Prosecution Insights
Last updated: April 19, 2026
Application No. 18/732,202

SYSTEMS AND METHODS FOR DRONE NAVIGATION

Non-Final OA §101§102
Filed
Jun 03, 2024
Examiner
WEBER, TAMARA L
Art Unit
3667
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
General Dynamics Mission Systems Inc.
OA Round
1 (Non-Final)
87%
Grant Probability
Favorable
1-2
OA Rounds
2y 3m
To Grant
99%
With Interview

Examiner Intelligence

Grants 87% — above average
87%
Career Allow Rate
531 granted / 609 resolved
+35.2% vs TC avg
Moderate +12% lift
Without
With
+12.0%
Interview Lift
resolved cases with interview
Typical timeline
2y 3m
Avg Prosecution
17 currently pending
Career history
626
Total Applications
across all art units

Statute-Specific Performance

§101
15.7%
-24.3% vs TC avg
§103
34.6%
-5.4% vs TC avg
§102
23.1%
-16.9% vs TC avg
§112
18.2%
-21.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 609 resolved cases

Office Action

§101 §102
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 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. Claim Status This action is in response to applicant’s filing on 6/3/2024. Claims 1-22 are pending and considered below. Specification The disclosure is objected to because of the following informalities: in paragraph [0029] (PGPub), “FIG. 2A” should be “FIG. 2”. Appropriate correction is required. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without integrating the judicial exception into a practical application and without an additional element which amounts to significantly more than the judicial exception. Regarding claims 1-12, step 1 analysis, the subject matter of claims 1-12 is included in the four patent-eligible subject matter categories (e.g., process, machine, manufacture or composition of matter). Claims 1-12 are directed to a device (at least one processor). Claims 1-12 are directed to a judicial exception. The claim limitations recite a revised step 2A, prong one, abstract idea (a mental process involving observation and evaluation which could be performed in the human mind). Claims 1-12 are directed to a device for repeatedly identifying a potential path segment in a geographic region; determining if the potential path segment is open to navigation; adding the potential path segment to a navigation path network; determining a cost factor of the potential path segment; repeatedly linking together potential path segments in the navigation path network; and determining a final navigation path. This limitation is a simple process that, under the broadest reasonable interpretation, covers performance of the limitation in the mind. For example, the claims encompass an operator determining a navigation path for a drone based on a map or chart of a geographic region. Claims 1-12 include the revised step 2A, prong two, additional elements of providing a spatial obstruction database; and identifying a starting position and a destination position. Providing a spatial obstruction database and identifying a starting position and a destination position is data gathering, which is a form of insignificant extra-solution activity. Claims 1-12 do not recite revised step 2A, prong two, additional elements that integrate the abstract idea into a practical application. Claims 1-12 generally link the use of the abstract idea to a particular technological environment or field of use (drone navigation systems). Claims 1-12 include the step 2B additional element of at least one processor. Applicant’s specification does not provide any indication that the processors are anything other than conventional processors. Receiving input and generating a result are well-understood, routine and conventional functions when claimed using generic processors. Processors are widely prevalent and in common use in drone navigation systems. Processors are not significantly more than the judicial exception since they are well-understood, routine and conventional features previously known to the drone navigation system industry. Therefore, claims 1-12 are rejected under 35 U.S.C. 101. Regarding claims 13-22, step 1 analysis, the subject matter of claims 13-22 is included in the four patent-eligible subject matter categories. Claims 13-22 are directed to a method. Claims 13-22 are directed to a judicial exception. The claim limitations recite a revised step 2A, prong one, abstract idea (a mental process involving observation and evaluation which could be performed in the human mind). Claims 13-22 are directed to a method for repeatedly identifying a potential path segment in a geographic region; determining if the potential path segment is open to navigation; adding the potential path segment to a navigation path network; determining a cost factor of the potential path segment; repeatedly linking together potential path segments in the navigation path network; and determining a final navigation path. This limitation is a simple process that, under the broadest reasonable interpretation, covers performance of the limitation in the mind. For example, the claims encompass an operator determining a navigation path for a drone based on a map or chart of a geographic region. Claims 13-22 include the revised step 2A, prong two, additional elements of providing a spatial obstruction database; and identifying a starting position and a destination position. Providing a spatial obstruction database and identifying a starting position and a destination position is data gathering, which is a form of insignificant extra-solution activity. Claims 13-22 do not recite revised step 2A, prong two, additional elements that integrate the abstract idea into a practical application. Claims 13-22 generally link the use of the abstract idea to a particular technological environment or field of use (drone navigation systems). Claims 13-22 do not include any step 2B additional elements. Therefore, claims 13-22 are rejected under 35 U.S.C. 101. Examiner suggests amending the independent claims to positively recite a vehicle control function in order to provide a revised step 2A, prong two, additional element that integrates the abstract idea into a practical application. For instance, the independent claims could be amended to include “maneuvering a drone based on the final navigation path”. See, the 2019 Revised Patent Subject Matter Eligibility Guidance, which is available on the USPTO Website. Claim Rejections - 35 USC § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claims 1-22 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kohn-Rich (US-2016/0210863-A1, hereinafter Kohn-Rich). Regarding claim 1, Kohn-Rich discloses: a spatial obstruction database for a geographic region, where the spatial obstruction database represents physical features and airspace restrictions in the geographic region as abstracted spatial obstructions with the spatial obstruction database (paragraphs [0020-0022], [0062-0077] and [0097-0104]; and FIG. 2, Nap-Of-the-Earth (NOE) path planning-200, environment-210, database update-216, optimal NOE trajectory computation-220, optimal path computation-222, autopilot-242, helicopter (plant) - 244, and state sensors-246); at least one processor configured to: (paragraphs [0023] and [0127-0129]; and FIG. 22, computing system-2200, processor(s) - 2210, and memory-2215); identify a starting position and a destination position in the geographic region (paragraph [0018]); repeatedly identify a potential path segment in the geographic region, and for each identified potential path segment: (paragraph [0018]); determine if the potential path segment is open to navigation (paragraph [0018]); responsive to determining that the potential path segment is open to navigation, add the potential path segment to a navigation path network and determine a cost factor of the potential path segment (paragraphs [0018], [0024-0027] and [0097-0104]); repeatedly link together potential path segments in the navigation path network to generate a plurality of navigation paths from the starting position to the destination position (paragraph [0018]); and determine a final navigation path from the starting position to the destination position based at least in part on the cost factor of the potential path segments in the plurality of navigation paths (paragraphs [0114-0118]; and FIG. 17, update cell heights and weights-1705, determine grid area for recomputation-1710, calculate shortest safe path-1715, perform geometric smoothing-1720, perform dynamic smoothing-1725, and provide nominal path-1745). Regarding claim 2, Kohn-Rich further discloses: wherein the at least one processor is configured to determine the final navigation path from the starting position to the destination position based at least in part on the cost factor of the potential path segments in the plurality of navigation paths by being configured to: (paragraphs [0114-0118]); select a subset of the navigation paths from the starting position to the destination position based at least in part on the cost factor of the potential path segments in the navigation paths (paragraphs [0018] and [0097-0104]; FIG. 6, an approximation of the shortest path by straight lines in the horizontal plane; and FIG. 9, geometric smoothing in the horizontal plane); determine intersection points of the selected subset of the navigation paths (paragraphs [0015], [0021-0026] and [0035]); divide the selected subset of the navigation paths into sections at the determined intersection points (paragraphs [0018] and [0097-0104]); and link selected sections to determine the final navigation path from the starting position to the destination position (paragraphs [0114-0118]). Regarding claim 3, Kohn-Rich further discloses: wherein the at least one processor is configured to determine the final navigation path from the starting position to the destination position based at least in part on the cost factor of the potential path segments in the plurality of navigation paths by being configured to: (paragraphs [0114-0118]); select a subset of the navigation paths from the starting position to the destination position based at least in part on the cost factor of the potential path segments in the navigation paths (paragraphs [0018] and [0097-0104]; FIG. 6, an approximation of the shortest path by straight lines in the horizontal plane; and FIG. 9, geometric smoothing in the horizontal plane); determine intersection points of the selected subset of the navigation paths (paragraphs [0015], [0021-0026] and [0035]); divide the selected subset of the navigation paths into sections at the determined intersection points (paragraphs [0018] and [0097-0104]); calculate a cost factor for each of the sections (paragraphs [0010-0018] and [0073]; and FIG. 3, terrain representation illustrating voxels); and link selected sections to determine the final navigation path from the starting position to the destination position based at least in part on the calculated cost factors for each of the sections (paragraphs [0114-0118]). Regarding claim 4, Kohn-Rich further discloses: wherein the at least one processor is configured to repeatedly identify the potential path segment in the geographic region by utilizing a random tree selection of points in the geographic region (paragraphs [0018] and [0021]). Regarding claim 5, Kohn-Rich further discloses: wherein the at least one processor is configured to repeatedly identify the potential path segment in the geographic region by utilizing a random tree selection of points in the geographic region proximate the starting position and points proximate the destination position and points between the starting position and ending position (paragraphs [0018] and [0021]). Regarding claim 6, Kohn-Rich further discloses: wherein the at least one processor is configured to determine if the potential path segment is open to navigation by being configured to: (paragraph [0107]; and FIG. 11, an approximation of the vertical basis profile by straight lines); query the spatial obstructions database for a volume that contains the potential path segment and return the abstracted spatial obstructions from the spatial obstruction database that correspond to the volume (paragraphs [0020-0027] and [0073]); and determine if any of the returned abstracted spatial obstructions for the volume intersect with the potential path segment to determine if the potential path segment is unobstructed (paragraphs [0085-0089]; and FIG. 5, computing visible and hidden cells along a line). Regarding claim 7, Kohn-Rich further discloses: wherein the at least one processor is configured to determine if the potential path segment is open to navigation by being configured to: (paragraph [0107]; and FIG. 11, an approximation of the vertical basis profile by straight lines); query the spatial obstructions database for a volume that contains the potential path segment and return the abstracted spatial obstructions (paragraphs [0020-0027] and [0073]); that correspond to physical features in the geographic region from the spatial obstruction database that correspond to the volume (paragraphs [0018] and [0065]); determine if any of the returned abstracted spatial obstructions for the volume that correspond to physical features in the geographic region intersect with the potential path segment to determine if the potential path segment is unobstructed by physical features (paragraphs [0085-0089]; and FIG. 5, computing visible and hidden cells along a line); query the spatial obstructions database for the volume that contains the potential path segment and return the abstracted spatial obstructions (paragraphs [0020-0027] and [0073]); that correspond to airspace restrictions in the geographic region from the spatial obstruction database that correspond to the volume (paragraphs [0018] and [0104]); and determine if any of the returned abstracted spatial obstructions for the volume that correspond to airspace restrictions in the geographic region intersect with the potential path segment to determine if the potential path segment is unobstructed by airspace restrictions (paragraphs [0085-0089]; and FIG. 5, computing visible and hidden cells along a line). Regarding claim 8, Kohn-Rich further discloses: wherein the at least one processor is configured to determine the cost factor of the potential path segment by being configured to: (paragraph [0018]); calculate a distance of the potential path segment (paragraph [0018]); and augment the calculated distance by at least one weighting factor, where the at least one weighting factor is based at least in part on a hazard associated with the potential path segment (paragraphs [0018] and [0104]). Regarding claim 9, Kohn-Rich further discloses: wherein the at least one processor is configured to determine the cost factor of the potential path segment by being configured to: calculate a Euclidean squared distance of the potential path segment (paragraph [0018]). Regarding claim 10, Kohn-Rich further discloses: wherein the spatial obstruction database represents the abstracted spatial obstructions as subregions having a defined footprint and defined height (paragraphs [0020-0027], [0065] and [0073]; and FIG. 3, terrain representation illustrating voxels). Regarding claim 11, Kohn-Rich further discloses: wherein the spatial obstruction database represents the abstracted spatial obstructions as subregions having a parallelepiped shape (paragraphs [0020-0027] and [0073]; and FIG. 3, terrain representation illustrating voxels). Regarding claims 12 and 22, Kohn-Rich further discloses: wherein the spatial obstruction database represents the physical features in the geographic region as the abstracted spatial obstructions within the spatial obstruction database by being configured to: (paragraphs [0018], [0020-0027] and [0065]); represent the geographic region as a plurality of subregions (paragraphs [0085-0089]; and FIG. 5, computing visible and hidden cells along a line); for each of the plurality of subregions that includes an obstruction, identify at least an obstructed high point and identifying the subregion as fully obstructed to the obstructed high point (paragraphs [0085-0089]); and wherein the spatial obstruction database is optimized for three-dimensional queries (paragraphs [0097-0107]; FIG. 9, geometric smoothing in the horizontal plane; and FIG. 11, an approximation of the vertical basis profile by straight lines). Regarding claim 13, Kohn-Rich further discloses: providing a spatial obstruction database for a geographic region, where the spatial obstruction database represents physical features and airspace restrictions in the geographic region as abstracted spatial obstructions with the spatial obstruction database (paragraphs [0020-0022], [0062-0077] and [0097-0104]; and FIG. 2, Nap-Of-the-Earth (NOE) path planning-200, environment-210, database update-216, optimal NOE trajectory computation-220, optimal path computation-222, autopilot-242, helicopter (plant) - 244, and state sensors-246); identifying a starting position and a destination position in the geographic region (paragraph [0018]); repeatedly identifying a potential path segment in the geographic region, and for each identified potential path segment: (paragraph [0018]); determining if the potential path segment is open to navigation (paragraph [0018]); responsive to determining that the potential path segment is open to navigation, adding the potential path segment to a navigation path network and determine a cost factor of the potential path segment (paragraphs [0018], [0024-0027] and [0097-0104]); repeatedly linking together potential path segments in the navigation path network to generate a plurality of navigation paths from the starting position to the destination position (paragraph [0018]); and determining a final navigation path from the starting position to the destination position based at least in part on the cost factor of the potential path segments in the plurality of navigation paths (paragraphs [0114-0118]; and FIG. 17, update cell heights and weights-1705, determine grid area for recomputation-1710, calculate shortest safe path-1715, perform geometric smoothing-1720, perform dynamic smoothing-1725, and provide nominal path-1745). Regarding claim 14, Kohn-Rich further discloses: wherein the determining the final navigation path from the starting position to the destination position based at least in part on the cost factor of the potential path segments in the plurality of navigation paths is performed at least in part by: (paragraphs [0114-0118]); selecting a subset of the navigation paths from the starting position to the destination position based at least in part on the cost factor of the potential path segments in the navigation paths (paragraphs [0018] and [0097-0104]; FIG. 6, an approximation of the shortest path by straight lines in the horizontal plane; and FIG. 9, geometric smoothing in the horizontal plane); determining intersection points of the selected subset of the navigation paths (paragraphs [0015], [0021-0026] and [0035]); divide the selected subset of the navigation paths into sections at the determined intersection points (paragraphs [0018] and [0097-0104]); and linking selected sections to determine the final navigation path from the starting position to the destination position (paragraphs [0114-0118]). Regarding claim 15, Kohn-Rich further discloses: wherein the determining the final navigation path from the starting position to the destination position based at least in part on the cost factor of the potential path segments in the plurality of navigation paths is performed at least in part by: (paragraphs [0114-0118]); selecting a subset of the navigation paths from the starting position to the destination position based at least in part on the cost factor of the potential path segments in the navigation paths (paragraphs [0018] and [0097-0104]; FIG. 6, an approximation of the shortest path by straight lines in the horizontal plane; and FIG. 9, geometric smoothing in the horizontal plane); determining intersection points of the selected subset of the navigation paths (paragraphs [0015], [0021-0026] and [0035]); dividing the selected subset of the navigation paths into sections at the determined intersection points (paragraphs [0018] and [0097-0104]); calculate a cost factor for each of the sections (paragraphs [0010-0018] and [0073]; and FIG. 3, terrain representation illustrating voxels); and linking selected sections to determine the final navigation path from the starting position to the destination position based at least in part on the calculated cost factors for each of the sections (paragraphs [0114-0118]). Regarding claim 16, Kohn-Rich further discloses: wherein the repeatedly identifying the potential path segment in the geographic region is performed at least in part by utilizing a random tree selection of points in the geographic region (paragraphs [0018] and [0021]). Regarding claim 17, Kohn-Rich further discloses: wherein the repeatedly identifying the potential path segment in the geographic region is performed at least in part by utilizing a random tree selection of points in the geographic region proximate the starting position and points proximate the destination position and points between the starting position and ending position (paragraphs [0018] and [0021]). Regarding claim 18, Kohn-Rich further discloses: wherein the determining if the potential path segment is open to navigation is performed at least in part by: (paragraph [0107]; and FIG. 11, an approximation of the vertical basis profile by straight lines); querying the spatial obstructions database for a volume that contains the potential path segment and return the abstracted spatial obstructions from the spatial obstruction database that correspond to the volume (paragraphs [0020-0027] and [0073]); and determining if any of the returned abstracted spatial obstructions for the volume intersect with the potential path segment to determine if the potential path segment is unobstructed (paragraphs [0085-0089]; and FIG. 5, computing visible and hidden cells along a line). Regarding claim 19, Kohn-Rich further discloses: wherein the determining if the potential path segment is open to navigation is performed at least in part by: (paragraph [0107]; and FIG. 11, an approximation of the vertical basis profile by straight lines); querying the spatial obstructions database for a volume that contains the potential path segment and return the abstracted spatial obstructions (paragraphs [0020-0027] and [0073]); that correspond to physical features in the geographic region from the spatial obstruction database that correspond to the volume (paragraphs [0018] and [0065]); determining if any of the returned abstracted spatial obstructions for the volume that correspond to physical features in the geographic region intersect with the potential path segment to determine if the potential path segment is unobstructed by physical features (paragraphs [0085-0089]; and FIG. 5, computing visible and hidden cells along a line); querying the spatial obstructions database for the volume that contains the potential path segment and return the abstracted spatial obstructions (paragraphs [0020-0027] and [0073]); that correspond to airspace restrictions in the geographic region from the spatial obstruction database that correspond to the volume (paragraphs [0018] and [0104]); and determining if any of the returned abstracted spatial obstructions for the volume that correspond to airspace restrictions in the geographic region intersect with the potential path segment to determine if the potential path segment is unobstructed by airspace restrictions (paragraphs [0085-0089]; and FIG. 5, computing visible and hidden cells along a line). Regarding claim 20, Kohn-Rich further discloses: wherein the determining the cost factor of the potential path segment is performed at least in part by: (paragraph [0018]); calculating a distance of the potential path segment (paragraph [0018]); and augmenting the calculated distance by at least one weighting factor, where the at least one weighting factor is based at least in part on a hazard associated with the potential path segment (paragraphs [0018] and [0104]). Regarding claim 21, Kohn-Rich further discloses: wherein the determining the cost factor of the potential path segment is performed at least in part by: calculating a Euclidean squared distance of the potential path segment (paragraph [0018]). Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Macfarlane et al. (US-2016/0371984-A1) discloses a system in which coordinates for drone air space are stored in a map database in association with at least one path segment (Abstract). Li et al. (US-2022/0108621-A1) discloses a method for planning a shortest possible three-dimensional path for autonomous flying robots to traverse from one location to the other in a geographical region (Abstract). Elgersma et al. (US-2022/0406197-A1) discloses a method for selecting a trajectory for navigation of a vehicle over a given area based on a trajectory cost for each sub-region (Abstract). Terpin et al. (US-2024/0118089-A1) discloses a system for determining paths for autonomous vehicles. Costs are assigned to a plurality of available path segments based on data indicating risk of encountering obstacles and the path is determined from a starting point to an ending point based on the assigned costs (Abstract). Lei et al., Deep Learning-Based Complete Coverage Path Planning With Re-Joint and Obstacle Fusion Paradigm, Frontiers in Robotics and AI, Volume 9, Article 843816, 3/22/2022, pp. 1-14, discloses a system for navigating autonomous vehicles which uses a map developed through fusion of obstacles (Abstract). Any inquiry concerning this communication or earlier communications from the examiner should be directed to TAMARA L WEBER whose telephone number is (303)297-4249. The examiner can normally be reached 8:30-5:00 MTN. 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, Faris Almatrahi can be reached at 3134464821. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. TAMARA L. WEBER Examiner Art Unit 3667 /TAMARA L WEBER/ Examiner, Art Unit 3667
Read full office action

Prosecution Timeline

Jun 03, 2024
Application Filed
Jan 15, 2026
Non-Final Rejection — §101, §102 (current)

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Prosecution Projections

1-2
Expected OA Rounds
87%
Grant Probability
99%
With Interview (+12.0%)
2y 3m
Median Time to Grant
Low
PTA Risk
Based on 609 resolved cases by this examiner. Grant probability derived from career allow rate.

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