DETAILED ACTION
Claims 1-14 are currently presented for examination.
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 Arguments
Following Applicants amendments to the Claims, the objections of the Claims is Withdrawn with respect to claim 13, and Maintained with respect to the remaining claims.
Only claim 13 was addressed.
Following Applicants amendments, the 112 interpretation and rejection of the claims is Withdrawn.
Following Applicants arguments and amendments, and in light of the 2019 Patent Eligibility guidance, the 101 rejection of the Claims is Maintained.
Applicant’s Argument: The claim cannot be done mentally as it contains AI/ML techniques and operates in real-time
Examiner’s Response: The Examiner disagrees as none of these argued elements are in the claim. Assuming arguendo, the use of AI/ML is the use of a computer as a tool to perform the abstract idea. (MPEP 2106.05(f)) As seen in MPEP 2106.05(a)(I) and § 2106.05(f)(2), the court found that accelerating a process when the increased speed solely comes from the capabilities of a general-purpose computer is not sufficient to show an improvement in computer-functionality and it amounts to a mere invocation of computers or machinery as a tool to perform an existing process (see FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016)).
Applicant’s Argument: The claims are not a mental process, citing multiple sections of the specification.
Examiner’s Response: The Examiner disagrees as the present claims do not reflect the complex environment or purported improvements cited by the Applicant, with reference to the sections of the specification cited in the arguments. The present claims do not improve the functioning of the computer as well as any other technology or technical field, or recite limitations that cannot practically be performed in the mind.
Applicant’s Argument: The claims are integrated into a practical application citing the processor, memory and modules, as well as portions of the specification.
Examiner’s Response: The Examiner disagrees as the present claims do not reflect the purported improvements cited by the Applicant, with reference to the sections of the specification cited in the arguments. The present claims do not improve the functioning of the computer as well as any other technology or technical field. the use of AI/ML is the use of a computer as a tool to perform the abstract idea. (MPEP 2106.05(f)) Additionally, it is unclear what particular machine is used as only broad rigid bodies are present in the claim. Also there is no change of a particular article to a different state, as the claim does not state how the article is changed or the mechanism used for changing, amounting to mere apply it. MPEP 2106.05(f)
Applicant’s Argument: The claim amounts to significantly more citing the specification.
Examiner’s Response: The Examiner disagrees, and again notes that the argued elements are not present in the claims.
Therefore, the 101 rejection of the claims is Maintained.
Following Applicants arguments and amendments, the 103 rejection of the claims is Maintained.
Applicant’s Argument: Applicant’s arguments directed the 103 rejection are based on newly amended subject matter.
Examiner’s Response: All arguments are addressed in the 103 rejection of the claims below.
Therefore, the 103 rejection is Maintained.
Claim Objections
Claim 1 is objected to because of the following informalities: the claim recites “contact forces” multiple times, when it is not the first recitation. Appropriate correction is required.
Claim 1 is objected to because of the following informalities: the claim recites “velocity impulses” when it is not the first recitation. Appropriate correction is required.
Claim 3 is objected to because of the following informalities: the claim recites “the objects” when it is the first recitation. Appropriate correction is required.
Claim 6 is objected to because of the following informalities: the claim recites “differentiable contact impulse solver” when it is not the first recitation. Appropriate correction is required.
Claim 7 is objected to because of the following informalities: the claim is dependent on claim 5, but is antecedently tied to claim 6. For the purposes of examination, the dependency of claim 7 will be interpreted as dependent on claim 6. This is also evidenced by similar dependent claim 14 being dependent on claim 13. Appropriate correction is required.
Claim 8 is objected to because of the following informalities: the claim recites “contact forces” multiple times, when it is not the first recitation. Appropriate correction is required.
Claim 8 is objected to because of the following informalities: the claim recites “velocity impulses” when it is not the first recitation. Appropriate correction is required.
Claim 10 is objected to because of the following informalities: the claim recites “the objects” when it is not the first recitation. Appropriate correction is required.
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.
Regarding claims 1-14, are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. abstract idea) without anything significantly more.
Step 1: Claims 1-7 are directed to a system, which is a machine, which is a statutory category of invention. Claims 8-14 are directed to a method, which is a process, which is a statutory category of invention. Therefore, claims 1-14 are directed to patent eligible categories of invention.
Step 2A, Prong 1: Claims 1 and 8 recite the abstract idea of simulating collision detection of rigid bodies, constituting an abstract idea based on Mathematical Concepts including mathematical formulas or equations as well as calculations or alternatively Mental Processes based on concepts performed in the human mind, or with the aid of pencil and paper. The limitation of "… learn active contacts of the rigid bodies; and” covers mental processes including evaluating a dataset and judging if bodies are moving, alternatively this can be viewed as a mathematical concept in the form of a calculation from time series data as seen in [0017] and [0021]. Additionally, the limitation of “… apply constraints on contact forces related to a compression phase,” covers mental processes including evaluating a dataset and making a judgement about how to constrain it, alternatively this can be viewed as a mathematical concept in the form of setting up equations as seen in [0021]-[0024]. Additionally, the limitation of “apply coefficient of restitution on contact forces related to a restitution phase” covers mental processes including evaluating a dataset to make a judgment about what coefficient to apply, alternatively this can be viewed as a mathematical concept in the form of setting up equations as seen in [0021]-[0024]. Additionally, the limitation of “solve for contact forces and velocity impulses associated with the active contacts in the compression phase and the restitution phase” covers mental processes including evaluating a dataset, alternatively this can be viewed as a mathematical concept in the form of a series of equations as seen in [0022]-[0026]. Additionally, the limitation of “estimate trajectories of the rigid bodies based on the contact forces and velocity impulses, so as to define estimated trajectories and” covers mental processes including evaluating a trajectory given calculated values, alternatively this can be viewed as a mathematical concept in the form of a series of equations as seen in [0026]-[0028]. Additionally, the limitation of “wherein the solving is optimized for maximum rate of energy dissipation” covers mental processes including evaluating calculated values with a specific constraint, alternatively this can be viewed as a mathematical concept in the form of a series of equations with a specific constraint as seen in [0023]. Thus, the claims recite the abstract idea of a mental process performed in the human mind, or with the aid of pencil and paper.
Dependent claims 2-7 and 9-14 further narrow the abstract ideas, identified in the independent claims.
Step 2A, Prong 2: The judicial exception is not integrated into a practical application. In Claim 1, the additional elements of “a processor”, “a non-transitory memory”, “modules”, “a collision detector,” “a differentiable contact impulse solver” (also recited in dependent claims), as well as “a neural network module” in claims 3 and 13, as well as “a collision detector module” in claim 8, merely uses a computer device as a tool to perform the abstract idea. (MPEP 2106.05(f)) The limitations of “a conveyor system” does not integrate the judicial exception into a practical application because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h). The limitation of “based on the estimated trajectories controlling a driver of the rigid bodies in the dynamic system” only amounts to mere instructions to apply as it only recites the idea of a solution or outcome and fails to recite details of how a solution to a problem is accomplished MPEP 2106.05(f), “(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it"… In contrast, claiming a particular solution to a problem or a particular way to achieve a desired outcome may integrate the judicial exception into a practical application or provide significantly more.” Therefore, the judicial exception is not integrated into a practical application.
Dependent claims 2-7 and 9-14 further narrow the abstract ideas, identified in the independent claims, and do not introduce further additional elements for consideration beyond those addressed above.
Step 2B: Claims 1 and 8 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. In Claim 1, the additional elements of “a processor”, “a non-transitory memory”, “modules”, “a collision detector,” “a differentiable contact impulse solver” (also recited in dependent claims), as well as “a neural network module” in claims 3 and 13, as well as “a collision detector module” in claim 8, merely uses a computer device as a tool to perform the abstract idea. (MPEP 2106.05(f)) The limitations of “a conveyor system” does not amount to significantly more because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h). The limitation of “based on the estimated trajectories controlling a driver of the rigid bodies in the dynamic system” only amounts to mere instructions to apply as it only recites the idea of a solution or outcome and fails to recite details of how a solution to a problem is accomplished MPEP 2106.05(f), “(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it"… In contrast, claiming a particular solution to a problem or a particular way to achieve a desired outcome may integrate the judicial exception into a practical application or provide significantly more.” Therefore, the claim as a whole does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered alone or in combination, do not amount to significantly more than the judicial exception. As stated in Section I.B. of the December 16, 2014 101 Examination Guidelines, “[t]o be patent-eligible, a claim that is directed to a judicial exception must include additional features to ensure that the claim describes a process or product that applies the exception in a meaningful way, such that it is more than a drafting effort designed to monopolize the exception.”
The dependent claims include the same abstract ideas recited as recited in the independent claims, and merely incorporate additional details that narrow the abstract ideas and fail to add significantly more to the claims.
Dependent claims 2 and 9 are directed to further defining the rigid bodies, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes” or alternatively “Mathematical Concepts.”
Dependent claims 3 and 10 are directed to further defining the method of learning, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes” or alternatively “Mathematical Concepts.”
Dependent claims 4 and 11 are directed to further defining the method of learning, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes” or alternatively “Mathematical Concepts.”
Dependent claims 5 and 12 are directed to further defining the learning tasks, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes” or alternatively “Mathematical Concepts.”
Dependent claims 6 and 13 are directed to further defining the determination of inverse inertia, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes” or alternatively “Mathematical Concepts.”
Dependent claims 7 and 14 are directed to further defining the inverse inertia, which further narrows the abstract idea identified in the independent claim, which is directed to “Mental Processes” or alternatively “Mathematical Concepts.”
Accordingly, claims 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without anything significantly more.
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, 6-8 and 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over Stewart “Rigid-Body Dynamics with Friction and Impact” in view of Todorov “Convex and analytically-invertible dynamics with contacts and constraints: Theory and implementation in MuJoCo”, in view of Keshmiri USPPN 2017/0364076.
Regarding claim 1, Stewart teaches learn active contacts of the rigid bodies; and (Abstract, Section 1-1.2, rigid bodies come into contact with a surface or other objects)
apply constraints on contact forces related to a compression phase, (Section 1.2 and 4.4, Using Poisson’s approach constrains are applied that limit the impact and bounce behavior as well as friction.)
apply coefficient of restitution on contact forces related to a restitution phase, (Section 1.2 and 2.1.2, a coefficient of restitution is applied to contact forces related to a restitution phase)
solve for contact forces and velocity impulses associated with the active contacts in the compression phase and the restitution phase, and (Section 1-1.4 and 2.1, contact forces are solved for; Sections 1-1.3, 2.1 and 4.4, Figure 1.3, 4.4 and 4.5, as well as velocity impulses during both phases)
estimate trajectories of the rigid bodies based on the contact forces and velocity impulses, so as to define estimated trajectories and (Section 1.1, 2.1.2, 3.1 and 4.2, Figure 4.1 and 4.5, trajectories based on contact forces and velocity impulses are solved)
wherein the solving is optimized for maximum rate of energy dissipation. (Section 1.1 the energy dissipation is maximized)
Stewart does not explicitly teach a processor; and a non-transitory memory having stored thereon modules executed by the processor, the modules comprising: a collision detector configured to …; and a differentiable contact impulse solver
Todorov teaches a processor; and a non-transitory memory having stored thereon modules executed by the processor, the modules comprising: a collision detector configured to …; and a differentiable contact impulse solver (Abstract, Section VI (B), a desktop computer is used to determine contact dynamics including by applying impulses)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Stewart with Todorov as the references deal with rigid body contacts, in order to implement a system that uses a computer to perform contact simulation and determines an inverse inertia that is positive semi definite. Todorov would modify Stewart by using a computer to perform contact simulation and determining an inverse inertia that is positive semi definite. The benefit of doing so the simulation is stable and it can run 100 times faster than real-time on a single core of a desktop processor. Also, it is possible to use projected and active-set methods in the forward dynamics, wish allows the system to specialize it to dynamic simulation. (Todorov Abstract, Section III(C))
The combination of Stewart and Todorov does not explicitly teach based on the estimated trajectories controlling a driver of the rigid bodies in the dynamic system,
Keshmiri teaches based on the estimated trajectories controlling a driver of the rigid bodies in the dynamic system, (Figures 1 and 2, [0035]-[0036], the robots are controlled by a driver based on the determined trajectories)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Stewart and Todorov with Keshmiri as the references deal with rigid body contacts, in order to implement a system that drives the rigid bodies with the determined trajectories. Keshmiri would modify Stewart and Todorov by driving the rigid bodies with the determined trajectories. The benefit of doing so is a collision free path can be generated. (Keshmiri [0065])
Regarding claim 6, the combination of Stewart, Todorov and Keshmiri teach the limitations of claim 1. Stewart does not explicitly teach wherein differentiable contact impulse solver is further configured to determine inverse inertia in contact space.
Todorov teaches wherein differentiable contact impulse solver is further configured to determine inverse inertia in contact space. (Section II (C) and V, an inverse inertia is used)
See motivation of claim 1.
Regarding claim 7, the combination of Stewart, Todorov and Keshmiri teach the limitations of claim 6. Stewart does not explicitly teach wherein the inverse inertia is positive semi-definite.
Todorov teaches wherein the inverse inertia is positive semi-definite. (Section III(B), the inverse inertia is positive semi-definite)
In regards to claim 8, it is the method embodiment of claim 1 with similar limitations to claim 1, and is such rejected using the same reasoning found in claim 1.
In regards to claim 13, it is the method embodiment of claim 6 with similar limitations to claim 6, and is such rejected using the same reasoning found in claim 6.
In regards to claim 14, it is the method embodiment of claim 7 with similar limitations to claim 7, and is such rejected using the same reasoning found in claim 7.
Claims 2 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Stewart “in view of Todorov, in view of Keshmiri and in view of Gupta “An experimental investigation on a fluidized motion conveying system”.
Regarding claim 2, the combination of Stewart, Todorov and Keshmiri teach the limitations of claim 1. Stewart, Todorov and Keshmiri does not explicitly teach wherein the rigid bodies relate to particulate material transported by a conveyor system.
Gupta teaches wherein the rigid bodies relate to particulate material transported by a conveyor system. (Abstract, Sections 1-2, Figure 1, particulate is transported by a conveyor system)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Stewart, Todorov and Keshmiri with Gupta as the references deal with characterization of motion, in order to implement a system that uses a conveyor system to transport particulate. Gupta would modify Stewart, Todorov and Keshmiri by using a conveyor system to transport particulate. The benefit of doing so is the material mass flow rate of any given solid can be determined. (Gupta Section 5)
In regards to claim 9, it is the method embodiment of claim 2 with similar limitations to claim 2, and is such rejected using the same reasoning found in claim 2.
Claims 3-5 and 10-12 are rejected under 35 U.S.C. 103 as being unpatentable over Stewart “in view of Todorov, in view of Keshmiri and in view of Finzi et al “Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints”.
Regarding claim 3, the combination of Stewart, Todorov and Keshmiri teach the limitations of claim 1. Stewart, Todorov and Keshmiri does not explicitly teach wherein the modules further comprise a neural network module configured to learn physical motions of the objects incorporating physics priors.
Finzi teaches wherein the modules further comprise a neural network module configured to learn physical motions of the objects incorporating physics priors. (Sections 1, 2 and 6, Figures 1-4, a neural network is used that incorporates physics for physical motion)
It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Stewart, Todorov and Keshmiri with Finzi as the references deal with characterization of motion, in order to implement a system that uses a neural network that incorporates physical motions and backpropagation. Finzi would modify Stewart, Todorov and Keshmiri by using a neural network that incorporates physical motions and backpropagation. The benefit of doing so is embedding problems in Cartesian coordinates simplifies the Hamiltonian and the Lagrangian that must be learned, resulting in systems that can be accurately modelled by neural networks with 100 times less data. (Finzi Section 1)
Regarding claim 4, the combination of Stewart, Todorov and Keshmiri teach the limitations of claim 1. Stewart, Todorov and Keshmiri does not explicitly teach wherein the differentiable contact impulse solver is further configured to perform backpropagation during simulation to perform learning of parameters.
Finzi teaches wherein the differentiable contact impulse solver is further configured to perform backpropagation during simulation to perform learning of parameters. (Section 2, Backpropagation is used)
See motivation of claim 3
Regarding claim 5, the combination of Stewart, Todorov, Keshmiri and Finzi teach the limitations of claim 4. Stewart teaches wherein the parameters include at least one of coefficient of friction and coefficient of restitution. (Section 1.1 and 1.2, a coefficient of friction and restitution is used)
In regards to claim 10, it is the method embodiment of claim 3 with similar limitations to claim 3, and is such rejected using the same reasoning found in claim 3.
In regards to claim 11, it is the method embodiment of claim 4 with similar limitations to claim 4, and is such rejected using the same reasoning found in claim 4.
In regards to claim 12, it is the method embodiment of claim 5 with similar limitations to claim 5, and is such rejected using the same reasoning found in claim 5.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chang et al. USPPN 2020/0114449: Also teaches path planning and controlling a robot based on the determined path.
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.
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/MICHAEL EDWARD COCCHI/Primary Examiner, Art Unit 2188