Prosecution Insights
Last updated: April 19, 2026
Application No. 18/788,816

SCALABLE SOFT BODY LOCOMOTION

Non-Final OA §103
Filed
Jul 30, 2024
Examiner
YANG, ANDREW GUS
Art Unit
2614
Tech Center
2600 — Communications
Assignee
Roblox Corporation
OA Round
1 (Non-Final)
69%
Grant Probability
Favorable
1-2
OA Rounds
2y 10m
To Grant
77%
With Interview

Examiner Intelligence

Grants 69% — above average
69%
Career Allow Rate
384 granted / 558 resolved
+6.8% vs TC avg
Moderate +8% lift
Without
With
+8.3%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
25 currently pending
Career history
583
Total Applications
across all art units

Statute-Specific Performance

§101
9.2%
-30.8% vs TC avg
§103
61.9%
+21.9% vs TC avg
§102
17.1%
-22.9% vs TC avg
§112
6.6%
-33.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 558 resolved cases

Office Action

§103
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. Claim(s) 1, 3-4, 16, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reynolds et al. (U.S. PGPUB 20020180739) in view of Miller, IV (U.S. PGPUB 20210166459). With respect to claim 1, Reynolds et al. disclose a computer-implemented method to animate a soft body, the computer-implemented method comprising: building a control space having information representative of forces corresponding to natural movement of the soft body, wherein the soft body is part of a virtual environment (paragraph 41, The simulator creates a soft body by creating a set of point masses, (one for each vertex of the triangular mesh) and a set of force components to act on these point masses. These force components describe how the point masses will tend to move when the body is deformed). However, Reynolds et al. do not expressly disclose coupling the control space and a physical space to define a controller pipeline that performs animation of the soft body; performing the animation of the soft body using the controller pipeline; and causing the animation of the soft body to be displayed in a user interface of the virtual environment. Miller, IV, who also deals with animating objects, discloses a method for coupling the control space and a physical space to define a controller pipeline that performs animation of the soft body (paragraph 259, The process 1900 can combine the animation state space Sa and the physical state space Sp into a state space Sa ⋅ Sp); performing the animation of the soft body using the controller pipeline (paragraph 264, the wearable display system 200 can use the policies to animate the motion of an avatar in the environment of the wearer of the system 200); and causing the animation of the soft body to be displayed in a user interface of the virtual environment (paragraph 233, The system 690 can select a control policy (e.g., available from the policy block 1536), lay down the selected control policy, and execute the policy so that the avatar is rendered as moving to a new position (and with a. desired pose) in the environment). Reynolds et al. and Miller, IV are in the same field of endeavor, namely computer graphics. Before the effective filing date of the claimed invention, it would have been obvious to apply the method of coupling the control space and a physical space to define a controller pipeline that performs animation of the soft body; performing the animation of the soft body using the controller pipeline; and causing the animation of the soft body to be displayed in a user interface of the virtual environment, as taught by Miller, IV, to the Reynolds et al. system, because the runtime engine can efficiently and quickly (e.g., in real time) use the policies (e.g., as lookups in a table) to identify the best way to move the avatar from a starting state (e.g., starting position or starting pose) to a desired ending (or goal) state (e.g., ending position or ending pose) (paragraph 39 of Miller, IV). With respect to claim 3, Reynolds et al. as modified by Miller, IV disclose the computer-implemented method of claim 1, wherein the forces corresponding to the natural movement of the soft body are forces that arise from rotational stresses within the soft body (Reynolds et al.: paragraph 52, this new shape probably includes some rotational and translational components and not just pure deformation (i.e. under the influences of the external forces the object has both changed shape AND rotated AND moved in space)). With respect to claim 4, Reynolds et al. as modified by Miller, IV disclose the computer-implemented method of claim 1, wherein the forces corresponding to the natural movement of the soft body are contact forces applied to the soft body from one or more other bodies that are part of the virtual environment (Reynolds et al.: paragraph 59, A process calculates the forces for the soft body given its deformation from the starting position. Given a set of forces (fexternali) acting on the n point masses due to large-scale effects (e.g. gravity), collisions, and other user applied forces the simulator adds internal forces arising from skin and volumetric force components created as described above). With respect to claim 16, Reynolds et al. as modified by Miller, IV disclose a non-transitory computer-readable medium with instructions stored thereon (Miller, IV: paragraph 328: Code modules or any type of data may be stored on any type of non-transitory computer-readable medium) that, responsive to execution by a processing device, causes the processing device to perform operations of claim 1; see rationale for rejection of claim 1. It would have been obvious to implement the method on a non-transitory computer readable medium because this would allow for generation and rendering of computer graphics. With respect to claim 19, Reynolds et al. as modified by Miller, IV disclose a system (Miller, IV: paragraph 45, FIG. 2 illustrates an example of wearable system 200), comprising: a memory with instructions stored thereon; and a processing device, coupled to the memory, the processing device configured to access the memory and execute the instructions (Miller, IV: paragraph 50, The local processing and data module 260 may comprise a hardware processor, as well as digital memory, such as non-volatile memory (e.g., flash memory), both of which may be utilized to assist in the processing, caching, and storage of data), wherein the instructions cause the processing device to perform operations of claim 1; see rationale for rejection of claim 1. It would have been obvious to execute the method on a system comprising memory and a processing device because this would allow for generation and rendering of computer graphics. Claim(s) 2, 5, 17-18, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reynolds et al. (U.S. PGPUB 20020180739) in view of Miller, IV (U.S. PGPUB 20210166459) and further in view of Kim et al. (U.S. Patent No. 10,366,184). With respect to claim 2, Reynolds et al. as modified by Miller, IV disclose the computer-implemented method of claim 1. However, Reynolds et al. as modified by Miller, IV do not expressly disclose building the control space is based on eigenfunctions of elastic energy of the soft body. Kim et al., who also deal with animating objects, disclose a method wherein building the control space is based on eigenfunctions of elastic energy of the soft body (column 24, lines 25-35, the simulation application determines eigenvalues and eigenvectors of the Hessian of the stable Neo-Hookean energy). Reynolds et al., Miller, IV, and Kim et al. are in the same field of endeavor, namely computer graphics. Before the effective filing date of the claimed invention, it would have been obvious to apply the method wherein building the control space is based on eigenfunctions of elastic energy of the soft body, as taught by Kim et al., to the Reynolds et al. as modified by Miller, IV system, because the stable Neo-Hookean energy tends to produce more realistic results than other elastic energy models such as the commonly used co-rotational model (column 27, lines 1-4 of Kim et al.). With respect to claim 5, Reynolds et al. as modified by Miller, IV and Kim et al. disclose the computer-implemented method of claim 1, wherein building the control space comprises simulating the forces corresponding to the natural movement of the soft body by solving an elastodynamic optimization problem using auxiliary variables as degrees of freedom (Kim et al.: column 13, lines 55-64, Panel A shows an example volumetric mesh, representing the arms and torso of a character, that is a hexahedral lattice mesh 310 with 45,809 elements and 156,078 degrees of freedom and is driven by 13 internal skeletal bones 215. Illustratively, a quasistatic simulation uses the stable Neo-Hookean energy, and a Poisson's ratio of ν=0.488, in a number of Newton iterations that converge to a minimum of the stable Neo-Hookean energy, in order to determine an energy-minimizing configuration of the hexahedral mesh). It would have been obvious to apply the method wherein building the control space comprises simulating the forces corresponding to the natural movement of the soft body by solving an elastodynamic optimization problem using auxiliary variables as degrees of freedom because the simulation application may then pose and render a surface mesh using the determined configuration (column 13, lines 53-55 of Kim et al.). With respect to claim 17, Reynolds et al. as modified by Miller, IV and Kim et al. disclose the non-transitory computer-readable medium of claim 16 for implementing the method of claim 2; see rationale for rejection of claim 2. With respect to claim 18, Reynolds et al. as modified by Miller, IV and Kim et al. disclose the non-transitory computer-readable medium of claim 16 for implementing the method of claim 5; see rationale for rejection of claim 5. With respect to claim 20, Reynolds et al. as modified by Miller, IV and Kim et al. disclose the system of claim 19 for executing the method of claim 2; see rationale for rejection of claim 2. Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reynolds et al. (U.S. PGPUB 20020180739) in view of Miller, IV (U.S. PGPUB 20210166459) and further in view of McCulloch (U.S. PGPUB 20160134840). With respect to claim 13, Reynolds et al. as modified by Miller, IV disclose the computer-implemented method of claim 1. However, Reynolds et al. as modified by Miller, IV do not expressly disclose the controller pipeline is associated with time-varying state-dependent values for controller activations that achieve specific animation task objectives and wherein a controller of the controller pipeline is trained using reinforcement learning to achieve the specific animation task objectives when performing animation of the soft body. McCulloch, who also deals with animating objects, discloses a method wherein the controller pipeline is associated with time-varying state-dependent values for controller activations that achieve specific animation task objectives (paragraph 94, the avatar representation is driven by optimized input in real-time by using the best quality input to drive avatar animation when there is more than one input to the model, paragraph 112, The 4D avatar model distinguishes the user from their surroundings, and in real-time generates and animates a lifelike/photorealistic 3D avatar) and wherein a controller of the controller pipeline is trained using reinforcement learning to achieve the specific animation task objectives when performing animation of the soft body (paragraph 93, the avatar representation is updated while in use, to refine representation by a training process, paragraph 273, the model is improved with use, as more video input provides for greater detail and likeness, and improves cues and trajectories to mimic expressions and behaviors). Reynolds et al., Miller, IV, and McCulloch are in the same field of endeavor, namely computer graphics. Before the effective filing date of the claimed invention, it would have been obvious to apply the method wherein the controller pipeline is associated with time-varying state-dependent values for controller activations that achieve specific animation task objectives and wherein a controller of the controller pipeline is trained using reinforcement learning to achieve the specific animation task objectives when performing animation of the soft body, as taught by McCulloch, to the Reynolds et al. as modified by Miller, IV system, because the more time the user spends creating the model, the better the likeness because the model automatically self-improves (paragraph 274 of McCulloch). Allowable Subject Matter Claims 6-12 and 14-15 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. The following is a statement of reasons for the indication of allowable subject matter: none of the cited art teaches or suggests elastodynamic optimization with reduced degrees of freedom of a subspace, i.e., the simulating comprises: using a subspace approximation for the degrees of freedom; and rewriting the elastodynamic optimization problem in terms of reduced space degrees of freedom of the subspace approximation. None of the cited art teaches or suggests minimizing Taylor expanded energy with control functions that are orthogonal to each other, i.e., the control space is built based on control functions that minimize a Taylor expanded energy of the soft body and that generate a non-null set of solution control functions that are orthogonal to each other. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. U.S. PGPUB 20180247158 to Yang for a method of a reduced deformable simulation pipeline U.S. PGPUB 20180165864 to Jin et al. for a method of combining summed force arrays to animate an avatar U.S. PGPUB 20160328628 to Bhat et al. for a method of using an objective function to project an error onto a control space of the animation model U.S. PGPUB 20140198106 to Sumner et al. for a method of simulating dynamics of a character in a subspace of deformations. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW GUS YANG whose telephone number is (571)272-5514. The examiner can normally be reached M-F 9 AM - 5:30 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, Kent Chang can be reached at (571)272-7667. 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. /ANDREW G YANG/Primary Examiner, Art Unit 2614 3/17/26
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Prosecution Timeline

Jul 30, 2024
Application Filed
Mar 17, 2026
Non-Final Rejection — §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
69%
Grant Probability
77%
With Interview (+8.3%)
2y 10m
Median Time to Grant
Low
PTA Risk
Based on 558 resolved cases by this examiner. Grant probability derived from career allow rate.

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