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 .
This is in response to Applicant’s communication filed on 2/3/26, wherein:
Claims 19-44 are currently pending;
Claims 1-18 have been cancelled;
Claims 19-32, 39-40 have been elected without traverse. Thus, claims 33-38 and 41-44 are withdrawn as to non-elected claims.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 19-24, 26-31, 39-40 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more. With respect to step 2A, prong 1, The claim(s) 19, 26, 39-40 as rewritten recite “apply a specific joint descriptor analyzer to the input data, the joint type analyzer generate intermediate data; and determine from the output data at least one joint in the virtual kinematic device” are process, under its broadest reasonable interpretation, covers performance of the limitation in the mind (e.g. including observation, evaluation, judgement and opinion). For example, as for the step “apply a specific joint descriptor analyzer to the input data”, the context of this limitation encompass that that a person can use pen and paper to write down the joint information e.g. value of joint angle, value of joint rotation and use this data for analyzing. As for the step “determine from the output data at least one joint in the virtual kinematic device”, this encompass a person can mentally determine what is the particular joint type (e.g. rotation joint, or spherical joint) based on observing or receiving the output data. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under the 2A prong 1 analysist.
With respect to the 2A prong 2 analysist, this judicial exception is not integrated into a practical application. In particular, the claim using a processor to perform the abstract idea recited high level of generality (i.e. a generic processor) such that it amounts no more than mere instructions to apply the exception using a generic component. Further, “receive input data and outputting data” are not considered as significantly more than the abstract idea because they are merely data gathering. In additional, the recites feature in the method claim 1, 26, 39-40 “a joint in a virtual kinematic device having two links” and “the joint type analyzer being modeled with a function trained by a machine learning (ML algorithm)” are considered as general link to the technological environment and there is no indication of controlling the kinematic device in the claim as well as no indication with respect to training the model using the machine learning algorithm.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
With respect to the 2B analysis, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discuss above with respect to integration of the abstract idea into a practical application, the additional element of using generic computer component to perform the abstract idea amounts no more than mere instructions to apply the excepting using a generic computer component. Further, the recites feature in the method claim 1, 26, 39-40 “a joint in a virtual kinematic device having two links” and “the joint type analyzer being modeled with a function trained by a machine learning (ML algorithm)” are considered as general link to the technological environment and there is no indication of controlling the kinematic device in the claim as well as no indication with respect to training the model using the machine learning algorithm. In addition, “receive input data and outputting data” are not considered as significantly more than the abstract idea because they are merely data gathering and is considered as well understood routine conventional as it has been held by the court. Particularly, receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; (see MPEP 2106.05(d)). Viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself.
Dependent claims 20-24, 27-31 are merely add further details of the abstract steps/elements recites in claims 1, 26 without including an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaning limitation beyond general linking the use of an abstract idea to a particular technological environment. Therefore, they are rejected for the same rational and are not paten eligible.
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)(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.
(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.
Claim(s) 19-32, 39 and 40 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by MINOYA (US 2021/0237270).
As for claim 19, MINOYA discloses a method for determining, by a data processing system, a joint in a virtual kinematic device, the virtual kinematic device being a virtual device having at least one kinematic capability that is defined by at least two links of the virtual device and a joint connecting the two links {see at least figure 1, 2, pars. 0019-0020, 0031 “simulation using the 3D model robot arm 20}, and the joint being defined by a joint type and by a joint descriptor for defining motion capabilities of a specific joint type {see at least par. 0019 e.g. rotary joint, linear joint} ; the method joint
comprising:
receiving input data containing data on two point cloud representations of two given links of a given virtual kinematic device {see at least figure 3, at least pars. 0022, 0030-0031 e.g. the joint state acquisition unit 104 acquires the joint state of the robot arm 20. The joint state acquisition unit 104 may acquire the joint angles (joint state) of the joints Jo1 to Jo4 ….acquire the joint state of the actual robot arm 20, or may acquire the joint state on a simulation using the 3D model robot arm 20};
applying a joint type analyzer to the input data, the joint type analyzer being modeled with a function trained by a machine learning (ML) algorithm and the joint type analyzer generating intermediate data {see at least figures 6-7, pars. 0011-001, 0031-0032, pars. 0062-0063 which discloses obtaining a joint state only by a machine learning model; use the learning result of machine learning in which the joint state of the robot arm 20 is input and the three dimensional grid data is output; par. 0035 discloses the joint state of the start (i.e., start joint state) of the robot arm 20, and the joint state of the goal (i.e., goal joint state) of the robot arm 20 are input }
providing the intermediate data containing data for selecting a specific joint type associated with the two given links; applying the selected specific joint descriptor analyzer to the input data, the specific joint descriptor analyzer being modeled with a function trained by a ML algorithm and the specific joint descriptor analyzer generating output data {see at least figures 6-7, pars. 0061-0062 which discloses inputting the specific type of joint (target joint state, and joint state)}
providing the output data containing specific joint descriptor data for determining the mutual motion capabilities of the specific joint type associated with the two given links; and determining from the output data at least one joint in the virtual kinematic device {see at least figures 5, 6 and 7, pars. 0062-0063, 0087 discloses e.g. the outputting the three dimensional grid data of the joint state}.
As for claim 20, MINOYA discloses wherein the joint type is selected from the group consisting of: a linear joint; a rotational joint; a spherical joint; a cylindrical joint; a helical joint; and a planar joint {see at least par. 0019}.
As for claim 21, MINOYA discloses wherein the joint descriptor data is one or more selected from the group consisting of: spatial data for defining a direction; spatial data for defining a location; scalar data for defining a helical pitch; and spatial data for defining a direction, location and/or helical pitch {see at least pars. 0029-0030}.
As for claim 22, MINOYA discloses wherein the data on the point cloud representation include data selected from the group consisting of: coordinates data; color data; entity identifiers data; surface normal data; and other features extracted from a computer vision technique or from another machine learning (ML) module {see at least pars. 0029-0032}.
As for claim 23, MINOYA discloses comprises receiving the input data from a ML module trained to identify two links from a point cloud representation {see at least figures 6-7, pars. 0031-0032; 0062-0063}.
As for claim 24, MINOYA discloses the input data from a 3D model of the virtual kinematic device {see at least pars. 0026, 0029-0032}
As for claim 25, MINOYA discloses controlling at least one manufacturing operation performed by a kinematic device in accordance with outcomes of a computer-implemented simulation of a corresponding set of virtual manufacturing operations of a corresponding virtual kinematic device {see at least pars. 0051, 0106}.
As for claims 26-32, 39-40, the limitations of these claims have been noted in the rejection above. They are therefore rejected for the same reason sets forth above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Arora et al (US 2010/0030532): system and method for digital human model prediction and simulation.
Schmidt et al (US 2023/0133725): a computer-implemented method for designing a 3D modeled object representing a transmission mechanism with a target 3D motion behavior.
Gomez (US 2023/0240767): Techniques for selective joint floating in a computer assisted system.
Pelletier-Doyle et al (US 2008/0024507): The complexity of a CAD model is reduced while its kinematic integrity is maintained by unloading certain data associated with the CAD model from the main memory of a computing device used in the design of the CAD model.
Fuerst et al (US 11,166,765): A virtual surgical robot being built from kinematic data is rendered to a display. A user input is received to effect a movement or a configuration of the virtual surgical robot.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Kira Nguyen whose telephone number is (571)270-1614. The examiner can normally be reached on Monday to Friday 9:00-5:00 ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Khoi Tran can be reached on 571-272-6919. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KIRA NGUYEN/Primary Examiner, Art Unit 3656