DETAILED ACTION
Claims 1-20 are currently pending.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/12/2025 and 09/12/2025 have been considered.
Claim Rejections - 35 USC § 102
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 –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-3, 10-13, and 16-18 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Foucard (US 2025/002977, effectively filed 07/18/2023).
Regarding claim 1, Foucard teaches:
A computer-implemented method comprising:
detecting, by a computing system, an object and a marker in sensor data captured in an environment; (Foucard, [0107] At 806, example method 800, can include determining, using a machine-learned object detection model and based on the sensor data, an association between one or more travel way markers of the plurality of travel way markers and the an object in the environment)
correlating, by the computing system, the marker in the sensor data with a corresponding marker in a data store associated with the environment based on features of the marker; (Foucard, [0107] At 806, example method 800, can include determining, using a machine-learned object detection model and based on the sensor data, an association between one or more travel way markers of the plurality of travel way markers and the an object in the environment)
determining, by the computing system, a location of the object in the environment based on a relative location of the object with respect to the marker and a location of the marker; (Foucard, [0110] generating, using the machine-learned object detection model, an offset with respect to the one or more travel way markers of a spatial region of the environment associated with the object… [0114] In some implementations, example method 800 can include identifying a lane in which the object is located. For instance, object detection model(s) can regress offsets based on projected travel way markers. Map data can associate the travel way markers with a particular lane or lane type. Example method 800 can include identifying the lane based on this association) and
providing, by the computing system, the location of the object to a vehicle for navigation of the vehicle that avoids the object. (Foucard [0056] The planning system 250 can evaluate trajectories or strategies (e.g., with scores, costs, rewards, constraints, etc, and rank them. )
Regarding claim 2, Foucard teaches:
The computer-implemented method of claim 1, wherein the marker is at least one of a solid line, a patterned line, or a pole in the environment. (Foucard [0107] travel way markers can include lane markers (e.g., centerline markers, lane boundary markers, etc.))
Regarding claim 3, Foucard teaches:
The computer-implemented method of claim 1, wherein the marker is at least one of
i) a line marker in a set of line markers that extend laterally across at least a portion of a road in the environment or
ii) a lane marker of the road in the environment. (Foucard [0107] travel way markers can include lane markers (e.g., centerline markers, lane boundary markers, etc.))
Regarding claim 10, Foucard teaches:
The computer-implemented method of claim 1, wherein the data store is associated with map data associated with the environment, the map data indicating the features of the marker. (Foucard [0046] The autonomy system can obtain the map data associate with an environment in which the autonomous platform was, is, or will be located… can provide information regarding… the location and direction of boundaries or boundary markings)
Regarding claim 11, Foucard teaches:
A system comprising:
at least one processor; (Foucard [0037] processor and memory) and
a memory storing instructions that, when executed, cause the system to perform operations comprising: (Foucard [0037] processor and memory)
detecting an object and a marker in sensor data captured in an environment; (Foucard, [0107] At 806, example method 800, can include determining, using a machine-learned object detection model and based on the sensor data, an association between one or more travel way markers of the plurality of travel way markers and the an object in the environment)
correlating the marker in the sensor data with a corresponding marker in a data store associated with the environment based on features of the marker; (Foucard, [0107] At 806, example method 800, can include determining, using a machine-learned object detection model and based on the sensor data, an association between one or more travel way markers of the plurality of travel way markers and the an object in the environment)
determining a location of the object in the environment based on a relative location of the object with respect to the marker and a location of the marker; (Foucard, [0110] generating, using the machine-learned object detection model, an offset with respect to the one or more travel way markers of a spatial region of the environment associated with the object… [0114] In some implementations, example method 800 can include identifying a lane in which the object is located. For instance, object detection model(s) can regress offsets based on projected travel way markers. Map data can associate the travel way markers with a particular lane or lane type. Example method 800 can include identifying the lane based on this association) and
providing the location of the object to a vehicle for navigation of the vehicle that avoids the object. (Foucard [0056] The planning system 250 can evaluate trajectories or strategies (e.g., with scores, costs, rewards, constraints, etc, and rank them. )
Regarding claim 12, Foucard teaches:
The system of claim 11, wherein the marker is at least one of a solid line, a patterned line, or a pole in the environment. (Foucard [0107] travel way markers can include lane markers (e.g., centerline markers, lane boundary markers, etc.))
Regarding claim 13, Foucard teaches:
The system of claim 11, wherein the marker is at least one of i) a line marker in a set of line markers that extend laterally across at least a portion of a road in the environment or ii) a lane marker of the road in the environment. (Foucard [0107] travel way markers can include lane markers (e.g., centerline markers, lane boundary markers, etc.))
Regarding claim 16, Foucard teaches:
A non-transitory computer-readable storage medium including instructions that, when executed, cause a computing system to perform operations comprising: (Foucard [0037] processor and memory)
detecting an object and a marker in sensor data captured in an environment; (Foucard, [0107] At 806, example method 800, can include determining, using a machine-learned object detection model and based on the sensor data, an association between one or more travel way markers of the plurality of travel way markers and the an object in the environment)
correlating the marker in the sensor data with a corresponding marker in a data store associated with the environment based on features of the marker; (Foucard, [0107] At 806, example method 800, can include determining, using a machine-learned object detection model and based on the sensor data, an association between one or more travel way markers of the plurality of travel way markers and the an object in the environment)
determining a location of the object in the environment based on a relative location of the object with respect to the marker and a location of the marker; (Foucard, [0110] generating, using the machine-learned object detection model, an offset with respect to the one or more travel way markers of a spatial region of the environment associated with the object… [0114] In some implementations, example method 800 can include identifying a lane in which the object is located. For instance, object detection model(s) can regress offsets based on projected travel way markers. Map data can associate the travel way markers with a particular lane or lane type. Example method 800 can include identifying the lane based on this association) and
providing the location of the object to a vehicle for navigation of the vehicle that avoids the object. (Foucard [0056] The planning system 250 can evaluate trajectories or strategies (e.g., with scores, costs, rewards, constraints, etc, and rank them. )
Regarding claim 17, Foucard teaches:
The non-transitory computer-readable storage medium of claim 16, wherein the marker is at least one of a solid line, a patterned line, or a pole in the environment. (Foucard [0107] travel way markers can include lane markers (e.g., centerline markers, lane boundary markers, etc.))
Regarding claim 18, Foucard teaches:
The non-transitory computer-readable storage medium of claim 16, wherein the marker is at least one of i) a line marker in a set of line markers that extend laterally across at least a portion of a road in the environment or ii) a lane marker of the road in the environment. (Foucard [0107] travel way markers can include lane markers (e.g., centerline markers, lane boundary markers, etc.))
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.
The factual inquiries 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.
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.
Claims 4-5, 14-15, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Foucard as applied to claims 1, 11, and 16 above, and further in view of Chalvatzaras (“A Survey on Map-Based Localization Techniques for Autonomous Vehicles”).
Regarding claim 4, Foucard fails to teach:
The computer-implemented method of claim 1, wherein the marker is disposed on a structure in the environment, the structure including at least one of a pole, cone, barrier, wall, fence, or divider.
Chalvatzaras teaches:
The computer-implemented method of claim 1, wherein the marker is disposed on a structure in the environment, the structure including at least one of a pole, cone, barrier, wall, fence, or divider. (Chalvatzaras, page 1578, bottom right column, The map matching step will then try to associate, by the perception stack, landmarks to map elements….. accounting for the odometry, lanes and poles of general example 3)
Before the time of filing, it would have been obvious to add the pole marker of Chalvatzaras to the object localization of Foucard. The inventions lie in the same field of endeavor of autonomous vehicles. The motivation for the combination is to improve localization accuracy. See Chalvatzaras page 1580, right column.
Regarding claim 5, the combination of Foucard and Chalvatzaras teaches:
The computer-implemented method of claim 1, wherein the marker includes at least one of a constant light source, colored light source, pulsing light source, or patterned light source. (Chalvatzaras, page 1580 right column, localization framework on semantic features found in urban scenes such as road marking, traffic lights, signs, and poles)
Before the time of filing, it would have been obvious to add the pole marker of Chalvatzaras to the object localization of Foucard. The inventions lie in the same field of endeavor of autonomous vehicles. The motivation for the combination is to improve localization accuracy. See Chalvatzaras page 1580, right column.
Regarding claim 14, the combination of Foucard and Chalvatzaras teaches:
The system of claim 11, wherein the marker is disposed on a structure in the environment, the structure including at least one of a pole, cone, barrier, wall, fence, or divider. (Chalvatzaras, page 1578, bottom right column, The map matching step will then try to associate, by the perception stack, landmarks to map elements….. accounting for the odometry, lanes and poles of general example 3)
Before the time of filing, it would have been obvious to add the pole marker of Chalvatzaras to the object localization of Foucard. The inventions lie in the same field of endeavor of autonomous vehicles. The motivation for the combination is to improve localization accuracy. See Chalvatzaras page 1580, right column.
Regarding claim 15, the combination of Foucard and Chalvatzaras teaches:
The system of claim 11, wherein the marker includes at least one of a constant light source, colored light source, pulsing light source, or patterned light source. (Chalvatzaras, page 1580 right column, localization framework on semantic features found in urban scenes such as road marking, traffic lights, signs, and poles)
Before the time of filing, it would have been obvious to add the pole marker of Chalvatzaras to the object localization of Foucard. The inventions lie in the same field of endeavor of autonomous vehicles. The motivation for the combination is to improve localization accuracy. See Chalvatzaras page 1580, right column.
Regarding claim 19, the combination of Foucard and Chalvatzaras teaches:
The non-transitory computer-readable storage medium of claim 16, wherein the marker is disposed on a structure in the environment, the structure including at least one of a pole, cone, barrier, wall, fence, or divider. (Chalvatzaras, page 1578, bottom right column, The map matching step will then try to associate, by the perception stack, landmarks to map elements….. accounting for the odometry, lanes and poles of general example 3)
Before the time of filing, it would have been obvious to add the pole marker of Chalvatzaras to the object localization of Foucard. The inventions lie in the same field of endeavor of autonomous vehicles. The motivation for the combination is to improve localization accuracy. See Chalvatzaras page 1580, right column.
Regarding claim 20, the combination of Foucard and Chalvatzaras teaches:
The non-transitory computer-readable storage medium of claim 16, wherein the marker includes at least one of a constant light source, colored light source, pulsing light source, or patterned light source. (Chalvatzaras, page 1580 right column, localization framework on semantic features found in urban scenes such as road marking, traffic lights, signs, and poles)
Before the time of filing, it would have been obvious to add the pole marker of Chalvatzaras to the object localization of Foucard. The inventions lie in the same field of endeavor of autonomous vehicles. The motivation for the combination is to improve localization accuracy. See Chalvatzaras page 1580, right column.
Allowable Subject Matter
Claims 6-9 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. Refer to PTO-892, Notice of References Cited for a listing of analogous art.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Molly K Wilburn whose telephone number is (571)272-3589. The examiner can normally be reached Monday-Friday 8am-4pm.
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/Molly Wilburn/Primary Examiner, Art Unit 2666
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