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 .
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 1-3, 5-7 are rejected under 35 U.S.C. 103 as being unpatentable over Fujimoto US 2023/0294744 in view of Cui et al WO 2023/287406(hereinafter Cui).
Regarding claim1, Fujimoto teaches a modular inspection assembly, comprising: a camera([0026], [0034], vision sensor 114, fig. 1); a linear rail and carriage for the camera, the linear rail configured to allow movement of the camera along an axis enabling adjustable positioning of the camera relative to an inspection target([0032-0034], rail 108 includes rail mount hardware 112 that equipped with vision sensor(camera) 114, fig. 1); a gimbal system providing rotational movement of the camera to orient the camera for capturing various inspection angles([0032], the rail mount hardware 112 includes electric motor that rotates one or more wheels[0034], the rail mounted robot 110 is equipped with a vision sensor 114 that may be rotatable and/otherwise movable relative to rail-mounted robot 110) ; a computer implementing AI models, each trained to perform specific inspection tasks([0055], using artificial intelligence techniques such as trained CNNs, image may be analyzed to detect sensor readings.), and an image processing unit manage the positioning and operation of the camera, linear rail, and gimbal system, allowing automated and flexible inspection of workpiece targets in real-time([0036], rail-mounted 110 may operate based on command(s) received from server(s) 102, [0052], the processor(s) 230, 330 of rail-mounted robot 110, 210, 310 may instruct motion controller 234, 334 to operate an electric motor, propelling the rail-mounted robot along the rail) but does not teach and Cui teaches the AI industrial computer implementing AI models and image processing unit([0022], AI based inspection system comprising field device 208.The field device 208 comprises industrial PC/industrial edge computer and deploys AI algorithm/model)
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to use AI industrial computer for inspection system as in Cui in order to perform accurate and efficient detection of defect in industrial/ manufacturing setting.
Regarding claim2, Fujimoto in view of Cui teaches the modular inspection assembly of claim 1, in which the rotational movement is around an axis that is parallel to that of the linear rail (Fujimoto: [0034], rail-mounted robot 110 is equipped with a vision sensor 114 that may be rotatable and/otherwise movable relative to rail-mounted robot 110).
Regarding claim3, Fujimoto in view of Cui teaches the modular inspection assembly of claim 1, in which the rotational movement is around an axis that is transverse to that of the linear rail(Fujimoto: [0034], rail-mounted robot 110 is equipped with a vision sensor 114 that may be rotatable and/otherwise movable relative to rail-mounted robot 110).
Regarding claim5, Fujimoto in view of Cui teaches the modular inspection assembly of claim 1, in which the rotation movement include multiple degrees of freedom (Fujimoto:[0034], rail-mounted robot 110 is equipped with a vision sensor 114 that may be rotatable and/otherwise movable relative to rail-mounted robot 110).
Regarding claim6, Fujimoto in view of Cui the modular inspection assembly of claim 1, in which the AI industrial computer configures the camera to move through a sequence preconfigured and discrete inspection poses during an inspection task (Fujimoto:[0042], processor(s) 230 also may operate motion controller 234 to propel rail-mounted robot 210 along modular rail section 208, and/or to operate one or more actuators 232 to perform various tasks in environment 100).
Regarding claim7, Fujimoto in view of Cui the modular inspection assembly of claim 1, in which the AI industrial computer configures the camera to continuously move through a tracking shot of dynamic inspection poses during an inspection task (Fujimoto:[0034], rail-mounted robot 110 is equipped with a vision sensor 114 that may be rotatable and/otherwise movable relative to rail-mounted robot 110).
Claim4 is rejected under 35 U.S.C. 103 as being unpatentable over Fujimoto in view of Cui as applied to claims 1-3, 5-7 above, and further in view of Han CN 209448818.
Regarding claim4, Fujimoto in view of Cui teaches all the limitations of claim1 above but do not teach and Han teaches the linear rail is a two-axis linear rail (abs. a visual detecting device comprising a visual detecting component, comprising a two-axis guide rail group).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to use two-axis rail system as in Han in order to move the mounted camera to perform accurate visual recognition/inspection.
Allowable Subject Matter
Claims8-22 are allowed.
The following is a statement of reasons for the indication of allowable subject matter.
The independent claim8 recites a method, performed by a workstation system, for automating deployment of AI models, the AI models being configurable to reduce task errors through real-time inspection and feedback on robotically or manually performed dexterous tasks that are predefined in the workstation system according to a sequence, the workstation system including a video inspection camera for monitoring a user-accessible workstation, a user interface display, and workstation computing device implementing the AI models, the method comprising: receiving from a user, via the user interface display, a selected action builder from a set of step-specific actions to define a step in the sequence, different action builders of the set being configured to orchestrate a corresponding Al model for processing a corresponding sensor modality input; in response to selection of the selected action builder, presenting on the user interface display an action-configuration user interface including a user-actuatable input and real-time video from the video inspection camera, the real-time video showing a region of interest of a workpiece, the user-actuatable input for capturing of the step in the sequence; repeating the receiving and the presenting for each step of the sequence performed seriatim to the workpiece at the user-accessible workstation; receiving captured data representing each step of the sequence for training corresponding AI models to configure the real-time inspection and feedback corresponding to the robotically or manually performed dexterous tasks in the sequence; and in response to a live deployment of the real-time inspection and feedback, monitoring associated sensor modality input and presenting to the user real-time feedback indicating success or failure for each step of the sequence.
Claim22 recites a workstation system for automating deployment of AI models, the AI models being configurable to reduce task errors through real-time inspection and feedback on robotically or manually performed dexterous tasks that are predefined in the workstation system according to a sequence, the workstation system comprising: a video inspection camera for monitoring a user-accessible workstation; a user interface display; and a workstation computing device implementing the AI models and configuring the workstation system to: receive from a user, via the user interface display, a selected action builder from a set of step-specific actions to define a step in the sequence, different action builders of the set being configured to orchestrate a corresponding AI model for processing a corresponding sensor modality input; in response to selection of the selected action builder, present on the user interface display an action-configuration user interface including a user-actuatable input and real-time video from the video inspection camera, the real-time video showing a region of interest of a workpiece, the user-actuatable input for capturing of the step in the sequence; repeat the receiving and the presenting for each step of the sequence performed seriatim to the workpiece at the user-accessible workstation; receive captured data representing each step of the sequence for training corresponding AI models to configure the real-time inspection and feedback corresponding to the robotically or manually performed dexterous tasks in the sequence; and in response to a live deployment of the real-time inspection and feedback, monitor associated sensor modality input and presenting to the user real-time feedback indicating success or failure for each step of the sequence.
The closest prior arts, either singularly or in combinations fails to anticipate or render the underlined limitations obvious.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GIRUMSEW WENDMAGEGN whose telephone number is (571)270-1118. The examiner can normally be reached 9:00-7:00 PM.
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, Thai Tran can be reached at (571) 272-7382. 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.
GIRUMSEW WENDMAGEGN
Primary Examiner
Art Unit 2484
/GIRUMSEW WENDMAGEGN/Primary Examiner, Art Unit 2484
Prosecution Insights