CTNF 18/825,534 CTNF 96531 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. 07-30-03-h AIA Claim Interpretation 07-30-03 AIA The following is a quotation of 35 U.S.C. 112(f): (f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph: An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. 07-30-05 The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked. As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph: (A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function; (B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and (C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function. Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function. Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function. Claim limitations in this application that use the word “means” (or “step”), see claims 15, 17-20 , are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. Claim Rejections - 35 USC § 102 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 Claim s 1-3, 5-10, 12-17, 19-20 are rejected under 35 U.S.C. 102( a)(1 ) as being anticipated by Buerkle et al . (US 20200225622, hereafter Buerkle) . Regarding claim 1 , Buerkle (‘622) discloses that An apparatus {Fig.1; Fig.2; [0042] lines 1 (Fig.1), 3-7 (vehicle 100 may include one or more processors 102 , one or more image acquisition devices 104 , one or more position sensors 106 , one or more speed sensors 108 , one or more radar sensors 110 , and / or one or more LIDAR sensors 112 .)} comprising : at least one radar sensor { Fig.1 item 110 (radar); Fig.2 item 110 (radar); [0042] line 6 (one or more radar sensors 110)}; at least one camera { Fig.1 item 104 (image acquisition devices); Fig.2 item 104 (image acquisition devices); [0044] lines 5-6 (one or more image acquisition devices 104 ( e.g. , one or more cameras)}; at least one memory { Fig.2 item 202 (memory); [0044] lines 11-12 (safety system 200 may further include one or more memories 202 )}; and at least one processor communicatively coupled to the at least one memory, the at least one radar sensor, and the at least one camera { Fig.1 item 102 (processor); Fig.2 items 102 (processor), 104 (image acquisition devices), 110 (radar), 202 (memory), 214, 216, 218 (processor); [0044] lines 4-6 (the safety system 200 may include one or more processors 102, one or more image acquisition devices 104 ( e.g. , one or more cameras)), 9 (one or more radar sensors 110), 11-12 (safety system 200 may further include one or more memories 202 ); [0045] lines 1-3 (the one or more processors 102 may include an application processor 214 , an image processor 216 , a communication processor 218)}, and configured to: obtain radar measurement data from the at least one radar sensor { Fig.2 items 110, 102, 214, 216, 218; [0052] lines 11-17 (The radar sensors 110 and / or the LIDAR sensors 112 may be configured to provide pre - processed sensor data , The third data interface may couple, the one or more radar sensors 110 and the one or more LIDAR sensors 112 to at least one of the one or more processors 102)}; obtain camera-derived data based on at least one image obtained by the at least one camera { Fig.2 items 104 (image acquisition devices), 102, 214, 216, 218; [0046] lines 6-8 (to transmit image data acquired by the one or more image acquisition devices 104 to the one or more processors 102 ( e.g. , to the image processor 216 ).)}; and determine a dynamic occupancy grid based on the radar measurement data and the camera-derived data {Fig.2 items 104 (image acquisition devices), 110 (radar); Fig.5 item 502a-n (sensor 1, sensor N), 506 (grid 1 creation), 508 (Grid N creation); Fig.10; Fig.12 item 1206 (Determining from sensor data a probability of whether a region relative to the ego vehicle corresponding to the cell and the selected cell size is occupied 1206); [0016] (Fig.10, modification of the occupancy grid); [0038] lines 5-6 (An input set may include sensor data , such as image data , radar data , LIDAR data); [0041] lines 1-3 (groupings of occupancy grid ( static or dynamic ) cells are referred to as sections or regions of cells .); [0044] lines 5-6 (one or more image acquisition devices 104 ( e.g. , one or more cameras), 9 (one or more radar sensors 110); [0058] lines 10-11 (An occupancy grid may be employed to represent a dynamic environment around the vehicle); [0064] line 6 (dynamically reconfigure the non - uniform grid)}. Regarding claim 2 , which depends on claim 1 , Buerkle (‘622) discloses that in the apparatus, the camera-derived data comprise (1) free space data , or (2) optical flow data {[0044] lines 5-6 (one or more image acquisition devices 104 ( e.g. , one or more cameras); [0050] lines 1-3 from bottom (video inputs for receiving image data from multiple image sensors and may also include video out capabilities); [0101] line 13 (video cameras)}, or (3) occupancy flow data {[0083] lines 1-2 (one or more processors may combine the sensor grids into one common grid 510), 9 (generate an updated dynamic grid representation)} , or (4) depth data {[0053] lines 5-6 (depth information from LIDAR or stereo processing of two or more images)} , or (5) ground hazard data {[0058] lines 1-2 (Occupancy grid mapping commonly uses one or more procedures to generate maps from sensor measurement data), 9-10 (presence or absence of the obstacle at that location in the vehicle's vicinity); [0113] lines 2-3 (the sensor data includes at least one of image sensor data , camera data)} , or a combination of two or more of (1)-(5) {see (2)-(4) above}. Regarding claim 3 , which depends on claim 1 , Buerkle (‘622) discloses that in the apparatus, the apparatus further comprises at least one lidar sensor communicatively coupled to the at least one processor { Fig.2 items 214, 216, 218 (processor) in 102(processor), 112 (lidar); [0042] lines 4 (one or more processors 102), 6-7 (one or more LIDAR sensors 112); [0045] lines 1-3 (the one or more processors 102 may include an application processor 214 , an image processor 216 , a communication processor 218)}, and wherein the at least one processor is configured to determine the dynamic occupancy grid based on lidar data obtained from the at least one lidar sensor { Fig.12 item 1206 (Determining from sensor data a probability of whether a region relative to the ego vehicle corresponding to the cell and the selected cell size is occupied 1206); [0038] lines 5-6 (An input set may include sensor data , such as image data , radar data , LIDAR data); [0058] lines 10-11 (An occupancy grid may be employed to represent a dynamic environment around the vehicle); [0064] line 6 (dynamically reconfigure the non - uniform grid)}. Regarding claim 5 , which depends on claim 1 , Buerkle (‘622) discloses that in the apparatus, the at least one processor is configured to: determine a radar measurement grid based on the radar measurement data {Fig.2 item 110 (radar); [0081] lines 4 (FIG . 5 as sensor one 502a through sensor n 502n), 11-12 (image sensor data ( e.g. one or more cameras , one or more lidar sensors , one or more radar sensors ,); [0082] lines 1-3 (Once the sensor data has been received , the occupancy grid manager may convert the sensor measurements at time t into an input grid 506 and 506.)}; determine at least one camera measurement grid based on the camera-derived data {Fig.2 item 104 ((image acquisition devices); [0044] lines 4-5 (the safety system 200 may include one or more processors 102, one or more image acquisition devices 104 ( e.g. , one or more cameras)); [0081] lines 4 (FIG . 5 as sensor one 502a through sensor n 502n), 11-12 (image sensor data ( e.g. one or more cameras , one or more lidar sensors , one or more radar sensors ,); [0082] lines 1-3 (Once the sensor data has been received , the occupancy grid manager may convert the sensor measurements at time t into an input grid 506 and 506.)}; determine a fused measurement grid based on the radar measurement grid and the at least one camera measurement grid {Fig.2 items 104 ((image acquisition devices), 110 (radar); Fig.5 item 510 (grid fusion); [0081] lines 4 (FIG . 5 as sensor one 502a through sensor n 502n), 11-12 (image sensor data ( e.g. one or more cameras , one or more lidar sensors , one or more radar sensors ,); [0083] lines 1-2 (one or more processors may combine the sensor grids into one common grid 510)}; and determine the dynamic occupancy grid based on the fused measurement grid {[0083] lines 1-2 (one or more processors may combine the sensor grids into one common grid 510), 7-9 (The particle filter may track the dynamic cells in the grid . The particle filter may generate an updated dynamic grid representation)}. Regarding claim 6 , which depends on claims 1 and 5 , Buerkle (‘622) discloses that in the apparatus, the at least one processor is configured to determine a predicted grid, and to determine the fused measurement grid based further on the predicted grid { Fig.5 item 510 (grid fusion); [0083] lines 3-4 (The occupancy grid manager may combine the scan grid 510 with a predicted grid of t - 1) , 12 (carry out any of the actions of the grid fusion 510)}. Regarding claim 7 , which depends on claims 1 and 5-6 , Buerkle (‘622) discloses that in the apparatus, the at least one processor is configured to determine the dynamic occupancy grid based further on a localization input including localization information of the apparatus {Fig.1 item 106 (position sensors); Fig.2 item 106 (position sensors); Fig.3 (ego vehicle, occupied cells); Fig.12 item 1204 (Selecting based on the one or more context factors a cell size for a cell of an occupancy grid comprising a plurality of cells , each cell representing a region relative to a vehicle), 1206 (Determining from sensor data a probability of whether a region relative to the ego vehicle corresponding to the cell and the selected cell size is occupied); [0009] lines 1-2 (Fig.3, a uniform occupancy grid of a non - uniform occupancy grid); [0018] lines 1-2 (Fig.12, method of occupancy grid management); [0042] line 5 (one or more position sensors 106); [0044] lines 6-8 (one or more position sensors 106 ( e.g. , a Global Navigation Satellite System ( GNSS ) , a Global Positioning System ( GPS ))}. Regarding claim 8 , Buerkle (‘622) discloses that A method, for determining a dynamic occupancy grid {[0016] (Fig.10, modification of the occupancy grid); [0018] lines 1-2 (Fig.12, method of occupancy grid management); [0058] lines 10-11 (An occupancy grid may be employed to represent a dynamic environment around the vehicle); [0064] line 6 (dynamically reconfigure the non - uniform grid)}, comprising: obtaining radar measurement data from at least one radar sensor of an apparatus; obtaining camera-derived data based on at least one image obtained by at least one camera of the apparatus; and determining the dynamic occupancy grid based on the radar measurement data and the camera-derived data. {The claim limitations above are the same or substantially the same scope as the corresponding claim limitations in claim 1 . Therefore the claim limitations above are rejected in the same or substantially the same manner as in claim 1 . See the rejections of claim 1 }. Regarding claims 9-10, 12-14 , Applicant recites claim limitations of the same or substantially the same scope as that of claims 2-3, 5-7 , respectively. Accordingly, claims 9-10, 12-14 are rejected in the same or substantially the same manner as claims 2-3, 5-7 , respectively, shown above. Regarding claim 15 , Buerkle (‘622) discloses that An apparatus {Fig.1; Fig.2; [0042] lines 1 (Fig.1), 3-7 (vehicle 100 may include one or more processors 102 , one or more image acquisition devices 104 , one or more position sensors 106 , one or more speed sensors 108 , one or more radar sensors 110 , and / or one or more LIDAR sensors 112 .)} comprising: means for obtaining radar measurement data from at least one radar sensor; means for obtaining camera-derived data based on at least one image obtained by at least one camera of the apparatus; and means for determining a dynamic occupancy grid based on the radar measurement data and the camera-derived data. {The claim limitations above are the same or substantially the same scope as the corresponding claim limitations in claim 1 . Therefore the claim limitations above are rejected in the same or substantially the same manner as in claim 1 . See the rejections of claim 1 }. Regarding claims 16-17, 19-20 , Applicant recites claim limitations of the same or substantially the same scope as that of claims 2-3, 5-6 , respectively. Accordingly, claims 16-17, 19-20 are rejected in the same or substantially the same manner as claims 2-3, 5-6 , respectively, shown above . Claim Rejections - 35 USC § 103 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. 07-22-aia AIA Claim s 4, 11, 18 are rejected under 35 U.S.C. 103 as being unpatentable over Buerkle (‘622) as applied to claim s 1, 8, 15 , respectively , above, and further in view of Moawad et al. (US 12174641, hereafter Moawad) and Wang et al . (US 2022/0065657, hereafter Wang) . Regarding claim 4 , which depends on claim 1 , Buerkle (‘622) does not explicitly disclose that “the at least one processor is configured to determine the dynamic occupancy grid based on high-definition map data stored in the at least one memory”. In the same field of endeavor, Moawad (‘641) discloses that in the apparatus, the at least one processor is configured to determine the dynamic occupancy grid based on high-definition map data stored in the at least one memory {Fig.14 item 1002 (HD map), 308 (Radar Occupancy Grid); col.3 lines 8-9 (Fig.14, determining a radar occupancy grid using an HD map); col.15 lines 30-32 (The adjusted polylines 1414 are used to mark corresponding grid cells of the radar occupancy grid 308 as occupied.); Examiner’s note: “adjusted” in Fig.14 item 1414 for “dynamic”}. It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Buerkle (‘622) with the teachings of Moawad (‘641) { determining a radar occupancy grid using an HD map } to determining a radar occupancy grid using an HD map. Doing so would obtain object attributes from HD map (e.g. street signs, overpasses, guard rails, traffic control devices, posts, buildings, k-rails) for polylines determination in determining occupancy grid so that the radar occupancy grid 308 may be generated without necessitating a vehicle driving through the corresponding area, as recognized by Moawad (‘641) { col.12 lines 16-21 (The HD map 1002 contains object attributes 1004 that are determined at 1006 for HD map objects 1008 within the HD map 1002. The HD map objects 1008 may comprise street signs, overpasses, guard rails, traffic control devices, posts, buildings, k-rails, or other semi-permanent objects.); col.15 lines 35-37 (the radar occupancy grid 308 may be generated without necessitating a vehicle driving through the corresponding area)}. However, Moawad (‘641) does not explicitly disclose that (see word with underline) “high-definition map data stored in the at least one memory ”. In the same field of endeavor, Wang (‘657) discloses that high-definition map data stored in the at least one memory { [0091] lines 26-27 (the HD map may be stored to memory ( See FIG . 6 ) .)}. A person of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that applying a known technique (e.g. the HD map may be stored to memory) to a known device (e.g. vehicle) ready for improvement to yield predictable results (e.g. use HD map for localization and mapping) and result in an improved system (e.g. collect data from surrounding environment and process it with aid of HD map so as to generate Simultaneous localization and mapping for a surrounding environment (e.g. occupancy grid) based on information determined from the processed collected data, as recognized by Wang (‘657) {[0003] lines 11-15 (Simultaneous localization and mapping ( SLAM ), a high - definition ( HD ) map, simultaneously tracking the vehicle's autonomous vehicle location within the environment ) ; [0091] lines 5-6 (collect a second set of signals 106 , from said the surrounding environment 101), 12-16 (the second set of signals may be processed by the SAR - based system 100 with aid of the controller 130 to generate the HD map of the surrounding environment 101. Processing the second set of signals may involve using), 18-19 (Occupancy Grid SLAM), 22-25 (generate a map of a surrounding environment based on, may be determined from the second set of signals received by the SAR - based system)}). Regarding claims 11 and 18 , Applicant recites claim limitations of the same or substantially the same scope as that of claim 4 . Accordingly, claims 11 and 18 are rejected in the same or substantially the same manner as claim 4 , shown above . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 2019/0258251 discloses that “ determine a dynamic occupancy grid based on the radar measurement data and the camera-derived data ” { Fig.42 item 3028 (self-calibration (camera, Lidar, radar)) to item 3030 (basic trajectory estimation) to item 3010 (obstacle perception) to item 3102 (dynamic occupancy grid)}, which further support the rejection of claims 1, 8, 15 . US 11,769,052 discloses that “ the camera-derived data comprise (1) free space data {col.2 lines 37-38 (a free-space boundary in the environment using image data generated by one or more cameras of a vehicle)} , or (2) optical flow data {col.45 lines 21-22 (a CNN for object identification and detection using data from camera sensors), 32-38 (focus processing of CNNs and floating point operations on the DLA(s) and leave other functions to the GPU(s) 2108 and/or other accelerator(s) 2114. accelerator(s) 2114, programmable vision accelerator(s) (PVA); col.47 lines 29-30 (the PVA may be used to perform dense optical flow)}, or (3) occupancy flow data col.41 lines 44-48 (Cameras, be used for surround view, providing information used to create and update the occupancy grid, as well as to generate side impact collision warnings) , or (4) depth data {col.41 lines 20-23 (wide-view cameras 2170 on the vehicle 2100. In addition, long-range camera(s) 2198 (e.g., a long-view stereo camera pair) may be used for depth-based object detection)} , or (5) ground hazard data { col.41 lines 44-48 (Cameras, be used for surround view, providing information used to create and update the occupancy grid, as well as to generate side impact collision warnings)} , or a combination of two or more of (1)-(5) { col.41 lines 44-48 (Cameras, be used for surround view, providing information used to create and update the occupancy grid, as well as to generate side impact collision warnings)}, which further support the rejection of claim 2, 9, 16 . Any inquiry concerning this communication or earlier communications from the examiner should be directed to YONGHONG LI whose telephone number is (571)272-5946. The examiner can normally be reached 8:30am - 5:00pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vladimir Magloire can be reached at (571)270-5144. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /YONGHONG LI/ Examiner, Art Unit 3648 Application/Control Number: 18/825,534 Page 2 Art Unit: 3648 Application/Control Number: 18/825,534 Page 3 Art Unit: 3648 Application/Control Number: 18/825,534 Page 4 Art Unit: 3648 Application/Control Number: 18/825,534 Page 5 Art Unit: 3648 Application/Control Number: 18/825,534 Page 6 Art Unit: 3648 Application/Control Number: 18/825,534 Page 7 Art Unit: 3648 Application/Control Number: 18/825,534 Page 8 Art Unit: 3648 Application/Control Number: 18/825,534 Page 9 Art Unit: 3648 Application/Control Number: 18/825,534 Page 10 Art Unit: 3648 Application/Control Number: 18/825,534 Page 11 Art Unit: 3648 Application/Control Number: 18/825,534 Page 12 Art Unit: 3648 Application/Control Number: 18/825,534 Page 13 Art Unit: 3648 Application/Control Number: 18/825,534 Page 14 Art Unit: 3648 Application/Control Number: 18/825,534 Page 15 Art Unit: 3648 Application/Control Number: 18/825,534 Page 16 Art Unit: 3648 Application/Control Number: 18/825,534 Page 17 Art Unit: 3648
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