Prosecution Insights
Last updated: August 18, 2026
Application No. 18/673,398

METHOD FOR ASSISTING THE LANDING OF AN AIRCRAFT AND SYSTEM CONFIGURED FOR EXECUTING SAME

Non-Final OA §103§112
Filed
May 24, 2024
Priority
May 31, 2023 — FR 2305453
Examiner
REIDY, SEAN PATRICK
Art Unit
3663
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Airbus SAS
OA Round
3 (Non-Final)
37%
Grant Probability
At Risk
3-4
OA Rounds
1y 6m
Est. Remaining
76%
With Interview

Examiner Intelligence

Grants only 37% of cases
37%
Career Allowance Rate
40 granted / 108 resolved
-15.0% vs TC avg
Strong +40% interview lift
Without
With
+39.5%
Interview Lift
resolved cases with interview
Typical timeline
3y 9m
Avg Prosecution
35 currently pending
Career history
154
Total Applications
across all art units

Statute-Specific Performance

§101
9.1%
-30.9% vs TC avg
§103
56.8%
+16.8% vs TC avg
§102
7.4%
-32.6% vs TC avg
§112
26.1%
-13.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 108 resolved cases

Office Action

§103 §112
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. Status of Claims This Office Action is in response to the Applicant’s Response dated 2/6/2026. 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 pages 8-11 of 16, filed 2/6/2026, with respect to specification objections, claim objections, and 101 rejections have been fully considered and are persuasive. The specification objections, claim objections, and 101 rejections of record have been withdrawn. Response to Arguments Applicant's arguments, see pages 8-9 of 16, filed 2/6/2026, have been fully considered but are only partially persuasive. The Applicant has argued against the 112 rejections of record, and in some cases amended the claims to overcome the 112 rejections of record, however only some of the rejections have been overcome. A detailed rejection follows below, reemphasizing the rejections which were not addressed. Applicant's arguments, see pages 12-13 of 16, filed 2/6/2026, have been fully considered but they are not persuasive. The Applicant has argued against the citation of Billhartz disclosing a second algorithm being different than a first algorithm, however the Examiner respectfully disagrees. Billhartz depicts the use of a machine model 208 to determine positional information with a specific confidence interval, as well as the use of machine model 210 to determine positional information with a specific confidence interval (see Billhartz at least Fig 2, [0037], [0039], [0047], [0049], and [0056]). Applicant's arguments, see pages 13-14 of 16, filed 2/6/2026, have been fully considered but they are not persuasive. The Applicant has argued that the teachings of Dame are improper because the reference is allegedly non-analogous to the inventive concept as presented, however the Examiner respectfully disagrees. Dame teaches an aircraft which records a number of positional measurements, and then compares the determined positions to detect a deviation. Applicant’s arguments, see pages 14-15 of 16, filed 2/6/2026, with respect to claim 10 and amended claims 2 and 5 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Claims 2, 5, and 10 are now 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). A detailed rejection follows below. Claim Objections Claims 2-6 are objected to because of the following informalities: Claim 2 as currently presented states “…the plurality of of predefined landing runways…” which the Examiner recommends updating to instead state “…the plurality of [ [ of ] ] predefined landing runways…” so as to remove the redundant term. Claim 2 as currently presented states “…a second difference…two smallest second differences…the second differences…the two smallest second differences…the second difference…the second difference…the second differences…the two smallest second differences…” to which the Examiner recommends updating to instead state “…a second difference…two smallest second differences…the two smallest second differences…the two smallest second differences…the second difference…the second difference…the two smallest second differences…the two smallest second differences…” so as to avoid potential misinterpretation of which “second difference” is the topic of focus. Claim 2 as currently presented states “…the two landing runways…” to which the Examiner recommends updating to instead state “…[ [ the ] ] two landing runways…” so as to avoid potential misinterpretation, since two specific landing runways have not been discussed prior to or during this claim. Claim 2 as currently presented states “…the interruption to the flight procedure…” to which the Examiner recommends updating to instead state “…[ [ the ] ] an interruption to the flight procedure…” or similarly “…the interruption to the landing procedure…” so as to avoid potential misinterpretation. Claim 3 as currently presented states “…a method for determining a translation between a landing runway and a current position of the aircraft…a method for determining a translation between a landing runway and the current position of the aircraft…” to which the Examiner recommends updating to instead state “…a first method for determining a translation between a landing runway and a current position of the aircraft…a second method for determining a translation between a landing runway and the current position of the aircraft…” so as to differentiate between the two methods and avoid potential misinterpretation. Claim 4 as currently presented states “…a predefined landing runway…the landing runway…” to which the Examiner recommends updating to instead state “…a predefined landing runway…the predefined landing runway…” so as to avoid potential misinterpretation. Claim 5 as currently presented states “…a predefined landing runway…the landing runway…the runway…” to 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 “…a plurality landing runways…each of the landing runways…the landing runways…” to which the Examiner recommends updating to instead state “…a plurality landing runways…each of the landing runways…each of the landing runways…” so as to avoid potential misinterpretation. Claim 5 as currently presented states “…a predefined landing runway…the predefined landing runway…the predefined landing runways…” to 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 “…an identifier of the runway…an identifier of the runway…” to which the Examiner recommends updating to instead state “…an identifier of the runway…[ [ an ] ] the identifier of the runway…” so as to avoid potential misinterpretation. Claim 5 (similar to claim 2, but not directly adjacent) as currently presented states “…a second difference…two smallest second differences…the second differences…the two smallest second differences…the second difference…the second difference…the second differences…the second difference…the two smallest second differences…” to which the Examiner recommends updating to instead state “…a second difference…two smallest second differences…the two smallest second differences…the two smallest second differences…the second difference…the second difference…the two smallest second differences…the second difference…the two smallest second differences…” so as to avoid potential misinterpretation of which “second difference” is the topic of focus. Claim 5 as currently presented states “…the interruption to the flight procedure…” to which the Examiner recommends updating to instead state “…[ [ the ] ] an interruption to the flight procedure…” or similarly “…the interruption to the landing procedure…” so as to avoid potential misinterpretation. Claim 6 as currently presented states “…executing a first algorithm…executing a second algorithm…” to which the Examiner recommends updating to instead state “…executing [ [ a ] ] the first algorithm…executing [ [ a ] ] the second algorithm…” so as to avoid potential misinterpretation. Claim 6 as currently presented states “…a method for determining a translation between a landing runway and a current position of the aircraft…a method for determining a translation between a landing runway and the current position of the aircraft…” to which the Examiner recommends updating to instead state “…a first method for determining a translation between a landing runway and a current position of the aircraft…a second method for determining a translation between a landing runway and the current position of the aircraft…” so as to differentiate between the two methods and avoid potential misinterpretation. Appropriate correction is required. 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. Claims 2 and 5 are rejected under 35 U.S.C. 112(b), as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention. Claim 2 and claim 5 as currently presented state "…a second difference…a list of recorded information representative of the second differences…the second difference is the smallest from amongst the list…” which is indefinite because it is unclear which “second difference” is the smallest; the Examiner recommends updating the terminology so as to differentiate between all of the recorded “second difference(s)” and the smallest of the “second difference(s)”. 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: Determining the scope and contents of the prior art. Ascertaining the differences between the prior art and the claims at issue. Resolving the level of ordinary skill in the pertinent art. 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..."); 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 method for determining a translation between a landing runway and a current position of the aircraft, together with a method for determining a 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 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."). Claims 2, 5, and 10 are 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). Regarding claim 2, Billhartz in view of Dame teach the method for assisting landing of an aircraft according to claim 1, wherein the destination airport comprises a plurality of predefined landing runways (see Dame at least [0034] "When initially formulating control instructions, the computing system can receive and use sensor data to gain a general understanding of the environment of the aircraft. In particular, the computing system uses sensor data to detect nearby airport markings, such signs, surface lines, changes in the material making up paths (e.g., concrete and grass boundaries), intersections between multiple paths (e.g., an intersection that exists between two runways), objects (e.g., aircrafts, vehicles), and people in the environment of the aircraft..."), the method comprising, for each of the predefined landing runways of the destination airport, considered successively: determining a third position of the aircraft with respect to an ith predefined landing runway being considered, based on the photographic image taken from the aircraft, on coordinates of the ith predefined landing runway in the database, and on 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."); determining a fourth position of the aircraft with respect to the ith predefined landing runway, based on the photographic image taken from the aircraft, on the coordinates of the ith predefined landing runway in the database, and on the second algorithm, 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."); then, recording information, for each of the plurality of of predefined landing runways, representative of a second difference between the third position and the fourth 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..."), in association with an identifier of the ith predefined landing runway being considered (see Billhartz at least [0029] "...To address and overcome technical challenges associated with autonomous approach and landing operations in aircraft, example implementations of the subject disclosure involve the use of a machine learning model to identify features in an image of a landing environment, and then determine the pose of the aircraft with respect to the landing environment in order to generate the horizontal, vertical, and other positional guidance necessary to land."); then, comparing the recorded information representative of two smallest second differences in position between the third position and the fourth position from amongst a list of recorded information representative of the second differences in position between the third position and the fourth position in association with the plurality of predefined landing runways, and, in response to a third difference between the two smallest second differences in position exceeding a predetermined threshold value (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..."): supplying, to the flight assistance controller (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."), information representative of the second difference between the third determined position and the fourth determined 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...") for the predefined landing runway for which the second difference is the smallest from amongst the list of recorded information representative of the second differences in position between the third position and the fourth position in association with the predefined landing runways, and the flight assistance controller is configured to proceed with 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."); and otherwise: supplying, to the flight assistance controller (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.") … It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the positional determinations of the aircraft with respect to the runway as taught by Billhartz in view of Dame with additional comparisons such as taught by Dame with a reasonable expectation of success for reasons similar to those provided above in 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 following: …information according to which it is not possible to discriminate between the two landing runways associated with the two smallest second differences in position, and the flight assistance controller is configured to trigger the interruption to the flight procedure. Conrardy, in the same field of endeavor, teaches the following: …information according to which it is not possible to discriminate between the two landing runways associated with the two smallest second differences in position, and the flight assistance controller is configured to trigger the interruption to the flight procedure (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]). Regarding claim 5, Billhartz in view of Dame and Conrardy teach the analogous material of that in claim 2 as recited in the instant claim and is rejected for similar reasons. 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]). Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Nagonda et al. (US-2023/0386352) teaches course corrections for an aircraft which may be experiencing an unstable runway overrun condition. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to SEAN REIDY whose telephone number is (571) 272-7660. The examiner can normally be reached on M-F 7:00 AM- 3:00 PM. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Abby Flynn can be reached on (571) 272-9855. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see https://ppair-my.uspto.gov/pair/PrivatePair. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /S.P.R./Examiner, Art Unit 3663 /ABBY J FLYNN/Supervisory Patent Examiner, Art Unit 3663
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Prosecution Timeline

May 24, 2024
Application Filed
Nov 06, 2025
Non-Final Rejection mailed — §103, §112
Feb 06, 2026
Response Filed
May 04, 2026
Final Rejection mailed — §103, §112
Jun 24, 2026
Request for Continued Examination
Jul 02, 2026
Response after Non-Final Action
Aug 17, 2026
Non-Final Rejection mailed — §103, §112 (current)

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Prosecution Projections

3-4
Expected OA Rounds
37%
Grant Probability
76%
With Interview (+39.5%)
3y 9m (~1y 6m remaining)
Median Time to Grant
High
PTA Risk
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