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 .
Status of claims
The following claims have been rejected or allowed for the following reasons:
Claim(s) 7 is rejected under 35 USC § 102
Claim(s) 8-9 is rejected under 35 USC § 103
Claim(s) 1-6 and 10-20 are withdrawn based on applicants response to restriction
Information Disclosure Statement
The information disclosure statement/statements (IDS) were filed on 9/15/25. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner
Claim Rejections - 35 USC § 102
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 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 7 is/are rejected under 35 U.S.C. 102 as being unpatentable over as applied to Claussen (US 20220347853 A1).
Regarding claim 7 Claussen teaches A method comprising: receiving one or more images of an object held by a robotic component, wherein each image is associated with a respective perturbation pose of the robotic component that is at an offset relative to a nominal pose; providing the one or more images of the object as input to a machine learning model that is configured to map an input comprising one or more images of an object to an output comprising data representing the offset between a perturbation pose of the robotic component and the nominal pose; (Claussen [0027] reads “The controller 101 uses a machine learning-based inference unit 211, such as a DNN model, with a dedicated hardware accelerator to process two image inputs 201, 202 to determine a configuration error 215. The configuration error 215 is the difference between a desired configuration image 201 and the current configuration 202 image for workpiece 205,”);
and generating correction data representing commands to move the robotic component based on the output to reduce the offset of the perturbation pose relative to the nominal pose so that the object is closer to a goal pose. (Claussen [0027] reads “Dynamic controller 212 operates by receiving a low-dimensional quantity of configuration error 215 (e.g., a relative pose) and in response, generates a control action signal 216 for positional adjustment of the robotic device 220 in 3D space which reduces the error by moving workpiece 205 nearer to the desired configuration 201. In an embodiment, each control action signal 216 may act on a pulse width modulation of power to a servo motor within robot 220 for fine resolution of motion control of a gripper that has grasped the workpiece 205 and is tasked with placement of the workpiece 205 to a target position represented by the image of desired configuration 201.”);
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.
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.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over as applied Claussen, in further view of Nakamura (US 20230390935 A1).
Regarding claim 8 Claussen teaches The method of claim 7.
Claussen does not teach wherein the offset between the perturbation pose of the robotic component and the nominal pose comprises an offset in any one of: translation, roll rotation, pitch, or yaw.
Nakamura in analogous art, teaches wherein the offset between the perturbation pose of the robotic component and the nominal pose comprises an offset in any one of: translation, roll rotation, pitch, or yaw. (Nakamura [0034] reads “Note that the operation command output by the learning type control device 2 is not limited to the target angle of each of the joints, and may be, for example, X, Y, and Z positions of the end effector 12 and position and orientation information represented by yaw, pitch, and roll angles. In this case, the robot control device 5 may be configured to internally calculate a solution of inverse kinematics of the working robot 6 and output the motor current of the working robot 6 as the control command.”);
It would have been obvious to one with ordinary skill in the art, before the effective filing date of the claimed invention to have modified the teachings of Claussen with that of Nakamura to provide a system to improve the accuracy of manipulation. (Nakamura [0005] reads “Meanwhile, the learning unit (trained model) which has been subjected to machine learning is basically an approximate inference device based on statistics, and can perform inference with high accuracy in a case where there is an input in a situation close to a situation where the learning unit has been subjected to the machine learning, but the inference accuracy of the learning unit decreases in a case where there is an input in a situation different from the time where the learning unit has been subjected to the machine learning.”);
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over as applied to Claussen, in further view of Li (Localization and manipulation of small parts using GelSight tactile sensing | NPL | 2014).
Regarding claim 9 Claussen teaches The method of claim 7, wherein a type of each image comprises any one of: an optical image, data derived from an optical image, (Claussen [0028] reads “The robot acquires 301 visual data of the object using, for example, one or more cameras (e.g., 3D cloud point cameras) arranged on or near the robot.”);
Claussen does not teach a tactile image, or data derived from a tactile image.
Li in analogous art, teaches a tactile image, or data derived from a tactile image. (Li page 2 paragraph 2 reads “The tactile map is a model of what the object surface is expected to feel like as a function of contact configuration and is created prior to manipulation (see Figure 1 (b)). During manipulation, the robot perceives tactile information regarding the pose of the object in the hand.”);
It would have been obvious to one with ordinary skill in the art, before the effective filing date of the claimed invention to have modified the teachings of Claussen with that of Li to provide an improved system for small parts manipulation with increased accuracy. (Li page 1 paragraph 2 reads “Small parts manipulation and insertion is an important robotics problem that has applications in manufacturing, space and hazardous environments, and medicine. A good example is the problem of grasping and inserting a USB cable, as shown in Figure 1. This insertion is challenging because the the tolerances are very low - less than plus or minus one millimeter. Nevertheless, this type of fine manipulation problem is important. Today, human factory workers are often employed to perform fine insertions and manipulation of exactly this kind.”);
Other references not Cited
Throughout examination other references were found that could read onto the prior art. Though these references were not used in this examination they could be used in future examination and could read on the contents of the current disclosure. These references are, Xu (US 20230339118 A1); Homberg (US 20190337152 A1); Sampedro (US 10058995 B1).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN MARTIN O'MALLEY whose telephone number is (571)272-6228. The examiner can normally be reached Mon - Fri 9 am - 5 pm.
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/JOHN MARTIN O'MALLEY/Examiner, Art Unit 3658 /KHOI H TRAN/Supervisory Patent Examiner, Art Unit 3656