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 .
Response to Amendment
The Amendment filed May 8th, 2026 has been entered. Claims 1-7 remain pending in the application. Applicant’s amendments to the Specification have overcome each and every objection previously set forth in the Non-Final Office Action mailed February 10th, 2026.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
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 1-3, and 5-7 are rejected 35 U.S.C. 103 as being unpatentable over Wang (United States Patent Application Publication 20210316669 A1), hereinafter Wang, in view of Bhaskaran et al. (United States Patent Application Publication 20200309923 A1), hereinafter Bhaskaran.
Regarding claim 1, Wang teaches an obstacle sensor inspection device that performs an inspection of an obstacle sensor detecting an obstacle present in the vicinity of a mobile body, the obstacle sensor inspection device comprising:
a running control unit configured to perform control such that the mobile body is caused to run along a running path ([0035] The steering system 134 includes suitable componentry that is configured to control the direction of movement of the autonomous vehicle 102 during navigation.; [0096] The hallway calibration environment 300, which may also be referred to as a tunnel calibration environment, includes a thoroughfare 305 through which a vehicle 102 drives, the thoroughfare 305 flanked on either side by targets detectable by the sensors 180 of the vehicle 102.);
an inspection processing unit configured to perform an inspection process for the obstacle sensor using a still object for inspection that is designated in advance in a sensor inspection section designated in advance in a state in which the mobile body is running along the running path ([0045] As described above, the remote computing system 150 is configured to send/receive a signal from the autonomous vehicle 140 regarding reporting data for training and evaluating machine learning algorithms, requesting assistance from remote computing system 150 or a human operator via the remote computing system 150; [0053] The sensor calibration target 200A illustrated in FIG. 2A is a planar board made from a substrate 205, with a pattern 210A printed, stamped, engraved, imprinted, or otherwise marked thereon. The pattern 210A of FIG. 2A is a checkerboard pattern.); and
a detection area setting unit configured to set a detection area of the obstacle sensor to a second area larger than a first area that is used at a time of normal running when the inspection process for the obstacle sensor is performed using the inspection processing unit ([0183] Depending on the sensors 180 on the vehicle 102 and the data captured by the sensors 180, the sensors 180 may require one or more full 360 degree rotations of the vehicle 102 on the platform 420, or may require less than one full 360 degree rotation of the vehicle 102 on the platform 420. In one embodiment, sufficient data for calibration of a sensor may mean data corresponding to targets covering at least a subset of the complete field of view of a particular sensor (collectively over a number of captures), with the subset reaching and/or exceeding a threshold percentage (e.g., 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 99%, 100%).),
wherein the inspection processing unit determines that the obstacle sensor is normal when the still object for inspection is detected by the obstacle sensor and determines that the obstacle sensor is abnormal when the still object for inspection is not detected by the obstacle sensor ([Fig. 10]; [0149] At step 1015, the calibration systems in the vehicle read the calibration scene and: (a) detect targets in each sensor frame, (b) associate detected targets, (c) generate residuals, (d) solve calibration optimization problem, (e) validate calibration optimization solution, and (f) output calibration results).
Wang fails to teach the sensor wherein the running control unit invalidates an operation of stopping or decelerating the mobile body in accordance with a detection result acquired by the obstacle sensor when the inspection process for the obstacle sensor is being performed by the inspection processing unit
However, Bhaskaran teaches the sensor wherein the running control unit invalidates an operation of stopping or decelerating the mobile body in accordance with a detection result acquired by the obstacle sensor when the inspection process for the obstacle sensor is being performed by the inspection processing unit ([0027] For example, the techniques may comprise training the ML model to differentiate between solid body motion and particulate matter and/or fluid motion; [0049] For example, FIG. 1B illustrates an example two-dimensional representation of false positive detections 138 (e.g., false positive LIDAR data) attributable to particulate matter 102 that autonomous vehicle 128 is able to pass through without harm to the autonomous vehicle 128 or its occupants; [0077] In those cases in which the sensor is passing through particulate matter, it is assumed that all such returns should be, in general, normally distributed. In such examples, comparing a single measurement to an average of measurements may, therefore, be indicative of a false return.)
It would have been obvious to one of ordinary skill in the art prior to the effective filing date of this invention to modify the invention of Wang to comprise the stop override similar to Bhaskaran, with a reasonable expectation of success. This would have the predictable result of ignoring non-collision object detection or other false identification of objects so as to avoid unpleasant driving experiences or other traffic incidents.
Regarding claim 2, Wang, as modified, teaches the obstacle sensor inspection device according to claim 1, further comprising an inspection preparation processing unit configured to perform a preparation process for causing the mobile body not to come into contact with the obstacle when the mobile body runs in the sensor inspection section, in a sensor inspection preparation section positioned on a side in front of the sensor inspection section in a traveling direction of the mobile body before the inspection process for the obstacle sensor is performed by the inspection processing unit ([0039] The internal computing system 110 can also include a constraint service 114 to facilitate safe propulsion of the autonomous vehicle 102. The constraint service 116 includes instructions for activating a constraint based on a rule-based restriction upon operation of the autonomous vehicle 102. For example, the constraint may be a restriction upon navigation that is activated in accordance with protocols configured to avoid occupying the same space as other objects, abide by traffic laws, circumvent avoidance areas, etc).
Regarding claim 3, Wang, as modified, teaches the obstacle sensor inspection device according to claim 2,
wherein the inspection preparation processing unit sets the detection area of the obstacle sensor to a third area larger than the first area and determines whether or not the obstacle is detected by the obstacle sensor in the state as the preparation process ([0183] Depending on the sensors 180 on the vehicle 102 and the data captured by the sensors 180, the sensors 180 may require one or more full 360 degree rotations of the vehicle 102 on the platform 420, or may require less than one full 360 degree rotation of the vehicle 102 on the platform 420. In one embodiment, sufficient data for calibration of a sensor may mean data corresponding to targets covering at least a subset of the complete field of view of a particular sensor (collectively over a number of captures), with the subset reaching and/or exceeding a threshold percentage (e.g., 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 99%, 100%).), and
wherein, in a case in which it is determined by the inspection preparation processing unit that the obstacle is not detected by the obstacle sensor, the inspection processing unit determines that the obstacle sensor is normal when the still object for inspection is detected by the obstacle sensor and determines that the obstacle sensor is abnormal when the still object for inspection is not detected by the obstacle sensor ([Fig. 10]; [0149] At step 1015, the calibration systems in the vehicle read the calibration scene and: (a) detect targets in each sensor frame, (b) associate detected targets, (c) generate residuals, (d) solve calibration optimization problem, (e) validate calibration optimization solution, and (f) output calibration results).
Regarding claim 5, Wang, as modified, teaches the obstacle sensor inspection device according to claim 1, wherein the second area is set to be wider than the first area in at least one of a traveling direction and a width direction of the mobile body ([0183] Depending on the sensors 180 on the vehicle 102 and the data captured by the sensors 180, the sensors 180 may require one or more full 360 degree rotations of the vehicle 102 on the platform 420, or may require less than one full 360 degree rotation of the vehicle 102 on the platform 420. In one embodiment, sufficient data for calibration of a sensor may mean data corresponding to targets covering at least a subset of the complete field of view of a particular sensor (collectively over a number of captures), with the subset reaching and/or exceeding a threshold percentage (e.g., 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 99%, 100%).).
Regarding claim 6, Wang, as modified, teaches the obstacle sensor inspection device according to claim 1,
wherein the running path includes a curved part ([0100] While the thoroughfare 305 of the hallway calibration environment 300 of FIG. 3 is a straight path, in some cases it may be a curved path, and by extension the left target channel 310 and right target channel 315 may be curved to follow the path of the thoroughfare 305.),
wherein the sensor inspection section is designated to be at a position on a side in front of the curved part in a traveling direction of the mobile body ([0096] The hallway calibration environment 300, which may also be referred to as a tunnel calibration environment, includes a thoroughfare 305 through which a vehicle 102 drives, the thoroughfare 305 flanked on either side by targets detectable by the sensors 180 of the vehicle 102.), and
wherein the still object for inspection is disposed at a position entering the inside of the second area when the mobile body runs in the sensor inspection section ([0099] The sensor targets illustrated in FIG. 3 are illustrated such that some are positioned closer to the thoroughfare 305 while some are positioned farther from the thoroughfare 305. Additionally, while some targets in FIG. 3 are facing a direction perpendicular to the thoroughfare 305, others are angled up or down with respect to the direction perpendicular to the thoroughfare 305.).
Regarding claim 7, Wang teaches an obstacle sensor inspection method for performing an inspection of an obstacle sensor detecting an obstacle present in the vicinity of a mobile body, the obstacle sensor inspection method comprising:
designating a sensor inspection section in which an inspection of the obstacle sensor is performed, a sensor inspection preparation section positioned on a side in front of the sensor inspection section in a traveling direction of the mobile body, and a still object for inspection used for an inspection of the obstacle sensor in the sensor inspection section, in the middle of a running path in which the mobile body runs ([0096] The hallway calibration environment 300, which may also be referred to as a tunnel calibration environment, includes a thoroughfare 305 through which a vehicle 102 drives, the thoroughfare 305 flanked on either side by targets detectable by the sensors 180 of the vehicle 102.);
performing control such that the mobile body is caused to run along the running path ([0035] The steering system 134 includes suitable componentry that is configured to control the direction of movement of the autonomous vehicle 102 during navigation.; [0096] The hallway calibration environment 300, which may also be referred to as a tunnel calibration environment, includes a thoroughfare 305 through which a vehicle 102 drives, the thoroughfare 305 flanked on either side by targets detectable by the sensors 180 of the vehicle 102.);
performing an inspection process for the obstacle sensor using the still object for inspection in a state in which the mobile body is running along the running path in the sensor inspection section ([0045] As described above, the remote computing system 150 is configured to send/receive a signal from the autonomous vehicle 140 regarding reporting data for training and evaluating machine learning algorithms, requesting assistance from remote computing system 150 or a human operator via the remote computing system 150; [0053] The sensor calibration target 200A illustrated in FIG. 2A is a planar board made from a substrate 205, with a pattern 210A printed, stamped, engraved, imprinted, or otherwise marked thereon. The pattern 210A of FIG. 2A is a checkerboard pattern.); and
setting a detection area of the obstacle sensor to a second area larger than a first area that is used at a time of normal running when the inspection process for the obstacle sensor is performed ([0183] Depending on the sensors 180 on the vehicle 102 and the data captured by the sensors 180, the sensors 180 may require one or more full 360 degree rotations of the vehicle 102 on the platform 420, or may require less than one full 360 degree rotation of the vehicle 102 on the platform 420. In one embodiment, sufficient data for calibration of a sensor may mean data corresponding to targets covering at least a subset of the complete field of view of a particular sensor (collectively over a number of captures), with the subset reaching and/or exceeding a threshold percentage (e.g., 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 99%, 100%).),
wherein, in the performing of an inspection process for the obstacle sensor, it is determined that the obstacle sensor is normal when the still object for inspection is detected by the obstacle sensor, and it is determined that the obstacle sensor is abnormal when the still object for inspection is not detected by the obstacle sensor ([Fig. 10]; [0149] At step 1015, the calibration systems in the vehicle read the calibration scene and: (a) detect targets in each sensor frame, (b) associate detected targets, (c) generate residuals, (d) solve calibration optimization problem, (e) validate calibration optimization solution, and (f) output calibration results).
Wang fails to teach the method invalidating an operation of stopping or decelerating the mobile body in accordance with a detection result acquired by the obstacle sensor when the inspection process for the obstacle sensor is being performed.
However, Bhaskaran teaches the method invalidating an operation of stopping or decelerating the mobile body in accordance with a detection result acquired by the obstacle sensor when the inspection process for the obstacle sensor is being performed ([0027] For example, the techniques may comprise training the ML model to differentiate between solid body motion and particulate matter and/or fluid motion; [0049] For example, FIG. 1B illustrates an example two-dimensional representation of false positive detections 138 (e.g., false positive LIDAR data) attributable to particulate matter 102 that autonomous vehicle 128 is able to pass through without harm to the autonomous vehicle 128 or its occupants; [0077] In those cases in which the sensor is passing through particulate matter, it is assumed that all such returns should be, in general, normally distributed. In such examples, comparing a single measurement to an average of measurements may, therefore, be indicative of a false return.).
It would have been obvious to one of ordinary skill in the art prior to the effective filing date of this invention to modify the invention of Wang to comprise the stop override similar to Bhaskaran, with a reasonable expectation of success. This would have the predictable result of ignoring non-collision object detection or other false identification of objects so as to avoid unpleasant driving experiences or other traffic incidents.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Bhaskaran, further in view of Matsuzaki (United States Patent Application Publication 20180210443A1), hereinafter Matsuzaki.
Regarding claim 4, Wang, as modified, teaches the obstacle sensor inspection device according to claim 2,
Wang fails to teach the device wherein the inspection preparation processing unit performs control of the mobile body to be decelerated to a speed for not coming into contact with the obstacle at the time of the mobile body running in the sensor inspection section as the preparation process
However, Matsuzaki teaches the device wherein the inspection preparation processing unit performs control of the mobile body to be decelerated to a speed for not coming into contact with the obstacle at the time of the mobile body running in the sensor inspection section as the preparation process (the device wherein the inspection preparation processing unit performs control of the mobile body to be decelerated to a speed for not coming into contact with the obstacle at the time of the mobile body running in the sensor inspection section as the preparation process)
It would have been obvious to one of ordinary skill in the art prior to the effective filing date of this invention to modify the invention of Wang, as modified, to comprise the speed reduction system to avoid obstacles similar to Matsuzaki, with a reasonable expectation of success. This would have the predictable result of using ensuring the controlled vehicle of Wang avoids obstacles in the safest way.
Response to Arguments
Applicant’s arguments, see page 7-9 of Applicant Arguments, filed May 8th, 2026, with respect to the rejection(s) of claim(s) 1-3, and 5-7 under 35 U.S.C. 102(a)(1) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of 35 U.S.C. 103.
As stated above, the amendments made to the independent claims 1 and 7 have overcome the previously stated rejection as presented. However, after further search a new prior art of record of Bhaskaran has been found that appears to teach, in combination argued as obvious to one of ordinary skill in the art above, the newly amended independent claims. The rejection has been modified, as necessitated by the amendments above, and is presented in this Final Office Action.
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 ROBERT WILLIAM VASQUEZ JR whose telephone number is (571)272-3745. The examiner can normally be reached Monday thru Thursday, Flex Friday, 8:00-5:00 PST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, HELAL ALGAHAIM can be reached at (571)270-5227. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ROBERT W VASQUEZ/Examiner, Art Unit 3645
/HELAL A ALGAHAIM/SPE , Art Unit 3645
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