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 .
Responsive to communications on 02/15/2023
Claims 1-20 pending in the application
Claims 12 and 13 are objected to
Claims 1-20 are rejected
Priority
Responsive to Application Data Sheet received on 2/15/2023. No claim to foreign or domestic priority made in the Application Data Sheet. Application Data Sheet accepted by the examiner.
Information Disclosure Statement
Responsive to IDS received on 02/15/2023. IDS form accepted by examiner. All references considered.
Drawings
Responsive to drawings received on 02/15/2023. The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because:
The following reference character(s) not mentioned in the description: (438)
Fig. 5 Labels 590 is labeled as “Start”. This seems to be improperly labeled. Examiner assumes this was meant to be labeled as “End”
Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
Responsive to abstract received on 02/15/2023. Abstract less than 150 words and contains no legal or implied phraseology. Abstract is accepted by the examiner.
Claim Objections
Claims 12-16 are objected to for the following informalities:
Claim 12 states “wherein the definition includes a definition of body shapes and materials for the EAPs”
as well as “a body of the skin system” Later on the claim states, “wherein the optimized shape and the optimized thickness are selected such that the outer surface of the body substantially matches the target shape at the predefined time during the operations of the mechanical assembly,” The claim should specify the “body” belongs to the skin system.
Claim 13 states “wherein the EAPs are formed of a material with a hardness greater than a hardness of the material used to form the body.“ The claim should specify the “body” belongs to the skin system.
Claims 14-16 are objected to for reliance on the above claims.
Appropriate correction is required.
Claim Interpretation
“integrally bound”: Various claims recite “whereby the EAPs are not integrally bound to the skin body.” From what the examiner understands, “integrally bound” refers to when the EAP is connected to the skin in a way that cannot be removed. For instance when the skin is molded around the EAP.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "the mechanical assembly design" in line 5. There is insufficient antecedent basis for this limitation in the claim.
Claim 8 recites the limitation "the skin system” There is insufficient antecedent basis for this limitation in the claim.
Claim 10 recites the limitation "the control parameters of motors” There is insufficient antecedent basis for this limitation in the claim.
Claim 11 recites the limitation "the mechanical assembly” There is insufficient antecedent basis for this limitation in the claim.
Claim 11 recites the limitation "the definition of the optimized design” There is insufficient antecedent basis for this limitation in the claim.
Claim 11 recites the limitation "the skin system” There is insufficient antecedent basis for this limitation in the claim.
Claim 12 recites the limitation “the user input” There is insufficient antecedent basis for this limitation in the claim. Claim 1 recites a user input, claim 12 which is independent does not.
Claim 17 recites the limitation “the mechanical assembly design” in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claims 2-7, 13-16, and 18-20 are rejected due to their dependence on the above 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 1-5, 12-14, and 17-19 are rejected under 35 U.S.C. 101 because the claimed invention recites a judicial exception, an abstract idea, which has not been integrated into practical application and the claims further do not recite significantly more than the judicial exception.
Claim 1
Step 1: Is the claimed invention one of the four statutory categories? :
YES. The claim recites A system for optimizing design of an elastomeric skin for covering a mechanical assembly, comprising: which is a machine.
Step 2A Prong 1, inquiry "Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?":
YES. Claim 1 recites, generating an optimized design for the skin by generating an optimized shape of the body and an optimized thickness of the body based on the initial shape and the initial thickness, wherein the optimized shape and the optimized thickness are selected such that the outer surface of the body of the skin substantially matches the target shape at the predefined time during the operations of the mechanical assembly.
This claim limitation pertains to an optimization process. The “skin design program” takes in input. These inputs are “an initial shape” and “an initial thickness.” The program outputs an “optimized shape” and “optimized thickness.” This input to output conversion is guided by the goal of matching a target shape for the assembly at a predefined time during operations of the assembly. As understood by the examiner, this process encompasses choosing a shape and thickness for the robot skin, so that the robot skin is optimized in a facial task (smiling). This is a planning step used in the design of skin systems.
As stated in paragraph 5 of the specifications, “To date, skin systems have typically been designed and fabricated through time- consuming manual processes that often relied heavily on the skill of the artisans involved in the process.“
MPEP 2106.04(a)(2)(III) states “Accordingly, the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions. “ As outlined, this claim limitation encompasses observing the initial values, and evaluating what the optimized values should be based on expert judgement to match a target shape.
Because this limitation is a mental design process, which can be performed by artisans of the field, this claim recites a mental process and the claim recites an abstract idea.
Step 2A Prong 2, Does the claim recite additional elements that integrate the judicial exception into a practical application?
NO. Claim 1 additionally recites a computing device configured to perform the following:
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” This limitation states that a computing device performs the judicial exceptions and other ideas, which does not integrate the exception into a practical application or provide significantly more.
receiving or accessing in memory user input including a definition of the mechanical assembly design and control parameters for the mechanical assembly;
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” This claim limitation amounts to receiving data using a computing device which is then used in the judicial exception.
Therefore this claim limitation does not integrate a judicial exception into a practical application or provide significantly more.
receiving or accessing in memory a set of design parameters for a skin, for at least partially covering the mechanical assembly, including material used to fabricate a body of the skin, an initial shape of the body of the skin, and an initial thickness of the body of the skin;
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” This claim limitation amounts to receiving data using a computing device which is then used in the judicial exception.
Therefore this claim limitation does not integrate a judicial exception into a practical application or provide significantly more.
and receiving or accessing in memory a target shape of an outer surface of the body of the skin at a predefined time of operations of the mechanical assembly;
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” This claim limitation amounts to receiving data using a computing device which is then used in the judicial exception.
Therefore this claim limitation does not integrate a judicial exception into a practical application or provide significantly more.
and a skin design program, running on the computing device
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” This limitation states that a computing device performs the judicial exceptions and other ideas, which does not integrate the exception into a practical application or provide significantly more.
Step 2B, does the claim recites additional elements that amount to significantly more than the judicial exception.
NO. As stated in Step 2A Prong 2, the additional elements do not integrate the exception into a practical application or provide significantly more.
Based on the above facts, the office concludes that claim 1 is not eligible under 35 USC 101.
Claim 2:
The system of claim 1, wherein the user input further comprises a definition of a set of Elastomeric Actuation Pieces (EAPs) for attaching the skin body to the mechanical assembly, wherein the definition includes a definition of body shapes and materials for the EAPs along with a location for mounting each of the EAPs on the mechanical assembly, and wherein the EAPs are attached on a first side to the mechanical assembly and have a second side with a recessed surface for receiving a portion of an EAP post extending outward from an inner surface of the skin body, whereby the EAPs are not integrally bound to the skin body.
This claim limitation pertains to the received user input by the program which outlines various information about the EAP’s which define the mechanical assembly. It is noted by the examiner that the claim does not require that a user inputs or determines these values. This is data received which is then optimized during the judicial exception.
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.”
This limitation is a further recitation of the “data receiving” step of claim 1, and is therefore also simply directed to the usage of a normal computer to receive data which is then used In the judicial exception. Therefore this does not integrate a judicial exception into a practical application or provide significantly more.”
Based on the above facts, the office concludes that claim 2 is not eligible under 35 USC 101.
Claim 3:
The system of claim 2, wherein the EAPs are formed of a material with a hardness greater than a hardness of the material used to form the body of the skin.
This claim limitation pertains to the defined EAP’s received in claim 2. The examiner notes that these EAP’s present in the claim are not physically present or tangible in a device. Instead, this is a “definition” of the material and hardness which was received in claim 2.
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.”
This limitation is a further recitation of the “data receiving” step of claim 1 and 2, and is therefore also simply directed to the usage of a normal computer to receive data which is then used In the judicial exception. Therefore this does not integrate a judicial exception into a practical application or provide significantly more.”
Based on the above facts, the office concludes that claim 3 is not eligible under 35 USC 101.
Claim 4:
The system of claim 2, wherein the generating of the optimized design further comprises optimizing time-varying positions of one or more of the EAPs.
This claim limitation pertains to the generation of an optimized design introduced in claim 1. As stated in claim 1, this was determined to be an abstract idea of design planning done by artisans in the field. As stated in this specifications par 5: “To date, skin systems have typically been designed and fabricated through time- consuming manual processes that often relied heavily on the skill of the artisans involved in the process. The manual design of an animatronic head combining actuators, supports, and an overlying skin has provided challenging as the design has to meet both artistic and mechanical targets.” Where the above passage suggests that, although it is difficult, skilled artisans consider time varying positions of the EAPs (actuators and supports) when designing movement of animatronics.
This is a further recitation of the abstract idea of claim 1, and therefore this claim also recites an abstract idea.
Based on the above facts, the office concludes that claim 4 is not eligible under 35 USC 101.
Claim 5:
The system of claim 1, wherein the generating of the optimized design further comprises generating a neutral pose for the skin body.
This claim limitation pertains to the generation of an optimized design introduced in claim 1. As stated in claim 1, this was determined to be an abstract idea of design planning done by artisans in the field. As stated in this specifications par 5: “To date, skin systems have typically been designed and fabricated through time- consuming manual processes that often relied heavily on the skill of the artisans involved in the process. Where the above passage suggests that, although it is difficult, skilled artisans likely consider a “neutral pose” for the skin in a robot.
This is a further recitation of the abstract idea of claim 1, and therefore this claim also recites an abstract idea.
Based on the above facts, the office concludes that claim 5 is not eligible under 35 USC 101.
Claim 12:
Step 1: Is the claimed invention one of the four statutory categories? :
YES. The claim recites A method for optimizing design of an elastomeric skin for covering a mechanical assembly, comprising: which is a process.
Step 2A Prong 1, inquiry "Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?":
YES. Claim 12 recites
generating an optimized design for the skin system by generating an optimized shape of the body and an optimized thickness of the body, wherein the optimized shape and the optimized thickness are selected such that the outer surface of the body substantially matches the target shape at the predefined time during the operations of the mechanical assembly,
This claim limitation pertains to an optimization process. The “skin design program” takes in input. These inputs are “an initial shape” and “an initial thickness.” The program outputs an “optimized shape” and “optimized thickness.” This input to output conversion is guided by the goal of matching a target shape for the assembly at a predefined time during operations of the assembly. As understood by the examiner, this process encompasses choosing a shape and thickness for the robot skin, so that the robot skin is optimized in a facial task (smiling). This is a planning step used in the design of skin systems.
As stated in paragraph 5 of the specifications, “To date, skin systems have typically been designed and fabricated through time- consuming manual processes that often relied heavily on the skill of the artisans involved in the process.“
MPEP 2106.04(a)(2)(III) states “Accordingly, the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions. “ As outlined, this claim limitation encompasses observing the initial values, and evaluating what the optimized values should be based on expert judgement to match a target shape.
Because this limitation is a mental design process, which can be performed by artisans of the field, this claim recites a mental process and the claim recites an abstract idea.
Step 2A Prong 2, Does the claim recite additional elements that integrate the judicial exception into a practical application?
NO. Claim 12 recites with a computing device, receiving or accessing in memory a set of design parameters for a skin system for covering at least a portion of the mechanical assembly;
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” This claim limitation amounts to receiving data using a computing device which is then used in the judicial exception.
Therefore this claim limitation does not integrate a judicial exception into a practical application or provide significantly more.
with the computing device, receiving or accessing in memory a target shape of an outer surface of a body of the skin system at a predefined time of operations of the mechanical assembly;
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” This claim limitation amounts to receiving data using a computing device which is then used in the judicial exception.
Therefore this claim limitation does not integrate a judicial exception into a practical application or provide significantly more.
with a skin design program running on the computing device,
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” This limitation states that a computing device performs the judicial exceptions and other ideas, which does not integrate the exception into a practical application or provide significantly more.
wherein the user input further comprises a definition of a set of elastomeric actuation pieces (EAPs) for attaching the body to the mechanical assembly, wherein the definition includes a definition of body shapes and materials for the EAPs along with a location for mounting each of the EAPs on the mechanical assembly, and wherein the EAPs are attached on a first side to the mechanical assembly and have a second side with a recessed surface for receiving a portion of an EAP post extending outward from an inner surface of the body, whereby the EAPs are not integrally bound to the body.
This claim limitation pertains to the received user input by the program which outlines various information about the EAP’s which define the mechanical assembly. It is noted by the examiner that the claim does not require that a user inputs or determines these values. This is data received which is then optimized during the judicial exception.
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.”
This limitation is directed to the usage of a normal computer to receive data which is then used In the judicial exception. Therefore this does not integrate a judicial exception into a practical application or provide significantly more.
Step 2B, does the claim recites additional elements that amount to significantly more than the judicial exception.
NO. As stated in Step 2A Prong 2, the above additional elements do not integrate a judicial exception into a practical application or provide significantly more.
Based on the above facts, the office concludes that claim 12 is not eligible under 35 USC 101.
Claim 13:
The method of claim 12, wherein the EAPs are formed of a material with a hardness greater than a hardness of the material used to form the body.
This claim limitation pertains to the defined EAP’s received in claim 12. The examiner notes that these EAP’s present in the claim are not physically present or tangible in a device. Instead, this is a “definition” of the material and hardness which was received in claim 12.
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.”
This limitation is a further recitation of the “data receiving” step of claim 12, and is therefore also simply directed to the usage of a normal computer to receive data which is then used In the judicial exception. Therefore this does not integrate a judicial exception into a practical application or provide significantly more.”
Based on the above facts, the office concludes that claim 13 is not eligible under 35 USC 101.
Claim 14:
The method of claim 12, wherein the generating of the optimized design further comprises optimizing time-varying positions of one or more of the EAPs.
This claim limitation pertains to the generation of an optimized design introduced in claim 12. As stated in claim 1, this was determined to be an abstract idea of design planning done by artisans in the field. As stated in this specifications par 5: “To date, skin systems have typically been designed and fabricated through time- consuming manual processes that often relied heavily on the skill of the artisans involved in the process. The manual design of an animatronic head combining actuators, supports, and an overlying skin has provided challenging as the design has to meet both artistic and mechanical targets.” Where the above passage suggests that, although it is difficult, skilled artisans consider time varying positions of the EAPs (actuators and supports) when designing movement of animatronics.
This is a further recitation of the abstract idea of claim 12, and therefore this claim also recites an abstract idea.
Based on the above facts, the office concludes that claim 14 is not eligible under 35 USC 101.
Claim 17:
Step 1: Is the claimed invention one of the four statutory categories? :
YES. The claim recites A computer system for optimizing design of an elastomeric skin for covering a mechanical assembly, comprising: which is a machine.
Step 2A Prong 1, inquiry "Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?":
YES. Claim 17 recites:, wherein the skin design program is configured for generating an optimized design for the skin by generating an optimized shape of the body and an optimized thickness of the body based on the initial shape and the initial thickness and wherein the optimized shape and the optimized thickness are selected such that the outer surface of the body of the skin substantially matches the target shape at the predefined time during the operations of the mechanical assembly.
This claim limitation pertains to an optimization process. The “skin design program” takes in input. These inputs are “an initial shape” and “an initial thickness.” The program outputs an “optimized shape” and “optimized thickness.” This input to output conversion is guided by the goal of matching a target shape for the assembly at a predefined time during operations of the assembly. As understood by the examiner, this process encompasses choosing a shape and thickness for the robot skin, so that the robot skin is optimized in a facial task (smiling). This is a planning step used in the design of skin systems.
As stated in paragraph 5 of the specifications, “To date, skin systems have typically been designed and fabricated through time- consuming manual processes that often relied heavily on the skill of the artisans involved in the process.“
MPEP 2106.04(a)(2)(III) states “Accordingly, the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions. “ As outlined, this claim limitation encompasses observing the initial values, and evaluating what the optimized values should be based on expert judgement to match a target shape.
Because this limitation is a mental design process, which can be performed by artisans of the field, this claim recites a mental process and the claim recites an abstract idea.
Step 2A Prong 2, Does the claim recite additional elements that integrate the judicial exception into a practical application?
NO. Claim 17 additionally recites memory storing user input including a definition of the mechanical assembly design and control parameters for the mechanical assembly, wherein the memory further stores a set of design parameters for a skin, for at least partially covering the mechanical assembly, including material used to fabricate a body of the skin, an initial shape of the body of the skin, and an initial thickness of the body of the skin;
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” This claim limitation amounts to receiving data using a computing device which is then used in the judicial exception.
Therefore this claim limitation does not integrate a judicial exception into a practical application or provide significantly more.
a graphical user interface (GUI) displayed on a monitor and configured for receiving user input including a target shape of an outer surface of the body of the skin at a predefined time of operations of the mechanical assembly;
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” This claim limitation amounts to receiving data using a computing device which is then used in the judicial exception.
Therefore this claim limitation does not integrate a judicial exception into a practical application or provide significantly more.
a skin design program provided by a processor executing code
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” This limitation states that a computing device performs the judicial exceptions and other ideas, which does not integrate the exception into a practical application or provide significantly more.
Step 2B, does the claim recites additional elements that amount to significantly more than the judicial exception.
NO. As stated in Step 2A Prong 2, the additional elements do not integrate the exception into a practical application or provide significantly more.
Based on the above facts, the office concludes that claim 17 is not eligible under 35 USC 101.
Claim 18:
The system of claim 17, wherein the user input further comprises a definition of a set of Elastomeric Actuation Pieces (EAPs) for attaching the skin body to the mechanical assembly, wherein the definition includes a definition of body shapes and materials for the EAPs along with a location for mounting each of the EAPs on the mechanical assembly, and wherein the EAPs are attached on a first side to the mechanical assembly and have a second side with a recessed surface for receiving a portion of an EAP post extending outward from an inner surface of the skin body, whereby the EAPs are not integrally bound to the skin body.
This claim limitation pertains to the received user input by the program which outlines various information about the EAP’s which define the mechanical assembly. It is noted by the examiner that the claim does not require that a user inputs or determines these values. This is data received which is then optimized during the judicial exception.
The MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.”
This limitation is a further recitation of the “data receiving” step of claim 17, and is therefore also simply directed to the usage of a normal computer to receive data which is then used In the judicial exception. Therefore this does not integrate a judicial exception into a practical application or provide significantly more.”
Based on the above facts, the office concludes that claim 18 is not eligible under 35 USC 101.
Claim 19:
The system of claim 18, wherein the generating of the optimized design further comprises optimizing time-varying positions of one or more of the EAPs.
This claim limitation pertains to the generation of an optimized design introduced in claim 17. As stated in claim 17, this was determined to be an abstract idea of design planning done by artisans in the field. As stated in this specifications par 5: “To date, skin systems have typically been designed and fabricated through time- consuming manual processes that often relied heavily on the skill of the artisans involved in the process. The manual design of an animatronic head combining actuators, supports, and an overlying skin has provided challenging as the design has to meet both artistic and mechanical targets.” Where the above passage suggests that, although it is difficult, skilled artisans consider time varying positions of the EAPs (actuators and supports) when designing movement of animatronics.
This is a further recitation of the abstract idea of claim 17, and therefore this claim also recites an abstract idea.
Based on the above facts, the office concludes that claim 19 is not eligible under 35 USC 101.
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, 5-6, 8-11, 17, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over (US 20210110001 A1) Mitchell_2021 and (US 20120185218 A1) Bickel_2012
.
Claim 1:Mitchell_2021 makes obvious A system for mechanical assembly, comprising: (par 5: “According to a third embodiment of the present disclosure, a system is provided. The system includes one or more computer processors, and a memory containing a program which when executed by the one or more computer processors performs an operation. The operation includes generating a first plurality of simulated meshes using a physics simulation model, wherein the first plurality of simulated meshes corresponds to a first plurality of actuator configurations for an animatronic mechanical design. The operation further includes training a machine learning model based on the first plurality of simulated meshes and the first plurality of actuator configurations. Additionally, the operation includes generating, using the machine learning model, a plurality of predicted meshes for the animatronic mechanical design, based on a second plurality of actuator configurations. Further, the operation includes facilitating virtual animation of the animatronic mechanical design based on the plurality of predicted meshes.”) … par 26: “As illustrated, once an initial design is developed, the Workflow 200 moves to a phase for Simulation 230. In an embodiment, the Simulation 230 generally includes using one or more physics simulation models to simulate artificial skin deformations based on the animatronic mechanical design, and to refine the design based on these simulations.”(Examiner note: i.e.: optimize)
a computing device configured to perform the following: (par 5: “The system includes one or more computer processors”)
receiving or accessing in memory (par 5: “The system includes one or more computer processors, and a memory containing a program which when executed by the one or more computer processors performs an operation. “) user input including a definition of the mechanical assembly design and control parameters for the mechanical assembly; (par 18: “ In some embodiments, a physics simulation model is used to simulate the animatronic mechanical design. In an embodiment, the simulation model receives a digital representation of the mechanical design, including the location, type, and orientation of each actuator, the attributes of the artificial skin, the actuation points, and any other attributes needed to simulate the design. “… par 39: “in the illustrated embodiment, the Storage 320 includes one or more Mechanical Designs “ … par 68: “The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like). In some embodiments, the user can specify two or more configurations, and the Design Application 330 can generate a series of values between them, in order to interpolate movement from a first pose to a second. The method 800 then proceeds to block 810.”) Examiner note: Where the above makes obvious receiving or accessing in memory user input, which includes both a definition of the mechanical assembly design and control parameters for the mechanical assembly
receiving or accessing in memory (par 5: “The system includes one or more computer processors, and a memory containing a program which when executed by the one or more computer processors performs an operation. “) a set of design parameters for a skin, for at least partially covering the mechanical assembly, including material used to fabricate a body of the skin, an initial shape of the body of the skin, and an initial thickness of the body of the skin;
par 39: “Further, in one embodiment, the Mechanical Design 355 defines the artificial skin (e.g., the material, density, thickness, actuation/connection points, a mesh representing the surface(s) of the skin (Examiner note: an initial shape of the body of the skin), and the like). In an embodiment, the Mechanical Design 355 generally includes the details necessary to simulate and/or construct the animatronic.”
and receiving or accessing in memory (par 5: “The system includes one or more computer processors, and a memory containing a program which when executed by the one or more computer processors performs an operation. “) a target shape of an outer surface of the body of the skin at a predefined time of operations of the mechanical assembly; (par 35: “After training the Deep Learning 255, the trained model(s) can be used to generate predicted meshes for the animatronic design, given a pose (Examiner note: ie: target shape) (e.g., a set of actuator configurations). Using these models, therefore, designers can provide actuator configurations (or a series of actuator configurations) to generate the corresponding predicted mesh(es). As depicted in the illustrated workflow 200, this enables Design validation 260. In one embodiment, a user provides a sequence of configurations, and the models output a series of meshes, which can be combined to create a predicted mesh that moves over time, representing the animatronic design in motion (e.g., as the actuators move). In some embodiments, this is output as a video or animation file.”
and a skin design program, (par 5: “Additionally, the operation includes generating, using the machine learning model, a plurality of predicted meshes for the animatronic mechanical design, based on a second plurality of actuator configurations”)
running on the computing device, (par 5: “The system includes one or more computer processors, and a memory containing a program which when executed by the one or more computer processors performs an operation”)
generating an par 26: As illustrated, once an initial design is developed, the Workflow 200 moves to a phase for Simulation 230. In an embodiment, the Simulation 230 generally includes using one or more physics simulation models to simulate artificial skin deformations based on the animatronic mechanical design, and to refine the design based on these simulations.)by generating an par 40: “In the illustrated embodiment, the Simulated Meshes 360 are three-dimensional surface meshes made of elements (e.g., tetrahedral elements). In one embodiment, during simulation, the simulator derives the deformed nodes of these elements and generates volumetric meshes, in order to output surface meshes of the deformed skin (e.g., to output Simulated Meshes 360). In one embodiment, the Simulated Meshes 360 are generated by using a physics simulation model that uses physics to simulate the deformations that will occur in an artificial skin given a set of configurations for actuators that are coupled to the skin. In embodiments, this simulation process is highly accurate, but is compute-intensive and time-consuming. In some embodiments, the actuator configurations used to create the Simulated Meshes 360 are selected in a way that ensures adequate coverage of all potential poses the animatronic can make (or that the designer expects to use).”) … par 41: “In this way, the models can be trained and refined to predict mesh deformations given sets of actuator parameters. In the illustrated embodiment, the Predicted Meshes 365 are three-dimensional surface meshes of the skin, each comprising a set of vertices connected by one or more edges and/or polygons. In some embodiments, rather than being trained to generate surface meshes, the simulation is trained on volumetric meshes (Examiner note: a three dimensional shape and thickness, where the optimized model are generated based on initial training parameters) (e.g., generated by the simulation components) and similarly generates volumetric meshes. In an embodiment, the Predicted Meshes 365 are generated by providing actuator configurations to the trained learning model(s). Although depicted as residing in Storage 320, in embodiments, the Mechanical Design(s) 355, Simulated Mesh(es) 360, and Predicted Mesh(es) 365 may reside in any suitable location.”
(par 35: “After training the Deep Learning 255, the trained model(s) can be used to generate predicted meshes for the animatronic design, given a pose (Examiner note: ie: target shape) (e.g., a set of actuator configurations). Using these models, therefore, designers can provide actuator configurations (or a series of actuator configurations) to generate the corresponding predicted mesh(es). As depicted in the illustrated workflow 200, this enables Design validation 260. In one embodiment, a user provides a sequence of configurations, and the models output a series of meshes, which can be combined to create a predicted mesh that moves over time, representing the animatronic design in motion (e.g., as the actuators move). In some embodiments, this is output as a video or animation file.”)
Mitchell_2021 does not expressly recite
wherein the optimized shape and the optimized thickness are selected such that the outer surface of the body of the skin substantially matches the target shape
Bickel_2012 however makes obvious
Par 57: “Accordingly, the skin patch 506 may be processed according to the optimization process described herein to generate an optimized skin patch 510 having a varying inner surface (i.e., material thickness). A deformation of the optimized skin patch 510 may be simulated according to the computational model and the resultant deformed shape 512 may be compared to the target surface 502. As shown, the optimization process determines an optimized skin geometry such that the skin has a shape and geometry that closely matches target surfaces when deformed.”)
Par 57: “Accordingly, the skin patch 506 may be processed according to the optimization process described herein to generate an optimized skin patch 510 having a varying inner surface (i.e., material thickness). A deformation of the optimized skin patch 510 may be simulated according to the computational model and the resultant deformed shape 512 may be compared to the target surface 502. As shown, the optimization process determines an optimized skin geometry such that the skin has a shape and geometry that closely matches target surfaces when deformed.”)
Par 57: “Accordingly, the skin patch 506 may be processed according to the optimization process described herein to generate an optimized skin patch 510 having a varying inner surface (i.e., material thickness). A deformation of the optimized skin patch 510 may be simulated according to the computational model and the resultant deformed shape 512 may be compared to the target surface 502. As shown, the optimization process determines an optimized skin geometry such that the skin has a shape and geometry that closely matches target surfaces when deformed.”)
wherein the optimized shape and the optimized thickness are selected such that the outer surface of the body of the skin substantially matches the target shape (Par 57: “Accordingly, the skin patch 506 may be processed according to the optimization process described herein to generate an optimized skin patch 510 having a varying inner surface (i.e., material thickness). A deformation of the optimized skin patch 510 may be simulated according to the computational model and the resultant deformed shape 512 may be compared to the target surface 502. As shown, the optimization process determines an optimized skin geometry such that the skin has a shape and geometry that closely matches target surfaces when deformed.”)
Bickel_2012 and Mitchell_2021 are analogous art to the claimed invention because they are from the same field of endeavor called synthetic skin optimization for robots. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Bickel_2012 and Mitchell_2021. The rationale for doing so would have been to follow a teaching and motivation present in the prior art. The prior art of Mitchell_2021 contains a base product, which is a simulation used to optimize actuator configurations to match a static pose, see par 31: “ In one embodiment, training the Deep Learning 255 comprises providing a set of actuator configurations as input to the model(s), and applying the corresponding simulated mesh as the target output. In an embodiment, the models are configured to optimize surface-to-surface loss such that the generated predicted mesh closely aligns with the simulated mesh. In one embodiment, optimizing surface-to-surface loss includes optimizing vertex-to-vertex loss.”Mitchell_2021 does teach controlling skin thickness, but not necessarily optimizing it, see par 24: “In one embodiment, the thickness and/or elasticity of the Artificial Skin 105 is controlled to provide predictable and preferred deformations.“ Mitchell_2021 does not expressly recite that the skin shape and thickness itself is being optimized to match the target, as understood by the examiner, Mitchell_2021 is teaching an optimization of the actuators to calculate skin deformation as well as a validation process where this skin is matched to a target, but not directly optimizing the thickness of the skin itself. Bickel_2012 teaches a method which allows the user to reconstruct a human subjects skin to a high accuracy level, specifically by optimizing the skin itself. see mapping above, and motivations of par 24: “The 3D reconstructions may comprise high-resolution data that includes data about pores and wrinkles of the subject's skin, as well as robust temporal correspondence, to provide information about the deformation behavior of the human subject's skin.” And par 94: “According to the experimental validation techniques described above, this process permits the design of a soft tissue animatronic character that accurately mimics a given real person.” Therefore, it would have been obvious to combine the simulation workflow of Mitchell_2021 with the optimization of skin thickness and shape of Bickel_2012 for the benefit of improving accuracy in machine robot skin models to obtain the invention as specified in the claims.
Claim 5:
The system of claim 1,
Mitchell_2021 makes obvious the generating of the optimized design further comprises generating a neutral pose for the skin body (Par 23: “FIG. 1 illustrates an animatronic face, according to one embodiment of the present disclosure. In the illustrated embodiment, the facial profile comprises an Artificial Skin 105, controlled by a set of Actuators 110A-N. Although linear actuators are illustrated, in embodiments, any collection of actuators can be used, including rotational, linear, and combinational actuators. Additionally, in embodiments, motors or Actuators 110A-N may be utilized to drive a mechanical assembly that in turn, actuates the Artificial Skin 105. As illustrated by the Configuration 100A, when the Actuators 110A-N have a first configuration, the Artificial Skin 105 has a neutral expression with the mouth held closed. As further illustrated in FIG. 1, when the Actuators 110A-N take a different Configuration 1008, the Artificial Skin 105 deforms to open the mouth and form a different expression.”) Examiner note: Where this makes obvious the generation of a neutral pose.
Claim 6:
The system of claim 1,
Mitchell_2021 makes obvious wherein the skin design program comprises a soft body simulator configured to simulate movement of the body of the skin during operations of the mechanical assembly. (Par 55: “ In one embodiment, the set of configurations used to generate the predictive meshes are provided by a user. In some embodiments, the user can specify two or more poses (e.g., sets of configurations), and the Design Application 330 generates intermediate poses (sets of actuator configurations) between the specified poses, in order to predict the deformation of the skin as the actuators move between poses, in addition to while stopped at each pose. “ par 68: “FIG. 8 is a flow diagram illustrating a method 800 for generating predicted meshes for an animatronic design, according to one embodiment disclosed herein. The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like). In some embodiments, the user can specify two or more configurations, and the Design Application 330 can generate a series of values between them, in order to interpolate movement from a first pose to a second. The method 800 then proceeds to block 810.”)
Claim 8:
The system of claim 6,
Mitchell_2021 makes obvious wherein the soft body simulator is configured to predict dynamic behavior of the skin system during operations of the mechanical assembly. (Par 55: “ In one embodiment, the set of configurations used to generate the predictive meshes are provided by a user. In some embodiments, the user can specify two or more poses (e.g., sets of configurations), and the Design Application 330 generates intermediate poses (sets of actuator configurations) between the specified poses, in order to predict the deformation of the skin as the actuators move between poses, in addition to while stopped at each pose. “ par 68: “FIG. 8 is a flow diagram illustrating a method 800 for generating predicted meshes for an animatronic design, according to one embodiment disclosed herein. The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like). In some embodiments, the user can specify two or more configurations, and the Design Application 330 can generate a series of values between them, in order to interpolate movement from a first pose to a second. The method 800 then proceeds to block 810.”)
Claim 9:The system of claim 6,
Mitchell_2021 makes obvious wherein the soft body simulator is configured to be Par 55: “ In one embodiment, the set of configurations used to generate the predictive meshes are provided by a user. In some embodiments, the user can specify two or more poses (e.g., sets of configurations), and the Design Application 330 generates intermediate poses (sets of actuator configurations) between the specified poses, in order to predict the deformation of the skin as the actuators move between poses, in addition to while stopped at each pose. “ par 68: “FIG. 8 is a flow diagram illustrating a method 800 for generating predicted meshes for an animatronic design, according to one embodiment disclosed herein. The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like). In some embodiments, the user can specify two or more configurations, and the Design Application 330 can generate a series of values between them, in order to interpolate movement from a first pose to a second. The method 800 then proceeds to block 810.”) in an unstressed, neutral pose. (par 23: “when the Actuators 110A-N have a first configuration, the Artificial Skin 105 has a neutral expression with the mouth held closed. As further illustrated in FIG. 1, when the Actuators 110A-N take a different Configuration 1008, the Artificial Skin 105 deforms to open the mouth and form a different expression.”) Examiner note: Where this makes obvious a neutral pose in the above process which interpolates between two poses).
Mitchell_2021 does not expressly recite
Bickel_2012 however makes obvious Par 75: “According to one embodiment, the optimization process may be utilized to modify a local thickness of the synthetic skin geometry (examiner note: shape and thickness) in such a way that when mechanical actuators of the animatronic device are set to values corresponding to a particular expressive pose, the resulting deformation of the skin matches the expressive poses' target positions q as closely as possible. In a physical simulation, the actuators settings result in hard positional constraints that can be directly be applied to the corresponding deformed positions. Parameters Pthk may be determined that indicate a thickness distribution in an undeformed configuration without directly affecting the deformed positions of the synthetic skin. … par 76: “In one embodiment, the thickness distribution may be represented by a parameterized surface, such as described in FIGS. 7A-B above. In one embodiment, the parameters a, of all sample points, as described above, may be gathered into Pthk' and optimal height values may be computed by minimizing Equation 11. It is noted that the MLS interpolation described in FIGS. 7A-B result in a linear mapping between undeformed positions X and parameters Pthk, thus the matrix ax!apthk (Examiner note: as understood by the examiner this is a partial derivative, but even if not, this passage makes obvious the fact that the equations are differentiable) may be constant and, consequently, may be precomputed”
As already discussed, Mitchell_2021 and Bickel_2012 are analogous art to the claimed invention because they are from the same field of endeavor called optimizing skin for robots. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Mitchell_2021 and Bickel_2012 for the reasons stated in claim 1. Therefore, it would have been obvious to combine the simulation workflow of Mitchell_2021 with the optimization of skin thickness and shape of Bickel_2012 for the benefit of improving accuracy in machine robot skin models to obtain the invention as specified in the claims.
Claim 10:
The system of claim 6,
Mitchell_2021 makes obvious wherein the soft body simulator is configured to Par 55: “ In one embodiment, the set of configurations used to generate the predictive meshes are provided by a user. In some embodiments, the user can specify two or more poses (e.g., sets of configurations), and the Design Application 330 generates intermediate poses (sets of actuator configurations) between the specified poses, in order to predict the deformation of the skin as the actuators move between poses, in addition to while stopped at each pose. “ par 68: “FIG. 8 is a flow diagram illustrating a method 800 for generating predicted meshes for an animatronic design, according to one embodiment disclosed herein. The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like). In some embodiments, the user can specify two or more configurations, and the Design Application 330 can generate a series of values between them, in order to interpolate movement from a first pose to a second. The method 800 then proceeds to block 810.”)
Mitchell_2021 does not expressly recite
Bickel_2012 however makes obvious par 56:: “in one embodiment, this energy may be utilized in a static equilibrium problem in order to compute the deformation of the skin in response to actuator placements, which may translate into a set of position constraints. The deformed configuration of the skin is then determined as the minimum of the total energy via Equation (6) as follows:”) Examiner note: Where the equation given is a differentiable equation which simulates the skin in repones to control parameters of the actuators.
As already discussed, Mitchell_2021 and Bickel_2012 are analogous art to the claimed invention because they are from the same field of endeavor called optimizing skin for robots. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Mitchell_2021 and Bickel_2012. The rational would have been applying a known technique for a known device ready for improvement to yeld a predictable result. Mitchell_2021 uses a simulation to predict deformation of the skin as the actuators move. Mitchell_2021 does not expressly recite that this simulation is differentiable in respect to the motion of the EAP’s, although one normally skilled in the art would understand a simulation comprising motion of EAP’s to be differentiable with respect ot the movement. Bickel_2012 in the prior art makes obvious and recites using EAP placements to compute skin deformation in a way that is differentiable. One ordinary skilled in the art would recognize applying the technique of having differentiable equations in a simulator would apply (and is likely already present) in the simulator of Mitchell_2021, which would allow them to compute skin deformation in a differentiable manner in response to movement. Therefore it would have been obvious to include the differentiable equations of Bickel_2012 in the simulator of Mitchel_2021 to yield the predictable result of calculating skin deformation with respect to actuator movement.
Claim 11:
Mitchell_2021 makes obvious A robot fabricated to include a physical implementation of the mechanical assembly covered by a skin fabricated ((par 37: “As illustrated, if the design is successfully validated, the workflow 200 proceeds to block 265, where production occurs, and the animatronic mechanical design can be physical constructed. In an embodiment, this includes sending the design parameters to one or more other systems or users to assemble the actuator frame, create the artificial skin, and the like. In contrast, if the user is not satisfied with the predictive motions and deformations (or if the automated system identifies potential concerns), the workflow 200 returns to the Design 210 stage. This iterative process can be repeated until the predicted deformations are satisfactory.”) based on the definition of the optimized design for the skin system of claim 1. (Examiner note: see claim 1)
Claim 17:
A computer system for ((par 5: “According to a third embodiment of the present disclosure, a system is provided. The system includes one or more computer processors, and a memory containing a program which when executed by the one or more computer processors performs an operation. The operation includes generating a first plurality of simulated meshes using a physics simulation model, wherein the first plurality of simulated meshes corresponds to a first plurality of actuator configurations for an animatronic mechanical design. The operation further includes training a machine learning model based on the first plurality of simulated meshes and the first plurality of actuator configurations. Additionally, the operation includes generating, using the machine learning model, a plurality of predicted meshes for the animatronic mechanical design, based on a second plurality of actuator configurations. Further, the operation includes facilitating virtual animation of the animatronic mechanical design based on the plurality of predicted meshes.”) … par 26: “As illustrated, once an initial design is developed, the Workflow 200 moves to a phase for Simulation 230. In an embodiment, the Simulation 230 generally includes using one or more physics simulation models to simulate artificial skin deformations based on the animatronic mechanical design, and to refine the design based on these simulations.”(Examiner note: i.e.: optimize)
memory storing user input including a definition of the mechanical assembly design and control parameters for the mechanical assembly, ((par 18: “ In some embodiments, a physics simulation model is used to simulate the animatronic mechanical design. In an embodiment, the simulation model receives a digital representation of the mechanical design, including the location, type, and orientation of each actuator, the attributes of the artificial skin, the actuation points, and any other attributes needed to simulate the design. “… par 39: “in the illustrated embodiment, the Storage 320 includes one or more Mechanical Designs “ … par 68: “The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like). In some embodiments, the user can specify two or more configurations, and the Design Application 330 can generate a series of values between them, in order to interpolate movement from a first pose to a second. The method 800 then proceeds to block 810.”) Examiner note: Where the above makes obvious receiving or accessing in memory user input, which includes both a definition of the mechanical assembly design and control parameters for the mechanical assembly)
wherein the memory further stores a set of design parameters for a skin, for at least partially covering the mechanical assembly, including material used to fabricate a body of the skin, an initial shape of the body of the skin, and an initial thickness of the body of the skin; (par 39: “Further, in one embodiment, the Mechanical Design 355 defines the artificial skin (e.g., the material, density, thickness, actuation/connection points, a mesh representing the surface(s) of the skin (Examiner note: an initial shape of the body of the skin. Keep in mind this is present in the storage/memory), and the like). In an embodiment, the Mechanical Design 355 generally includes the details necessary to simulate and/or construct the animatronic.”
a graphical user interface (GUI) displayed on a monitor and configured for receiving user input including a target shape of an outer surface of the body of the skin at a predefined time of operations of the mechanical assembly; ((par 35: “After training the Deep Learning 255, the trained model(s) can be used to generate predicted meshes for the animatronic design, given a pose (Examiner note: ie: target shape) (e.g., a set of actuator configurations). Using these models, therefore, designers can provide actuator configurations (or a series of actuator configurations) to generate the corresponding predicted mesh(es). As depicted in the illustrated workflow 200, this enables Design validation 260. In one embodiment, a user provides a sequence of configurations, and the models output a series of meshes, which can be combined to create a predicted mesh that moves over time, representing the animatronic design in motion (e.g., as the actuators move). In some embodiments, this is output as a video or animation file.” … par 49: “in the illustrated embodiment, the Validation Component 350 is used to validate the models and/or the Mechanical Design 355. In one embodiment, the Validation Component 350 provides a graphical user interface (GUI) that enables users can specify one or more actuator configurations, and view the corresponding Predicted Mesh(es)”)
a skin design program (par 5: “Additionally, the operation includes generating, using the machine learning model, a plurality of predicted meshes for the animatronic mechanical design, based on a second plurality of actuator configurations”)provided by a processor executing code, (par 5: “The system includes one or more computer processors, and a memory containing a program which when executed by the one or more computer processors performs an operation”) wherein the skin design program is configured for generating an par 26: As illustrated, once an initial design is developed, the Workflow 200 moves to a phase for Simulation 230. In an embodiment, the Simulation 230 generally includes using one or more physics simulation models to simulate artificial skin deformations based on the animatronic mechanical design, and to refine the design based on these simulations.)by generating an par 40: “In the illustrated embodiment, the Simulated Meshes 360 are three-dimensional surface meshes made of elements (e.g., tetrahedral elements). In one embodiment, during simulation, the simulator derives the deformed nodes of these elements and generates volumetric meshes, in order to output surface meshes of the deformed skin (e.g., to output Simulated Meshes 360). In one embodiment, the Simulated Meshes 360 are generated by using a physics simulation model that uses physics to simulate the deformations that will occur in an artificial skin given a set of configurations for actuators that are coupled to the skin. In embodiments, this simulation process is highly accurate, but is compute-intensive and time-consuming. In some embodiments, the actuator configurations used to create the Simulated Meshes 360 are selected in a way that ensures adequate coverage of all potential poses the animatronic can make (or that the designer expects to use).”) … par 41: “In this way, the models can be trained and refined to predict mesh deformations given sets of actuator parameters. In the illustrated embodiment, the Predicted Meshes 365 are three-dimensional surface meshes of the skin, each comprising a set of vertices connected by one or more edges and/or polygons. In some embodiments, rather than being trained to generate surface meshes, the simulation is trained on volumetric meshes (Examiner note: a three dimensional shape and thickness, where the optimized model are generated based on initial training parameters) (e.g., generated by the simulation components) and similarly generates volumetric meshes. In an embodiment, the Predicted Meshes 365 are generated by providing actuator configurations to the trained learning model(s). Although depicted as residing in Storage 320, in embodiments, the Mechanical Design(s) 355, Simulated Mesh(es) 360, and Predicted Mesh(es) 365 may reside in any suitable location.”
par 35: “After training the Deep Learning 255, the trained model(s) can be used to generate predicted meshes for the animatronic design, given a pose (Examiner note: ie: target shape) (e.g., a set of actuator configurations). Using these models, therefore, designers can provide actuator configurations (or a series of actuator configurations) to generate the corresponding predicted mesh(es). As depicted in the illustrated workflow 200, this enables Design validation 260. In one embodiment, a user provides a sequence of configurations, and the models output a series of meshes, which can be combined to create a predicted mesh that moves over time, representing the animatronic design in motion (e.g., as the actuators move). In some embodiments, this is output as a video or animation file.”)
Mitchell_2021 does not expressly recite
Bickel_2012 however makes obvious
Par 57: “Accordingly, the skin patch 506 may be processed according to the optimization process described herein to generate an optimized skin patch 510 having a varying inner surface (i.e., material thickness). A deformation of the optimized skin patch 510 may be simulated according to the computational model and the resultant deformed shape 512 may be compared to the target surface 502. As shown, the optimization process determines an optimized skin geometry such that the skin has a shape and geometry that closely matches target surfaces when deformed.”)
Par 57: “Accordingly, the skin patch 506 may be processed according to the optimization process described herein to generate an optimized skin patch 510 having a varying inner surface (i.e., material thickness). A deformation of the optimized skin patch 510 may be simulated according to the computational model and the resultant deformed shape 512 may be compared to the target surface 502. As shown, the optimization process determines an optimized skin geometry such that the skin has a shape and geometry that closely matches target surfaces when deformed.”)
Par 57: “Accordingly, the skin patch 506 may be processed according to the optimization process described herein to generate an optimized skin patch 510 having a varying inner surface (i.e., material thickness). A deformation of the optimized skin patch 510 may be simulated according to the computational model and the resultant deformed shape 512 may be compared to the target surface 502. As shown, the optimization process determines an optimized skin geometry such that the skin has a shape and geometry that closely matches target surfaces when deformed.”)
Bickel_2012 and Mitchell_2021 are analogous art to the claimed invention because they are from the same field of endeavor called synthetic skin optimization for robots. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Bickel_2012 and Mitchell_2021. The rationale for doing so would have been to follow a teaching and motivation present in the prior art. The prior art of Mitchell_2021 contains a base product, which is a simulation used to optimize actuator configurations to match a static pose, see par 31: “ In one embodiment, training the Deep Learning 255 comprises providing a set of actuator configurations as input to the model(s), and applying the corresponding simulated mesh as the target output. In an embodiment, the models are configured to optimize surface-to-surface loss such that the generated predicted mesh closely aligns with the simulated mesh. In one embodiment, optimizing surface-to-surface loss includes optimizing vertex-to-vertex loss.”Mitchell_2021 does teach controlling skin thickness, but not necessarily optimizing it, see par 24: “In one embodiment, the thickness and/or elasticity of the Artificial Skin 105 is controlled to provide predictable and preferred deformations.“ Mitchell_2021 does not expressly recite that the skin shape and thickness itself is being optimized to match the target, as understood by the examiner, Mitchell_2021 is teaching an optimization of the actuators to calculate skin deformation as well as a validation process where this skin is matched to a target, but not directly optimizing the thickness of the skin itself. Bickel_2012 teaches a method which allows the user to reconstruct a human subjects skin to a high accuracy level, specifically by optimizing the skin itself. see mapping above, and motivations of par 24: “The 3D reconstructions may comprise high-resolution data that includes data about pores and wrinkles of the subject's skin, as well as robust temporal correspondence, to provide information about the deformation behavior of the human subject's skin.” And par 94: “According to the experimental validation techniques described above, this process permits the design of a soft tissue animatronic character that accurately mimics a given real person.” Therefore, it would have been obvious to combine the simulation workflow of Mitchell_2021 with the optimization of skin thickness and shape of Bickel_2012 for the benefit of improving accuracy in machine robot skin models to obtain the invention as specified in the claims.
Claim 20:
Mitchell_2021 makes obvious The system of claim 17, wherein the skin design program comprises a soft body simulator configured to simulate movement of the body of the skin during operations of the mechanical assembly ((Par 55: “ In one embodiment, the set of configurations used to generate the predictive meshes are provided by a user. In some embodiments, the user can specify two or more poses (e.g., sets of configurations), and the Design Application 330 generates intermediate poses (sets of actuator configurations) between the specified poses, in order to predict the deformation of the skin as the actuators move between poses, in addition to while stopped at each pose. “ par 68: “FIG. 8 is a flow diagram illustrating a method 800 for generating predicted meshes for an animatronic design, according to one embodiment disclosed herein. The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like). In some embodiments, the user can specify two or more configurations, and the Design Application 330 can generate a series of values between them, in order to interpolate movement from a first pose to a second. The method 800 then proceeds to block 810.”)
and wherein the soft body simulator is configured for at least one of the following:
processing frictional contact between soft bodies and between rigid and soft bodies via a contact model that is differentiable; (the claim requires at least one, this is not required)
predicting dynamic behavior of the skin system during operations of the mechanical assembly; (Par 55: “ In one embodiment, the set of configurations used to generate the predictive meshes are provided by a user. In some embodiments, the user can specify two or more poses (e.g., sets of configurations), and the Design Application 330 generates intermediate poses (sets of actuator configurations) between the specified poses, in order to predict the deformation of the skin as the actuators move between poses, in addition to while stopped at each pose. “ par 68: “FIG. 8 is a flow diagram illustrating a method 800 for generating predicted meshes for an animatronic design, according to one embodiment disclosed herein. The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like). In some embodiments, the user can specify two or more configurations, and the Design Application 330 can generate a series of values between them, in order to interpolate movement from a first pose to a second. The method 800 then proceeds to block 810.”)
differentiating with respect to the shape and the thickness of the body of the skin in an unstressed, neutral pose; (the claim requires at least one, this is not required)
and differentiating with respect to motion of either the EAPs or the control parameters of motors of the mechanical assembly operable to drive motion of the mechanical assembly. (the claim requires at least one, this is not required)
Claims 2-4, 12-15, and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Mitchel_2021, Bikel_2012, US 20160075036 A1 (Lessing_2016) and US20200030707 A1 (Hayashi_2020)
Claim 2:
Mitchell_2021 makes obvious The system of claim 1, wherein the user input further comprises a definition of a set of par 18: “In an embodiment, the simulation model receives a digital representation of the mechanical design, including the location, type, and orientation of each actuator,” … par 68: “The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like).”) wherein the definition includes a definition of par 18: “In an embodiment, the simulation model receives a digital representation of the mechanical design, including the location, type, and orientation of each actuator, the attributes of the artificial skin, the actuation points, and any other attributes needed to simulate the design.” … Par 39: “For example, in such an embodiment, the Mechanical Design 355 indicates the number, type, power, location, orientation, and any other relevant parameters for each actuator and/or actuation point in the design. In an embodiment, the Mechanical Design 355 indicates both the configuration of actuators, as well as the location, size, orientation, and the like of each actuation point they drive.”) and wherein the EAPs are attached on a first side to the mechanical assembly par 39: “ In some embodiments, the Mechanical Design 355 further specifies the details of the underlying mechanical assembly (e.g., its shape and material, where the skin and/or actuators attach, and the like) Examiner note: Where actuators attach implies that the actuators are attached to the mechanical assembly by at least a first side, see also figure 1. par 17: “In order to develop mechanical animatronic designs, experienced developers construct a mechanical assembly, determine the size(s), shape(s), and location(s) of actuation points where the actuators connect to or contact with the artificial skin,” Examiner note: Where “or contact” implies that the EAPS’s are not integrally bound to the body
Mitchell_2021 does not expressly recite Elastomeric
Lessing_2016 however makes obvious Elastomeric (par 6: “Furthermore, conventional soft robotic actuators are constructed from a single elastomeric material such as silicone elastomer”)
stiffness or wall thickness to accommodate a certain desired behavior. ) Examiner note: Where this makes obvious choosing between different elastomer chape and materials for an EAP.
Mitchell_2021 and Lessing_2016 are analogous art to the claimed invention because they are from the same field of endeavor called robotics. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Mitchell_2021 and Lessing_2016. The rationale for doing so would have been obvious to try. The prior art of Mitchell_2021 identifies a need for a robotic device which uses actuators to move skin for a robot. The prior art of Mitchell_2021 identifies that varying types of actuators may be chosen. See par 18: “including the location, type, and orientation of each actuator.” Mitchell_2021 is silent on the actuator being elastomeric. However, the prior art of Lessing_2016 identifies elastomeric actuators as the conventional solution used in order to actuate a soft robot. Furthermore, Mitchell_2021 states to choose par 39: “and any other relevant parameters for each actuator and/or actuation point in the design.” Where Lessing_2016 states that body shape and material is a relevant parameter for actuators in a design. One reasonably skilled in the art would have known to pursue using an elastomeric actuator as well including body shapes and materials in light of both references. Therefore, it would have been obvious to combine the simulation workflow and robotic face moving technology of Mitchell_2021 with the use of elastomeric actuators of varying materials and shape of Lessing_2016 to accommodate for desired behavior when designing robot skin systems and to obtain the invention as specified in the claims.
Mitchell_2021 and Lessing_2016 do not expressly recite and have a second side with a recessed surface for receiving a portion of an EAP post extending outward from an inner surface of the skin body,
Hayashi_2020 makes obvious and have a second side with a recessed surface for receiving a portion of an EAP post extending outward from an inner surface of the skin body, whereby the EAPs are not integrally bound to the skin bodypar 8: “Another aspect of the invention is also a robot including an outer skin with which a main body is covered. A recessed fitting portion is provided extended along an outer face of the main body. A fitting member of a form complementing the recessed fitting portion is provided on the outer skin. The outer skin is fixed to the main body by the fitting member being fitted into the recessed fitting portion (Examiner note: where the EAP is the recessed fitting portion)
Mitchell_2021 and Hayashi_2020 are analogous art to the claimed invention because they are from the same field of endeavor called robot skins. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Mitchell_2021 and Hayashi_2020.The rationale for doing so would have been to follow a teaching and motivation proposed in the prior art. Mitchell_2021 teaches a fabrication method for robot skins. Hayashi par 154 states “a user can easily mount and remove the outer skin 314, meaning that when the outer skin 314 becomes dirty, the user can maintain cleanliness by replacing and laundering by him or herself.” Therefore, it would have been obvious to combine the robot skins of Mitchell_2021 with the attachment technique of Hayashi_2020 for the benefit of being able to remove and clean the outer skin, rather than having it integrally molded to the EAPs to obtain the invention as specified in the claims.
Claim 3:
Mitchell_2021 makes obvious The system of claim 2, Par 24: “ In some embodiments, the artificial skin is a silicone (or other similarly elastic) material that is rigidly attached to the animatronic design in some places, and attached to movable actuators in others. )
Mitchell_2021 does not expressly recite wherein the EAPs are formed of a material with a hardness greater
Lessing_2016 however makes obvious wherein the EAPs are formed of a material with a hardness greater (par 6: “ Furthermore, conventional soft robotic actuators are constructed from a single elastomeric material such as silicone elastomer. Some actuators incorporate elastomers of differing stiffness or wall thickness to accommodate a certain desired behavior. This layer of varying thickness or stiffness is sometimes referred to as a strain limiting layer. Some actuators use incorporated or coextruded fibrous materials in the elastomer body of the actuator itself. Such co-molded fibers are intended to improve resistance to puncture and strengthen the actuator. Some actuators use textile socks with slits to increase the operating pressure regime of an actuator.” .. par 7: “In the case of silicones, whose stiffness is highly correlated with hardness, useful materials for soft actuators typically fall within the range of 10-80A Durometer yielding at most an 800% differential in stiffness between select regions of the actuator. “) Examiner note: Where the skin of Mitchell_2021 is silicon, and elastomers with co-molded fibers from silicone would have a greater hardness as implied in this passage.
Mitchell_2021 and Lessing_2016 are analogous art to the claimed invention because they are from the same field of endeavor called robotic skins. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Mitchell_2021 and Lessing_2016 The rationale for doing so would have been to follow a teaching and motivation in the prior art. Lessing_2016 implies that hardening actuators par 6: “to improve resistance to puncture and strengthen the actuator”. Therefore, it would have been obvious to combine the face technology of Mitchell_2021 with increased hardness of actuators of Lessing_2016 for the benefit of strengthening the actuator so it does not break when stretching the silicon skin to obtain the invention as specified in the claims.
Claim 4:
Michell_2021 makes obvious The system of claim 2, wherein the generating of the Par 53: “In some embodiments, the animatronic mechanical design further specifies the endpoints of each actuator. For example, if the actuator has its movement restricted (e.g., by other components of the design, or to ensure the movement is within the desired goals), the animatronic mechanical design specifies the extremes of the travel each actuator is allowed.” … Par 55: “ In one embodiment, the set of configurations used to generate the predictive meshes are provided by a user. In some embodiments, the user can specify two or more poses (e.g., sets of configurations), and the Design Application 330 generates intermediate poses (sets of actuator configurations) between the specified poses, in order to predict the deformation of the skin as the actuators move between poses, in addition to while stopped at each pose. These predicted meshes can be used to validate the underlying design.” )
Mitchell_2021 does not expressly recite optimized .. optimizing
Bickel_2012 however makes obvious optimized .. optimizing (par 81: “The method 600 continues at step 608, where the processor generates a plurality of actuation parameters, where each actuation parameter is optimized to deform the surface geometry such that deformed surface base matches a corresponding one of the target surfaces. The actuation parameter optimization according to embodiments of the invention find the best values for controlling the mechanical actuators of the animatronic device such that the resulting deformed skin matches a given target pose as closely as possible.”)
As already stated, Mitchell_2021 and Bickel_2012 are analogous art to the claimed invention of robotic skin optimization. Therefore, it would have been obvious to combine the simulation workflow of Mitchell_2021 with the optimization of skin thickness and shape of Bickel_2012 for the benefit of improving accuracy in machine robot skin models to match a target surface to obtain the invention as specified in the claims.
Claim 12:
Mitchell_2021 makes obvious A method for par 5: “According to a third embodiment of the present disclosure, a system is provided. The system includes one or more computer processors, and a memory containing a program which when executed by the one or more computer processors performs an operation. The operation includes generating a first plurality of simulated meshes using a physics simulation model, wherein the first plurality of simulated meshes corresponds to a first plurality of actuator configurations for an animatronic mechanical design. The operation further includes training a machine learning model based on the first plurality of simulated meshes and the first plurality of actuator configurations. Additionally, the operation includes generating, using the machine learning model, a plurality of predicted meshes for the animatronic mechanical design, based on a second plurality of actuator configurations. Further, the operation includes facilitating virtual animation of the animatronic mechanical design based on the plurality of predicted meshes.”) … par 26: “As illustrated, once an initial design is developed, the Workflow 200 moves to a phase for Simulation 230. In an embodiment, the Simulation 230 generally includes using one or more physics simulation models to simulate artificial skin deformations based on the animatronic mechanical design, and to refine the design based on these simulations.”(Examiner note: i.e.: optimize)
with a computing device, receiving or accessing in memory (par 5: “The system includes one or more computer processors, and a memory containing a program which when executed by the one or more computer processors performs an operation. “) a set of design parameters for a skin system for covering at least a portion of the mechanical assembly; par 18: “ In some embodiments, a physics simulation model is used to simulate the animatronic mechanical design. In an embodiment, the simulation model receives a digital representation of the mechanical design, including the location, type, and orientation of each actuator, the attributes of the artificial skin, the actuation points, and any other attributes needed to simulate the design. “… par 39: “in the illustrated embodiment, the Storage 320 includes one or more Mechanical Designs “ … par 68: “The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like). In some embodiments, the user can specify two or more configurations, and the Design Application 330 can generate a series of values between them, in order to interpolate movement from a first pose to a second. The method 800 then proceeds to block 810.”) Examiner note: Where the above makes obvious receiving or accessing in memory user input, which includes both a definition of the mechanical assembly design and control parameters for the mechanical assembly
with the computing device, receiving or accessing in memory (par 5: “The system includes one or more computer processors, and a memory containing a program which when executed by the one or more computer processors performs an operation. “) a target shape of an outer surface of a body of the skin system at a predefined time of operations of the mechanical assembly; (par 35: “After training the Deep Learning 255, the trained model(s) can be used to generate predicted meshes for the animatronic design, given a pose (Examiner note: ie: target shape) (e.g., a set of actuator configurations). Using these models, therefore, designers can provide actuator configurations (or a series of actuator configurations) to generate the corresponding predicted mesh(es). As depicted in the illustrated workflow 200, this enables Design validation 260. In one embodiment, a user provides a sequence of configurations, and the models output a series of meshes, which can be combined to create a predicted mesh that moves over time, representing the animatronic design in motion (e.g., as the actuators move). In some embodiments, this is output as a video or animation file.”
with a skin design program (par 5: “Additionally, the operation includes generating, using the machine learning model, a plurality of predicted meshes for the animatronic mechanical design, based on a second plurality of actuator configurations”) running on the computing device, (par 5: “The system includes one or more computer processors, and a memory containing a program which when executed by the one or more computer processors performs an operation”) generating an par 26: As illustrated, once an initial design is developed, the Workflow 200 moves to a phase for Simulation 230. In an embodiment, the Simulation 230 generally includes using one or more physics simulation models to simulate artificial skin deformations based on the animatronic mechanical design, and to refine the design based on these simulations.) by generating an par 40: “In the illustrated embodiment, the Simulated Meshes 360 are three-dimensional surface meshes made of elements (e.g., tetrahedral elements). In one embodiment, during simulation, the simulator derives the deformed nodes of these elements and generates volumetric meshes, in order to output surface meshes of the deformed skin (e.g., to output Simulated Meshes 360). In one embodiment, the Simulated Meshes 360 are generated by using a physics simulation model that uses physics to simulate the deformations that will occur in an artificial skin given a set of configurations for actuators that are coupled to the skin. In embodiments, this simulation process is highly accurate, but is compute-intensive and time-consuming. In some embodiments, the actuator configurations used to create the Simulated Meshes 360 are selected in a way that ensures adequate coverage of all potential poses the animatronic can make (or that the designer expects to use).”) … par 41: “In this way, the models can be trained and refined to predict mesh deformations given sets of actuator parameters. In the illustrated embodiment, the Predicted Meshes 365 are three-dimensional surface meshes of the skin, each comprising a set of vertices connected by one or more edges and/or polygons. In some embodiments, rather than being trained to generate surface meshes, the simulation is trained on volumetric meshes (Examiner note: a three dimensional shape and thickness, where the optimized model are generated based on initial training parameters) (e.g., generated by the simulation components) and similarly generates volumetric meshes. In an embodiment, the Predicted Meshes 365 are generated by providing actuator configurations to the trained learning model(s). Although depicted as residing in Storage 320, in embodiments, the Mechanical Design(s) 355, Simulated Mesh(es) 360, and Predicted Mesh(es) 365 may reside in any suitable location.”
par 35: “After training the Deep Learning 255, the trained model(s) can be used to generate predicted meshes for the animatronic design, given a pose (Examiner note: ie: target shape) (e.g., a set of actuator configurations). Using these models, therefore, designers can provide actuator configurations (or a series of actuator configurations) to generate the corresponding predicted mesh(es). As depicted in the illustrated workflow 200, this enables Design validation 260. In one embodiment, a user provides a sequence of configurations, and the models output a series of meshes, which can be combined to create a predicted mesh that moves over time, representing the animatronic design in motion (e.g., as the actuators move). In some embodiments, this is output as a video or animation file.”)
wherein the user input further comprises a definition of a set of par 18: “In an embodiment, the simulation model receives a digital representation of the mechanical design, including the location, type, and orientation of each actuator,” … par 68: “The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like).”) wherein the definition includes a definition of par 18: “In an embodiment, the simulation model receives a digital representation of the mechanical design, including the location, type, and orientation of each actuator, the attributes of the artificial skin, the actuation points, and any other attributes needed to simulate the design.” … Par 39: “For example, in such an embodiment, the Mechanical Design 355 indicates the number, type, power, location, orientation, and any other relevant parameters for each actuator and/or actuation point in the design. In an embodiment, the Mechanical Design 355 indicates both the configuration of actuators, as well as the location, size, orientation, and the like of each actuation point they drive.”) and wherein the EAPs are attached on a first side to the mechanical assembly par 39: “ In some embodiments, the Mechanical Design 355 further specifies the details of the underlying mechanical assembly (e.g., its shape and material, where the skin and/or actuators attach, and the like) Examiner note: Where actuators attach implies that the actuators are attached to the mechanical assembly by at least a first side, see also figure 1whereby the EAPs are not integrally bound to the body. (par 17: “In order to develop mechanical animatronic designs, experienced developers construct a mechanical assembly, determine the size(s), shape(s), and location(s) of actuation points where the actuators connect to or contact with the artificial skin,” Examiner note: Where “or contact” implies that the EAPS’s are not integrally bound to the body
Mitchell_2021 does not expressly recite
optimized
wherein the optimized shape and the optimized thickness are selected such that the outer surface of the body substantially matches
Elastomeric
Bickel_2012 however makes obvious Par 57: “Accordingly, the skin patch 506 may be processed according to the optimization process described herein to generate an optimized skin patch 510 having a varying inner surface (i.e., material thickness). A deformation of the optimized skin patch 510 may be simulated according to the computational model and the resultant deformed shape 512 may be compared to the target surface 502. As shown, the optimization process determines an optimized skin geometry such that the skin has a shape and geometry that closely matches target surfaces when deformed.”)
optimizedPar 57: “Accordingly, the skin patch 506 may be processed according to the optimization process described herein to generate an optimized skin patch 510 having a varying inner surface (i.e., material thickness). A deformation of the optimized skin patch 510 may be simulated according to the computational model and the resultant deformed shape 512 may be compared to the target surface 502. As shown, the optimization process determines an optimized skin geometry such that the skin has a shape and geometry that closely matches target surfaces when deformed.”)
wherein the optimized shape and the optimized thickness are selected such that the outer surface of the body substantially matches Par 57: “Accordingly, the skin patch 506 may be processed according to the optimization process described herein to generate an optimized skin patch 510 having a varying inner surface (i.e., material thickness). A deformation of the optimized skin patch 510 may be simulated according to the computational model and the resultant deformed shape 512 may be compared to the target surface 502. As shown, the optimization process determines an optimized skin geometry such that the skin has a shape and geometry that closely matches target surfaces when deformed.”)
Bickel_2012 and Mitchell_2021 are analogous art to the claimed invention because they are from the same field of endeavor called synthetic skin optimization for robots. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Bickel_2012 and Mitchell_2021. The rationale for doing so would have been to follow a teaching and motivation present in the prior art. The prior art of Mitchell_2021 contains a base product, which is a simulation used to optimize actuator configurations to match a static pose, see par 31: “ In one embodiment, training the Deep Learning 255 comprises providing a set of actuator configurations as input to the model(s), and applying the corresponding simulated mesh as the target output. In an embodiment, the models are configured to optimize surface-to-surface loss such that the generated predicted mesh closely aligns with the simulated mesh. In one embodiment, optimizing surface-to-surface loss includes optimizing vertex-to-vertex loss.”Mitchell_2021 does teach controlling skin thickness, but not necessarily optimizing it, see par 24: “In one embodiment, the thickness and/or elasticity of the Artificial Skin 105 is controlled to provide predictable and preferred deformations.“ Mitchell_2021 does not expressly recite that the skin shape and thickness itself is being optimized to match the target, as understood by the examiner, Mitchell_2021 is teaching an optimization of the actuators to calculate skin deformation as well as a validation process where this skin is matched to a target, but not directly optimizing the thickness of the skin itself. Bickel_2012 teaches a method which allows the user to reconstruct a human subjects skin to a high accuracy level, specifically by optimizing the skin itself. see mapping above, and motivations of par 24: “The 3D reconstructions may comprise high-resolution data that includes data about pores and wrinkles of the subject's skin, as well as robust temporal correspondence, to provide information about the deformation behavior of the human subject's skin.” And par 94: “According to the experimental validation techniques described above, this process permits the design of a soft tissue animatronic character that accurately mimics a given real person.” Therefore, it would have been obvious to combine the simulation workflow of Mitchell_2021 with the optimization of skin thickness and shape of Bickel_2012 for the benefit of improving accuracy in machine robot skin models to obtain the invention as specified in the claims.
Bickel_2012 and Mitchell_2021 do not expressly recite Elastomeric
Lessing_2016 however makes obvious Elastomeric (par 6: “Furthermore, conventional soft robotic actuators are constructed from a single elastomeric material such as silicone elastomer”)
stiffness or wall thickness to accommodate a certain desired behavior. ) Examiner note: Where this makes obvious choosing between different elastomer chape and materials for an EAP.
Mitchell_2021 and Lessing_2016 are analogous art to the claimed invention because they are from the same field of endeavor called robotics. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Mitchell_2021 and Lessing_2016. The rationale for doing so would have been obvious to try. The prior art of Mitchell_2021 identifies a need for a robotic device which uses actuators to move skin for a robot. The prior art of Mitchell_2021 identifies that varying types of actuators may be chosen. See par 18: “including the location, type, and orientation of each actuator.” Mitchell_2021 is silent on the actuator being elastomeric. However, the prior art of Lessing_2016 identifies elastomeric actuators as the conventional solution used in order to actuate a soft robot. Furthermore, Mitchell_2021 states to choose par 39: “and any other relevant parameters for each actuator and/or actuation point in the design.” Where Lessing_2016 states that body shape and material is a relevant parameter for actuators in a design. One reasonably skilled in the art would have known to pursue using an elastomeric actuator as well including body shapes and materials in light of both references. Therefore, it would have been obvious to combine the simulation workflow and robotic face moving technology of Mitchell_2021 with the use of elastomeric actuators of varying materials and shape of Lessing_2016 to accommodate for desired behavior when designing robot skin systems and to obtain the invention as specified in the claims.
Mitchell_2021 and Lessing_2016 do not expressly recite and have a second side with a recessed surface for receiving a portion of an EAP post extending outward from an inner surface of the skin body,
Hayashi_2020 makes obvious and have a second side with a recessed surface for receiving a portion of an EAP post extending outward from an inner surface of the skin body, whereby the EAPs are not integrally bound to the skin bodypar 8: “Another aspect of the invention is also a robot including an outer skin with which a main body is covered. A recessed fitting portion is provided extended along an outer face of the main body. A fitting member of a form complementing the recessed fitting portion is provided on the outer skin. The outer skin is fixed to the main body by the fitting member being fitted into the recessed fitting portion (Examiner note: where the EAP is the recessed fitting portion)
Mitchell_2021 and Hayashi_2020 are analogous art to the claimed invention because they are from the same field of endeavor called robot skins. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Mitchell_2021 and Hayashi_2020.The rationale for doing so would have been to follow a teaching and motivation proposed in the prior art. Mitchell_2021 teaches a fabrication method for robot skins. Hayashi par 154 states “a user can easily mount and remove the outer skin 314, meaning that when the outer skin 314 becomes dirty, the user can maintain cleanliness by replacing and laundering by him or herself.” Therefore, it would have been obvious to combine the robot skins of Mitchell_2021 with the attachment technique of Hayashi_2020 for the benefit of being able to remove and clean the outer skin, rather than having it integrally molded to the EAPs to obtain the invention as specified in the claims.
Claim 13:
The method of claim 12, wherein the EAPs are formed of a material with a hardness greater than a hardness of the material used to form the body. ( Par 24: “ In some embodiments, the artificial skin is a silicone (or other similarly elastic) material that is rigidly attached to the animatronic design in some places, and attached to movable actuators in others. )
Mitchell_2021 does not expressly recite wherein the EAPs are formed of a material with a hardness greater
Lessing_2016 however makes obvious wherein the EAPs are formed of a material with a hardness greater (par 6: “ Furthermore, conventional soft robotic actuators are constructed from a single elastomeric material such as silicone elastomer. Some actuators incorporate elastomers of differing stiffness or wall thickness to accommodate a certain desired behavior. This layer of varying thickness or stiffness is sometimes referred to as a strain limiting layer. Some actuators use incorporated or coextruded fibrous materials in the elastomer body of the actuator itself. Such co-molded fibers are intended to improve resistance to puncture and strengthen the actuator. Some actuators use textile socks with slits to increase the operating pressure regime of an actuator.” .. par 7: “In the case of silicones, whose stiffness is highly correlated with hardness, useful materials for soft actuators typically fall within the range of 10-80A Durometer yielding at most an 800% differential in stiffness between select regions of the actuator. “) Examiner note: Where the skin of Mitchell_2021 is silicon, and elastomers with co-molded fibers from silicone would have a greater hardness as implied in this passage.
Mitchell_2021 and Lessing_2016 are analogous art to the claimed invention because they are from the same field of endeavor called robotic skins. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Mitchell_2021 and Lessing_2016 The rationale for doing so would have been to follow a teaching and motivation in the prior art. Lessing_2016 implies that hardening actuators par 6: “to improve resistance to puncture and strengthen the actuator”. Therefore, it would have been obvious to combine the face technology of Mitchell_2021 with increased hardness of actuators of Lessing_2016 for the benefit of strengthening the actuator so it does not break when stretching the silicon skin to obtain the invention as specified in the claims.
Claim 14:
The method of claim 12, wherein the generating of the optimized design further comprises optimizing time-varying positions of one or more of the EAPs. (Par 53: “In some embodiments, the animatronic mechanical design further specifies the endpoints of each actuator. For example, if the actuator has its movement restricted (e.g., by other components of the design, or to ensure the movement is within the desired goals), the animatronic mechanical design specifies the extremes of the travel each actuator is allowed.” … Par 55: “ In one embodiment, the set of configurations used to generate the predictive meshes are provided by a user. In some embodiments, the user can specify two or more poses (e.g., sets of configurations), and the Design Application 330 generates intermediate poses (sets of actuator configurations) between the specified poses, in order to predict the deformation of the skin as the actuators move between poses, in addition to while stopped at each pose. These predicted meshes can be used to validate the underlying design.” )
Mitchell_2021 does not expressly recite optimized .. optimizing
Bickel_2012 however makes obvious optimized .. optimizing (par 81: “The method 600 continues at step 608, where the processor generates a plurality of actuation parameters, where each actuation parameter is optimized to deform the surface geometry such that deformed surface base matches a corresponding one of the target surfaces. The actuation parameter optimization according to embodiments of the invention find the best values for controlling the mechanical actuators of the animatronic device such that the resulting deformed skin matches a given target pose as closely as possible.”)
As already stated, Mitchell_2021 and Bickel_2012 are analogous art to the claimed invention of robotic skin optimization. Therefore, it would have been obvious to combine the simulation workflow of Mitchell_2021 with the optimization of skin thickness and shape of Bickel_2012 for the benefit of improving accuracy in machine robot skin models to match a target surface to obtain the invention as specified in the claims.
Claim 15:
Mitchell_2021 makes obvious The method of claim 12, wherein the generating of the optimized design further comprises generating a neutral pose for the skin body (Par 23: “FIG. 1 illustrates an animatronic face, according to one embodiment of the present disclosure. In the illustrated embodiment, the facial profile comprises an Artificial Skin 105, controlled by a set of Actuators 110A-N. Although linear actuators are illustrated, in embodiments, any collection of actuators can be used, including rotational, linear, and combinational actuators. Additionally, in embodiments, motors or Actuators 110A-N may be utilized to drive a mechanical assembly that in turn, actuates the Artificial Skin 105. As illustrated by the Configuration 100A, when the Actuators 110A-N have a first configuration, the Artificial Skin 105 has a neutral expression with the mouth held closed. As further illustrated in FIG. 1, when the Actuators 110A-N take a different Configuration 1008, the Artificial Skin 105 deforms to open the mouth and form a different expression.”) Examiner note: Where this makes obvious the generation of a neutral pose.
and wherein the skin design program comprises a soft body simulator configured to simulate movement of the body of the skin during operations of the mechanical assembly. (Par 55: “ In one embodiment, the set of configurations used to generate the predictive meshes are provided by a user. In some embodiments, the user can specify two or more poses (e.g., sets of configurations), and the Design Application 330 generates intermediate poses (sets of actuator configurations) between the specified poses, in order to predict the deformation of the skin as the actuators move between poses, in addition to while stopped at each pose. “ par 68: “FIG. 8 is a flow diagram illustrating a method 800 for generating predicted meshes for an animatronic design, according to one embodiment disclosed herein. The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like). In some embodiments, the user can specify two or more configurations, and the Design Application 330 can generate a series of values between them, in order to interpolate movement from a first pose to a second. The method 800 then proceeds to block 810.”)
Claim 18:
Mitchell_2021 makes obvious The system of claim 17, wherein the user input further comprises a definition of a set of par 18: “In an embodiment, the simulation model receives a digital representation of the mechanical design, including the location, type, and orientation of each actuator,” … par 68: “The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like).”) wherein the definition includes a definition of par 18: “In an embodiment, the simulation model receives a digital representation of the mechanical design, including the location, type, and orientation of each actuator, the attributes of the artificial skin, the actuation points, and any other attributes needed to simulate the design.” … Par 39: “For example, in such an embodiment, the Mechanical Design 355 indicates the number, type, power, location, orientation, and any other relevant parameters for each actuator and/or actuation point in the design. In an embodiment, the Mechanical Design 355 indicates both the configuration of actuators, as well as the location, size, orientation, and the like of each actuation point they drive.”) and wherein the EAPs are attached on a first side to the mechanical assembly par 39: “ In some embodiments, the Mechanical Design 355 further specifies the details of the underlying mechanical assembly (e.g., its shape and material, where the skin and/or actuators attach, and the like) Examiner note: Where actuators attach implies that the actuators are attached to the mechanical assembly by at least a first side, see also figure 1. par 17: “In order to develop mechanical animatronic designs, experienced developers construct a mechanical assembly, determine the size(s), shape(s), and location(s) of actuation points where the actuators connect to or contact with the artificial skin,” Examiner note: Where “or contact” implies that the EAPS’s are not integrally bound to the body
Mitchell_2021 does not expressly recite Elastomeric
Lessing_2016 however makes obvious Elastomeric (par 6: “Furthermore, conventional soft robotic actuators are constructed from a single elastomeric material such as silicone elastomer”)
stiffness or wall thickness to accommodate a certain desired behavior. ) Examiner note: Where this makes obvious choosing between different elastomer chape and materials for an EAP.
Mitchell_2021 and Lessing_2016 are analogous art to the claimed invention because they are from the same field of endeavor called robotics. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Mitchell_2021 and Lessing_2016. The rationale for doing so would have been obvious to try. The prior art of Mitchell_2021 identifies a need for a robotic device which uses actuators to move skin for a robot. The prior art of Mitchell_2021 identifies that varying types of actuators may be chosen. See par 18: “including the location, type, and orientation of each actuator.” Mitchell_2021 is silent on the actuator being elastomeric. However, the prior art of Lessing_2016 identifies elastomeric actuators as the conventional solution used in order to actuate a soft robot. Furthermore, Mitchell_2021 states to choose par 39: “and any other relevant parameters for each actuator and/or actuation point in the design.” Where Lessing_2016 states that body shape and material is a relevant parameter for actuators in a design. One reasonably skilled in the art would have known to pursue using an elastomeric actuator as well including body shapes and materials in light of both references. Therefore, it would have been obvious to combine the simulation workflow and robotic face moving technology of Mitchell_2021 with the use of elastomeric actuators of varying materials and shape of Lessing_2016 to accommodate for desired behavior when designing robot skin systems and to obtain the invention as specified in the claims.
Mitchell_2021 and Lessing_2016 do not expressly recite and have a second side with a recessed surface for receiving a portion of an EAP post extending outward from an inner surface of the skin body,
Hayashi_2020 makes obvious and have a second side with a recessed surface for receiving a portion of an EAP post extending outward from an inner surface of the skin body, whereby the EAPs are not integrally bound to the skin bodypar 8: “Another aspect of the invention is also a robot including an outer skin with which a main body is covered. A recessed fitting portion is provided extended along an outer face of the main body. A fitting member of a form complementing the recessed fitting portion is provided on the outer skin. The outer skin is fixed to the main body by the fitting member being fitted into the recessed fitting portion (Examiner note: where the EAP is the recessed fitting portion)
Mitchell_2021 and Hayashi_2020 are analogous art to the claimed invention because they are from the same field of endeavor called robot skins. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Mitchell_2021 and Hayashi_2020.The rationale for doing so would have been to follow a teaching and motivation proposed in the prior art. Mitchell_2021 teaches a fabrication method for robot skins. Hayashi par 154 states “a user can easily mount and remove the outer skin 314, meaning that when the outer skin 314 becomes dirty, the user can maintain cleanliness by replacing and laundering by him or herself.” Therefore, it would have been obvious to combine the robot skins of Mitchell_2021 with the attachment technique of Hayashi_2020 for the benefit of being able to remove and clean the outer skin, rather than having it integrally molded to the EAPs to obtain the invention as specified in the claims.
Claim 19:The system of claim 18, wherein the generating of the Par 53: “In some embodiments, the animatronic mechanical design further specifies the endpoints of each actuator. For example, if the actuator has its movement restricted (e.g., by other components of the design, or to ensure the movement is within the desired goals), the animatronic mechanical design specifies the extremes of the travel each actuator is allowed.” … Par 55: “ In one embodiment, the set of configurations used to generate the predictive meshes are provided by a user. In some embodiments, the user can specify two or more poses (e.g., sets of configurations), and the Design Application 330 generates intermediate poses (sets of actuator configurations) between the specified poses, in order to predict the deformation of the skin as the actuators move between poses, in addition to while stopped at each pose. These predicted meshes can be used to validate the underlying design.” )
Mitchell_2021 does not expressly recite optimized .. optimizing
Bickel_2012 however makes obvious optimized .. optimizing (par 81: “The method 600 continues at step 608, where the processor generates a plurality of actuation parameters, where each actuation parameter is optimized to deform the surface geometry such that deformed surface base matches a corresponding one of the target surfaces. The actuation parameter optimization according to embodiments of the invention find the best values for controlling the mechanical actuators of the animatronic device such that the resulting deformed skin matches a given target pose as closely as possible.”)
As already stated, Mitchell_2021 and Bickel_2012 are analogous art to the claimed invention of robotic skin optimization. Therefore, it would have been obvious to combine the simulation workflow of Mitchell_2021 with the optimization of skin thickness and shape of Bickel_2012 for the benefit of improving accuracy in machine robot skin models to match a target surface to obtain the invention as specified in the claims.
Claims 7 is rejected under 35 U.S.C. 103 as being unpatentable over Mitchell_2021, Bickel_2012, and US 8786613 B2 (Millman_2014)
Claim 7:
The system of claim 6, wherein the soft body simulator is configured
Mitchell_2021 does not expressly recite to process frictional contact between soft bodies and between rigid and soft bodies via a contact model that is differentiable.
Millmen_2014 however makes obvious to process frictional contact between soft bodies and between rigid and soft bodies via a contact model that is differentiable. (Abstract : “The method and system provide flexible simulation, the ability to combine rigid and flexible simulation on plural portions of a model, rendering of haptic forces and force-feedback to a user.” … par 98: “t Step 26, plural forces and optionally torques are calculated on the entity using any of the obtained or previously calculated positions, orientations, velocities, and accelerations. The plural forces and torques may be calculated from the combined effects of any of gravity, friction, interaction with other entities, interactions within a single entity, collision with other entities, interaction with objects controlled by a user holding, wearing, or manipulating a haptic or other device, or other forces, these forces affecting the combined rigid and flexible components of the entity. “ Examiner note: Where the examiner understands the flexible components of this application to refer to soft bodies based on the background. Where the examiner understands this model to be differentiable based on Fig 9 and Tables 2-4.
Mitchell_2021 and Millman_2014 are analogous art to the claimed invention because they are from the same field of endeavor called robotic simulation. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Mitchell_2021 and Millman_2014. The rationale for doing so would have been to follow a teaching or motivation proposed in the prior art. Millman_2014 states par 41: “A method and system for drawing, displaying, editing animating, simulating and interacting with one or more virtual polygonal, spline, volumetric models, three-dimensional visual models or robotic models. The method and system provide flexible simulation, the ability to combine rigid and flexible simulation on plural portions of a model,” Mitchell_2021 teaches to perform these functions with a robot skin simulator, including animation par 50: “In some embodiments, the Deep Learning Component 345 and/or Validation Component 350 are further used to provide animators with a realistic and accurate rig to animate with using digital artist tools. This in turn allows animators to animate using these offline tools in a manner that is very similar to animating on the actual animatronic itself. For example, users may use buttons, sliders, and the like to move actuators in the rig, while the Deep Learning Component 345 generates predicted meshes for the input values. This allows users to view and animate the planned animatronic in a highly-realistic environment. In some embodiments, the user can further use these input values as the actuator values that are used to animate the physical animatronic.” When animating planned animatronic in highly-realistic environments which include rigid bodies, one ordinarily skilled in the art would be motivated to include the simulation of Millman_2014 which simulates these interactions to combine rigid and flexible simulation on plural portions of a model. Therefore, it would have been obvious to combine the simulation and animation simulator of Mitchell_2021 with the explicit simulation of interactions between soft and rigid bodies of Millman_2014 for the benefit of combine rigid and flexible simulation on plural portions of a model to simulate highly realistic environments to obtain the invention as specified in the claims.
Claims 16 is rejected under 35 U.S.C. 103 as being unpatentable over Mitchell_2021, Bickel_2012, Lessing_2016, Hayashi_2020 and Millman_2014
The method of claim 15,
Mitchell_2021 makes obvious wherein the soft body simulator is configured Par 55: “ In one embodiment, the set of configurations used to generate the predictive meshes are provided by a user. In some embodiments, the user can specify two or more poses (e.g., sets of configurations), and the Design Application 330 generates intermediate poses (sets of actuator configurations) between the specified poses, in order to predict the deformation of the skin as the actuators move between poses, in addition to while stopped at each pose. “ par 68: “FIG. 8 is a flow diagram illustrating a method 800 for generating predicted meshes for an animatronic design, according to one embodiment disclosed herein. The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like). In some embodiments, the user can specify two or more configurations, and the Design Application 330 can generate a series of values between them, in order to interpolate movement from a first pose to a second. The method 800 then proceeds to block 810.”)
wherein the soft body simulator is configured to be Par 55: “ In one embodiment, the set of configurations used to generate the predictive meshes are provided by a user. In some embodiments, the user can specify two or more poses (e.g., sets of configurations), and the Design Application 330 generates intermediate poses (sets of actuator configurations) between the specified poses, in order to predict the deformation of the skin as the actuators move between poses, in addition to while stopped at each pose. “ par 68: “FIG. 8 is a flow diagram illustrating a method 800 for generating predicted meshes for an animatronic design, according to one embodiment disclosed herein. The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like). In some embodiments, the user can specify two or more configurations, and the Design Application 330 can generate a series of values between them, in order to interpolate movement from a first pose to a second. The method 800 then proceeds to block 810.”) in an unstressed, neutral pose, (par 23: “when the Actuators 110A-N have a first configuration, the Artificial Skin 105 has a neutral expression with the mouth held closed. As further illustrated in FIG. 1, when the Actuators 110A-N take a different Configuration 1008, the Artificial Skin 105 deforms to open the mouth and form a different expression.”) Examiner note: Where this makes obvious a neutral pose in the above process which interpolates between two poses).
and wherein the soft body simulator is configured to be Par 55: “ In one embodiment, the set of configurations used to generate the predictive meshes are provided by a user. In some embodiments, the user can specify two or more poses (e.g., sets of configurations), and the Design Application 330 generates intermediate poses (sets of actuator configurations) between the specified poses, in order to predict the deformation of the skin as the actuators move between poses, in addition to while stopped at each pose. “ par 68: “FIG. 8 is a flow diagram illustrating a method 800 for generating predicted meshes for an animatronic design, according to one embodiment disclosed herein. The method 800 begins at block 805, where a Design Application 330 receives a set of one or more desired configurations. In an embodiment, these actuator positions are specified by a user, in order to visualize the resulting deformations of an animatronic. In one embodiment, the user specifies these values by entering them manually (e.g., typing them in, dragging a sliding element on a GUI, and the like). In some embodiments, the user can specify two or more configurations, and the Design Application 330 can generate a series of values between them, in order to interpolate movement from a first pose to a second. The method 800 then proceeds to block 810.”)
Mitchell_2021 does not expressly recite to process frictional contact between soft bodies and between rigid and soft bodies via a contact model that is differentiable.
Millmen_2014 however makes obvious to process frictional contact between soft bodies and between rigid and soft bodies via a contact model that is differentiable. (Abstract : “The method and system provide flexible simulation, the ability to combine rigid and flexible simulation on plural portions of a model, rendering of haptic forces and force-feedback to a user.” … par 98: “t Step 26, plural forces and optionally torques are calculated on the entity using any of the obtained or previously calculated positions, orientations, velocities, and accelerations. The plural forces and torques may be calculated from the combined effects of any of gravity, friction, interaction with other entities, interactions within a single entity, collision with other entities, interaction with objects controlled by a user holding, wearing, or manipulating a haptic or other device, or other forces, these forces affecting the combined rigid and flexible components of the entity. “ Examiner note: Where the examiner understands the flexible components of this application to refer to soft bodies based on the background. Where the examiner understands this model to be differentiable based on Fig 9 and Tables 2-4.
Mitchell_2021 and Millman_2014 are analogous art to the claimed invention because they are from the same field of endeavor called robotic simulation. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Mitchell_2021 and Millman_2014. The rationale for doing so would have been to follow a teaching or motivation proposed in the prior art. Millman_2014 states par 41: “A method and system for drawing, displaying, editing animating, simulating and interacting with one or more virtual polygonal, spline, volumetric models, three-dimensional visual models or robotic models. The method and system provide flexible simulation, the ability to combine rigid and flexible simulation on plural portions of a model,” Mitchell_2021 teaches to perform these functions with a robot skin simulator, including animation par 50: “In some embodiments, the Deep Learning Component 345 and/or Validation Component 350 are further used to provide animators with a realistic and accurate rig to animate with using digital artist tools. This in turn allows animators to animate using these offline tools in a manner that is very similar to animating on the actual animatronic itself. For example, users may use buttons, sliders, and the like to move actuators in the rig, while the Deep Learning Component 345 generates predicted meshes for the input values. This allows users to view and animate the planned animatronic in a highly-realistic environment. In some embodiments, the user can further use these input values as the actuator values that are used to animate the physical animatronic.” When animating planned animatronic in highly-realistic environments which include rigid bodies, one ordinarily skilled in the art would be motivated to include the simulation of Millman_2014 which simulates these interactions to combine rigid and flexible simulation on plural portions of a model. Therefore, it would have been obvious to combine the simulation and animation simulator of Mitchell_2021 with the explicit simulation of interactions between soft and rigid bodies of Millman_2014 for the benefit of combine rigid and flexible simulation on plural portions of a model to simulate highly realistic environments to obtain the invention as specified in the claims.
Bickel_2012 however makes obvious Par 75: “According to one embodiment, the optimization process may be utilized to modify a local thickness of the synthetic skin geometry (examiner note: shape and thickness) in such a way that when mechanical actuators of the animatronic device are set to values corresponding to a particular expressive pose, the resulting deformation of the skin matches the expressive poses' target positions q as closely as possible. In a physical simulation, the actuators settings result in hard positional constraints that can be directly be applied to the corresponding deformed positions. Parameters Pthk may be determined that indicate a thickness distribution in an undeformed configuration without directly affecting the deformed positions of the synthetic skin. … par 76: “In one embodiment, the thickness distribution may be represented by a parameterized surface, such as described in FIGS. 7A-B above. In one embodiment, the parameters a, of all sample points, as described above, may be gathered into Pthk' and optimal height values may be computed by minimizing Equation 11. It is noted that the MLS interpolation described in FIGS. 7A-B result in a linear mapping between undeformed positions X and parameters Pthk, thus the matrix ax!apthk (Examiner note: as understood by the examiner this is a partial derivative, but even if not, this passage makes obvious the fact that the equations are differentiable) may be constant and, consequently, may be precomputed”
par 56:: “in one embodiment, this energy may be utilized in a static equilibrium problem in order to compute the deformation of the skin in response to actuator placements, which may translate into a set of position constraints. The deformed configuration of the skin is then determined as the minimum of the total energy via Equation (6) as follows:”) Examiner note: Where the equation given is a differentiable equation which simulates the skin in repones to control parameters of the actuators.
As already discussed, Mitchell_2021 and Bickel_2012 are analogous art to the claimed invention because they are from the same field of endeavor called optimizing skin for robots. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Mitchell_2021 and Bickel_2012 for the reasons stated in claim 1. Therefore, it would have been obvious to combine the simulation workflow of Mitchell_2021 with the optimization of skin thickness and shape of Bickel_2012 for the benefit of improving accuracy in machine robot skin models to obtain the invention as specified in the claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AHMAD HUSSAM SHALABY whose telephone number is (571)272-7414. The examiner can normally be reached Mon-Fri 7:30am - 5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Emerson Puente can be reached at 5712723652. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/A.H.S./Examiner, Art Unit 2187
/EMERSON C PUENTE/Supervisory Patent Examiner, Art Unit 2187
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