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 .
The current application is CON. of Application No. 18/195329 filed on May 09, 2023 which now Pat. No. 12019448.
Response to Amendment/Arguments
Applicant's amendment/arguments filed 05/06/2026 have been fully considered and are moot in view new grounds of rejection. Applicant's arguments with respect to the claims have been considered. The arguments do not apply to any of the references being used in the current 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.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Vallespi-Gonzalez (20170323179).
With regard to claim 1, Vallespi-Gonzalez discloses A computer-implemented method comprising:
determining, by a computing system, a map of an environment based on sensor data of the environment (a control system 100 (of an autonomous vehicle 10) obtains a road segment upon which the vehicle 10 operates based on sensor data 99, see [0025]+);
identifying, by the computing system, a point of interest in the map associated with an area in the environment where a change to the area would affect navigation of the area (any discrepancies between image maps created from the real-time sensor data and the previously recorded sub-map environment data potentially identify areas with unknown features/objects or changes since the environment data was last updated, see [0013]+ & [0058]+); and
storing, by the computing system, additional sensor data for the area (sensor data continuously connected by the sensor array and stored as sub-maps 231, see [0043]+); and
generating, by the computing system, control data for an autonomous vehicle to reroute, slow, or stop based on the change affecting navigation (the data processing system (the AV control system 220 can respond to different types of objects by generating control commands 221 to reactively operate the steering, braking and acceleration system 225 accordingly, see [0049]+).
Although Vallespi-Gonzalez’s disclosure is not described as same world languages but Examiner interprets the teaching feature above are equivalent to the scope of the claim. For this reason, Vallespi-Gonzalez is obvious suggestively, if not anticipatory, of the claimed subject matter.
With regard to claim 2, Vallespi-Gonzalez teaches that the computer-implemented method of claim 1, further comprising: comparing, by the computing system, data associated with the map and the sensor data of the environment, wherein the change to the area and the additional sensor data are determined based on the comparing (the disparity mapper 126 can continuously compare the sensor data 111 to identify potential hazards, change, and etc., see [0036]+).
With regard to claim 3, Vallespi-Gonzalez teaches that the computer-implemented method of claim 2, wherein the comparing data associated with the map and the sensor data of the environment comprises: projecting, by the computing system, the data associated with the map data over the sensor data of the environment (the event logic 124 detects changed object which projected to be on a collision trajectory, so that enable the control system to make evasive actions or plan for any potential threats, see [0038]+).
With regard to claim 4, Vallespi-Gonzalez teaches that the computer-implemented method of claim 1, further comprising: in response to a determination that the change to the area would affect navigation, estimating, by the computing system, a value of a road condition to determine whether a vehicle can safely navigate in the area (the controller continuously adjusts and alter the movement of the vehicle in response to receiving a corresponding set of commands from the control system 100. The absent events or conditions which affect the vehicle 10 in safety processing along the route, the control system 100 generates additional commands form which the controllers 84 can generate various vehicle controls signals, see [0031]+)
.
With regard to claim 5, Vallespi-Gonzalez teaches that the computer-implemented method of claim 1, wherein data associated with the map includes at least one of a three-dimensional (3D) reconstruction of the area, a point cloud of the area, images of the area, and semantic information for the area (the object detection system compares the images to 3D environment data for the road segment to determines pixels in the images, see [0014]+).
With regard to claim 6, Vallespi-Gonzalez teaches that the computer-implemented method of claim 1, wherein at least one of addition, removal, and modification of data associated with the map is based on the additional sensor data (Any discrepancies between image maps created from the real-time sensor data and the previous recorded sub-map environment data which updated, see [0013]+).
With regard to claim 7, Vallespi-Gonzalez teaches that the computer-implemented method of claim 6, wherein the data associated with the map is associated with a point cloud of the area and the additional sensor data is associated with LiDAR data (see [0036]+).
With regard to claim 8, Vallespi-Gonzalez teaches that the computer-implemented method of claim 1, further comprising: updating, by the computing system, the data associated with the map based on the additional sensor data (see [0042]+).
With regard to claim 9, Vallespi-Gonzalez teaches that the computer-implemented method of claim 1, wherein the change to the area is associated with at least one of size, geometry, height, appearance, markings, and content of at least one of a road, sign, barrier, overhead obstruction, and environmental feature (the event alert 135 indicate a classification of the event, information about the event such as the type of object which indicating a type of action should take (e.g., location of object relative to path o vehicle, size or type of object, etc.), see [0040]+).
With regard to claim 10, Vallespi-Gonzalez teaches that the computer-implemented method of claim 1, further comprising: , by the computing system, an alert indicating the change to the area when a vehicle utilizing data associated with the map is operating in a manual mode of operation (the vehicle operated either autonomously or manually, see [0023]+ & [0040]-[0045]+).
With regard to claims 11 & 16, Vallespi-Gonzalez discloses a system comprising: at least one processor; and a memory storing instructions that, when executed by the at least one processor (an AV 200 shown in Fig.2), cause the system to perform operations comprising:
determining a map of an environment based on sensor data of the environment (a control system 100 (of an autonomous vehicle 10) obtains a road segment upon which the vehicle 10 operates based on sensor data 99, see [0025]+);
identifying a point of interest in the map associated with an area in the environment where a change to the area would affect navigation of the area (any discrepancies between image maps created from the real-time sensor data and the previously recorded sub-map environment data potentially identify areas with unknown features/objects or changes since the environment data was last updated, see [0013]+ & [0058]+);
storing additional sensor data for the area (sensor data continuously connected by the sensor array and stored as sub-maps 231, see [0043]+); and
generating control data for an autonomous vehicle to reroute, slow, or stop based on the change affecting navigation (the AV control system 220 can respond to different types of objects by generating control commands 221 to reactively operate the steering, braking and acceleration system 225 accordingly, see [0049]+).
Although Vallespi-Gonzalez’s disclosure is not described as same world languages but Examiner interprets the teaching feature above are equivalent to the scope of the claim. For this reason, Vallespi-Gonzalez is obvious suggestively, if not anticipatory, of the claimed subject matter.
With regard to claims 12 & 17, Vallespi-Gonzalez teaches that the system of claim 11, wherein the operations further comprise: comparing data associated with the map and the sensor data of the environment, wherein the change to the area and the additional sensor data are determined based on the comparing (the disparity mapper 126 can continuously compare the sensor data 111 to identify potential hazards, change, and etc., see [0036]+).
With regard to claims 13 & 18, Vallespi-Gonzalez teaches that the system of claim 12, wherein the comparing data associated with the map and the sensor data of the environment comprises: projecting the data associated with the map data over the sensor data of the environment (the event logic 124 detects changed object which projected to be on a collision trajectory, so that enable the control system to make evasive actions or plan for any potential threats, see [0038]+).
With regard to claims 14 & 19, Vallespi-Gonzalez teaches that the system of claim 11, wherein the operations further comprise:in response to a determination that the change to the area would affect navigation, estimating, by the computing system, a value of a road condition to determine whether a vehicle can safely navigate in the area (the controller continuously adjusts and alter the movement of the vehicle in response to receiving a corresponding set of commands from the control system 100. The absent events or conditions which affect the vehicle 10 in safety processing along the route, the control system 100 generates additional commands form which the controllers 84 can generate various vehicle controls signals, see [0031]+)
With regard to claims 15 & 20, Vallespi-Gonzalez teaches that the system of claim 11, wherein data associated with the map includes at least one of a three-dimensional (3D) reconstruction of the area, a point cloud of the area, images of the area, and semantic information for the area (the object detection system compares the images to 3D environment data for the road segment to determines pixels in the images, see [0014]+).
Prior Arts Cited
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Miyatani (20240329655) discloses an information processing device which calculates position and an orientation of a movable apparatus based on measurement information of a sensor that measures an environment in surrounding of the movable apparatus (see the summary).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NGA X NGUYEN whose telephone number is (571)272-5217. The examiner can normally be reached M-F 5:30AM - 2:30PM.
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, JELANI SMITH can be reached at 571-270-3969. 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.
/NGA X NGUYEN/Primary Examiner, Art Unit 3662
Prosecution Insights