DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This Office Action is in response to the Office Action Response dated September 15, 2026. Claims 1-20 are presently pending and are presented for examination.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on September 15, 2026 is in compliance with the provisions of 37 CFT 1.97. Accordingly, the information disclosure statement has been considered by the examiner.
Response to Arguments
Applicant’s amendments have overcome the Drawing and Specification Objections. Applicant’s arguments are moot in view of new grounds of rejection.
Claim Rejections - 35 USC § 103
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.
Claims 1-5, 7-12 and 14-19 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Publication No. 2018/0364717, to Douillard et al. (hereinafter Douillard), in view of U.S. Patent Publication No. 2021/0082148, to Parkison et al. (hereinafter Parkison).
As per claim 1, and similarly with respect to claims 8 and 15, Douillard discloses a method comprising: retrieving, by a processor, image data of a space around an ego…(e.g. see Fig. 2 and para 0036-0039, wherein a vehicle architecture 200 is provided including a LIDAR module 204,Camera module 206 and Radar module 208 generating data received by a computer system 202); predicting, by the processor, by executing an artificial intelligence model, an occupancy attribute of a plurality of voxels corresponding to the space around the ego (e.g. see paras 0017, 0051, 0056-0058, 0088, 0092-0094, wherein occupancy of voxels are evaluated based upon image data (e.g. at least LIDAR), via annotation module 232 that includes machine learning module (i.e. artificial intelligence)); generating, by the processor, a 3D model corresponding to the space around the ego and each voxel's occupancy attribute (e.g. see Fig. 3, and paras 0060-0070, wherein a 3D representation of each voxel around a vehicle for identifying occupancy); upon receiving a destination, localizing, by the processor, the ego by identifying a current location of the ego using a key image feature within the image data corresponding to the 3D model without receiving a location of the ego from a location tracking sensor (e.g. see paras 0055 and 0098, wherein the vehicle is localized based upon image data corresponding to the 3D representation of each voxel (i.e. without receiving location data from a location tracking sensor), which would be during travel to some predetermined destination); and generating, by the processor, a path for the ego to travel from the current location to the destination (e.g. see Fig. 7, steps 710-712, wherein the vehicle travels through the unoccupied voxels).
Douillard fails to disclose retrieving, by a processor, image data of a space around an ego, the image data comprising two-dimensional images captured by a camera of the ego, and that the localization is based upon image data which is ultimately based upon two-dimensional images captured by a camera. However, Parkison teaches localizing a vehicle by utilizing features of a 2D image data captured by a camera and map data defining a 3D model (e.g. see para 0022). It would have been obvious for one having ordinary skill before the priority date to modify the system of Douillard to include utilizing 2D image data captured by a camera for localizing a vehicle, as taught by Parkison, as a matter of Designer’s Choice of a limited number of available means (e.g. see Parkison, para 0022) for capturing image data.
As per claim 2, and similarly with respect to claims 9 and 16, Douillard, as modified by Parkison, teaches the features of claim 1, 8 and 15, respectively, and Douillard further discloses further comprising periodically localizing, by the processor, the ego during the path (e.g. the Office notes that the process would have to be repeated (i.e. periodically localizing) to reach the predetermined destination).
As per claim 3, and similarly with respect to claims 10 and 17, Douillard, as modified by Parkison, teaches the features of claim 1, 8 and 15, respectively, and Douillard further discloses wherein localizing the ego comprises tracking the key image feature in successive image data (e.g. see para 0018, wherein the objects are tracked, which requires successive image data).
As per claim 4, and similarly with respect to claims 11 and 18, Douillard, as modified by Parkison, teaches the features of claim 1, 8 and 15, respectively, and Douillard further discloses wherein the key image point corresponds to a unique point within the image data (e.g. see Fig. 3, wherein the LIDAR identifies unique points).
As per claim 5, and similarly with respect to claims 12 and 19, Douillard, as modified by Parkison, teaches the features of claim 1, 8 and 15, respectively, and Douillard further discloses wherein generating the path comprises generating at least one of a trajectory, yaw rate, forward velocity, or a lateral velocity for the ego (e.g. see Fig. 7, steps 710-712, wherein the vehicle travels through the unoccupied voxels).
As per claim 7, and similarly with respect to claim 14, Douillard, as modified by Parkison, teaches the features of claim 1 and 8, respectively, and Douillard further discloses wherein the 3D model further corresponds to a surface attribute of at least one object within the space around the ego (e.g. see para 0062-0066).
Claims 6, 13 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Douillard, in view of Parkison, and in further view of Designer’s Choice.
As per claim 6, and similarly with respect to claims 13 and 20, Douillard, as modified by Parkison, teaches the features of claim 1, 8 and 15, respectively, but fails to specifically teach wherein the path is generated using an iterative linear quadratic regulator (TLQR) protocol. However, Douillard teaches using machine learning algorithms to determine a path for a vehicle (e.g. see paras 0056-0058). Selecting a specific machine learning algorithm to determine a path would only require ordinary skill in the art. It would have been obvious for one having ordinary skill before the priority date to select a machine learning algorithm to provide an accurate path for a vehicle (e.g. see paras 0056-0058).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to James M. McPherson whose telephone number is (313) 446-6543. The examiner can normally be reached on 7:30 AM - 5PM Mon-Fri Eastern Alt Fri. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Abby Flynn can be reached on 571 272-9855. 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.
/JAMES M MCPHERSON/Primary Examiner, Art Unit 3663B
Prosecution Insights