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 .
This is the first office action on the merits and is responsive to the papers filed on 11/4/2022. Claims 1-7 and 15-20 are currently pending.
Election/Restrictions
1. Claims 8-14 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 12/21/2025.
Claim Objections
2. Claim 18 is objected to because of the following informalities:
“FGPA” should be unabbreviated in the claims at least once.
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.
3. Claims 1-7 and 15-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Any claim not specifically mentioned, including Claims 2-7 and 16-20, have been included based on its dependency.
4. Claim 1 recites the limitation "the motions of orbital objects" in Line 4. There is insufficient antecedent basis for this limitation in the claim.
5. Claim 1 recites the limitation "sending predictions to a reinforcement learning agent" in Lines 4-5. There is insufficient antecedent basis for this limitation in the claim. More specifically, it is unclear if the predicts sent are the same predicts made by the neural network. Under the broadest reasonable interpretation of the claims, the predicted are interpreted to be the same.
6. Claim 15 recites the limitation "the movement of identified objects" in Line 5. There is insufficient antecedent basis for this limitation in the claim.
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.
7. Subject Matter Eligibility Analysis of Claim 1 (see MPEP §2106.03):
As a method, the claim is directed to a statutory category (Step 1).
Claim 1 is 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 significantly more. Claim 1 is directed to generating commands for optimizing satellite safety and collision avoidance. This limitation akin to a mental process as a human mind can determine that a satellite needs to change its course to avoid an obstacle. For example, the human mind can determine a satellite is on a collision course with space debris and can also determine a command to avoid the space debris (Step 2A, Prong 1).
The applicant does not recite additional elements that integrate the judicial exception into a practical application. There is no control of the spacecraft based on the generated commands that is performed to actually avoid the object. The applicant has recited a claim in which predicts the satellite will collide with an object and generate a command that would avoid the object (Step 2A, Prong 2).
The claim does not provide an inventive concept and the claim recites no additional elements. Accordingly, the lack of additional elements does not integrate the abstract idea into a practical application because there are no meaningful limits imposed on practicing the abstract idea (see MPEP §2106.05(I)(a)) (Step 2B).
In conclusion, Claim 1 is directed toward non-subject matter eligible material and is thus rejected under 35 U.S.C 101 as being patent ineligible.
Claim Rejections - 35 USC § 103
8. 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.
9. 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.
10. The factual inquiries 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.
11. Claims 1, 3-5, 7, 15, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Schmitt (US 20190279375 A1) in view of Kaplan (US 20180346153 A1).
12. Regarding Claim 1, Schmitt teaches a method for… satellite control (Schmitt: [0010] and [0023]),
The method comprising a satellite with one LIDAR sensor, collecting environmental data via electron pulses (Schmitt: [0012]);
The data aggregating in a protected space processor and undergoing further processing by a neural network making predictions about the motions of orbital objects (Schmitt: [0016] and [0034]);
Sending predictions to a reinforcement learning agent (Schmitt: [0016] and [0036]).
Schmitt does not explicitly teach a method for optimized satellite control, and generating commands for optimizing satellite safety and collision avoidance. However, Schmitt teaches that the tracking algorithm is used for relative navigation between the target objects and the satellite in [0010] and [0034].
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date to steer the satellite for optimized trajectory control and collision avoidance as similarly shown in Schmitt's [0010] and [0034] use of relative navigation to provide the benefit of autonomously controlling a satellite for improved object detection.
Additionally, Kaplan teaches a method for optimized satellite control, and generating commands for optimizing satellite safety and collision avoidance (Kaplan: [0053]).
Schmitt and Kaplan are considered to be analogous to the claim invention because they are in the same field of satellite control. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Schmitt to incorporate the teachings of Kaplan for the reinforcement learning software program to processing signals and steering the satellite for optimized trajectory control and collision avoidance because it provides the benefit of optimizing fuel consumption while avoiding collisions. This provides the additional benefit of an increased safety of the satellite and reduced cost to operate.
13. Regarding Claim 3, Schmitt and Kaplan remains as applied above in Claim 1, and further, Schmitt teaches the neural network making predictions about the motions of orbital objects is a convolutional neural network (Schmitt: [0034] and [0036] Note that the convolutional neural network is equivalent to the artificial neural network that tracks target objects with LIDAR and camera systems.).
14. Regarding Claim 4, Schmitt and Kaplan remains as applied above in Claim 1, and further, Schmitt teaches the neural network making predictions about the motions of orbital objects is a recurrent neural network (Schmitt: [0036] and [0046] Note that the recurrent neural network is equivalent to the artificial neural network that repeats the training and connected to hidden layers.).
15. Regarding Claim 5, Schmitt and Kaplan remains as applied above in Claim 1, and further, Schmitt teaches the neural network making predictions about the motions of orbital objects is a deep neural network (Schmitt: [0036] and [0046] Note that the deep neural network is equivalent to the artificial neural network connected to multiple hidden layers.).
16. Regarding Claim 7, Schmitt and Kaplan remains as applied above in Claim 1, and further, Kaplan teaches the satellite further comprises two LIDAR sensors, wherein one LIDAR sensor is mounted on top of the satellite body and one LIDAR sensor is mounted on the bottom of the satellite body (Kaplan: [0034]).
17. Regarding Claim 15, Schmitt teaches a method for… satellite control (Schmitt: [0010] and [0023]),
The method comprising a LIDAR sensor searching and sensing a trajectory environment (Schmitt: [0012]),
And signaling data regarding the identification of orbital objects in the satellite's potential flight path to an on-board processor; wherein the on-board processor analyzes the data regarding orbital objects in the satellite's flight path using a neural network (Schmitt: [0016] and [0034]);
The neural network predicting the movement of identified objects in the satellite's potential flight path and further sending signals to an embedded reinforcement learning software program (Schmitt: [0016] and [0036]).
Schmitt does not explicitly teach a method for optimized satellite control, and the embedded reinforcement learning software program processing the signals and accordingly steering the satellite for optimized trajectory control and collision avoidance. However, Schmitt teaches that the tracking algorithm is used for relative navigation between the target objects and the satellite in [0010] and [0034].
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date to steer the satellite for optimized trajectory control and collision avoidance as similarly shown in Schmitt's [0010] and [0034] use of relative navigation to provide the benefit of autonomously controlling a satellite for improved object detection.
Additionally, Kaplan teaches a method for optimized satellite control, and the embedded reinforcement learning software program processing the signals and accordingly steering the satellite for optimized trajectory control and collision avoidance (Kaplan: [0053]).
Schmitt and Kaplan are considered to be analogous to the claim invention because they are in the same field of satellite control. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Schmitt to incorporate the teachings of Kaplan for the reinforcement learning software program to processing signals and steering the satellite for optimized trajectory control and collision avoidance because it provides the benefit of optimizing fuel consumption while avoiding collisions. This provides the additional benefit of an increased safety of the satellite and reduced cost to operate.
18. Regarding Claim 19, Schmitt and Kaplan remains as applied above in Claim 15, and further, Kaplan teaches there are two independent on-board processors, computing in parallel and communicating between one another to generate optimal steering commands (Kaplan: [0039] Note that it would have been obvious to one having ordinary skill in the art at the time the invention was made to have two independent on-board processors, since it has been held that mere duplication of the essential working parts of a device involves only routine skill in the art, St. Regis Paper Co. v. Bemis Co., 193 USPQ 8.).
19. Regarding Claim 20, Schmitt and Kaplan remains as applied above in Claim 15, and further, Kaplan teaches the neural network predicting the movement of identified objects in the satellite's potential flight path sends signals to an embedded expert system software program (Kaplan: [0053] and [0056]);
The embedded expert system software program processing the signals and steering the satellite for optimized trajectory control, collision avoidance, and orbital distance minimization (Kaplan: [0054] and [0056]).
20. Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Schmitt (US 20190279375 A1), in view of Kaplan (US 20180346153 A1), and in further view of McVey (US 20210025977 A1).
21. Regarding Claim 2, Schmitt and Kaplan remains as applied above in Claim 1.
Schmitt and Kaplan fail to explicitly teach the mounted LIDAR sensor is an infrared space LIDAR sensor.
However, in the same field of endeavor, McVey teaches the mounted LIDAR sensor is an infrared space LIDAR sensor (McVey: [0040]).
Schmitt, Kaplan, and McVey are considered to be analogous to the claim invention because they are in the same field of satellite object detection. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Schmitt and Kaplan to incorporate the teachings of McVey to use an infrared LIDAR sensor because it provides the benefit of reducing the beam divergence compared to flash-mode LIDAR imagers. This provides the additional benefit of increased accuracy for object detection.
22. Claims 6 and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Schmitt (US 20190279375 A1), in view of Kaplan (US 20180346153 A1), and in further view of Jacomb-Hood (US 9573702 B1).
23. Regarding Claim 6, Schmitt and Kaplan remains as applied above in Claim 1.
Schmitt and Kaplan fail to explicitly teach the commands for optimizing satellite safety and collision avoidance manipulate a right panel connector, connecting a satellite body to a right panel and a left panel connector, connecting a satellite body to a left panel.
However, in the same field of endeavor, Jacomb-Hood teaches the commands for optimizing satellite safety and collision avoidance manipulate a right panel connector, connecting a satellite body to a right panel and a left panel connector, connecting a satellite body to a left panel (Jacomb-Hood: [Column 3, Lines 29-34] and [Column 8, Lines 38-62]).
Schmitt, Kaplan, and Jacomb-Hood are considered to be analogous to the claim invention because they are in the same field of satellite control. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Schmitt and Kaplan to incorporate the teachings of Jacomb-Hood to control the left- and right-side panel for optimizing satellite safety and collision avoidance because it provides the benefit of controlling the satellite to change positions and avoid collisions with detected objects.
24. Regarding Claim 16, Schmitt and Kaplan remains as applied above in Claim 15.
Schmitt and Kaplan fail to explicitly teach the reinforcement learning software program processing the signals of the neural network, controlling the left side panel and right panel asynchronously.
However, in the same field of endeavor, Jacomb-Hood teaches the reinforcement learning software program processing the signals of the neural network, controlling the left side panel and right panel asynchronously (Jacomb-Hood: [Column 8, Lines 38-62]).
Schmitt, Kaplan, and Jacomb-Hood are considered to be analogous to the claim invention because they are in the same field of satellite control. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Schmitt and Kaplan to incorporate the teachings of Jacomb-Hood to control the left- and right-side panel asynchronously because it provides the benefit of controlling the satellite to change positions and avoid collisions with detected objects.
25. Regarding Claim 17, Schmitt and Kaplan remains as applied above in Claim 15.
Schmitt and Kaplan fail to explicitly teach the reinforcement learning software program processing the signals of the neural network, controlling the left side panel and right panel concurrently.
However, in the same field of endeavor, Jacomb-Hood teaches the reinforcement learning software program processing the signals of the neural network, controlling the left side panel and right panel concurrently (Jacomb-Hood: [Column 8, Lines 38-62]).
Schmitt, Kaplan, and Jacomb-Hood are considered to be analogous to the claim invention because they are in the same field of satellite control. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Schmitt and Kaplan to incorporate the teachings of Jacomb-Hood to control the left- and right-side panel concurrently because it provides the benefit of controlling the satellite to change positions and avoid collisions with detected objects.
26. Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Schmitt (US 20190279375 A1), in view of Kaplan (US 20180346153 A1), and in further view of Geist (US 11586497 B1).
27. Regarding Claim 18, Schmitt and Kaplan remains as applied above in Claim 15.
Schmitt and Kaplan fail to explicitly teach the on-board processor is a radiation hardened FGPA.
However, in the same field of endeavor, Geist teaches the on-board processor is a radiation hardened FGPA (Geist: [Column 3, Lines 35-40] and [Column 5, Lines 33-36]).
Schmitt, Kaplan, and Geist are considered to be analogous to the claim invention because they are in the same field of satellite control. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Schmitt and Kaplan to incorporate the teachings of Geist for the on-board processor to be a radiation hardened FGPA because it provides the benefit of mitigating radiation to increase the health span of the processors on the satellite.
Conclusion
28. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Gigleux (US 20220390605 A1)
29. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL T SILVA whose telephone number is (571)272-6506. The examiner can normally be reached Mon-Tues: 7AM - 4:30PM ET; Wed-Thurs: 7AM-6PM ET; Fri: OFF.
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/MICHAEL T SILVA/Examiner, Art Unit 3663
/ANGELA Y ORTIZ/Supervisory Patent Examiner, Art Unit 3663