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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 1/29/2026 has been entered.
Terminal Disclaimer
The terminal disclaimer filed on 10/17/2025 disclaiming the terminal portion of any patent granted on this application which would extend beyond the expiration date of patent # 12227400 has been reviewed and is accepted. The terminal disclaimer has been recorded.
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, and 5-11 are rejected under 35 U.S.C. 103 as being unpatentable over:
Nussbaum (US 9,376,296 B2), which qualifies as prior art under 35 USC 102(a)(1), in view of
Perlstein (US 2018/0339890 A1), which qualifies as prior art under 35 USC 102(a)(2), and
Perlstein-2 (US 20190100420), which qualifies as prior art under 35 USC 102(a)(2).
Regarding claim 11, Nussbaum discloses, except for elements highlighted in italicized bold below,
an intelligent lift automation system (
PNG
media_image1.png
676
497
media_image1.png
Greyscale
PNG
media_image2.png
393
570
media_image2.png
Greyscale
) comprising:
a lift situated in a lift area (
PNG
media_image3.png
642
527
media_image3.png
Greyscale
PNG
media_image4.png
535
1048
media_image4.png
Greyscale
);
a plurality of detectors operable to generate:
a first set of images useful in determining a position of a vehicle in the lift area (
PNG
media_image5.png
183
324
media_image5.png
Greyscale
PNG
media_image6.png
186
1057
media_image6.png
Greyscale
PNG
media_image7.png
911
1045
media_image7.png
Greyscale
PNG
media_image8.png
764
875
media_image8.png
Greyscale
) and
a second set of images useful by artificial intelligence software in determining a position of a set of lift points on the vehicle; wherein the plurality of detectors comprise a plurality of cameras, the second set of images are generated by the plurality of cameras, and at least two of the plurality of cameras have distinct viewpoints; and
a lift controller (
PNG
media_image9.png
402
568
media_image9.png
Greyscale
) configured to:
based on the first set of images, virtualize the position of the vehicle relative to the lift (
PNG
media_image10.png
938
926
media_image10.png
Greyscale
PNG
media_image11.png
913
1063
media_image11.png
Greyscale
);
based on the second set of images, use artificial intelligence software to associate the virtualized position of the vehicle with a lift point map, wherein the lift point map describes the positions of the set of lift points on the vehicle (
PNG
media_image12.png
845
1120
media_image12.png
Greyscale
);
generate a positive identification that comprises at least one image from the second set of images and a positive image descriptor associated with the at least one image, where the positive image descriptor indicates the presence of a valid lift point in the at least one image; and
control one or more movements of the lift to engage the valid lift point (
PNG
media_image13.png
522
1029
media_image13.png
Greyscale
PNG
media_image14.png
300
1029
media_image14.png
Greyscale
).
As noted above, Nussbaum does not discloses:
“a second set of images useful by artificial intelligence software in determining a position of a set of lift points on the vehicle”; “wherein the plurality of detectors comprise a plurality of cameras, the second set of images are generated by the plurality of cameras, and at least two of the plurality of cameras have distinct viewpoints”; and
“based on the second set of images, use artificial intelligence software to associate the virtualized position of the vehicle with a lift point map, wherein the lift point map describes the positions of the set of lift points on the vehicle;
generate a positive identification that comprises at least one image from the second set of images and a positive image descriptor associated with the at least one image, where the positive image descriptor indicates the presence of a valid lift point in the at least one image”.
Nussbaum does teach a computer database “associating the virtualized position of the vehicle with a lift point map, wherein the lift point map describes the positions of the set of lift points on the vehicle” (
PNG
media_image12.png
845
1120
media_image12.png
Greyscale
).
Perlstein also discloses an automated vehicle lift, and teaches:
“a second set of images useful by artificial intelligence software in determining a position of a set of lift points on the vehicle”; wherein the plurality of detectors comprise a plurality of cameras, the second set of images are generated by the plurality of cameras, and at least two of the plurality of cameras have distinct viewpoints” and
“based on the second set of images, use artificial intelligence software to associate the virtualized position of the vehicle with a lift point map, wherein the lift point map describes the positions of the set of lift points on the vehicle;
generate a positive identification that comprises at least one image from the second set of images and a positive image descriptor associated with the at least one image, where the positive image descriptor indicates the presence of a valid lift point in the at least one image” (
PNG
media_image15.png
834
694
media_image15.png
Greyscale
PNG
media_image16.png
542
668
media_image16.png
Greyscale
PNG
media_image17.png
204
656
media_image17.png
Greyscale
PNG
media_image18.png
266
670
media_image18.png
Greyscale
PNG
media_image19.png
306
654
media_image19.png
Greyscale
PNG
media_image20.png
592
652
media_image20.png
Greyscale
PNG
media_image21.png
676
660
media_image21.png
Greyscale
PNG
media_image22.png
768
658
media_image22.png
Greyscale
PNG
media_image23.png
286
842
media_image23.png
Greyscale
PNG
media_image24.png
369
674
media_image24.png
Greyscale
PNG
media_image25.png
896
699
media_image25.png
Greyscale
).
It would have been obvious (before the effective filing date of the claimed invention) or (at the time the invention was made) to one of ordinary skill in the art to supplement the lift arms and computer of Nussbaum, to automate the attachment of the lift arm to the lift points based on image processing and machine learning as is taught by Perlstein above, with motivation coming from Perlstein:
PNG
media_image26.png
698
655
media_image26.png
Greyscale
.
Furthermore, the prior art collectively includes each element claimed (though not all in the same reference), and one of ordinary skill in the art could have combined the elements in the manner explained above using known engineering design, interface and/or programming techniques, without changing a “fundamental” operating principle of Nussbaum, while the teaching of Perlstein continues to perform the same function as originally taught prior to being combined, in order to produce the repeatable and predictable result described in the previous paragraph above. It is for at least the aforementioned reasons that the examiner has reached a conclusion of obviousness with respect to the claim in question.
Nussbaum in view of Perlstein does not specifically teach that the distinct viewpoints comprising a plan view of the vehicle and a profile view of the side of the vehicle.
However, in the same field of endeavor, Perlstein-2 teaches: the distinct viewpoints comprising a plan view of the vehicle and a profile view of the side of the vehicle (¶ [0127] “…one or more camera(s) may be mounted on service bay 160. These camera(s) are directed at vehicle 140 from the top or the sides, or alternatively from the bottom.”; ¶ [0129] “…Guidance system 150 also determines the present location of rolling-jacks 104-5 based on sensor data or other image data, such as from cameras on the sides or below vehicle 140.”
Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Nussbaum in view of Perlstein to incorporate the teachings of Perlstein-2 by including: the distinct viewpoints comprising a plan view of the vehicle and a profile view of the side of the vehicle in order to determine the present location of rolling-jacks based on sensor data or other image data.
Regarding claim 1, a vehicle lift operable to lift a vehicle within a lift area, the vehicle lift comprising:
a lift post that is operable to raise and lower a lift arm assembly; a set of lift arms, wherein each arm of the set of lift arms is attached to the lift post by a post connection at a proximal end of the lift arm, and wherein the system is operable to automatically position a distal end of the lift arm (Nussbaum of the Nussbaum/Perlstein combination:
PNG
media_image27.png
647
534
media_image27.png
Greyscale
);
a set of lift area detectors operable to determine physical characteristics of objects in the lift area, the set of lift area detectors comprising a plurality of cameras configured to capture plurality of images of the vehicle, at least the plurality of cameras having distinct viewpoints (Nussbaum of the Nussbaum/Perlstein combination:
PNG
media_image5.png
183
324
media_image5.png
Greyscale
PNG
media_image6.png
186
1057
media_image6.png
Greyscale
PNG
media_image23.png
286
842
media_image23.png
Greyscale
PNG
media_image7.png
911
1045
media_image7.png
Greyscale
PNG
media_image8.png
764
875
media_image8.png
Greyscale
); and
a lift controller (Nussbaum of the Nussbaum/Perlstein combination:
PNG
media_image2.png
393
570
media_image2.png
Greyscale
) configured to:
access an identification dataset that comprises data usable by artificial intelligence software to perform image analysis to identify objects within the one or more images of the vehicle (Perlstein of the Nussbaum/Perlstein combination:
PNG
media_image28.png
265
656
media_image28.png
Greyscale
PNG
media_image29.png
337
667
media_image29.png
Greyscale
PNG
media_image30.png
610
684
media_image30.png
Greyscale
PNG
media_image31.png
302
661
media_image31.png
Greyscale
);
control the position of the distal end of each lift arm in the set of lift arms (Perlstein of the Nussbaum/Perlstein combination:
PNG
media_image32.png
309
638
media_image32.png
Greyscale
);
using information from the set of lift area detectors, determine a virtualized position of the vehicle within the lift area (Nussbaum of the Nussbaum/Perlstein combination:
PNG
media_image5.png
183
324
media_image5.png
Greyscale
PNG
media_image6.png
186
1057
media_image6.png
Greyscale
PNG
media_image7.png
911
1045
media_image7.png
Greyscale
PNG
media_image8.png
764
875
media_image8.png
Greyscale
);
using the set of lift area detectors, capture a set of one or more images of each lift point in a set of one or more lift points on the vehicle; using artificial intelligence software, perform an image analysis on the set of one or more images of each lift point using the identification dataset to produce a set of results; and automatically position the distal end of each lift arm of the set of lift arms at a different lift point of the set of lift points based on the virtualized position of the vehicle and the set of results (Perlstein of the Nussbaum/ combination:
PNG
media_image33.png
751
604
media_image33.png
Greyscale
PNG
media_image34.png
842
656
media_image34.png
Greyscale
PNG
media_image35.png
374
647
media_image35.png
Greyscale
PNG
media_image36.png
518
652
media_image36.png
Greyscale
PNG
media_image37.png
372
682
media_image37.png
Greyscale
).
Nussbaum in view of Perlstein does not specifically teach that the distinct viewpoints comprising a plan view of the vehicle and a profile view of the side of the vehicle.
However, in the same field of endeavor, Perlstein-2 teaches: the distinct viewpoints comprising a plan view of the vehicle and a profile view of the side of the vehicle (¶ [0127] “…one or more camera(s) may be mounted on service bay 160. These camera(s) are directed at vehicle 140 from the top or the sides, or alternatively from the bottom.”; ¶ [0129] “…Guidance system 150 also determines the present location of rolling-jacks 104-5 based on sensor data or other image data, such as from cameras on the sides or below vehicle 140.”
Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Nussbaum in view of Perlstein to incorporate the teachings of Perlstein-2 by including: the distinct viewpoints comprising a plan view of the vehicle and a profile view of the side of the vehicle in order to determine the present location of rolling-jacks based on sensor data or other image data.
Regarding claim 3, the vehicle lift of claim 1, wherein the lift controller is further configured to provide an identification dataset update to an identification server, where the identification dataset update comprises information from the set of lift area detectors (Perlstein of the Nussbaum/ combination:
PNG
media_image38.png
692
741
media_image38.png
Greyscale
).
Regarding claim 4, the vehicle lift of claim 3, wherein the lift controller is further configured to receive a new identification dataset from the identification server, wherein the new identification dataset is configured based at least in part upon the identification dataset update (Perlstein of the Nussbaum/ combination:
PNG
media_image39.png
692
741
media_image39.png
Greyscale
PNG
media_image40.png
390
654
media_image40.png
Greyscale
PNG
media_image41.png
329
650
media_image41.png
Greyscale
).
Regarding claim 5, the vehicle lift of claim 1, wherein the lift controller is configured to, when performing the image analysis: capture a profile view image of the vehicle and perform a profile image analysis on the profile view image using the identification dataset to identify a lift point within the profile view image; determine whether the lift point within the profile view image is contained within a target envelope of the lift arm; and cause a lift monitor device to display the profile view image, the lift point, and the target envelope (Perlstein of the Nussbaum/ combination:
PNG
media_image42.png
355
427
media_image42.png
Greyscale
PNG
media_image43.png
748
567
media_image43.png
Greyscale
).
Regarding claim 6, the vehicle lift of claim 5, wherein the lift controller is further configured to: receive a confirmation from the lift monitor device indicating that the lift point is positioned within the target envelope; create an identification dataset update comprising the profile view image and the lift point; and provide the identification dataset update to an identification server (Perlstein of the Nussbaum/ combination:
PNG
media_image43.png
748
567
media_image43.png
Greyscale
PNG
media_image44.png
341
594
media_image44.png
Greyscale
PNG
media_image45.png
892
660
media_image45.png
Greyscale
).
Regarding claim 7, the vehicle lift of claim 1, wherein the lift controller is configured to, when performing the image analysis:
capture a plan view image of the vehicle and perform a plan view image analysis on the plan view image using the identification dataset to identify a lift point within the plan view image; determine whether the lift point within the plan view image is contained within a target envelope of the lift arm; and cause a lift monitor device to display the plan view image, the lift point, and the target envelope (Perlstein of the Nussbaum/ combination:
PNG
media_image46.png
358
567
media_image46.png
Greyscale
PNG
media_image47.png
878
686
media_image47.png
Greyscale
).
Regarding claim 8, the vehicle lift of claim 7, wherein the lift controller is further configured to: receive a confirmation from the lift monitor device indicating that the lift point is positioned within the target envelope; create an identification dataset update comprising the plan view image and the lift point; and provide the identification dataset update to the identification server (Perlstein of the Nussbaum/ Perlstein combination:
PNG
media_image43.png
748
567
media_image43.png
Greyscale
PNG
media_image44.png
341
594
media_image44.png
Greyscale
PNG
media_image45.png
892
660
media_image45.png
Greyscale
).
Regarding claim 9, the vehicle lift of claim 1, wherein the lift controller is further configured to: for each lift arm of the set of lift arms, cause a lift monitor device to display a plan view image of a lift point above an adapter of that lift point; receive a confirmation from the lift monitor device indicating that the set of lift arms is correctly positioned; create an identification dataset update comprising each plan view image and an identified lift point within each plan view image; and provide the identification dataset update to an identification server (Nussbaum of the Nussbaum/ Perlstein combination:
PNG
media_image48.png
228
307
media_image48.png
Greyscale
PNG
media_image49.png
974
1042
media_image49.png
Greyscale
).
Regarding claim 10, the vehicle lift of claim 9, wherein the lift controller is further configured to receive a new identification dataset from the identification server, and wherein the new identification dataset is based at least in part upon the identification dataset update (Perlstein of the Nussbaum/ Perlstein combination:
PNG
media_image50.png
381
719
media_image50.png
Greyscale
).
Claims 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over:
Nussbaum (US 9,376,296 B2), which qualifies as prior art under 35 USC 102(a)(1), in view of
Perlstein (US 2018/0339890 A1), which qualifies as prior art under 35 USC 102(a)(2), and
Perlstein-2 (US 20190100420), which qualifies as prior art under 35 USC 102(a)(2); and
BERDELLE-HILGE (US 20110113609), which qualifies as prior art under 35 USC 102(a)(1).
Regarding claim 19:
Nussbaum, Perlstein, and Perlstein-2 teaches the limitations of claims 1 as applied above.
Nussbaum, Perlstein, and Perlstein-2 does not explicitly teach: wherein the plan view of the vehicle is from below the vehicle.
However, in the same field of endeavor, BERDELLE-HILGE teaches: wherein the plan view of the vehicle is from below the vehicle (¶ [0066] “At least one lift table camera 4a, 4b produces at least one vehicle image from below in an imaging direction that is perpendicular or obliquely upward.”).
Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Nussbaum in view of Perlstein and Perlstein-2 to incorporate the teachings of BERDELLE-HILGE by including: wherein the plan view of the vehicle is from below the vehicle in order to evaluate the vehicle image(s) for each fastening element and each connection element.
Regarding claim 20: the claim limitations are similar to those of claim 19; therefore, rejected in the same manner as applied above.
Allowable Subject Matter
Claims 2-4 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.
Regarding claim 2, Nussbaum of the Nussbaum/Perlstein combination further teaches wherein the lift controller is configured to, when determining the virtualized position of the vehicle: capture an image of the vehicle using a camera in the set of lift area detectors (
PNG
media_image5.png
183
324
media_image5.png
Greyscale
PNG
media_image6.png
186
1057
media_image6.png
Greyscale
). However, it is the examiner’s findings that in the context of the claim as a whole including the limitation of the parent claim, the prior of record as applied above and that having been searched does not teach or suggest, without reliance upon impermissible hindsight, the additional limitations of:
“perform an image analysis on the image using the identification dataset to identify a position of a first target point in the image;
determine a position of the vehicle in a first dimension and in a second dimension as a function of the location of the first target point within the image, a distance between the first target point on the vehicle and a first proximity sensor in the set of lift area detectors, and an angle of the proximity sensor relative to the first target point; and
determine an orientation of the vehicle within the lift area as a function of the position in the first dimension and output from a second proximity sensor of the set of lift area detectors.”
Claims 3-4 depend from claim 2.
Claims 12-18 are allowed.
Claim 12 is similar to claim 2 but in the independent form; therefore, allowed at least for similar reasons.
Claims 13-18 depend from claim 12.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1 and 11 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WASSIM MAHROUKA whose telephone number is (571)272-2945. The examiner can normally be reached Monday-Thursday 8:00-5:00 EST.
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, Stephen Koziol can be reached at (408) 918-7630. 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.
/WASSIM MAHROUKA/Primary Examiner, Art Unit 2665