DETAILED CORRESPONDENCE
This is the first office action regarding application number 19/115,604, filed on 26 March 2025.
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 .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitations use a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are:
a. “acquisition section” in claim 1
b. “calculation section” in claims 1-3, 5, 7 and 9
c. “control section” in claim 1
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. Regarding the limitations reciting the “acquisition section”, “calculation section” and “control section”, the specification discloses a computer in Figures 6-7 and their corresponding paragraphs and an algorithm for performing the claimed functions in Figure 8 and its corresponding paragraph.
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitations to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitations recite sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1 and 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over NPL_ Matsuno et al. "Experimental study on control of an asteroid sample…" (Matsuno hereinafter), in view of Lin et al. (US 20240116178 A1 and Lin hereinafter).
Regarding Claim 1
Matsuno teaches a control device (see Abstract, all; Section 4: Control law, all) comprising:
an acquisition section that acquires a state of a control object at a time point t (see Fig. 4, t=0s; Section 2: Complementarity system "Let x0 be the state vector at the time t0..."; Section 5: Experiment "The initial state is defined as follows:...");
a calculation section that, on the basis of the state at the time point t, calculates a state of the control object at a time point t+1 so as to satisfy a complementarity condition (see Equations 1-3, 9 and 17-19; Fig. 4, all; Section 2: Complementarity system, all, especially "The complementarity system is described by differential-algebraic equations ... where x is a state vector, u is an input vector of the system, w is a variable which represents the effect from the constraint (for example constraint force), and z is an output related to the constraint condition."; Section 3.2: Complementarity modeling of sample return robot - Mode selection and condition for keeping contact, all, especially "As we consider the state that the robot contacts with the environment, the following conditions are satisfied."; Section 4, Control law, all), the complementarity condition relating to a contact force generated at a contact point at the control object and a distance between the control object and the contact point (see Fig. 1, all; Fig. 2, all; Equations 1-3, 9 and 17-19; Section 2: Complementarity system, all, especially "The complementarity system is described by differential-algebraic equations ... where x is a state vector, u is an input vector of the system, w is a variable which represents the effect from the constraint (for example constraint force), and z is an output related to the constraint condition ... each time t we must have either zi(t)=0 and wi(t)≥0, or wi(t)=0 and zi(t)≥0 ... We consider an example of a scalar system. Let z be the distance from environment to an object and w be the vertical force as shown in Fig. 1. In this two bodies system, we have two modes that z(t)=0,w(t)≥0 and w(t)=0,z(t)≥0. The former is called “constraint mode” and the latter is called “non-constraint mode”. The first condition implies that if the object contacts to the environment (z(t)=0) then the interaction between them generates the constraint force (w(t)≥0). The second condition comes from the fact that if the two bodies break contact, then the interaction between them vanishes and relative acceleration must be positive."; Section 3: Complementarity modeling of sample return robot, all, especially "The dynamic system that the point P=(px,py)T of the end effector is constrained at the contact point O can be represented as..."; Section 4, Control law, all); and
a control section that controls the control object so as to achieve the calculated state at the time point t+1 (see Figs. 4-6, all; Section 3.2: Complementarity modeling of sample return robot - Mode selection and condition for keeping contact "As we consider the state that the robot contacts with the environment, the following conditions are satisfied."; Section 4, Control law, all; Section 5: Experiment, all, especially "The control law (20), (24) accomplishes the desired task under the assumption that the robot does not slide and the system has enough friction ... In the case 2, we consider the uncertainty of the friction and we set fxd=0. To demonstrate the validity of the proposed control law (20) (24), experiments for the two cases have been carried out.").
Matsuno is silent regarding calculate the state of the control object at the time point t+1 so as to minimize an objective function,
the objective function representing a difference between the state at the time point t+1 and a target value.
Lin teaches a control device (see all Figs.; [0006]) comprising:
an acquisition section that acquires a state of a control object at a time point t (see [0016 "The reference signal r is provided to a junction 102, where a current robot state x is also provided as feedback."], [0028 "The control module 410 receives the reference signal r on a line 402 and robot state data (q and) on feedback lines 450 and 460."] and [0037]);
a calculation section that, on the basis of the state at the time point t, calculates a state of the control object at a time point t+1 so as to minimize an objective function (see claim 1; [0006], [0028 "The optimization block 412 computes an optimal control sequence or signal to achieve the prescribed reference, and the dynamics model block 414 is used in the optimization computation to predict the future state. The optimization block 412 and the dynamics model block 414 operate iteratively until the predicted future state matches the reference state within some tolerance, and system constraints are met."], [0037 "Equation (4) is the optimization objective function which minimizes the deviation between the reference state (the target state, which is given) and the state computed by the system dynamics model (Equation (3)), by varying the input variable (the torque u). Equation (5) is an equality constraint which defines how to predict the next step value for the state variable x based on the current step value of x and the current step value of the input variable u; this is determined using the system dynamics model (Equation (3))."] and [0055]), and the objective function representing a difference between the state at the time point t+1 and a target value (see Equation 4; claim 1, "...said calculation including an optimization computation with an objective function which determines a torque rate vector to minimize a difference between a predicted robot state and a reference robot state from the motion program while satisfying a constraint defining a robot dynamics equation of motion which computes the predicted robot state based on the torque rate vector and a constraint defining bounds on the torque rate vector..."; [0006], [0028], [0037 "Equation (4) is the optimization objective function which minimizes the deviation between the reference state (the target state, which is given) and the state computed by the system dynamics model (Equation (3)), by varying the input variable (the torque u). Equation (5) is an equality constraint which defines how to predict the next step value for the state variable x based on the current step value of x and the current step value of the input variable u; this is determined using the system dynamics model (Equation (3))."] and [0055]); and
a control section that controls the control object so as to achieve the calculated state at the time point t+1 (see Fig. 4, all; [0018], [0030 "The robot mechanics 424 include all of the mass, inertia and friction properties of the arms and joints in the robot 420. Altogether, the joint motors 422 and the mechanics 424 respond to the motor torque vector u—causing the robot 420 to assume a new state, defined by joint velocities q and, after an integral block 430, joint positions q. The robot state data q and q are provided to the control module 410 on the feedback lines 450 and 460, as mentioned earlier."], [0037] and [0063]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the control device of Matsuno to minimize an objective function representing a difference between the state at the time point t+1 and a target value, as taught by Lin, in order to more accurately model robot system dynamics while adhering to system constraints.
Regarding Claim 10
Matsuno teaches a control method (see Abstract, all; Section 4: Control law, all) comprising a computer executing processing including:
acquiring a state of a control object at a time point t (see Fig. 4, t=0s; Section 2: Complementarity system "Let x0 be the state vector at the time t0..."; Section 5: Experiment "The initial state is defined as follows:...");
on the basis of the state at the time point t, calculating a state of the control object at a time point t+1 so as to satisfy a complementarity condition (see Equations 1-3, 9 and 17-19; Fig. 4, all; Section 2: Complementarity system, all, especially "The complementarity system is described by differential-algebraic equations ... where x is a state vector, u is an input vector of the system, w is a variable which represents the effect from the constraint (for example constraint force), and z is an output related to the constraint condition."; Section 3.2: Complementarity modeling of sample return robot - Mode selection and condition for keeping contact, all, especially "As we consider the state that the robot contacts with the environment, the following conditions are satisfied."; Section 4, Control law, all), the complementarity condition relating to a contact force generated at a contact point at the control object and a distance between the control object and the contact point (see Fig. 1, all; Fig. 2, all; Equations 1-3, 9 and 17-19; Section 2: Complementarity system, all, especially "The complementarity system is described by differential-algebraic equations ... where x is a state vector, u is an input vector of the system, w is a variable which represents the effect from the constraint (for example constraint force), and z is an output related to the constraint condition ... each time t we must have either zi(t)=0 and wi(t)≥0, or wi(t)=0 and zi(t)≥0 ... We consider an example of a scalar system. Let z be the distance from environment to an object and w be the vertical force as shown in Fig. 1. In this two bodies system, we have two modes that z(t)=0,w(t)≥0 and w(t)=0,z(t)≥0. The former is called “constraint mode” and the latter is called “non-constraint mode”. The first condition implies that if the object contacts to the environment (z(t)=0) then the interaction between them generates the constraint force (w(t)≥0). The second condition comes from the fact that if the two bodies break contact, then the interaction between them vanishes and relative acceleration must be positive."; Section 3: Complementarity modeling of sample return robot, all, especially "The dynamic system that the point P=(px,py)T of the end effector is constrained at the contact point O can be represented as..."; Section 4, Control law, all); and
controlling the control object so as to achieve the calculated state at the time point t+1 (see Figs. 4-6, all; Section 3.2: Complementarity modeling of sample return robot - Mode selection and condition for keeping contact "As we consider the state that the robot contacts with the environment, the following conditions are satisfied."; Section 4, Control law, all; Section 5: Experiment, all, especially "The control law (20), (24) accomplishes the desired task under the assumption that the robot does not slide and the system has enough friction ... In the case 2, we consider the uncertainty of the friction and we set fxd=0. To demonstrate the validity of the proposed control law (20) (24), experiments for the two cases have been carried out.").
Matsuno is silent regarding calculating the state of the control object at the time point t+1 so as to minimize an objective function,
the objective function representing a difference between the state at the time point t+1 and a target value.
Lin teaches a control method (see all Figs.; [0006]) comprising a computer executing processing including:
acquiring a state of a control object at a time point t (see [0016 "The reference signal r is provided to a junction 102, where a current robot state x is also provided as feedback."], [0028 "The control module 410 receives the reference signal r on a line 402 and robot state data (q and) on feedback lines 450 and 460."] and [0037]);
on the basis of the state at the time point t, calculating a state of the control object at a time point t+1 so as to minimize an objective function (see claim 1; [0006], [0028 "The optimization block 412 computes an optimal control sequence or signal to achieve the prescribed reference, and the dynamics model block 414 is used in the optimization computation to predict the future state. The optimization block 412 and the dynamics model block 414 operate iteratively until the predicted future state matches the reference state within some tolerance, and system constraints are met."], [0037 "Equation (4) is the optimization objective function which minimizes the deviation between the reference state (the target state, which is given) and the state computed by the system dynamics model (Equation (3)), by varying the input variable (the torque u). Equation (5) is an equality constraint which defines how to predict the next step value for the state variable x based on the current step value of x and the current step value of the input variable u; this is determined using the system dynamics model (Equation (3))."] and [0055]), and the objective function representing a difference between the state at the time point t+1 and a target value (see Equation 4; claim 1, "...said calculation including an optimization computation with an objective function which determines a torque rate vector to minimize a difference between a predicted robot state and a reference robot state from the motion program while satisfying a constraint defining a robot dynamics equation of motion which computes the predicted robot state based on the torque rate vector and a constraint defining bounds on the torque rate vector..."; [0006], [0028], [0037 "Equation (4) is the optimization objective function which minimizes the deviation between the reference state (the target state, which is given) and the state computed by the system dynamics model (Equation (3)), by varying the input variable (the torque u). Equation (5) is an equality constraint which defines how to predict the next step value for the state variable x based on the current step value of x and the current step value of the input variable u; this is determined using the system dynamics model (Equation (3))."] and [0055]); and
controlling the control object so as to achieve the calculated state at the time point t+1 (see Fig. 4, all; [0018], [0030 "The robot mechanics 424 include all of the mass, inertia and friction properties of the arms and joints in the robot 420. Altogether, the joint motors 422 and the mechanics 424 respond to the motor torque vector u—causing the robot 420 to assume a new state, defined by joint velocities q and, after an integral block 430, joint positions q. The robot state data q and q are provided to the control module 410 on the feedback lines 450 and 460, as mentioned earlier."], [0037] and [0063]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the process of Matsuno to include instructions to minimize an objective function representing a difference between the state at the time point t+1 and a target value, as taught by Lin, in order to more accurately model robot system dynamics while adhering to system constraints.
Regarding Claim 11
Matsuno teaches a non-transitory storage medium (see Abstract, all; Section 4: Control law, all) storing a control program that is executable by a computer to execute processing comprising:
acquiring a state of a control object at a time point t (see Fig. 4, t=0s; Section 2: Complementarity system "Let x0 be the state vector at the time t0..."; Section 5: Experiment "The initial state is defined as follows:...");
on the basis of the state at the time point t, calculating a state of the control object at a time point t+1 so as to satisfy a complementarity condition (see Equations 1-3, 9 and 17-19; Fig. 4, all; Section 2: Complementarity system, all, especially "The complementarity system is described by differential-algebraic equations ... where x is a state vector, u is an input vector of the system, w is a variable which represents the effect from the constraint (for example constraint force), and z is an output related to the constraint condition."; Section 3.2: Complementarity modeling of sample return robot - Mode selection and condition for keeping contact, all, especially "As we consider the state that the robot contacts with the environment, the following conditions are satisfied."; Section 4, Control law, all), the complementarity condition relating to a contact force generated at a contact point at the control object and a distance between the control object and the contact point (see Fig. 1, all; Fig. 2, all; Equations 1-3, 9 and 17-19; Section 2: Complementarity system, all, especially "The complementarity system is described by differential-algebraic equations ... where x is a state vector, u is an input vector of the system, w is a variable which represents the effect from the constraint (for example constraint force), and z is an output related to the constraint condition ... each time t we must have either zi(t)=0 and wi(t)≥0, or wi(t)=0 and zi(t)≥0 ... We consider an example of a scalar system. Let z be the distance from environment to an object and w be the vertical force as shown in Fig. 1. In this two bodies system, we have two modes that z(t)=0,w(t)≥0 and w(t)=0,z(t)≥0. The former is called “constraint mode” and the latter is called “non-constraint mode”. The first condition implies that if the object contacts to the environment (z(t)=0) then the interaction between them generates the constraint force (w(t)≥0). The second condition comes from the fact that if the two bodies break contact, then the interaction between them vanishes and relative acceleration must be positive."; Section 3: Complementarity modeling of sample return robot, all, especially "The dynamic system that the point P=(px,py)T of the end effector is constrained at the contact point O can be represented as..."; Section 4, Control law, all); and
controlling the control object so as to achieve the calculated state at the time point t+1 (see Figs. 4-6, all; Section 3.2: Complementarity modeling of sample return robot - Mode selection and condition for keeping contact "As we consider the state that the robot contacts with the environment, the following conditions are satisfied."; Section 4, Control law, all; Section 5: Experiment, all, especially "The control law (20), (24) accomplishes the desired task under the assumption that the robot does not slide and the system has enough friction ... In the case 2, we consider the uncertainty of the friction and we set fxd=0. To demonstrate the validity of the proposed control law (20) (24), experiments for the two cases have been carried out.").
Matsuno is silent regarding calculating the state of the control object at the time point t+1 so as to minimize an objective function,
the objective function representing a difference between the state at the time point t+1 and a target value.
Lin teaches a non-transitory storage medium (see all Figs.; [0006]) storing a control program that is executable by a computer to execute processing comprising:
acquiring a state of a control object at a time point t (see [0016 "The reference signal r is provided to a junction 102, where a current robot state x is also provided as feedback."], [0028 "The control module 410 receives the reference signal r on a line 402 and robot state data (q and) on feedback lines 450 and 460."] and [0037]);
on the basis of the state at the time point t, calculating a state of the control object at a time point t+1 so as to minimize an objective function (see claim 1; [0006], [0028 "The optimization block 412 computes an optimal control sequence or signal to achieve the prescribed reference, and the dynamics model block 414 is used in the optimization computation to predict the future state. The optimization block 412 and the dynamics model block 414 operate iteratively until the predicted future state matches the reference state within some tolerance, and system constraints are met."], [0037 "Equation (4) is the optimization objective function which minimizes the deviation between the reference state (the target state, which is given) and the state computed by the system dynamics model (Equation (3)), by varying the input variable (the torque u). Equation (5) is an equality constraint which defines how to predict the next step value for the state variable x based on the current step value of x and the current step value of the input variable u; this is determined using the system dynamics model (Equation (3))."] and [0055]), and the objective function representing a difference between the state at the time point t+1 and a target value (see Equation 4; claim 1, "...said calculation including an optimization computation with an objective function which determines a torque rate vector to minimize a difference between a predicted robot state and a reference robot state from the motion program while satisfying a constraint defining a robot dynamics equation of motion which computes the predicted robot state based on the torque rate vector and a constraint defining bounds on the torque rate vector..."; [0006], [0028], [0037 "Equation (4) is the optimization objective function which minimizes the deviation between the reference state (the target state, which is given) and the state computed by the system dynamics model (Equation (3)), by varying the input variable (the torque u). Equation (5) is an equality constraint which defines how to predict the next step value for the state variable x based on the current step value of x and the current step value of the input variable u; this is determined using the system dynamics model (Equation (3))."] and [0055]); and
controlling the control object so as to achieve the calculated state at the time point t+1 (see Fig. 4, all; [0018], [0030 "The robot mechanics 424 include all of the mass, inertia and friction properties of the arms and joints in the robot 420. Altogether, the joint motors 422 and the mechanics 424 respond to the motor torque vector u—causing the robot 420 to assume a new state, defined by joint velocities q and, after an integral block 430, joint positions q. The robot state data q and q are provided to the control module 410 on the feedback lines 450 and 460, as mentioned earlier."], [0037] and [0063]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the non-transitory storage medium of Matsuno to include instructions to minimize an objective function representing a difference between the state at the time point t+1 and a target value, as taught by Lin, in order to more accurately model robot system dynamics while adhering to system constraints.
Claims 2-3 are rejected under 35 U.S.C. 103 as being unpatentable over Matsuno (as modified by Lin) as applied to claim 1 above, and further in view of Jha et al. (US 20230294283 A1 and Jha hereinafter).
Regarding Claim 2
Modified Matsuno teaches the control device according to claim 1 (as discussed above in claim 1),
Matsuno further teaches wherein the calculation section, on the basis of the state at the time point t, calculates the state at the time point t+1 so as to satisfy the complementarity condition (see Equations 1-3, 9 and 17-19; Fig. 4, all; Section 2: Complementarity system, all, especially "The complementarity system is described by differential-algebraic equations ... where x is a state vector, u is an input vector of the system, w is a variable which represents the effect from the constraint (for example constraint force), and z is an output related to the constraint condition."; Section 3.2: Complementarity modeling of sample return robot - Mode selection and condition for keeping contact, all, especially "As we consider the state that the robot contacts with the environment, the following conditions are satisfied."; Section 4, Control law, all) relating to the contact force generated at the contact point at the control object and the distance between the control object and the contact point (see Fig. 1, all; Fig. 2, all; Equations 1-3, 9 and 17-19; Section 2: Complementarity system, all, especially "The complementarity system is described by differential-algebraic equations ... where x is a state vector, u is an input vector of the system, w is a variable which represents the effect from the constraint (for example constraint force), and z is an output related to the constraint condition ... each time t we must have either zi(t)=0 and wi(t)≥0, or wi(t)=0 and zi(t)≥0 ... We consider an example of a scalar system. Let z be the distance from environment to an object and w be the vertical force as shown in Fig. 1. In this two bodies system, we have two modes that z(t)=0,w(t)≥0 and w(t)=0,z(t)≥0. The former is called “constraint mode” and the latter is called “non-constraint mode”. The first condition implies that if the object contacts to the environment (z(t)=0) then the interaction between them generates the constraint force (w(t)≥0). The second condition comes from the fact that if the two bodies break contact, then the interaction between them vanishes and relative acceleration must be positive."; Section 3: Complementarity modeling of sample return robot, all, especially "The dynamic system that the point P=(px,py)T of the end effector is constrained at the contact point O can be represented as..."; Section 4, Control law, all) and
a complementarity condition relating to a linear contact velocity at a contact surface contacted by the contact point (see Fig. 2, all; Equations 17-19; Abstract "In a phenomenon of the impact between the robot and the asteroid, there is a complementary relation between the robot acceleration and the constraint force on the contact point"; Section 2: Complementarity system, all; Section 3: Complementarity modeling of sample return robot, all, especially "So we consider the complementarity relation between the vertical force and the vertical acceleration.... In the case of β<0 the acceleration along the Y axis of the robot is zero and the robot generates the constraint force. Therefore, the parameter β in (16) should be negative to keep the contact."; Section 4, Control law, all; The "acceleration" in Matsuno corresponds to the claimed "velocity" because an acceleration is the rate at which an object's velocity changes over time.).
Matsuno is silent regarding so as to minimize the objective function representing the difference between the state of the control object at the time point t+1 and the target value.
Lin teaches wherein the calculation section, on the basis of the state at the time point t, calculates the state at the time point t+1 (see claim 1; [0006], [0028 "The optimization block 412 computes an optimal control sequence or signal to achieve the prescribed reference, and the dynamics model block 414 is used in the optimization computation to predict the future state. The optimization block 412 and the dynamics model block 414 operate iteratively until the predicted future state matches the reference state within some tolerance, and system constraints are met."], [0037 "Equation (4) is the optimization objective function which minimizes the deviation between the reference state (the target state, which is given) and the state computed by the system dynamics model (Equation (3)), by varying the input variable (the torque u). Equation (5) is an equality constraint which defines how to predict the next step value for the state variable x based on the current step value of x and the current step value of the input variable u; this is determined using the system dynamics model (Equation (3))."] and [0055]), and
so as to minimize the objective function representing the difference between the state of the control object at the time point t+1 and the target value (see Equation 4; claim 1, "...said calculation including an optimization computation with an objective function which determines a torque rate vector to minimize a difference between a predicted robot state and a reference robot state from the motion program while satisfying a constraint defining a robot dynamics equation of motion which computes the predicted robot state based on the torque rate vector and a constraint defining bounds on the torque rate vector..."; [0006], [0028], [0037 "Equation (4) is the optimization objective function which minimizes the deviation between the reference state (the target state, which is given) and the state computed by the system dynamics model (Equation (3)), by varying the input variable (the torque u). Equation (5) is an equality constraint which defines how to predict the next step value for the state variable x based on the current step value of x and the current step value of the input variable u; this is determined using the system dynamics model (Equation (3))."] and [0055]).
Matsuno additionally teaches a complementarity condition relating to a linear contact velocity at a contact surface contacted by the contact point under broadest reasonable interpretation, as discussed above. For the sake of compact prosecution and for the possible argument that the "acceleration" of Matsuno does not encompass the claimed "linear contact velocity", Jha teaches the claim limitation.
That is, Jha teaches a control device (see all Figs.; [0016]) comprising:
an acquisition section that acquires a state of a control object at a time point t (see [0016 "...acquiring measurement data from vision sensors and force sensors arranged on the robotic system…"], [0066 "The tactile sensors 1101 and vision sensors 1102 can be used to measure the contact state between the manipulator and the object, and monitor slipping between the object and the manipulator."] and [0081]-[0083]);
a calculation section that, on the basis of the state at the time point t, calculates a state of the control object at a time point t+1 so as to satisfy a complementarity condition (see Equations 5-9; [0016 "...determining an input-output relation for the object based on a nonlinear static model representing input-output relationships between contact forces and movements of the object on the workbench; representing interaction between the object and the manipulator using complementarity constraints to capture the contact state between the object and the manipulator ... solving the bilevel optimization problem using the non-linear optimization solver and generating control data with respect to a sequence of the contact forces being applied to the object by using the manipulator"], [0047 "Some embodiments of the current disclosure are based on the realization that the friction cone could be succintly represented using complementarity constraints."]-[0050] and [0083 "The controller 1100 is configured to compute a sequence of control forces applied to the object using the bilevel optimization algorithm. The robot 1150 applies the sequence of control forces (sequence of the contact forces) to the object against the external contact surface (e.g. 810) in step 1040."]), the complementarity condition relating to a contact force generated at a contact point at the control object (see Equations 5-9; [0016 "...representing interaction between the object and the manipulator using complementarity constraints to capture the contact state between the object and the manipulator…"], [0044] and [0047]-[0050], especially [0049 "The above equations (1)-(7) provide the non-linear input-output relationship that determine the movement of the object 201 on a workbench up on the application of the contact forces (i.e, represent the input output relationship between the contact forces and the object movement)."]); and
a control section that controls the control object so as to achieve the calculated state at the time point t+1 (see [0016 "...generating control data with respect to a sequence of the contact forces being applied to the object by using the manipulator; and transmitting the control data that instruct the manipulator to perform the reorienting the object on the workbench according to the sequence of the contact forces."] and [0084 "The manipulation controller 1100 is configured to generate and transmit the control data including instructions with respect to the computed sequence of control forces to the low-level robot controller (e.g., an actuator controller of the manipulator) such that the instructions cause the manipulator to apply the computed sequence of control forces (contact forces) on the object in step 1050. The robot grasps the re-oriented parts so that they can be then used for the desired task (assembly or packing) in step 1060."]);
wherein the calculation section, on the basis of the state at the time point t, calculates the state at the time point t+1 so as to satisfy the complementarity condition (see Equations 5-9; [0016 "...determining an input-output relation for the object based on a nonlinear static model representing input-output relationships between contact forces and movements of the object on the workbench; representing interaction between the object and the manipulator using complementarity constraints to capture the contact state between the object and the manipulator ... solving the bilevel optimization problem using the non-linear optimization solver and generating control data with respect to a sequence of the contact forces being applied to the object by using the manipulator"], [0047 "Some embodiments of the current disclosure are based on the realization that the friction cone could be succintly represented using complementarity constraints."]-[0050] and [0083 "The controller 1100 is configured to compute a sequence of control forces applied to the object using the bilevel optimization algorithm. The robot 1150 applies the sequence of control forces (sequence of the contact forces) to the object against the external contact surface (e.g. 810) in step 1040."]) relating to the contact force generated at the contact point at the control object (see Equations 5-9; [0016 "...representing interaction between the object and the manipulator using complementarity constraints to capture the contact state between the object and the manipulator…"], [0044] and [0047]-[0050], especially [0049 "The above equations (1)-(7) provide the non-linear input-output relationship that determine the movement of the object 201 on a workbench up on the application of the contact forces (i.e, represent the input output relationship between the contact forces and the object movement)."]) and
a complementarity condition relating to a linear contact velocity at a contact surface contacted by the contact point (see Equations 5-9; [0048]-[0050], especially [0048 "...where the slipping velocity at point i follows … represent the slipping velocity along positive and negative directions for each axis, respectively."] and [0050 "Interactions between an object and a robot arm of the robotic system can be represented using complementarity constraints to capture the contact state between the object and the robot arm (i.e., the manipulator) of the robotic system. In some cases, the interactions are based on the contact state represented by the relation between a slipping velocity of the object on a table-top and the friction of the object with the table-top when the object is moved by the force applied by the robot arm. Thus, we consider the following complementarity constraints that represent the relation between the slipping velocity at point P..."]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the control device of Matsuno to minimize an objective function representing a difference between the state at the time point t+1 and a target value, as taught by Lin, in order to more accurately model robot system dynamics while adhering to system constraints.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to further modify the control device of modified Matsuno to include a complementarity condition relating to a linear contact velocity at a contact surface contacted by the contact point, as taught by Jha, in order to represent interactions between a robot arm and an object which are based on a contact state represented by the relationship between a slipping velocity and friction.
Regarding Claim 3
Modified Matsuno teaches the control device according to claim 1 (as discussed above in claim 1),
Matsuno further teaches wherein the control object is each of a robot and an object body (see Figs. 1-2, all; Abstract "In a phenomenon of the impact between the robot and the asteroid, there is a complementary relation between the robot acceleration and the constraint force on the contact point. To pay attention to the complementarity, we derive a condition to constrain the robot on the surface of the asteroid based on complementarity system (CS)."; Section 3: Complementarity modeling of sample return robot, all, especially "When the robot contacts with the surface of the asteroid the robot receives the constraint force f=[fx fy]T. The dynamic system that the point P=(px,py)T of the end effector is constrained at the contact point O can be represented as"),
data of the states is calculated on the basis of sensor data obtained by a sensor that senses states of the robot and the object body (see Figs. 4-6, all; Section 5: Experiment, all, especially "The joint angle θ(t) and the displacement l(t) can be measured by the rotary encoders, and the angular velocity θ˙(t) and the linear velocity l(t) by F/V converters. The attitude angle and the angular velocity of the robot body can be measured by a gyro sensor. Fig. 4 shows the configuration of the robot at the initial, middle, and take-off instants for case 1 and case 2. Fig. 5 and 6 show the transient responses for experiments in case 1 and case 2, respectively. "), and
the calculation section, on the basis of the states at the time point t, calculates the states of the control objects at the time point t+1 so as to satisfy complementarity conditions (see Equations 1-3, 9 and 17-19; Fig. 4, all; Section 2: Complementarity system, all, especially "The complementarity system is described by differential-algebraic equations ... where x is a state vector, u is an input vector of the system, w is a variable which represents the effect from the constraint (for example constraint force), and z is an output related to the constraint condition."; Section 3.2: Complementarity modeling of sample return robot - Mode selection and condition for keeping contact, all, especially "As we consider the state that the robot contacts with the environment, the following conditions are satisfied."; Section 4, Control law, all) that each relate to
a contact force generated between a contact point of the robot and a contact point of the object body, and a distance between the contact point of the robot and the contact point of the object body (see Fig. 1, all; Fig. 2, all; Equations 1-3, 9 and 17-19; Section 2: Complementarity system, all, especially "The complementarity system is described by differential-algebraic equations ... where x is a state vector, u is an input vector of the system, w is a variable which represents the effect from the constraint (for example constraint force), and z is an output related to the constraint condition ... each time t we must have either zi(t)=0 and wi(t)≥0, or wi(t)=0 and zi(t)≥0 ... We consider an example of a scalar system. Let z be the distance from environment to an object and w be the vertical force as shown in Fig. 1. In this two bodies system, we have two modes that z(t)=0,w(t)≥0 and w(t)=0,z(t)≥0. The former is called “constraint mode” and the latter is called “non-constraint mode”. The first condition implies that if the object contacts to the environment (z(t)=0) then the interaction between them generates the constraint force (w(t)≥0). The second condition comes from the fact that if the two bodies break contact, then the interaction between them vanishes and relative acceleration must be positive."; Section 3: Complementarity modeling of sample return robot, all, especially "The dynamic system that the point P=(px,py)T of the end effector is constrained at the contact point O can be represented as..."; Section 4, Control law, all).
Lin additionally teaches data of the states is calculated on the basis of sensor data obtained by a sensor that senses states of the robot (see [0018 "The new robot state x (typically described by joint positions and rotational velocities) is measured by robot sensors (e.g., joint encoders) and provided on line 130. The robot state x is also provided on feedback line 140 to the junction 102 where it is used to computed the error signal e for the next robot control cycle."]-[0019] and [0037]), and
the calculation section, on the basis of the states at the time point t, calculates the states of the control objects at the time point t+1 (see claim 1; [0006], [0028 "The optimization block 412 computes an optimal control sequence or signal to achieve the prescribed reference, and the dynamics model block 414 is used in the optimization computation to predict the future state. The optimization block 412 and the dynamics model block 414 operate iteratively until the predicted future state matches the reference state within some tolerance, and system constraints are met."], [0037 "Equation (4) is the optimization objective function which minimizes the deviation between the reference state (the target state, which is given) and the state computed by the system dynamics model (Equation (3)), by varying the input variable (the torque u). Equation (5) is an equality constraint which defines how to predict the next step value for the state variable x based on the current step value of x and the current step value of the input variable u; this is determined using the system dynamics model (Equation (3))."] and [0055]).
Jha additionally teaches wherein the control object is each of a robot and an object body (see "manipulator" and "object" in most Figs.; [0016 ".representing interaction between the object and the manipulator using complementarity constraints to capture the contact state between the object and the manipulator…"]),
data of the states is calculated on the basis of sensor data obtained by a sensor that senses states of the robot and the object body (see [0016 "...acquiring measurement data from vision sensors and force sensors arranged on the robotic system…"], [0066 "The tactile sensors 1101 and vision sensors 1102 can be used to measure the contact state between the manipulator and the object, and monitor slipping between the object and the manipulator."] and [0081]-[0083]), and
the calculation section, on the basis of the states at the time point t, calculates the states of the control objects at the time point t+1 so as to satisfy complementarity conditions (see Equations 5-9; [0016 "...determining an input-output relation for the object based on a nonlinear static model representing input-output relationships between contact forces and movements of the object on the workbench; representing interaction between the object and the manipulator using complementarity constraints to capture the contact state between the object and the manipulator ... solving the bilevel optimization problem using the non-linear optimization solver and generating control data with respect to a sequence of the contact forces being applied to the object by using the manipulator"], [0047 "Some embodiments of the current disclosure are based on the realization that the friction cone could be succintly represented using complementarity constraints."]-[0050] and [0083 "The controller 1100 is configured to compute a sequence of control forces applied to the object using the bilevel optimization algorithm. The robot 1150 applies the sequence of control forces (sequence of the contact forces) to the object against the external contact surface (e.g. 810) in step 1040."]) that each relate to
a contact force generated between two of a contact point of the robot, a contact point of the object body, and a contact point of another body (see Equations 5-9; [0016 "...representing interaction between the object and the manipulator using complementarity constraints to capture the contact state between the object and the manipulator…"], [0044] and [0047]-[0050], especially [0049 "The above equations (1)-(7) provide the non-linear input-output relationship that determine the movement of the object 201 on a workbench up on the application of the contact forces (i.e, represent the input output relationship between the contact forces and the object movement)."]).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Matsuno (as modified by Lin and Jha) as applied to claim 3 above, and further in view of NPL_ Posa et al. "A direct method for trajectory optimization…" (Posa hereinafter).
Regarding Claim 4
Modified Matsuno teaches the control device according to claim 3,
Matsuno further teaches wherein the complementarity conditions include, for each of a plurality of the contact points:
a complementarity condition (4a) relating to, in the state qt at the time point t, a contact force λni generated in a perpendicular direction of a contact surface contacted by an i-th contact point and a distance ϕi(qt) between the i-th contact point and the contact surface (see Fig. 1, all; Fig. 2, all; Equations 1-3; Section 2: Complementarity system, all, especially "The complementarity system is described by differential-algebraic equations ... where x is a state vector, u is an input vector of the system, w is a variable which represents the effect from the constraint (for example constraint force), and z is an output related to the constraint condition ... each time t we must have either zi(t)=0 and wi(t)≥0, or wi(t)=0 and zi(t)≥0 ... We consider an example of a scalar system. Let z be the distance from environment to an object and w be the vertical force as shown in Fig. 1. In this two bodies system, we have two modes that z(t)=0,w(t)≥0 and w(t)=0,z(t)≥0. The former is called “constraint mode” and the latter is called “non-constraint mode”. The first condition implies that if the object contacts to the environment (z(t)=0) then the interaction between them generates the constraint force (w(t)≥0). The second condition comes from the fact that if the two bodies break contact, then the interaction between them vanishes and relative acceleration must be positive."; Section 3: Complementarity modeling of sample return robot, all, especially "The dynamic system that the point P=(px,py)T of the end effector is constrained at the contact point O can be represented as..."; Section 4, Control law, all);
complementarity condition (4a) (see Figure 1; Equations 1-3).
Matsuno is silent regarding a complementarity condition (4b) relating to, in the state qt at the time point t with a generalized velocity vt at the time point t, a contact force λfi+ in a first horizontal direction of the contact surface contacted by the i-th contact point, a signed linear contact velocity ψi(qt,vt) that is positive in the first horizontal direction of the contact surface, and an absolute value γi of the linear contact velocity;
a complementarity condition (4c) relating to, in the state qt at the time point t with the generalized velocity vt at the time point t, a contact force λfi- in a second horizontal direction of the contact surface contacted by the i-th contact point, the signed linear contact velocity ψi(qt,vt), and the absolute value γi of the linear contact velocity; and
a complementarity condition (4d) relating to, at the contact surface contacted by the i-th contact point, the absolute value γi of the linear contact velocity, a coefficient of friction μi of the contact surface, the contact force λni generated in the perpendicular direction of the contact surface, the contact force λfi+ in the first horizontal direction, and the contact force λfi- in the second horizontal direction
complementarity condition (4b),
complementarity condition (4c), and
complementarity condition (4d).
Jha teaches wherein the complementarity conditions include, for each of a plurality of the contact points:
a complementarity condition (4d) relating to, at the contact surface contacted by the i-th contact point, the absolute value γi of the linear contact velocity, a coefficient of friction μi of the contact surface, the contact force λni generated in the perpendicular direction of the contact surface, the contact force λfi+ in the first horizontal direction, and the contact force λfi- in the second horizontal direction (see Equations 5-9; [0048]-[0051])
complementarity condition (4d) (see Equations 5-9; [0048]-[0051]).
Posa teaches a control device (see Abstract, all; Section 4: Example Applications, all) comprising:
an acquisition section that acquires a state of a control object at a time point t (see Equations 8-16; Section 3.1: Optimization Constraints, all, especially "To integrate the dynamics, both forwards and backwards Euler methods are equally applicable. Time-stepping simulation methods commonly use semi-implicit methods, but the dynamics constraints in our optimization problem are already fully implicit and so we chose backwards integration for added numerical stability.");
a calculation section that, on the basis of the state at the time point t, calculates a state of the control object at a time point t+1 so as to satisfy a complementarity condition (see Equations 8-16; Section 3.1: Optimization Constraints, all),
wherein the complementarity conditions include, for each of a plurality of the contact points:
a complementarity condition (4a) relating to, in the state qt at the time point t, a contact force λni generated in a perpendicular direction of a contact surface contacted by an i-th contact point and a distance ϕi(qt) between the i-th contact point and the contact surface (see Equations 8-9 and 13; Section 3.1: Optimization Constraints, all);
a complementarity condition (4b) relating to, in the state qt at the time point t with a generalized velocity vt at the time point t, a contact force λfi+ in a first horizontal direction of the contact surface contacted by the i-th contact point, a signed linear contact velocity ψi(qt,vt) that is positive in the first horizontal direction of the contact surface, and an absolute value γi of the linear contact velocity (see Equations 9, 11 and 15; Section 3.1: Optimization Constraints, all);
a complementarity condition (4c) relating to, in the state qt at the time point t with the generalized velocity vt at the time point t, a contact force λfi- in a second horizontal direction of the contact surface contacted by the i-th contact point, the signed linear contact velocity ψi(qt,vt), and the absolute value γi of the linear contact velocity (see Equations 9, 12 and 16; Section 3.1: Optimization Constraints, all); and
a complementarity condition (4d) relating to, at the contact surface contacted by the i-th contact point, the absolute value γi of the linear contact velocity, a coefficient of friction μi of the contact surface, the contact force λni generated in the perpendicular direction of the contact surface, the contact force λfi+ in the first horizontal direction, and the contact force λfi- in the second horizontal direction (see Equations 9-10 and 14; Section 3.1: Optimization Constraints, all)
complementarity condition (4a) (see Equations 8-9 and 13),
complementarity condition (4b) (see Equations 9, 11 and 15)
complementarity condition (4c) (see Equations 9, 12 and 16)
complementarity condition (4d) (see Equations 9-10 and 14).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to further modify the control device of modified Matsuno to include the various complementarity conditions relating to a linear contact velocity and contact force at a contact surface contacted by the contact point, as taught by Posa, in order to enforce the friction cone and ensure that, if the contact is sliding, the tangential force properly lies on the edge of the cone and directly opposes the direction of motion.
Allowable Subject Matter
Claims 5-9 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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/TANNER L CULLEN/Examiner, Art Unit 3656 /KHOI H TRAN/Supervisory Patent Examiner, Art Unit 3656
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