CTNF 19/085,740 CTNF 80309 DETAILED ACTION This is the First Office Action on the Merits and is directed towards claims 1-20 as originally presented and filed on 03/20/2025. This application is currently subject to a Double Patent rejection with the parent application as expounded upon more fully below. Notice of Pre-AIA or AIA Status Priority is claimed as set forth below, accordingly the earliest effective filing date is April 27, 2022 (20220427). 07-03-aia AIA 15-10-aia The present application, effectively filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Priority This application is a continuation application of U.S. application no. 18/072,982, filed on December 1, 2022, now U.S. Patent 12,287,647. (“Parent Application”) which claims priority under 35 U.S.C. 119(e) to United States Provisional Patent Application Serial No. 63/335,433, filed April 27, 2022. See MPEP §201.07[R-08.2017]. In accordance with MPEP §609.02 [R-07.2015] Section A. 2 and MPEP §2001.06(b)[R-08.2017] (last paragraph), the Examiner has reviewed and considered the prior art cited in the Parent Application. Also in accordance with MPEP §2001.06(b) [R-08.2017] (last paragraph), all documents cited or considered ‘of record’ in the Parent Application are now considered cited or ‘of record’ in this application. Additionally, Applicant(s) are reminded that a listing of the information cited or ‘of record’ in the Parent Application need not be resubmitted in this application unless Applicants desire the information to be printed on a patent issuing from this application. See MPEP §609.02 [R- 07.2015] Section A. 2. Finally, Applicants are reminded that the prosecution history of the Parent Application is relevant in this application. See e.g., Microsoft Corp. v. Multi-Tech Sys., Inc. , 357 F.3d 1340, 1350, 69 USPQ2d 1815, 1823 (Fed. Cir. 2004) (holding that statements made in prosecution of one patent are relevant to the scope of all sibling patents). Information Disclosure Statement As required by M.P.E.P. 609 [R-07.2022], Applicant's 03/20/2025 and 10/13/2025 submission(s) of Information Disclosure Statement (IDS)(s) is/are acknowledged by the Examiner and the reference(s) cited therein has/have been considered in the examination of the claim(s) now pending. A copy of the submitted IDS(s) initialed and dated by the Examiner is/are attached to the instant Office action. Specification 07-29 AIA The disclosure is objected to because of the following informalities: para [0001] should be updated to reflect the issuance of the parent application . Appropriate correction is required. Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 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. 07-07-aia AIA 07-07 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 – 07-08-aia AIA (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. 07-15-aia AIA Claim(s) 1, 6, 8, 10, 11, 14-17 and 19 is/are rejected under 35 U.S.C. 102 (a)(1) as being clearly anticipated by US 20230221721 A1 to Konno; Ryuhei . Regarding claim 1 Konno teaches in for example the Figure(s) reproduced immediately below: PNG media_image1.png 325 680 media_image1.png Greyscale PNG media_image2.png 472 713 media_image2.png Greyscale PNG media_image3.png 403 416 media_image3.png Greyscale PNG media_image4.png 479 610 media_image4.png Greyscale PNG media_image5.png 425 382 media_image5.png Greyscale PNG media_image6.png 543 784 media_image6.png Greyscale PNG media_image7.png 456 482 media_image7.png Greyscale and associated descriptive texts an apparatus of an autonomous drone (in Fig. 16, i.e. UAV, Fig. 4 item 406 “housing 406 of the UAV” and para: “[0003] Unmanned autonomous vehicles, otherwise known as drones, are known in the art. For consumer use these vehicles are of a size that allows them to be portable and be remotely controlled by a control device. In some instances, these vehicles can be controlled by a dedicated remote control device. In other instances, these vehicles may be controlled by a personal computing device such as a smartphone whereby a user ca control the position and movement of the vehicle by interacting with the screen of the smartphone such that the movement of the drone follows a path defined by the finger of the user as it moves across the screen of the smartphone. These vehicles are also known to include image capturing devices that can be controllable to capture images during flight. However, there is difficulty in controlling an operating these vehicles while attempting to capture images during flight”) comprising: a processor (in Fig. 16 above); and a memory (in Fig. 16 above) storing instructions that, when executed by the processor, configure the processor to perform operations comprising: capturing an image using an image capturing device of the autonomous drone (in Fig.16 via “camera” as explained in for example only para: “[0040 ] U pon capture of the one or more images from the preset distance and transmission of the captured images to the control device, the UAV may be preprogrammed to return to a rest position. This may occur by the UAV capturing and storing images from its initial launch position until the point where the UAV reached the preset distance and designating these images as flight path images. The UAV can, upon return to the rest position capture images as it begins to move back to the rest position by comparing newly captured flight images to the stored flight images to control the one or more propulsion devices to return to the rest position . “); processing the image to identify an object (in Fig. 2A step S202, wherein it is understood that the object in the template is identified as a “human face” as explained in para: “[0041] Turning now to FIGS. 2 A- 2 C, a more detailed description of the operations performed in step S 113 of FIG. 1 B will now be described. FIG. 2 A details an exemplary algorithm for performing the operation of moving to the preset location of S 113 in FIG. 1 A. In S 201 , after the UAV has launched from a rest position, a determination is made by the UAV of a size of an object being detected by the image capture apparatus during flight from the rest position. The determined size of the object is based on the selection of the one or more image elements defining the preset distance to which the UAV is expected to fly from the object or subject. The size determined by the preset distance will be used by the circuitry of the UAV to select an image capture template stored in a memory thereof. In one embodiment, the image capture template includes a representative object to be captured such as a human face and an associated size of the object. During the size determination in S 201 , the image capture device continually captures images and detects one or more objects in the captured images and, once an object that matches the object in the template is identified , the UAV is controls the one or more propulsion devices of the UAV to move such that a sized of the detected object matches a size of the object/template as set forth in the selected image capture template. In one embodiment, the memory of UAV stores a plurality of templates each corresponding to an expected size of an object according to the preset distance that is selectable at the control device. In another embodiment, the memory of the UAV stores a single image capture template representing the object to be captured and, in response to the identification information that is received from the control device, performs a scaling operation on the image capture template to create, in real-time, modified image capture templates having a larger scale of the identification information indicates that the preset distance is closer than a preset distance associated with the stored image capture template or smaller scale if the present distance associated with the stored image capture template is larger than the preset distance associated with the image capture template. In another embodiment, in addition to templates that are pre-stored in memory of the UAV, the control application executing on the control device may include a template maker function whereby a user can use an image capture device of the control device to capture an image of the object to be captured by the UAV. For example, the template maker function allows a user to capture an image of themselves or of another person nearby or of a pet such that the UAV can fly to the predetermined distance and capture new images from the preset perspective. In another embodiment, a user may select one or more objects within the user-captured image to be the desired object on which the UAV is to focus for the image capture operation in S 114 of FIG. 1 A.”); navigating the autonomous drone based on a first type of navigation for a period of time, wherein the first type of navigation is based on a position of the autonomous drone relative to the object (in Fig. 2A step S203-S204 the first type of navigation is based on the images from the camera that take place for the period of time that it takes to reach the “determined size” as explained in for example only paragraphs: “[0039] In S111, the UAV receives the control signal generated by the control device which includes the one or more commands for controlling the UAV. UAV parses the control signal to determine the identification information therefrom that will be used to by the circuitry to control operation of the one or more propulsion devices of the UAV. The circuitry of the UAV will use the identification information to initiate the one or more propulsion devices to launch from a rest position one a surface in S112. The rest position may be any surface that supports the UAV when it is not flying such as the ground or in a hand of a user. Upon launch, the UAV is caused to move into a position based on the identification information contained in the control signal such that the UAV can control the image capture device to capture one or more images of the object at the preset distance selected by the user. The manner in which the UAV moves into position includes tracking of the object upon launch in S112 and will be discussed hereinafter with respect to FIGS. 2A-2C. In S114, upon determination by the UAV that the object are at the predetermined distance based on the identification information in the control signal received from the control device, the image capture device is caused to capture one or more images of the object and transmit the captured one or more images back to the control device and display on the operation terminal in S115. It should be understood that the operation in S114 detailing the capturing of images may include capture one or more still images of the object as well as capturing a series of continuous images as video. In yet another embodiment, the image capture device of the UAV used to capture the one or more images includes an audio capture device which can simultaneously capture images and sound from the object which is encoded into a an audio-visual data that is then transmitted back to the control device for output using the display screen of the control device and a speaker of the control device. [0043] Upon determining the size of the object in S 201 , during flight, the image capture device of the UAV is controlled to operate the one or more propulsion devices to move and hover while continually capturing images and perform object detection on the captured images to detect the object to be captured. Object detection is based on one or more features of objects in the determined template. For example, if the object in the template is a human face, there are certain features that are stored in the template representing aspects of the face such as eyes, nose, mouth, face size etc. The UAV performs real-time comparison of a live-view of the image being captured by the image capture device such that it is determined that the one or more features of the object from the template are present in the live view image being captured by the image capture device. The live view of this image is transmitted back to the control device and displayed in the viewer section of the GUI on the operation panel allowing the user to visualize what is being captured in real-time. [0044] In S 203 , the one or more propulsion devices are controlled such that the UAV is caused to fly away from the launch point in order to reach the pre-set distance defined by the identification information in the control signal generated by the control device. The power applied to the one or more propulsion devices is, in part, determined based on the object being detected in S 202 such that focus on the object is maintained. In one embodiment, if there are more than one object in the captured image, a user may select one or more of the objects/subjects from within the viewer section on the GUI of the operation panel. In another embodiment, the object can be pre-selected if there are multiple objects/subjects within the captured image frame. For example, if the captured image from contains three human faces, the focus may be automatically placed on the human face closest to the middle of the frame.”); and navigating the autonomous drone based on a second type of navigation after the period of time (such as based on an acceptable image in for example Fig. 10A and 10B steps S1002-S1004 as explained in for example, only paragraphs: “[0045] While the object is being continually in S203, the UAV executes a size determination algorithm to determine of a size of the detected object in the captured image meets a predetermined object size contained in the image capture template. This operation is continually performed, in real-time, until the result of the determination indicates that the size of the detected object matches the object size in the template at which point the UAV is controlled to maintain a current position (e.g. hover) such that image capture operation can be performed. Further detail of the operations in FIG. 2 A are illustrated in FIG. 2 B and include the respective steps to which the description applies. [0057] FIG. 10 A depicts a control algorithm for image capture processing performed in S 114 in FIG. 1 B and an illustration of the movement of the UAV in order to perform the image capture operation described in FIG. 10 A. In S 1001 , a determination is made as to whether the UAV has reached the designated position based on the identification information that identifies a distance from an object to be imaged. This determination is continually performed until that position is reached. A live view of the image is analyzed in S1002. The analysis in S1002 is one or more image analysis algorithms to detect objects other than the target object to be imaged and to also detect one or more features of the images. In S1003, a determination is made as to whether the image features analyzed in S1002 indicate that the image is acceptable. If the determination is negative, the one or more propulsion devices of the UAV are controlled to move the UAV in an attempt to obtain a better image. This movement may cause the UAV to move in any direction so long as the distance as prescribed by the original distance selection by the user is maintained. As such, the UAV may move left and/or right in a circumferential path so that the features of the live view image being analyzed are acceptable at which point the shutter is released in S1005 . An example of the feature analysis will be described with respect to image brightness and contrast. As shown in FIG. 10B, if the UAV reaches a predetermined position to capture the object but the sun is behind the object, the image will be too bright and there will be a high degree of contrast . In S 1002 , the live view image being captured is analyzed to detect the features of brightness and contrast. If the result of the image analysis indicates that brightness level and contrast level exceed predetermined levels, either individual thresholds for each feature or a composite threshold based on both features, the determination in S 1003 is that the image would be unacceptable and the UAV needs to move directionally . In one embodiment, the directionality of the light captured in the live view image can be analyzed in order to predict a movement direction for the UAV to move in S1004 such that the live view image being captured is acceptable based on the features being analyzed. In another embodiment, the image analysis performed in S1002 analyzed object other than the target object. In the instance shown here, the image analysis detects that the sun is in the image frame. The movement in S1004 causes the UAV to move directionally until such a time that the detected other object (e.g. the sun) is no longer in the live view image frame so that the shutter can be released and the still image captured for transmission to the control device .”). Regarding claim 6 and the limitation the apparatus of claim 1 wherein navigating the autonomous drone based on the first type of navigation further comprises: navigating the autonomous drone relative to the object to one or more waypoints (see Figure 1A wherein given the BRI it is understood that the “preset position 1-3” connote one or more waypoints. See also Fig. 2C positions 1-3). Regarding claim 6 and the limitation the apparatus of claim 1 wherein the object is a person or a face (see paras: [0041] “ the template maker function allows a user to capture an image of themselves or of another person nearby” and [0043] “Object detection is based on one or more features of objects in the determined template. For example, if the object in the template is a human face , there are certain features that are stored in the template representing aspects of the face such as eyes, nose, mouth, face size etc. “. Regarding claim 8 and the limitation the apparatus of claim 1 wherein the operations further comprise: determining a height above a ground based on sensor data, and wherein the navigating the autonomous drone based on the first type of navigation is further based on the height above the ground ( as explained in for example, para: “[0048] FIG. 4 depicts a further embodiment for controlling the operation of the UAV to capture an image from a preset distance from a user. In this embodiment, the image capture device is moveable such that an angle of the image capture device can be changed. Shown herein, the image capture device 402 is connected to the housing 406 of the UAV by a connection member 404 . The image capture device 402 can be moved by the connection member to pivot in a vertical direction to change an angle of the image capture device relative to a surface. In another embodiment, the image capture device 402 may selectively pivot about the connection member 404 to change the angle of the image capture device relative to the surface. The ability of the image capture device 402 to move and change angles is used to control an altitude of the UAV during the image capture operation. In one embodiment, a user manually positions the image capture device in a particular position. In another embodiment, the predetermined distance settings associated with the image elements displayed on the operation panel also include preset camera angle values that, when selected, are interpreted by the UAV to control the position of the image capture device to reach the preset camera angle and, in doing so, causes the flight path of the UAV to be modified such that, once the preset distance from the object is reached, the altitude of the UAV is modified based on the camera angle value associated with the selected setting. For example, if a vertical value of the image capture device is negative, the image capture device is controlled to have an image capture field below an underside of the UAV and in a direction towards the ground. In this instance, an altitude of the UAV is caused to increase above the surface so that the distance between the UAV and the object to be captured reach the selected predetermined distance. In another example, if a vertical value of the image capture device is positive, the image capture device is controlled to have an image capture field above a top side of the UAV and in a direction towards away ground. In this instance, an altitude of the UAV is caused to decrease so that the UAV moves closer to the surface so that the distance between the UAV and the object to be captured reach the selected predetermined distance. In other embodiments, the angle of the image capture device may be user-defined using input via the GUI on the operation panel and the altitude of the UAV is controlled based on the real-time movement of the image capture device via the operation panel. Examples of image capture device angles are further illustrated in FIG. 7 .”). Regarding claim 14 and the limitation the apparatus of claim 1 wherein the navigating the autonomous drone based on the first type of navigation is based on identifying the object in subsequent images captured by the image capturing device and orienting the autonomous drone in space relative to the object (see Figs. 1B-2C and the explanations above of with regard to especially steps S203 and S204 “NO” return to S203). Regarding claim 15 and the limitation the apparatus of claim 14 wherein the operations further comprise: processing a second image to determine one or more additional objects, and wherein the navigating the autonomous drone based on the first type of navigation is further based on the one or more additional objects (it is understood that the user selecting one or more objects within the “user captured image” connotes processing a second image as claimed an explained in for example, only para [0041]: “ the template maker function allows a user to capture an image of themselves or of another person nearby or of a pet such that the UAV can fly to the predetermined distance and capture new images from the preset perspective. In another embodiment, a user may select one or more objects within the user-captured image to be the desired object on which the UAV is to focus for the image capture operation in S114 of FIG. 1A .”). Regarding claim 16 and the limitation the apparatus of claim 1 wherein the image is a first image and wherein the navigating the autonomous drone based on the first type of navigation further comprises: navigating to a first waypoint based on a first position of the object determined from the first image (see Fig. 1A Preset position 1 and Figs. 2A-C steps S202-S204 “No”); capturing a second image (see Fig. 1A Preset position 2 and Figs. 2A-C steps S202-S204 “No”); navigating to a second waypoint based on a second position of the object determined from the second image (see Fig. 1A Preset position 3 and Figs. 2A-C steps S202-S204 “No”);; and capturing a third image (see Fig. 1A Preset position 2 and Figs. 2A-C steps S202-S204 “YES” and Fig. 10A and B step S1005);. Regarding claim 17 and the limitation a method performed on an apparatus of an autonomous drone, the method comprising: capturing an image using an image capturing device of the autonomous drone; processing the image to identify an object; navigating the autonomous drone based on a first type of navigation for a period of time, wherein the first type of navigation is based on a position of the autonomous drone relative to the object; and navigating the autonomous drone based on a second type of navigation after the period of time (see the rejection of corresponding parts of claim 1 above incorporated herein by reference and especially see the figures reproduced above.). Regarding claim 19 and the limitation a non-transitory computer-readable storage medium, the non-transitory computer- readable storage medium including instructions that, when executed by at least one processor of an apparatus of an autonomous drone, cause the at least one processor to perform operations (in para [0065] “) comprising: capturing an image using an image capturing device of the autonomous drone; processing the image to identify an object; navigating the autonomous drone based on a first type of navigation for a period of time, wherein the first type of navigation is based on a position of the autonomous drone relative to the object; and navigating the autonomous drone based on a second type of navigation after the period of time (see the rejection of corresponding parts of claim 1 above incorporated herein by reference.) . Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA 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. 07-23-aia AIA 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. 07-20-02-aia AIA This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention. 07-21-aia AIA Claim s 1-12 and 14-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20180046187 A1 to Martirosyan; Hayk et al. (Martirosyan) in view of US 20180348764 A1 to Zhang; Tong et al. (Zhang) . Regarding claim 1 Martirosyan teaches in for example the Figure(s) reproduced immediately below: PNG media_image8.png 626 494 media_image8.png Greyscale PNG media_image9.png 578 503 media_image9.png Greyscale PNG media_image10.png 598 634 media_image10.png Greyscale PNG media_image11.png 534 701 media_image11.png Greyscale PNG media_image12.png 607 471 media_image12.png Greyscale PNG media_image13.png 512 437 media_image13.png Greyscale PNG media_image14.png 506 656 media_image14.png Greyscale PNG media_image15.png 617 482 media_image15.png Greyscale PNG media_image16.png 450 517 media_image16.png Greyscale and associated descriptive texts an apparatus of an autonomous drone comprising: at least one processor (as shown in the figures above and especially figures 1, 13 and 14 given the Broadest Reasonable Interpretation (BRI) a Person of Ordinary Skill In The Art (POSITA) would understand the claimed limitations connote an apparatus “system 1300” of an autonomous drone connotes “UAV 100” and at least one processor(s) connotes item 1312 as explained in for example only paras: “[0092] UAV system 1300 is only one example of a system that may be part of a UAV 100 . A UAV 100 may include more or fewer components than shown in system 1300, may combine two or more components as functional units, or a may have a different configuration or arrangement of the components. Some of the various components of system 1300 shown in FIG. 13 may be implemented in hardware, software or a combination of both hardware and software, including one or more signal processing and/or application specific integrated circuits. Also, UAV 100 may include an off-the-shelf UAV (e.g. a currently available remote controlled quadcopter) coupled with a modular add-on device (for example one including components within outline 1390 ) to perform the innovative functions described in this disclosure. [0095] Memory 1316 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid-state memory devices. Access to memory 1316 by other components of system 1300, such as the processors 1312 and the peripherals interface 1310 , may be controlled by the memory controller 1314 .”) ; and at least one memory storing instructions that, when executed by the at least one processor, configure the at least one processor to perform operations comprising (see para [0095] above and memory 1316): navigating the autonomous drone based on a first type of navigation for a period of time (given the BRI a first type of navigation connotes inter alia using a GPS and that discussed in for example paras: “[0026] As mentioned earlier, a relative position and/or orientation of the UAV 100 , a relative position and/or orientation of the subject 102 , and/or a relative position and/or pose of a mobile device 104 operated by a user may be determined using one or more of the subsystems illustrated in FIG. 2. For example, using only the GPS system 202 , a position on the globe may be determined for any device comprising a GPS receiver (e.g. the UAV 100 and/or the mobile device 104 ). While GPS by itself in certain implementations may provide highly accurate global positioning it is generally is not capable of providing accurate information regarding orientation. Instead a technique of multiple inputs and multiple outputs (“MIMO”) (as illustrated in FIG. 2) may be used for localization, potentially in conjunction with other localization subsystems. [0027] Consider the example based on the illustration in FIG. 2; a user (human subject 102 ) is utilizing an autonomous UAV 100 via a mobile device 104 to film herself overhead. In order navigate the UAV 100 and inform the tracking by an image capture device of the subject 102 (in this case the user), a relative position and orientation of the UAV 100 relative to the mobile device 104 (or any other point of reference) may be necessary. [0028] According to the present teachings a relative position between the UAV 100 and the mobile device 104 may be determined using a GPS system to determine a global position of the UAV 100 , a global position of the mobile device 104 and compare the two. [0029] Similarly, using an array of cellular and or/Wi-fi antennae, a position relative to the known locations of antennae may be determined for both the UAV 100 and mobile device 104 using known positioning techniques. Some known positioning techniques include those based on signal trilateration, for example round trip time of arrival (RTT) in which a signal is sent and received by a signal transceiver and distance is calculated based on the elapsed time, received signal strength (RSS) in which the power levels of the transmitted signal and the received signals are analyzed and a distance determined based on a known propagation loss. Other known positioning techniques include those based on signal triangulation, for example angle of arrival (AoA) in which angles of arriving signals are determined and through applied geometry a position determined. Current Wi-Fi standards, such as 802.11ac, allow for RF signal beamforming (i.e. directional signal transmission using phased-shifted antenna arrays) from transmitting Wi-Fi routers. Beamforming may be accomplished through the transmission of RF signals at different phases from spatially distributed antennas (a “phased antenna array”) such that constructive interference may occur at certain angles while destructive interference may occur at others, thereby resulting in a targeted directional RF signal field. Such a targeted field is illustrated conceptually in FIG. 2 by dotted lines 212 emanating from WiFi routers 210.”); capturing images using an image capturing device during the period of time (see Fig. 6 and para: “[0043] According to some embodiments, UAV 100 may comprise multiple high resolution image capture devices 602 (e.g. cameras) with spatial offsets from each other, thereby providing the capability to capture an unobstructed view of the physical environment surrounding UAV 100 . In some embodiments, image capture devices 602 may be arranged to provide a full 360 degree view around UAV 100 , as illustrated in FIG. 6. However, a full 360 degree view may not be necessary in all embodiments. In some embodiments, the image capture devices 602 may be arranged such that at least two cameras are provided with overlapping fields of view, thereby allowing for stereoscopic (i.e. 3D) image/video capture and depth recovery (e.g. through computer vision algorithms) at multiple angles around UAV 100 . For example, FIG. 6 shows a high-level illustration of the concept of multiple image capture devices 602 mounted to UAV 100 with overlapping fields of view as represented by the dotted lines. FIG. 6 is provided to illustrate the concept, but does not indicate a particular configuration or geometry as a limitation. According to some embodiments, a UAV in accordance with the present teachings may include more or fewer image capture devices 602 . For example, in some embodiments, the individual fields of view of any given image capture device may be expanded through the use of a “fisheye” lens, thereby reducing the total number of image capture devices needed to provide a 360 degree view around UAV 100 .”); processing the images to generate structural information of a real-world environment depicted in the images (see para: “[0072] In some embodiments, a criterion may be specified to keep the subject in view while avoiding a collision with another object in the physical environment. FIG. 9 shows an example scenario involving a UAV 100 in flight over a physical environment 920 and capturing images of a human subject 102 . As shown in FIG. 9, UAV 100 may be in autonomous flight along a current planned flight path 904 to maneuver to avoid a collision with another object 930 in the physical environment while keeping human subject 102 in view (as indicated by field of view lines 910 . The example illustrated in FIG. 9 is idealized and shows a relatively large stationary object 930 (for example a building or other structure), but the same concepts may apply to avoid smaller mobile objects such as a bird in flight. As shown in FIG. 9, based on the estimated motions of UAV 100 and subject 102 , a system in accordance with the present teachings may generate control commands to dynamically adjust image capture includes by generating control commands to maneuver UAV 100 along flight path 904 to avoid object 930 while keeping human subject in view (as indicated by field of view lines 910 ). Notably, this illustrates that the addition of another constraint to the specified criterion (i.e. avoiding a collision) narrows the number of possible flight paths UAV 100 can take while still satisfying the specified criterion. For example, because the human subject 102 is moving to the right of object 930 and based on the characteristics of object 930 , in order to keep human subject 102 in view, UAV 100 must also maneuver to the right of object 930 . Any of the previously described localization techniques may be utilized to detect the presence of the object 930 with relation to human subject 102 and/or UAV 100 and to generate control commands configured to cause UAV 100 to avoid a collision with object 930 . For example, in some embodiments, based in part on images captured by an array of image capture devices mounted to UAV 100 and using a process of visual inertial odometry, the geometry and position/orientation of object 930 relative to UAV 100 may be determined. ”); and navigating the autonomous drone based on a second type of navigation after the period of time the second type of navigation being based on the structural information (given the BRI the second type of navigation connotes SLAM as shown in for example Fig. 9 and paras: “[0074] As with FIG. 9, the example illustrated in FIG. 10 is idealized and shows a relatively simple stationary object 1030 (for example a building or other structure). In this example, a specified criterion to avoid collision with the object may produce the same or similar results as a specified criterion to keep the view unobstructed. In other words, in both situations, UAV 100 may maintain a maximum separation distance while maneuvering to both avoid a collision with an object and keep the view unobstructed. However, consider an example with an object having more complex features such as a tree with sparse canopy cover. Here, if a criterion is specified to keep the subject in view while avoiding contact with the tree, a system in accordance with the present teachings may generate control commands configured to cause UAV 100 to fly over the tree while tracking the human subject 102 walking under the tree. Collision is avoided and because the canopy is sparse, the subject 102 remains in view. However, this will still result in poor image capture because the view of the subject 102 will be obstructed by intermittent leaves. Instead, if a criterion is specified to keep the view of the subject unobstructed, the system may instead generate control commands configured to cause UAV 100 to rapidly reduce its altitude to drop below the canopy of the tree and to continue to track human subject 102 . In such an example, UAV 100 may increase its altitude again once human subject 102 has emerged from under the canopy of the tree. [0075] As previously discussed, in some embodiments, the estimated motion of UAV 100 and subject 102 may be based in part on localization data relative to a computer-generated 3D map. For example if a pre-generated 3D map of the surrounding physical environment is available, the motions of UAV 100 and/or subject 102 relative to the 3D map may be estimated using any of the previously described localization techniques. Alternatively, if a pre-generated 3D map is not available, systems in accordance with the present teachings may continually generate and update a 3D map of the physical environment while the UAV 100 is in flight through the environment through a process sometimes referred to as SLAM (simultaneous localization and mapping). Again, as previously discussed, such a 3D map may be generated using a process of visual inertial odometry based in part on images captured by an image capture device associated with UAV 100. ”). Although the claims are interpreted in light of the specification, limitations from the specification are NOT imported into the claims. The Examiner must give the claim language the Broadest Reasonable Interpretation (BRI) the claims allow. See MPEP 2111.01 Plain Meaning [R-10.2024], which states II. IT IS IMPROPER TO IMPORT CLAIM LIMITATIONS FROM THE SPECIFICATION " Though understanding the claim language may be aided by explanations contained in the written description, it is important not to import into a claim limitations that are not part of the claim . For example, a particular embodiment appearing in the written description may not be read into a claim when the claim language is broader than the embodiment." Superguide Corp. v. DirecTV Enterprises, Inc., 358 F.3d 870, 875, 69 USPQ2d 1865, 1868 (Fed. Cir. 2004). See also Liebel-Flarsheim Co. v. Medrad Inc., 358 F.3d 898, 906, 69 USPQ2d 1801, 1807 (Fed. Cir. 2004) (discussing recent cases wherein the court expressly rejected the contention that if a patent describes only a single embodiment, the claims of the patent must be construed as being limited to that embodiment); E-Pass Techs., Inc. v. 3Com Corp., 343 F.3d 1364, 1369, 67 USPQ2d 1947, 1950 (Fed. Cir. 2003) ("Inter US-20100280751-A1 1pretation of descriptive statements in a patent’s written description is a difficult task, as an inherent tension exists as to whether a statement is a clear lexicographic definition or a description of a preferred embodiment. The problem is to interpret claims ‘in view of the specification’ without unnecessarily importing limitations from the specification into the claims."); Altiris Inc. v. Symantec Corp., 318 F.3d 1363, 1371, 65 USPQ2d 1865, 1869-70 (Fed. Cir. 2003) (Although the specification discussed only a single embodiment, the court held that it was improper to read a specific order of steps into method claims where, as a matter of logic or grammar, the language of the method claims did not impose a specific order on the performance of the method steps, and the specification did not directly or implicitly require a particular order). See also subsection IV., below. When an element is claimed using language falling under the scope of 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112 , 6th paragraph (often broadly referred to as means- (or step-) plus- function language), the specification must be consulted to determine the structure, material, or acts corresponding to the function recited in the claim, and the claimed element is construed as limited to the corresponding structure, material, or acts described in the specification and equivalents thereof. In re Donaldson, 16 F.3d 1189, 29 USPQ2d 1845 (Fed. Cir. 1994) (see MPEP § 2181 - MPEP § 2186 ). In Zletz, supra, the examiner and the Board had interpreted claims reading "normally solid polypropylene" and "normally solid polypropylene having a crystalline polypropylene content" as being limited to "normally solid linear high homopolymers of propylene which have a crystalline polypropylene content." The court ruled that limitations, not present in the claims, were improperly imported from the specification. See also In re Marosi, 710 F.2d 799, 802, 218 USPQ 289, 292 (Fed. Cir. 1983) ("'[C]laims are not to be read in a vacuum, and limitations therein are to be interpreted in light of the specification in giving them their ‘broadest reasonable interpretation.'" (quoting In re Okuzawa, 537 F.2d 545, 548, 190 USPQ 464, 466 (CCPA 1976)). The court looked to the specification to construe "essentially free of alkali metal" as including unavoidable levels of impurities but no more.).” Martirosyan does not appear to expressly disclose navigating the autonomous drone based on a first type of navigation for a period of time. In analogous art Zhang teaches in for example, the figures below: PNG media_image17.png 718 589 media_image17.png Greyscale PNG media_image18.png 534 477 media_image18.png Greyscale PNG media_image19.png 783 434 media_image19.png Greyscale PNG media_image20.png 685 596 media_image20.png Greyscale PNG media_image21.png 608 598 media_image21.png Greyscale And associated descriptive texts navigating the autonomous drone based on a first type of navigation for a period of time (given the BRI a first type of navigation connotes the take-off or release and hover procedure as set forth in paras: “[0104] In one aspect of the present invention, take-off of the aerial system 12 is managed using a release and hover procedure (see below). [0105] After the aerial system 12 is released and hovering, the owner or specific user must be recognized. In one aspect of the present invention only commands or instructions from the owner or specific user are followed. In another aspect of the present invention, commands from any user within the field of view of the at least one camera may be followed. [0106] To identify the owned, the aerial system 12 , once aloft, may automatically spin 360 degrees slowly to search for its owner 18 . Alternatively, the aerial system 12 can wait still for the owner 18 to show up in the field of view. This may be set in the default settings. Once the owner 18 is found, an exemplary default action for the drone system 12 is to automatically adjust its own position and orientation to aim the owner at the center of the camera field of view with a preferred distance (by yawing and/or moving in forward/backward direction). In one preferred embodiment, after the owner 18 or any person is recognized as the target, the aerial system 12 can then start tracking the target and scan for gesture commands. [0134] Detecting a flight event 100 S 10 functions to detect an imminent operation event 110 S 10 requiring or otherwise associated with aerial system flight. The imminent operation event 110 S 10 can be freefall (e.g., aerial system motion along a first axis parallel a gravity vector), imminent freefall, aerial system arrangement in a predetermined orientation (e.g., arrangement with a major aerial system plane within a predetermined range from perpendicular to a gravity vector for a predetermined amount of time, such as 0.5 s), manual support of the aerial system 12 in mid-air (e.g., based on the acceleration patterns, rotation patterns, vibration patterns, temperature patterns, etc.), or be any other suitable imminent operation event. 100 S 10 preferably includes detecting a change in a sensor signal associated with imminent operation. The change is preferably detected by the processing system 22 based on signals received from the on-board sensors 36 , 44 (e.g., orientation sensors), but can alternatively be detected by the remote computing system (e.g., wherein the sensor signals are transmitted to the remote computing system), or detected by any other suitable system. The predetermined change can be set by a manufacturer, received from the client running on the remote computing system, received from a user 18 , or otherwise determined. [0154] The method can optionally include monitoring sensor signals associated with aerial system altitude and determining the lift mechanism operation parameters based on the altitude. In one variation, this can function to select lift mechanism operation parameters to regain an initial aerial system altitude (e.g., compensate for any altitude losses due to freefall prior to recovery). The altitude can be determined based on signals sampled by an altimeter, and/or a relative altitude can be determined based on image analysis, range finding (e.g., using a vertically-oriented rangefinder to determine distance to the ground, floor, and/or ceiling). The altimeter signals (and/or other altitude data) that are considered in determining the lift mechanism operation parameters can be altimeter signals acquired concurrently with the sensor signals for the first axis, before the imminent operation change is detected, after the imminent operation change is detected (e.g., in response to change detection), or at any other suitable time. For example, the method can include determining the initial aerial system altitude within a predetermined time window from imminent operation event detection (e.g., prior to imminent operation event detection, based on altimeter measurements recorded prior to imminent operation event detection), spooling up the rotors to hover the aerial system immediately after imminent operation event detection, and increasing the rotor speed until the aerial system reaches the initial aerial system altitude after the aerial system 12 is stabilized. However, the altimeter signals (and/or other altitude data) can be used in any other suitable manner.”). It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the hand control disclosed in Zhang with the UAV control taught in Martirosyan with a reasonable expectation of success because it would have “improved the flying time of the UAV” as taught by Zhang Para(s): “[0003] Traditional user interface for operating a drone is not user friendly. When a user wants to take a photo or video with a drone equipped with a camera, a dedicated remote controller or a cell phone is used to wirelessly control and maneuver the drone. And it takes a significant amount of effort for the user to position the drone to a desired location and camera view angle before a photo or video can be captured. The battery time is not long for small/medium size drones, typically in the range of 5-20 mins. The longer it takes to position the drone, the less time it leaves for the user to actually use the drone to capture photos and videos. So it is beneficial to have an intuitive, easy-to-use and reliable drone selfie interaction such that the drone can be placed to a desired location as quickly as possible and that most of the flying time of the drone camera can be saved and utilized for its most important functionality: taking photos and video”. Regarding claim 2 and the limitation the apparatus of claim 1, wherein the operations further comprise: capturing an image using an image capturing device of the apparatus of the autonomous drone; processing the image to identify an objec t (see Martirosyan Para: “[0035] According to some embodiments, an image capture device of UAV 100 may be a single camera (i.e. a non-stereoscopic camera). Here, computer vision algorithms may identify the presence of an object and identify the object as belonging to a known type with particular dimensions. In such embodiments, an object may be identified by comparing the captured image to stored two-dimensional (2D) and/or three dimensional (3D) appearance models. For example, through computer vision, the subject 102 may be identified as an adult male human. In some embodiments the 2D and/or 3D appearance models may be represented as a trained neural network that utilizes deep learning to classify objects in images according to detected patterns With this recognition data, as well as other position and/or orientation data for the UAV 100 (e.g. data from GPS, WiFi, Cellular, and/or IMU, as discussed above), UAV 100 may estimate a relative position and/or orientation of the subject 102 .”), wherein the first type of navigation is based on a position of the autonomous drone relative to the object (given the BRI connotes Martirosyan fig. 3 and para: “[0030] As illustrated in FIG. 3, a UAV 100 and/or mobile device 104 may include a phased array of WiFi antenna and a relative position and/or pose may be calculated without the necessity for external existing Wi-Fi routers. According to some embodiments, the UAV 100 and/or mobile device 104 may transmit and/or receive a beamformed RF signal via a phased antenna array. The UAV 100 and/or mobile device 104 may then detect the phase differences and power levels of the respective incoming signals and calculate an AoA for the incoming signals. For example according to FIG. 3, the mobile device 104 may determine an AoA of θ 1 for the RF signals 302 transmitted by the UAV 100 . Similarly the UAV 100 may determine an AoA of θ 2 for the RF signals 304 transmitted by the mobile device 104 . This AoA information may then be incorporated with information gathered by an IMU on the UAV 100 and/or mobile device 104 (as well as other positioning data as described earlier) in order to infer a relative position and/or orientation between the UAV 100 and the mobile device 104 .”). Regarding claim 3 and the limitation the apparatus of claim 1, wherein the period of time is based on a time to generate the structural information (given the BRI see Martirosyan fig. 5A and para: “[0036] According to some embodiments, computer vision may be used along with measurements from an IMU (or accelerometer(s) or gyroscope(s)) within the UAV 100 and/or mobile device 104 carried by a user (e.g. human subject 102) as illustrated in FIG. 5A-5B. FIG. 5A shows a simplified diagram that illustrates how sensor data gathered by an IMU at a mobile device 104 may be applied to sensor data gathered by an image capture device at UAV 100 to determine position and/or orientation data of a physical object (e.g. a user 102). Outline 550 represents the 2-dimensional image captured field of view at UAV 100. As shown in FIG. 5A, the field of view includes the image of a physical object (here user 102) moving from one position to another. From its vantage point, UAV 100 may determine a distance A traveled across the image capture field of view. The mobile device 104, carried by user 102, may determine an actual distance B traveled by the user 102 based on measurements by internal sensors (e.g. the IMU) and an elapsed time. The UAV 100 may then receive the sensor data and/or the distance B calculation from mobile device 104 (e.g., via wireless RF signal). Correlating the difference between the observed distance A and the received distance B, UAV 100 may determine a distance D between UAV 100 and the physical object (user 102). With the calculated distance as well as other position and/or orientation data for the UAV 100 (e.g. data from GPS, WiFi, Cellular, and/or IMU, as discussed above) a relative position and/or orientation may be determined between the UAV 100 and the physical object (e.g. user 102).”). Regarding claim 4 and the limitation the apparatus of claim 1, wherein the second type of navigation is based on one or more of: visual inertial odometry (see Martirosyan para [0072]), optical flow (see Martirosyan para [0072]),, or Simultaneous Localization and Mapping (SLAM) (see Martirosyan para: “[0075] As previously discussed, in some embodiments, the estimated motion of UAV 100 and subject 102 may be based in part on localization data relative to a computer-generated 3D map. For example if a pre-generated 3D map of the surrounding physical environment is available, the motions of UAV 100 and/or subject 102 relative to the 3D map may be estimated using any of the previously described localization techniques. Alternatively, if a pre-generated 3D map is not available, systems in accordance with the present teachings may continually generate and update a 3D map of the physical environment while the UAV 100 is in flight through the environment through a process sometimes referred to as SLAM (simultaneous localization and mapping). Again, as previously discussed, such a 3D map may be generated using a process of visual inertial odometry based in part on images captured by an image capture device associated with UAV 100 .”). Regarding claim 5 and the limitation the apparatus of claim 1, wherein the second type of navigation is simultaneous localization and mapping (see Martirosyan para [0075] above). Regarding claim 6 and the limitation the apparatus of claim 1, wherein navigating the autonomous drone based on the first type of navigation further comprises: navigating the autonomous drone relative to an object to one or more waypoints (given the BRI connotes Martirosyan Fig. 9 above and para [0072]). Regarding claim 7 and the limitation the apparatus of claim 6, wherein the object is a person or a face (see Martirosyan “human subject 102”) . Regarding claim 8 and the limitation the apparatus of claim 1, wherein the operations further comprise: determining a height above a ground based on sensor data, and wherein the navigating the autonomous drone based on the first type of navigation is further based on the height above the ground (see Martirosyan para: “[0071] Given the idealized physical environment 820 illustrated in FIG. 8A and assuming that the only specified criterion is to keep the human subject 102 in view, the system generating the control commands may have multiple options for dynamically adjusting image capture by the UAV 100 to meet the specified criterion. For example control commands may be generated that cause UAV 100 to simply follow human subject 102 at a constant distance (or at least within a maximum separation distance) while maintaining a constant altitude (or at least above a minimum altitude). Alternatively, control commands may be generated that cause UAV 100 to fly past human subject 102 while an image capture device configured for active tracking (e.g. using a hybrid mechanical-digital gimbal) is adjusted to keeps the subject 102 in the field of view 810 , as illustrated in FIG. 8A. As will be described, the specified one or more criteria may include further constraints.”). Regarding claim 9 and the limitation the apparatus of claim 1, wherein the image capturing device is a first image capturing device, wherein the first image capturing device is mounted horizontally relative to an axis of propellers of the autonomous drone, and a second image capturing device is mounted vertically relative to the axis of the propellers and is directed downward, and wherein the operations further comprise: capturing at least one image in the first type of navigation using the first image capturing device; and processing the at least one image to identify an object, wherein the first type of navigation is based on a position of the autonomous drone relative to the objec t ( see Martirosyan paras: “[0048] Instead a UAV 100 , according to some embodiments, may include a hybrid approach comprising mechanical gimbals providing freedom of motion along one or more axes along with real-time image processing (herein referred to as a “digital gimbal”). For example, a single axis mechanical gimbal capable of adjusting the orientation of an image capture device in conjunction with the yaw control of the UAV 100 and digital image processing may produce a full range or image capture from looking straight down from the UAV 100 to the ground to looking straight up from the UAV 100 to the sky while minimizing the mechanical complexity of the stabilization system. [0106] UAV system 1300 may also include one or more image capture devices 1334 . FIG. 13 shows an image capture device 1334 coupled to a image capture controller 1332 in I/O subsystem 1360 . The image capture device 1334 may include one or more optical sensors. For example, image capture device 1334 may include a charge-coupled device (CCD) or complementary metal-oxide semiconductor (CMOS) phototransistors. The optical sensors of image capture device 1334 receive light from the environment, projected through one or more lens (the combination of an optical sensor and lens can be referred to as a “camera”) and converts the light to data representing an image. In conjunction with an imaging module located in memory 1316 , the image capture device 1334 may capture images (including still images and/or video). In some embodiments, an image capture device 1334 may include a single fixed camera. In other embodiments, an image capture device 13340 may include a single adjustable camera (adjustable using a gimbal mechanism with one or more axes of motion). In some embodiments, an image capture device 1334 may include a camera with a wide-angle lens providing a wider field of view. In some embodiments, an image capture device 1334 may include an array of multiple cameras providing up to a full 360 degree view in all directions. In some embodiments, an image capture device 1334 may include two or more cameras (of any type as described herein) placed next to each other in order to provide stereoscopic vision. In some embodiments, an image capture device 1334 may include multiple cameras of any combination as described above. For example, UAV 100 may include four sets of two cameras each positioned so as to provide a stereoscopic view at multiple angles around the UAV 100 . In some embodiments, a UAV 100 may include some cameras dedicated for image capture of a subject and other cameras dedicated for image capture for navigation (e.g. through visual inertial odometry).”). Regarding claim 10 the combination of Martirosyan teaches wherein the operations further comprise: after the processing the at least one image to identify the object, taking off from a hand (in the obviousness to combine and the rejection of corresponding parts of claim 1 above incorporated herein by reference, see especially Zhang figures 16 and 17). Regarding claim 11 and the limitation the apparatus of claim 9, wherein the operations further comprise: determining a distance of the autonomous drone from the object (see the obviousness to combine and the teachings of both references and also especially Zhang paras: “[0167] In a second embodiment, the control instruction is a landing instruction including a landing area, and 100 S 16 can include automatically generating a flight path to the landing area, generating lift mechanism operation instructions to follow the generated flight path, and executing the instructions. This can function to automatically land the lift mechanism 40 . The flight path can be generated based on the intervening physical volume between the aerial system 12 and the landing area (e.g., as determined based on visual and/or image processing of images recorded by a front facing or downward facing camera), be a predetermined flight path, or otherwise determined. In one example, determining the flight path and/or lift mechanism operation instructions includes: determining the distance between the aerial system and the landing area (e.g., based on LIDAR, the relative size of a reference object or point within the field of view, etc.), and determining a rotor spool down rate based on the instantaneous rotor speed, the standby rotor speed, and the distance. In a second example, determining the flight path and/or lift mechanism operation instructions includes tracking the landing area (e.g., to track flight progress toward the landing area, to track the current position of a moving landing area, etc.) and automatically controlling the aerial system 12 to land on the landing area. However, the lift mechanism operation instructions can be otherwise generated. [0168] In a first specific example, in which the landing area is an open hand, 100 S 16 includes automatically controlling the aerial system 12 to land on the open hand (e.g., operating the lift mechanism 40 , such as by reducing the rotor speeds, to slowly lower the aerial system 12 onto the open hand) in response to detecting the open hand. In a second specific example, in which the landing area is a “ready-to-grab” hand, 100 S 16 includes automatically controlling the aerial system 12 to fly proximal the hand (e.g., within reach of the hand, in contact with the hand, within a threshold distance of the hand, such as 1 in, 3 in, or 1 foot, etc.) in response to detecting the hand (e.g., immediately after detecting the hand, a period of time after detecting the hand, before detecting a standby event 100 S 18 and/or operating in a standby mode 100 S 20 , etc.). However, the aerial system 12 can be operated according to the control instruction 100 S 16 in any suitable manner.“). Regarding claim 12 and the limitation the apparatus of claim 11, wherein the determining is based on a number of pixels of an image sensor the object occupies in the captured image and an estimated size of the object (see the teachings of Martirosyan Fig. 5A and paras [0036-39]). Regarding claim 14 and the limitation the apparatus of claim 1, wherein the operations further comprise: capturing at least one image using an image capturing device of the apparatus of the autonomous drone; processing the at least one image to identify an object, wherein the navigating the autonomous drone based on the first type of navigation is based on identifying the object in subsequent images captured by the image capturing device and orienting the autonomous drone in space relative to the object (given the BRI see the obviousness to combine and the rejection of corresponding parts of claim 1 above incorporated herein by reference and especially the “hover state” explained in for example Zhang paras: “[0122] In a first step 90S10, the user may release the aerial system 12 and the aerial system 12 takes off and begins to hover. In a second step 90S12, the aerial system 12 enters a hover idle state during which the aerial system 12 may begin to search for a target or any user (based on default settings). [0132] The method can additionally function to automatically fly the aerial system 12 , independent of control instruction receipt. In a first variation, the aerial system automatically hovers (e.g., in place) when the aerial system 12 is released (e.g., from a user's hand). In a second variation, the aerial system automatically flies along a force application vector, stops, and hovers in response to the aerial system 12 being thrown or pushed along the force application vector. In a third variation, the aerial system 12 can automatically take off from a user's hand. However, the method can otherwise fly the aerial system 12 .”). Regarding claim 15 and the limitation the apparatus of claim 14, wherein the operations further comprise: processing a second image to determine one or more additional objects, and wherein the navigating the autonomous drone based on the first type of navigation is further based on the one or more additional objects (see the obviousness to combine and the rejection of corresponding parts of claims 14 and 1 above incorporated herein by reference wherein given the BRI a POSITA would understand that when both references are before them they explicitly teach avoiding obstacles while keeping the user in frame while recording video and or taking pictures). Regarding claim 16 and the limitation the apparatus of claim 1, wherein the navigating the autonomous drone based on the first type of navigation further comprises: capturing a first image using an image capturing device of the apparatus of the autonomous drone; processing the first image to identify an object, navigating to a first waypoint based on a first position of the object determined from the first image; capturing a second image; and navigating to a second waypoint based on a second position of the object determined from the second image (see the obviousness to combine and the rejection of corresponding parts of claims 14 and 1 above incorporated herein by reference wherein given the BRI a POSITA would understand that when both references are before them they explicitly teach avoiding obstacles while keeping the user in frame while recording video and or taking pictures. See especially Martirosyan Fig. 9 ). Regarding claim 17 and the limitation a method performed on an apparatus of an autonomous drone, the method comprising: navigating the autonomous drone based on a first type of navigation for a period of time; capturing images using an image capturing device during the period of time; processing the images to generate structural information of a real-world environment depicted in the images; and navigating the autonomous drone based on a second type of navigation after the period of time the second type of navigation being based on the structural information (see the obviousness to combine and the rejection of corresponding parts of claim 1 above incorporated herein by reference). Regarding claim 18 and the limitation the method of claim 17, further comprising: capturing an image using an image capturing device of the apparatus of the autonomous drone; processing the image to identify an object, wherein the first type of navigation is based on a position of the autonomous drone relative to the objec t (see the obviousness to combine and the rejection of corresponding parts of claims 2 and 1 above incorporated herein by reference). Regarding claim 19 and the limitation a non-transitory computer-readable storage medium, the non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of an apparatus of an autonomous drone, cause the at least one processor to perform operations comprising: navigating the autonomous drone based on a first type of navigation for a period of time; capturing images using an image capturing device during the period of time; processing the images to generate structural information of a real-world environment depicted in the images; and navigating the autonomous drone based on a second type of navigation after the period of time the second type of navigation being based on the structural information (see the obviousness to combine and the rejection of corresponding parts of claim 1 above incorporated herein by reference and especially para: “[0091] FIG. 13 shows a diagram of an example UAV system 1300 including various functional system components that may be part of a UAV 100, according to some embodiments. UAV system 1300 may include one or more means for propulsion (e.g. rotors 1302 and motor(s) 1304), one or more electronic speed controllers 1306, a flight controller 1308, a peripheral interface 1310, a processor(s) 1312, a memory controller 1314, a memory 1316 (which may include one or more computer readable storage mediums), a power module 1318, a GPS module 1320, a communications interface 1322, an audio circuitry 1324, an accelerometer 1326 (including subcomponents such as gyroscopes), an inertial measurement unit (IMU) 1328, a proximity sensor 1330, an optical sensor controller 1332 and associated optical sensor(s) 1334, a mobile device interface controller 1336 with associated interface device(s) 1338, and any other input controllers 1340 and input device 1342, for example display controllers with associated display device(s). These components may communicate over one or more communication buses or signal lines as represented by the arrows in FIG. 13. As mentioned earlier, piloting input may be provided wirelessly by a user 102 on the ground or in another vehicle via remote control or portable multi-function device 104.”). Regarding claim 20 and the limitation t he non-transitory computer-readable storage medium of claim 19, further comprising: capturing an image using an image capturing device of the apparatus of the autonomous drone; processing the image to identify an object, wherein the first type of navigation is based on a position of the autonomous drone relative to the object (see the obviousness to combine and the rejection of corresponding parts of claims 2 and 1 above incorporated herein by reference) . 07-21-aia AIA Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over US 20230221721 A1 to Konno; Ryuhei as applied claim 1 above in view of US 20180321676 A1 to Matuszeski; Thaddeus Benjamin et al. (Matuszeski) . Regarding claim 13 Konno teaches in for example the rejection of corresponding parts of claim 1 above incorporated herein by reference the limitations the apparatus of claim 1 wherein the operations further comprise: hovering at a constant location relative to the object (in Fig. 2A step S205 “Stay at the position”). Konno does not appear to expressly disclose determining a windspeed based on an electrical power applied to electrical motors that operate propellers of the autonomous drone; and in response to determining the windspeed is above a threshold value, landing the autonomous drone. In the analogous art of autonomous drone landing in response to windspeed, Matuszeski teaches hovering at a constant location, determining a windspeed based on an electrical power applied to electrical motors that operate propellers of the autonomous drone (in para: “[0071] A processor of the UAV 100 may continuously calculate the energy required to return to and land 1212 on the launch location 1202 . The processor may also continuously calculate the energy required to perform a land now 1214 operation at its current location. If the processor determines that the UAV 100 has just enough battery to return and land 1212, the processor may cause the UAV to abort the present mission and return and land 1212 at its launch location 1202. In one embodiment, the need to return and land 1212 may occur if there are high winds and the UAV is using more energy than anticipated to fly through its flight path 1204. The user 402 may also command the UAV 100 to return and land 1212 via the controller 104 by using two or more activators, such as selecting a tab, pressing or holding a lock button, and sliding a button in a slider. The user 402 may enact a return and land 1212 command via the controller 104 if the user 402 detects a fault, wants the UAV 100 to land, observes a negative change in the weather such as thunderstorms, etc. The return and land 1212 command returns the UAV 100 to its launching location 1202 for landing, with no damage to the UAV 100 or objects in the surrounding area. In some embodiments, the UAV 100 may enact an automated return and land 1212 if it detects a fault or error that does not carry a risk of returning to the launch location 1202, such as a malfunction or obscuration of a visual sensor used to gather data 1210.”); and in response to determining the windspeed is above a threshold value, landing the autonomous drone ( in for example, only para: “[0070] Once the UAV is in flight, the user 402 may send one or more flight termination commands 1208 to the UAV 100 via the controller 104 . The UAV 100 may send data 1210 to the controller 104 during flight. The UAV data may include sensed information, UAV status, any errors or faults, time to land, sensor status, location of the UAV, etc. In one embodiment, the UAV 100 may determine a wind speed and/or direction by launching vertically, hovering, and calculating a wind speed and/or direction based on the movement of the UAV 100 relative to the ground 1203 and/or launch location 1202 while hovering . The UAV 100 may use this calculated wind speed and/or direction to determine an optimized flight path 1204 and/or determine a time to land. In one embodiment, the UAV may send a signal to the controller indicating that based on the UAV processor calculations, the current flight path may not be achievable and accordingly, request that a user at the controller initiate a land now or return and land action .”) It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the windspeed detection and land action disclosed in Matuszeski with the navigation methods of the drone taught in Konno with a reasonable expectation of success because it would have ensured that the drone would have enough battery power to be able to safely land when high winds are determined as taught by Matuszeski Paras [0070-71] above . 07-21-aia AIA Claim s 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20180046187 A1 to Martirosyan; Hayk et al. (Martirosyan) in view of US 20180348764 A1 to Zhang; Tong et al. (Zhang) as applied to the claims above and further in view of US 20180321676 A1 to Matuszeski; Thaddeus Benjamin et al. (Matuszeski) . Regarding claim 13 the combination of Martirosyan teaches in for example the rejection of corresponding parts of claim 1 above incorporated herein by reference the limitations the apparatus of claim 1 wherein the operations further comprise: hovering at a constant location relative to the object (in Zhang hover ). The combination of Martirosyan does not appear to expressly disclose determining a windspeed based on an electrical power applied to electrical motors that operate propellers of the autonomous drone; and in response to determining the windspeed is above a threshold value, landing the autonomous drone. In the analogous art of autonomous drone landing in response to windspeed, Matuszeski teaches hovering at a constant location, determining a windspeed based on an electrical power applied to electrical motors that operate propellers of the autonomous drone (in para: “[0071] A processor of the UAV 100 may continuously calculate the energy required to return to and land 1212 on the launch location 1202 . The processor may also continuously calculate the energy required to perform a land now 1214 operation at its current location. If the processor determines that the UAV 100 has just enough battery to return and land 1212, the processor may cause the UAV to abort the present mission and return and land 1212 at its launch location 1202. In one embodiment, the need to return and land 1212 may occur if there are high winds and the UAV is using more energy than anticipated to fly through its flight path 1204. The user 402 may also command the UAV 100 to return and land 1212 via the controller 104 by using two or more activators, such as selecting a tab, pressing or holding a lock button, and sliding a button in a slider. The user 402 may enact a return and land 1212 command via the controller 104 if the user 402 detects a fault, wants the UAV 100 to land, observes a negative change in the weather such as thunderstorms, etc. The return and land 1212 command returns the UAV 100 to its launching location 1202 for landing, with no damage to the UAV 100 or objects in the surrounding area. In some embodiments, the UAV 100 may enact an automated return and land 1212 if it detects a fault or error that does not carry a risk of returning to the launch location 1202, such as a malfunction or obscuration of a visual sensor used to gather data 1210.”); and in response to determining the windspeed is above a threshold value, landing the autonomous drone ( in for example, only para: “[0070] Once the UAV is in flight, the user 402 may send one or more flight termination commands 1208 to the UAV 100 via the controller 104 . The UAV 100 may send data 1210 to the controller 104 during flight. The UAV data may include sensed information, UAV status, any errors or faults, time to land, sensor status, location of the UAV, etc. In one embodiment, the UAV 100 may determine a wind speed and/or direction by launching vertically, hovering, and calculating a wind speed and/or direction based on the movement of the UAV 100 relative to the ground 1203 and/or launch location 1202 while hovering . The UAV 100 may use this calculated wind speed and/or direction to determine an optimized flight path 1204 and/or determine a time to land. In one embodiment, the UAV may send a signal to the controller indicating that based on the UAV processor calculations, the current flight path may not be achievable and accordingly, request that a user at the controller initiate a land now or return and land action .”) It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the windspeed detection and land action disclosed in Matuszeski with the navigation methods of the drone taught in The combination of Martirosyan with a reasonable expectation of success because it would have ensured that the drone would have enough battery power to be able to safely land when high winds are determined as taught by Matuszeski Paras [0070-71] above . Double Patenting 08-33 AIA The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg , 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman , 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi , 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum , 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel , 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington , 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13. The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA/25, or PTO/AIA/26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer. Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 16 and 19 of U.S. Patent No. 12,287,647. Although the claims at issue are not identical, they are not patentably distinct from each other as shown by the side by side comparison below. Those claims not specifically recited are rejected for depending from a rejected base claims. CLAIM OF INSTANT APPLCATION CLAIM OF U.S. Patent No. 12,287,647. 1. An apparatus of an autonomous drone comprising: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, configure the at least one processor to perform operations comprising: navigating the autonomous drone based on a first type of navigation for a period of time; capturing images using an image capturing device during the period of time; processing the images to generate structural information of a real-world environment depicted in the images; and navigating the autonomous drone based on a second type of navigation after the period of time the second type of navigation being based on the structural information. 1. An apparatus of an autonomous drone comprising: at least one processor; and a memory storing instructions that, when executed by the at least one processor, configure the at least one processor to perform operations comprising: capturing an image using an image capturing device of the autonomous drone; processing the image to identify an object; navigating the autonomous drone based on a first type of navigation for a period of time, wherein the first type of navigation is based on a position of the autonomous drone relative to the object; capturing images using the image capturing device during the period of time; processing the images to generate structural information of a real-world environment depicted in the images; and navigating the autonomous drone based on a second type of navigation after the period of time, the period of time being based on a time to generate the structural information, and the second type of navigation being based on the structural information. 17. A method performed on an apparatus of an autonomous drone, the method comprising: navigating the autonomous drone based on a first type of navigation for a period of time; capturing images using an image capturing device during the period of time; processing the images to generate structural information of a real-world environment depicted in the images; and navigating the autonomous drone based on a second type of navigation after the period of time the second type of navigation being based on the structural information. 16. A method performed on an apparatus of an autonomous drone, the method comprising: capturing an image using an image capturing device of the autonomous drone; processing the image to identify an object; navigating the autonomous drone based on a first type of navigation for a period of time, wherein the first type of navigation is based on a position of the autonomous drone relative to the object; capturing images using the image capturing device during the period of time; processing the images to generate structural information of a real-world environment depicted in the images; and navigating the autonomous drone based on a second type of navigation after the period of time, the period of time being based on a time to generate the structural information, and the second type of navigation being based on the structural information. 19. A non-transitory computer-readable storage medium, the non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of an apparatus of an autonomous drone, cause the at least one processor to perform operations comprising: navigating the autonomous drone based on a first type of navigation for a period of time; capturing images using an image capturing device during the period of time; processing the images to generate structural information of a real-world environment depicted in the images; and navigating the autonomous drone based on a second type of navigation after the period of time the second type of navigation being based on the structural information. 19. A non-transitory computer-readable storage medium, the non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of an apparatus of an autonomous drone, cause the at least one processor to perform operations comprising: capturing an image using an image capturing device of the autonomous drone; processing the image to identify an object; navigating the autonomous drone based on a first type of navigation for a period of time, wherein the first type of navigation is based on a position of the autonomous drone relative to the object; capturing images using the image capturing device during the period of time; processing the images to generate structural information of a real-world environment depicted in the images; and navigating the autonomous drone based on a second type of navigation after the period of time, the period of time being based on a time to generate the structural information, and the second type of navigation being based on the structural information. Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure as teaching, inter alia, the state of the art at the time of the invention. For example: CN 109843720 A to ELANE, O et al. teaches, inter alia an unmanned aerial vehicle and a control system for unmanned aerial vehicle that takes off from a user’s hand in for example the ABSTRACT, Figures and/or Paragraphs below: “Embodiments of the present invention relate to an unmanned aerial vehicle (UAV), the unmanned aerial vehicle is small enough for the user so as to store it in the clothes pocket, purse or hand bag thereof. The UAV is also lightweight and safe to allow the user holding it in the hand outward to takeoff and landing. Additional embodiments of the invention relates to a multifunctional image capture of the UAV. in the flying process, the flap 106 is configured to extend channel exhaust form the thrust vector effect. for example, the first UAV100 can be altered by channel 101 of air flow in vertical rise is changed only. may indicate that one or more actuators 105 to their corresponding flap 106 into channel air flow to obtain the airflow through the channel 101 of the change by the microprocessor. In some embodiments of the invention, microprocessor instruction attributable to direct input from a user or due to an inertial measurement unit (IMU), an optical flow sensor, any other sensor or combinations thereof of the sensor reading.”. US 20190248487 A1 to Holtz; Kristen Marie et al. teaches, inter alia AERIAL VEHICLE SMART LANDING that can land on a user’s hand in for example the ABSTRACT, Figures and/or Paragraphs below: “A technique is introduced for autonomous landing by an aerial vehicle. In some embodiments, the introduced technique includes processing a sensor data such as images captured by onboard cameras to generate a ground map comprising multiple cells. A suitable footprint, comprising a subset of the multiple cells in the ground map that satisfy one or more landing criteria, is selected and control commands are generated to cause the aerial vehicle to autonomously land on an area corresponding to the footprint. In some embodiments, the introduced technique involves a geometric smart landing process to select a relatively flat area on the ground for landing. In some embodiments, the introduced technique involves a semantic smart landing process where semantic information regarding detected objects is incorporated into the ground map. [0109] In an example edge case, the UAV 100 may detect an obstruction to a planned path for takeoff (e.g., from the ground or the user's hand) by checking a planned trajectory for takeoff against an obstacle map (e.g., a voxel-based occupancy map). In response to detecting the potential for obstructed takeoff, the system may cause a warning regarding the obstruction to be presented to the user via the mobile device 104 . The system may further be configured to restrict takeoff until the detected obstruction is no longer there.”. Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL LAWSON GREENE JR whose telephone number is (571)272-6876. The examiner can normally be reached on MON-THUR 7-5:30PM (EST) or via email at DanielL.GreeneJr@USPTO.GOV under the guidance of MPEP Section 502.03 Communications via Internet Electronic Mail (email) [R-07.2022]. The written authorization may be found at https://www.uspto.gov/patents/apply/forms and submitted via EFS-Web, mail, or fax. The Examiner’s Fax number is 571-273-6876. Examiner interviews are available via telephone 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, Hunter Lonsberry can be reached on (571) 272-7298. 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 http://pair-direct.uspto.gov. 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. /DANIEL L GREENE/Primary Examiner, Art Unit 3665 20260613 Application/Control Number: 19/085,740 Page 2 Art Unit: 3665 Application/Control Number: 19/085,740 Page 3 Art Unit: 3665
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