DETAILED ACTION
Claims 1-18 are considered in this office action. Claims 1-18 are pending examination.
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 .
Response to Arguments
Applicant's arguments filed 03/31/2026 have been fully considered but they are not persuasive. The applicant simply argues that new claim amendments are not being taught by Yeshurun, Gall and Chen. However, upon further search and consideration, the new claim amendments are being taught by Sun (US2019/0227555). Sun clearly discloses using video and audio provided by the drone to control the vehicle in Para [0036] and [0078-0079].
The office thanks the applicant for agreeing to file the terminal disclaimer in view of Double Patenting rejection.
The examiner believes he has responded to all the arguments presented by the applicant at this time. However, if the applicant believes that the examiner has missed any arguments to respond, the applicant is invited to call the examiner directly to expedite the process.
Claim Rejections - 35 USC § 103
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 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.
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 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3-7, 10-13, and 16-18 are rejected under 35 U.S.C. 103 as being unpatentable over Yeshurun (US20180341262A1) in view of Sun et al. (US2019/0227555) and in further view of CN103770736A and herein after will be referred as Yeshurun, Sun and CN736 respectively.
Regarding Claim 1, Yeshurun teaches a self-aware mobile system (Fig.1 #10) comprising:
a vehicle, vessel, or aircraft comprising (Para [0031] “As illustrated in FIG. 1, there is provided a system, which is generally indicated at 10. The system 10 is configured to facilitate active protection of a target such as a vehicle 12, which may be a tank, a personnel carrier, a marine vehicle, an airborne vehicle, etc., from an incoming threat.”):
Sun teaches a plurality of video and audial sensors adapted to obtain information about surroundings of the vehicle, vessel, or aircraft and to transmit video and audial data representing the information about surroundings of the vehicle, vessel, or aircraft and at least one computer system configured to receive data from the plurality of sensors, perform fusion of the received data to generate artificial vision data representing the surroundings of the vehicle, vessel, or aircraft, and to use the artificial vision data to provide autonomous functioning of the vehicle, vessel, or aircraft (Para [0036] and [0078]).
Sun also teaches wherein video data from the video and audial data is provided via an unmanned aircraft system (UAS) drone, wherein the video data is operable to be used as feedback into the at least one computer system allowing decision support for automated guidance and collision avoidance (Para [0078-0079]).
CN736 teaches wherein the at least one computer system is further adapted to provide detection of approaching vehicles, vessels, or aircraft using sound alone by filtering out a sound of wind, a surrounding environment, and an engine (Para [0010-0013]: “During operation, the central processing unit compares the acoustic signals detected by the multiple sound acquisition units in real time. When the sound pressure and/or sound intensity value of the acoustic signal in a certain direction acquired by the sound acquisition unit is higher than the sound pressure and/or sound intensity value in other directions acquired by the sound acquisition unit, it is determined that other vehicles are approaching in that direction; the central processing unit issues an alarm through the in-vehicle warning unit. [0011] Furthermore, considering that the external noise sources of a vehicle during driving, especially at high speeds, mainly consist of engine noise, road noise (tire noise) and wind noise, and that road noise (tire noise) is mainly generated by the tires and is concentrated at the tires, having a relatively independent sound field, it is easier to collect than wind noise and engine noise. Therefore, as a preferred implementation, taking a four-wheeled vehicle (such as a sedan) as an example, the sound acquisition unit shall include at least four sets of microphone modules located near the tires on the front and rear sides of the vehicle. [0012] Furthermore, considering that the collected tire noise inevitably contains other vehicle noises, such as engine noise, vibration noise, and wind noise, which can cause interference, the central processing unit includes a filtering module and a judgment and comparison module. [0013] The filtering module performs filtering processing on the acoustic signal uploaded by the sound acquisition unit.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yeshurun to incorporate the teachings of Sun and CN736 to include autonomous vehicle and autonomous sensors for operating the vehicle in autonomous mode. Doing so would optimize providing security for autonomous vehicles as well as disclosed in Yeshurun.
Similarly Claims 7 and 13 are rejected on the similar rational.
Regarding Claim 4, Yeshurun in view of Sun and in further view of CN736 teach the system of claim 1.
Sun also teaches wherein the generated information representing the surroundings of the vehicle, vessel, or aircraft is displayed to a human operator of the vehicle, vessel, or aircraft to provide automation assistance (0078-0079).
Similarly Claims 10 and 16 are rejected on the similar rational.
Regarding Claim 5, Yeshurun in view of Sun and in further view of CN736 teach the system of claim 4.
Yeshurun teaches wherein the vehicle, vessel, or aircraft is a military or tactical vehicle (Para [0031]: “As illustrated in FIG. 1, there is provided a system, which is generally indicated at 10. The system 10 is configured to facilitate active protection of a target such as a vehicle 12, which may be a tank, a personnel carrier, a marine vehicle, an airborne vehicle, etc., from an incoming threat.”) and the generated information representing the surroundings of the vehicle, vessel, or aircraft is communicated with a human vehicle commander regarding when normal operations of a vehicle escalate into a combat response (Para [0043] : “Alternatively or additionally, one or more of the UAVs 14 may comprise surveillance equipment 20 configured to facilitate detection of an incoming threat. The UAV 14 may be configured to transmit data gathered by the surveillance equipment 20 to the platform controller and/or the UAV controller for further processing (i.e., to identify the type of or specific threat, and/or to identify whether the threat's trajectory, and assess the likelihood of it impacting the vehicle and/or where on the vehicle the impact is likely to occur). The surveillance equipment 20 may comprise one or more of an optical sensor, infrared sensor, a motion sensor, a thermal sensor, and a pulse-Doppler radar. The surveillance equipment 20 may additionally or alternatively comprise any other device which is suitable to facilitate detection of an oncoming threat.”).
Similarly Claims 11 and 17 are rejected on the similar rational.
Regarding Claim 6, Yeshurun in view of Sun and in further view of CN736 teach the system of claim 1.
Sun also teaches wherein the generated information representing the surroundings of the vehicle, vessel, or aircraft is used to provide full automation of the vehicle, vessel, or aircraft (Para [0078-0079]).
Similarly Claims 12 and 18 are rejected on the similar rational.
Regarding Claim 19, Yeshurun in view of Sun and in further view of CN736 teach the system of claim 4.
Sun also teaches wherein the human operator is located remotely from the vehicle, vessel, or aircraft, to provide automation assistance ( Para [0044] Line 3-6).
Claims 2-3, 8-9 and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Yeshurun in view of Sun and in further view of CN736 and in further view of Yangfang (CN102694962A) and herein after will be referred as Yangfang respectively.
Regarding Claim 2, Yeshurun in view of Sun and in further view of CN736 teaches the system of claim 1.
Yeshurun may not expressly teaches further comprising digital signal processing circuitry adapted to filter the video and audial data to reduce noise.
Even though the examiner believes it is well known in the art to use a filter system to reduce the noise in the data for further processing/filtering it for noise reduction for optimized results. However, to avoid arguments from the applicant the examiner is citing a prior art that teaches filtering of data for noise reduction and it goes in detail how it filters the data to reduce noise in the data.
Yangfang teaches comprising digital signal processing circuitry adapted to filter the video and audial data to reduce noise (Para [0040-0046]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yeshurun, Gall and Chen to incorporate the teachings of Yangfang to include filtering of data. Doing so would optimize the result.
Similarly Claims 8 and 14 are rejected on the similar rational.
Regarding Claim 3, Yeshurun in view of Sun and in further view of CN736 and in further view of Yangfang teaches the system of claim 2.
Yeshurun may not expressly teaches wherein the computer system is further adapted to perform machine learning to generate improved tuning parameters for the digital signal processing circuitry adapted to filter the video and audial data.
However, it is well known in the art to use machine learning to generate improved parameters and using this improved parameter for further filtering to reduce the noise in the data would be obvious to ordinary person skilled in the art for optimization of results from the collected data.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Yeshurun, Sun and Yangfang to incorporate the teachings of well-known to include machine learning to generate improved tuning parameters. Doing so would optimize the result.
Similarly Claims 9 and 15 are rejected on the similar rational.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ABDHESH K JHA whose telephone number is (571)272-6218. The examiner can normally be reached M-F:0800-1700.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, James J Lee can be reached on 571-270-5965. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ABDHESH K JHA/Primary Examiner, Art Unit 3668
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