, Billhartz in view of Dame teach a storage medium comprising a computer program product according to claim 8 (see Billhartz at least [0017] "Some example implementations provide a computer-readable storage medium for supporting an aircraft approaching a runway on an airfield, the computer-readable storage medium being non-transitory and having computer-readable program code stored therein that, in response to execution by processing circuitry, causes an apparatus to at least perform the method of any preceding example implementation, or any combination of any preceding example implementations." and [0105] "The memory 604 is generally any piece of computer hardware that is capable of storing information such as, for example, data, computer programs (e.g., computer-readable program code 606) and/or other suitable information either on a temporary basis and/or a permanent basis. The memory can include volatile and/or non-volatile memory, and can be fixed or removable. Examples of suitable memory include random access memory (RAM), read-only memory (ROM), a hard drive, a flash memory, a thumb drive, a removable computer diskette, an optical disk, a magnetic tape or some combination of the above. Optical disks can include compact disk-read only memory (CD-ROM), compact disk-read/write (CD-R/W), DVD or the like. In various instances, the memory can be referred to as a computer-readable storage medium. The computer-readable storage medium is a non-transitory device capable of storing information, and is distinguishable from computer-readable transmission media such as electronic transitory signals capable of carrying information from one location to another. Computer-readable medium as described herein can generally refer to a computer-readable storage medium or computer-readable transmission medium.").
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Billhartz in view of Dame, and further in view of Conrardy et al. (US-2014/0225753; hereinafter Conrardy; already of record).
Regarding claim 10, Billhartz in view of Dame teach the method for assisting landing of an aircraft on a runway of a destination airport according to claim 1. However, while Billhartz controls an aircraft according to data detected via sensors, such as guiding an aircraft during a landing operation, and Dame teaches the determination of a difference between positional measurements, neither reference explicitly discloses or teaches …the interruption of the landing procedure includes controlling the aircraft to perform a go-around with engine throttle.
Conrardy, in the same field of endeavor, teaches the following:
…the interruption of the landing procedure includes controlling the aircraft to perform a go-around with engine throttle (see Conrardy at least [0029] "It is also contemplated that a user in the cockpit 12 may be alerted as to the location of the aircraft with respect to the runway on which it is to land. For example, the alert may indicate the aircraft should perform a go around procedure as indicated in FIG. 5 at 170. This may be determined by the controller 30 based on the Vref speed and the location of the aircraft. In the illustrated example, the aircraft 10 should go around because the speed of the aircraft is much greater than the Vref speed and the aircraft 10 is too far down the runway 152. Going around will allow the aircraft 10 to safely touchdown and decelerate prior to the end of the runway 152...").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the aircraft controls as disclosed by Billhartz with an interruption such as taught by Conrardy with a reasonable expectation of success so as to proceed maneuvering in a safe manner (see Conrardy at least [0029]).
Allowable Subject Matter
Claim 2 and analogous claim 5 are objected to as being dependent upon a rejected base claim, as well as outstanding claim objections as listed above, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter: upon amendments of 6/24/2026 having been entered, and the indefiniteness issues having been resolved, the Examiner recognizes that no reference as individually presented, or any reasonable combination of references, would result in teaching the specificity of comparing positions of multiple runways, and from a list of compared differences, then proceeding to compare the smallest of two differences, resulting in additional control determinations, as detailed in claims 2 and 5.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. S. et al. (US-2020/0051442) teaches a system that detects runways and compares the runway’s location against a threshold.
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/S.P.R./Examiner, Art Unit 3663
/ABBY J FLYNN/Supervisory Patent Examiner, Art Unit 3663
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